dotdigital and Tryzens launch new integration, empowering retailers to supercharge their ecommerce marketing

The new pre-built integration, or ‘cartridge’, has been built by Tryzens, a leading ecommerce specialist in partnership with dotdigital, an omnichannel marketing automation platform provider. Tryzens is the partner of choice for dotdigital and has helped enhance the cartridge, which has now become certified in Salesforce’s Commerce Cloud Partner Marketplace.

The new cartridge will enable ecommerce retailers on Salesforce Commerce Cloud and marketers to more effectively respond to e-store behaviours through smart win-back tactics.

dotdigital employs more than 350 people globally and integrates with leading ecommerce platforms, from Salesforce Commerce Cloud to Magento. dotdigital’s Engagement Cloud empowers marketers at some of the world’s most innovative brands, including Oliver Bonas, Paperchase, and City Lit to deliver smart, automated marketing programs that customers find engaging.

The dotdigital Engagement Cloud cartridge comes with a host of pre-configured options to enable retailers and marketers to better harness essential customer data to develop targeted and personalized omnichannel marketing campaigns. The level of technical pre-configuration applied to the cartridge means time to value can be reduced for retailers who want to connect their store with dotdigital Engagement Cloud.

The solution
encompasses abandoned cart functionality, allowing ecommerce merchants to send
customers a timely reminder that they left something behind, steering them back
onto the path to purchase. The solution can also be used to serve AI-powered
product recommendations based on orders, browsing history, and more.

Greg Straw, Partner Manager at Tryzens, said: “Email is one of the most important channels in every marketer’s toolkit, thanks not only to its unrivalled ubiquity, but also because it enables rich and personalized engagement with customers. The new functionality we’ve built into the dotdigital Engagement Cloud cartridge makes it easier than ever for ecommerce retailers to supercharge and optimize their marketing automation campaigns. In addition, we’ve made it easier to track and measure the ROI of these campaigns so that retailers can ensure that they are hitting the right notes with their target audiences and generating sales improvements.”

Steve Shaw, Group CTO at dotdigital, added: “The new dotdigital Engagement Cloud cartridge has been built with speed and convenience in mind; with highly configurable options and efficient data integration, it enables marketers the flexibility to tailor their store’s marketing and campaigns (whether that be email, mobile, or targeted ads). Omnichannel messaging through digital channels has become an effective strategy for engaging with shoppers and improving customer loyalty, so this speed and convenience will be a very welcome development for retailers in an increasingly competitive market.”


About Tryzens

Established in 2004, Tryzens is an
international digital commerce consultancy that take a holistic approach to
growing your business, no matter how or where your customers choose to buy. Our
team of trading specialists, strategists and technology experts are passionate
about growing your business by implementing solutions that optimise performance
across all channels.

With offices in offices in London, Melbourne, Sofia, and Trivandrum, we have partnered with some of the world’s most successful retailers and brand owners including Sweaty Betty, Cotton On Group, T.M.Lewin, Fisher & Paykel, and Liberty London to provide beginning to end services that help grow businesses and provide the best customer experiences.

To read more about the Tryzens partner programme click here.

Press contact:

Edward Dodge / Harry
Thompson

Spreckley

T: +44 (0)207 388 9988

E: tryzens@spreckley.co.uk

About Salesforce Commerce Cloud

Salesforce Commerce Cloud empowers retailers to unify customer experiences across all points of commerce, including web, social, mobile, and store. From shopping to fulfillment to customer service, the Commerce Cloud delivers 1-to-1 shopping experiences that consistently delight customers, driving increased engagement, loyalty, and conversion. With embedded predictive intelligence and a robust partner ecosystem, the Commerce Cloud helps retailers deliver superior customer experiences for retailers, from planning to launch and beyond.

Additional resources:

Salesforce, Commerce Cloud, and others are trademarks of salesforce.com, inc.

The post dotdigital and Tryzens launch new integration, empowering retailers to supercharge their ecommerce marketing appeared first on dotdigital blog.

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Deconstructing the App Store Rankings Formula with a Little Mad Science

Posted by AlexApptentive

After seeing Rand’s “Mad Science Experiments in SEO” presented at last year’s MozCon, I was inspired to put on the lab coat and goggles and do a few experiments of my own—not in SEO, but in SEO’s up-and-coming younger sister, ASO (app store optimization).

Working with Apptentive to guide enterprise apps and small startup apps alike to increase their discoverability in the app stores, I’ve learned a thing or two about app store optimization and what goes into an app’s ranking. It’s been my personal goal for some time now to pull back the curtains on Google and Apple. Yet, the deeper into the rabbit hole I go, the more untested assumptions I leave in my way.

Hence, I thought it was due time to put some longstanding hypotheses through the gauntlet.

As SEOs, we know how much of an impact a single ranking can mean on a SERP. One tiny rank up or down can make all the difference when it comes to your website’s traffic—and revenue.

In the world of apps, ranking is just as important when it comes to standing out in a sea of more than 1.3 million apps. Apptentive’s recent mobile consumer survey shed a little more light this claim, revealing that nearly half of all mobile app users identified browsing the app store charts and search results (the placement on either of which depends on rankings) as a preferred method for finding new apps in the app stores. Simply put, better rankings mean more downloads and easier discovery.

Like Google and Bing, the two leading app stores (the Apple App Store and Google Play) have a complex and highly guarded algorithms for determining rankings for both keyword-based app store searches and composite top charts.

Unlike SEO, however, very little research and theory has been conducted around what goes into these rankings.

Until now, that is.

Over the course of five studies analyzing various publicly available data points for a cross-section of the top 500 iOS (U.S. Apple App Store) and the top 500 Android (U.S. Google Play) apps, I’ll attempt to set the record straight with a little myth-busting around ASO. In the process, I hope to assess and quantify any perceived correlations between app store ranks, ranking volatility, and a few of the factors commonly thought of as influential to an app’s ranking.

But first, a little context

Image credit: Josh Tuininga, Apptentive

Both the Apple App Store and Google Play have roughly 1.3 million apps each, and both stores feature a similar breakdown by app category. Apps ranking in the two stores should, theoretically, be on a fairly level playing field in terms of search volume and competition.

Of these apps, nearly two-thirds have not received a single rating and 99% are considered unprofitable. These studies, therefore, single out the rare exceptions to the rule—the top 500 ranked apps in each store.

While neither Apple nor Google have revealed specifics about how they calculate search rankings, it is generally accepted that both app store algorithms factor in:

  • Average app store rating
  • Rating/review volume
  • Download and install counts
  • Uninstalls (what retention and churn look like for the app)
  • App usage statistics (how engaged an app’s users are and how frequently they launch the app)
  • Growth trends weighted toward recency (how daily download counts changed over time and how today’s ratings compare to last week’s)
  • Keyword density of the app’s landing page (Ian did a great job covering this factor in a previous Moz post)

I’ve simplified this formula to a function highlighting the four elements with sufficient data (or at least proxy data) for our analysis:

Ranking = fn(Rating, Rating Count, Installs, Trends)

Of course, right now, this generalized function doesn’t say much. Over the next five studies, however, we’ll revisit this function before ultimately attempting to compare the weights of each of these four variables on app store rankings.

(For the purpose of brevity, I’ll stop here with the assumptions, but I’ve gone into far greater depth into how I’ve reached these conclusions in a 55-page report on app store rankings.)

Now, for the Mad Science.

Study #1: App-les to app-les app store ranking volatility

The first, and most straight forward of the five studies involves tracking daily movement in app store rankings across iOS and Android versions of the same apps to determine any trends of differences between ranking volatility in the two stores.

I went with a small sample of five apps for this study, the only criteria for which were that:

  • They were all apps I actively use (a criterion for coming up with the five apps but not one that influences rank in the U.S. app stores)
  • They were ranked in the top 500 (but not the top 25, as I assumed app store rankings would be stickier at the top—an assumption I’ll test in study #2)
  • They had an almost identical version of the app in both Google Play and the App Store, meaning they should (theoretically) rank similarly
  • They covered a spectrum of app categories

The apps I ultimately chose were Lyft, Venmo, Duolingo, Chase Mobile, and LinkedIn. These five apps represent the travel, finance, education banking, and social networking categories.

Hypothesis

Going into this analysis, I predicted slightly more volatility in Apple App Store rankings, based on two statistics:

Both of these assumptions will be tested in later analysis.

Results

7-Day App Store Ranking Volatility in the App Store and Google Play

Among these five apps, Google Play rankings were, indeed, significantly less volatile than App Store rankings. Among the 35 data points recorded, rankings within Google Play moved by as much as 23 positions/ranks per day while App Store rankings moved up to 89 positions/ranks. The standard deviation of ranking volatility in the App Store was, furthermore, 4.45 times greater than that of Google Play.

Of course, the same apps varied fairly dramatically in their rankings in the two app stores, so I then standardized the ranking volatility in terms of percent change to control for the effect of numeric rank on volatility. When cast in this light, App Store rankings changed by as much as 72% within a 24-hour period while Google Play rankings changed by no more than 9%.

Also of note, daily rankings tended to move in the same direction across the two app stores approximately two-thirds of the time, suggesting that the two stores, and their customers, may have more in common than we think.

Study #2: App store ranking volatility across the top charts

Testing the assumption implicit in standardizing the data in study No. 1, this one was designed to see if app store ranking volatility is correlated with an app’s current rank. The sample for this study consisted of the top 500 ranked apps in both Google Play and the App Store, with special attention given to those on both ends of the spectrum (ranks 1–100 and 401–500).

Hypothesis

I anticipated rankings to be more volatile the higher an app is ranked—meaning an app ranked No. 450 should be able to move more ranks in any given day than an app ranked No. 50. This hypothesis is based on the assumption that higher ranked apps have more installs, active users, and ratings, and that it would take a large margin to produce a noticeable shift in any of these factors.

Results

App Store Ranking Volatility of Top 500 Apps

One look at the chart above shows that apps in both stores have increasingly more volatile rankings (based on how many ranks they moved in the last 24 hours) the lower on the list they’re ranked.

This is particularly true when comparing either end of the spectrum—with a seemingly straight volatility line among Google Play’s Top 100 apps and very few blips within the App Store’s Top 100. Compare this section to the lower end, ranks 401–)500, where both stores experience much more turbulence in their rankings. Across the gamut, I found a 24% correlation between rank and ranking volatility in the Play Store and 28% correlation in the App Store.

To put this into perspective, the average app in Google Play’s 401–)500 ranks moved 12.1 ranks in the last 24 hours while the average app in the Top 100 moved a mere 1.4 ranks. For the App Store, these numbers were 64.28 and 11.26, making slightly lower-ranked apps more than five times as volatile as the highest ranked apps. (I say slightly as these “lower-ranked” apps are still ranked higher than 99.96% of all apps.)

The relationship between rank and volatility is pretty consistent across the App Store charts, while rank has a much greater impact on volatility at the lower end of Google Play charts (ranks 1-100 have a 35% correlation) than it does at the upper end (ranks 401-500 have a 1% correlation).

Study #3: App store rankings across the stars

The next study looks at the relationship between rank and star ratings to determine any trends that set the top chart apps apart from the rest and explore any ties to app store ranking volatility.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

As discussed in the introduction, this study relates directly to one of the factors commonly accepted as influential to app store rankings: average rating.

Getting started, I hypothesized that higher ranks generally correspond to higher ratings, cementing the role of star ratings in the ranking algorithm.

As far as volatility goes, I did not anticipate average rating to play a role in app store ranking volatility, as I saw no reason for higher rated apps to be less volatile than lower rated apps, or vice versa. Instead, I believed volatility to be tied to rating volume (as we’ll explore in our last study).

Results

Average App Store Ratings of Top Apps

The chart above plots the top 100 ranked apps in either store with their average rating (both historic and current, for App Store apps). If it looks a little chaotic, it’s just one indicator of the complexity of ranking algorithm in Google Play and the App Store.

If our hypothesis was correct, we’d see a downward trend in ratings. We’d expect to see the No. 1 ranked app with a significantly higher rating than the No. 100 ranked app. Yet, in neither store is this the case. Instead, we get a seemingly random plot with no obvious trends that jump off the chart.

A closer examination, in tandem with what we already know about the app stores, reveals two other interesting points:

  1. The average star rating of the top 100 apps is significantly higher than that of the average app. Across the top charts, the average rating of a top 100 Android app was 4.319 and the average top iOS app was 3.935. These ratings are 0.32 and 0.27 points, respectively, above the average rating of all rated apps in either store. The averages across apps in the 401–)500 ranks approximately split the difference between the ratings of the top ranked apps and the ratings of the average app.
  2. The rating distribution of top apps in Google Play was considerably more compact than the distribution of top iOS apps. The standard deviation of ratings in the Apple App Store top chart was over 2.5 times greater than that of the Google Play top chart, likely meaning that ratings are more heavily weighted in Google Play’s algorithm.

App Store Ranking Volatility and Average Rating

Looking next at the relationship between ratings and app store ranking volatility reveals a -15% correlation that is consistent across both app stores; meaning the higher an app is rated, the less its rank it likely to move in a 24-hour period. The exception to this rule is the Apple App Store’s calculation of an app’s current rating, for which I did not find a statistically significant correlation.

Study #4: App store rankings across versions

This next study looks at the relationship between the age of an app’s current version, its rank and its ranking volatility.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

In alteration of the above function, I’m using the age of a current app’s version as a proxy (albeit not a very good one) for trends in app store ratings and app quality over time.

Making the assumptions that (a) apps that are updated more frequently are of higher quality and (b) each new update inspires a new wave of installs and ratings, I’m hypothesizing that the older the age of an app’s current version, the lower it will be ranked and the less volatile its rank will be.

Results

How update frequency correlates with app store rank

The first and possibly most important finding is that apps across the top charts in both Google Play and the App Store are updated remarkably often as compared to the average app.

At the time of conducting the study, the current version of the average iOS app on the top chart was only 28 days old; the current version of the average Android app was 38 days old.

As hypothesized, the age of the current version is negatively correlated with the app’s rank, with a 13% correlation in Google Play and a 10% correlation in the App Store.

How update frequency correlates with app store ranking volatility

The next part of the study maps the age of the current app version to its app store ranking volatility, finding that recently updated Android apps have less volatile rankings (correlation: 8.7%) while recently updated iOS apps have more volatile rankings (correlation: -3%).

Study #5: App store rankings across monthly active users

In the final study, I wanted to examine the role of an app’s popularity on its ranking. In an ideal world, popularity would be measured by an app’s monthly active users (MAUs), but since few mobile app developers have released this information, I’ve settled for two publicly available proxies: Rating Count and Installs.

Hypothesis

Ranking = fn(Rating, Rating Count, Installs, Trends)

For the same reasons indicated in the second study, I anticipated that more popular apps (e.g., apps with more ratings and more installs) would be higher ranked and less volatile in rank. This, again, takes into consideration that it takes more of a shift to produce a noticeable impact in average rating or any of the other commonly accepted influencers of an app’s ranking.

Results

Apps with more ratings and reviews typically rank higher

The first finding leaps straight off of the chart above: Android apps have been rated more times than iOS apps, 15.8x more, in fact.

The average app in Google Play’s Top 100 had a whopping 3.1 million ratings while the average app in the Apple App Store’s Top 100 had 196,000 ratings. In contrast, apps in the 401–)500 ranks (still tremendously successful apps in the 99.96 percentile of all apps) tended to have between one-tenth (Android) and one-fifth (iOS) of the ratings count as that of those apps in the top 100 ranks.

Considering that almost two-thirds of apps don’t have a single rating, reaching rating counts this high is a huge feat, and a very strong indicator of the influence of rating count in the app store ranking algorithms.

To even out the playing field a bit and help us visualize any correlation between ratings and rankings (and to give more credit to the still-staggering 196k ratings for the average top ranked iOS app), I’ve applied a logarithmic scale to the chart above:

The relationship between app store ratings and rankings in the top 100 apps

From this chart, we can see a correlation between ratings and rankings, such that apps with more ratings tend to rank higher. This equates to a 29% correlation in the App Store and a 40% correlation in Google Play.

Apps with more ratings typically experience less app store ranking volatility

Next up, I looked at how ratings count influenced app store ranking volatility, finding that apps with more ratings had less volatile rankings in the Apple App Store (correlation: 17%). No conclusive evidence was found within the Top 100 Google Play apps.

Apps with more installs and active users tend to rank higher in the app stores

And last but not least, I looked at install counts as an additional proxy for MAUs. (Sadly, this is a statistic only listed in Google Play. so any resulting conclusions are applicable only to Android apps.)

Among the top 100 Android apps, this last study found that installs were heavily correlated with ranks (correlation: -35.5%), meaning that apps with more installs are likely to rank higher in Google Play. Android apps with more installs also tended to have less volatile app store rankings, with a correlation of -16.5%.

Unfortunately, these numbers are slightly skewed as Google Play only provides install counts in broad ranges (e.g., 500k–)1M). For each app, I took the low end of the range, meaning we can likely expect the correlation to be a little stronger since the low end was further away from the midpoint for apps with more installs.

Summary

To make a long post ever so slightly shorter, here are the nuts and bolts unearthed in these five mad science studies in app store optimization:

  1. Across the top charts, Apple App Store rankings are 4.45x more volatile than those of Google Play
  2. Rankings become increasingly volatile the lower an app is ranked. This is particularly true across the Apple App Store’s top charts.
  3. In both stores, higher ranked apps tend to have an app store ratings count that far exceeds that of the average app.
  4. Ratings appear to matter more to the Google Play algorithm, especially as the Apple App Store top charts experience a much wider ratings distribution than that of Google Play’s top charts.
  5. The higher an app is rated, the less volatile its rankings are.
  6. The 100 highest ranked apps in either store are updated much more frequently than the average app, and apps with older current versions are correlated with lower ratings.
  7. An app’s update frequency is negatively correlated with Google Play’s ranking volatility but positively correlated with ranking volatility in the App Store. This likely due to how Apple weighs an app’s most recent ratings and reviews.
  8. The highest ranked Google Play apps receive, on average, 15.8x more ratings than the highest ranked App Store apps.
  9. In both stores, apps that fall under the 401–500 ranks receive, on average, 10–20% of the rating volume seen by apps in the top 100.
  10. Rating volume and, by extension, installs or MAUs, is perhaps the best indicator of ranks, with a 29–40% correlation between the two.

Revisiting our first (albeit oversimplified) guess at the app stores’ ranking algorithm gives us this loosely defined function:

Ranking = fn(Rating, Rating Count, Installs, Trends)

I’d now re-write the function into a formula by weighing each of these four factors, where a, b, c, & d are unknown multipliers, or weights:

Ranking = (Rating * a) + (Rating Count * b) + (Installs * c) + (Trends * d)

These five studies on ASO shed a little more light on these multipliers, showing Rating Count to have the strongest correlation with rank, followed closely by Installs, in either app store.

It’s with the other two factors—rating and trends—that the two stores show the greatest discrepancy. I’d hazard a guess to say that the App Store prioritizes growth trends over ratings, given the importance it places on an app’s current version and the wide distribution of ratings across the top charts. Google Play, on the other hand, seems to favor ratings, with an unwritten rule that apps just about have to have at least four stars to make the top 100 ranks.

Thus, we conclude our mad science with this final glimpse into what it takes to make the top charts in either store:

Weight of factors in the Apple App Store ranking algorithm

Rating Count > Installs > Trends > Rating

Weight of factors in the Google Play ranking algorithm

Rating Count > Installs > Rating > Trends


Again, we’re oversimplifying for the sake of keeping this post to a mere 3,000 words, but additional factors including keyword density and in-app engagement statistics continue to be strong indicators of ranks. They simply lie outside the scope of these studies.

I hope you found this deep-dive both helpful and interesting. Moving forward, I also hope to see ASOs conducting the same experiments that have brought SEO to the center stage, and encourage you to enhance or refute these findings with your own ASO mad science experiments.

Please share your thoughts in the comments below, and let’s deconstruct the ranking formula together, one experiment at a time.

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The Nifty Guide to Local Content Strategy and Marketing

Posted by NiftyMarketing

This is my Grandma.

She helped raised me and I love her dearly. That chunky baby with the Gerber cheeks is
me. The scarlet letter “A” means nothing… I hope.

This is a rolled up newspaper. 

rolled up newspaper

When I was growing up, I was the king of mischief and had a hard time following parental guidelines. To ensure the lessons she wanted me to learn “sunk in” my grandma would give me a soft whack with a rolled up newspaper and would say,

“Mike, you like to learn the hard way.”

She was right. I have
spent my life and career learning things the hard way.

Local content has been no different. I started out my career creating duplicate local doorway pages using “find and replace” with city names. After getting whacked by the figurative newspaper a few times, I decided there had to be a better way. To save others from the struggles I experienced, I hope that the hard lessons I have learned about local content strategy and marketing help to save you fearing a rolled newspaper the same way I do.

Lesson one: Local content doesn’t just mean the written word

local content ecosystem

Content is everything around you. It all tells a story. If you don’t have a plan for how that story is being told, then you might not like how it turns out. In the local world, even your brick and mortar building is a piece of content. It speaks about your brand, your values, your appreciation of customers and employees, and can be used to attract organic visitors if it is positioned well and provides a good user experience. If you just try to make the front of a building look good, but don’t back up the inside inch by inch with the same quality, people will literally say, “Hey man, this place sucks… let’s bounce.”

I had this experience proved to me recently while conducting an interview at
Nifty for our law division. Our office is a beautifully designed brick, mustache, animal on the wall, leg lamp in the center of the room, piece of work you would expect for a creative company.

nifty offices idaho

Anywho, for our little town of Burley, Idaho it is a unique space, and helps to set apart our business in our community. But, the conference room has a fluorescent ballast light system that can buzz so loudly that you literally can’t carry on a proper conversation at times, and in the recent interviews I literally had to conduct them in the dark because it was so bad.

I’m cheap and slow to spend money, so I haven’t got it fixed yet. The problem is I have two more interviews this week and I am so embarrassed by the experience in that room, I am thinking of holding them offsite to ensure that we don’t product a bad content experience. What I need to do is just fix the light but I will end up spending weeks going back and forth with the landlord on whose responsibility it is.

Meanwhile, the content experience suffers. Like I said, I like to learn the hard way.

Start thinking about everything in the frame of content and you will find that you make better decisions and less costly mistakes.

Lesson two: Scalable does not mean fast and easy growth

In every sales conversation I have had about local content, the question of scalability comes up. Usually, people want two things:

  1. Extremely Fast Production 
  2. Extremely Low Cost

While these two things would be great for every project, I have come to find that there are rare cases where quality can be achieved if you are optimizing for fast production and low cost. A better way to look at scale is as follows:

The rate of growth in revenue/traffic is greater than the cost of continued content creation.

A good local content strategy at scale will create a model that looks like this:

scaling content graph

Lesson three: You need a continuous local content strategy

This is where the difference between local content marketing and content strategy kicks in. Creating a single piece of content that does well is fairly easy to achieve. Building a true scalable machine that continually puts out great local content and consistently tells your story is not. This is a graph I created outlining the process behind creating and maintaining a local content strategy:

local content strategy

This process is not a one-time thing. It is not a box to be checked off. It is a structure that should become the foundation of your marketing program and will need to be revisited, re-tweaked, and replicated over and over again.

1. Identify your local audience

Most of you reading this will already have a service or product and hopefully local customers. Do you have personas developed for attracting and retaining more of them? Here are some helpful tools available to give you an idea of how many people fit your personas in any given market.

Facebook Insights

Pretend for a minute that you live in the unique market of Utah and have a custom wedding dress line. You focus on selling modest wedding dresses. It is a definite niche product, but one that shows the idea of personas very well.

You have interviewed your customer base and found a few interests that your customer base share. Taking that information and putting it into Facebook insights will give you a plethora of data to help you build out your understanding of a local persona.

facebook insights data

We are able to see from the interests of our customers there are roughly 6k-7k current engaged woman in Utah who have similar interests to our customer base.

The location tab gives us a break down of the specific cities and, understandably, Salt Lake City has the highest percentage with Provo (home of BYU) in second place. You can also see pages this group would like, activity levels on Facebook, and household income with spending habits. If you wanted to find more potential locations for future growth you can open up the search to a region or country.

localized facebook insights data

From this data it’s apparent that Arizona would be a great expansion opportunity after Utah.

Neilson Prizm

Neilson offers a free and extremely useful tool for local persona research called Zip Code Lookup that allows you to identify pre-determined personas in a given market.

Here is a look at my hometown and the personas they have developed are dead on.

Neilson Prizm data

Each persona can be expanded to learn more about the traits, income level, and areas across the country with other high concentrations of the same persona group.

You can also use the segment explorer to get a better idea of pre-determined persona lists and can work backwards to determine the locations with the highest density of a given persona.

Google Keyword Planner Tool

The keyword tool is fantastic for local research. Using our same Facebook Insight data above we can match keyword search volume against the audience size to determine how active our persona is in product research and purchasing. In the case of engaged woman looking for dresses, it is a very active group with a potential of 20-30% actively searching online for a dress.

google keyword planner tool

2. Create goals and rules

I think the most important idea for creating the goals and rules around your local content is the following from the must read book Content Strategy for the Web.

You also need to ensure that everyone who will be working on things even remotely related to content has access to style and brand guides and, ultimately, understands the core purpose for what, why, and how everything is happening.

3. Audit and analyze your current local content

The point of this step is to determine how the current content you have stacks up against the goals and rules you established, and determine the value of current pages on your site. With tools like Siteliner (for finding duplicate content) and ScreamingFrog (identifying page titles, word count, error codes and many other things) you can grab a lot of information very fast. Beyond that, there are a few tools that deserve a more in-depth look.

BuzzSumo

With BuzzSumo you can see social data and incoming links behind important pages on your site. This can you a good idea which locations or areas are getting more promotion than others and identify what some of the causes could be.

Buzzsumo also can give you access to competitors’ information where you might find some new ideas. In the following example you can see that one of Airbnb.com’s most shared pages was a motiongraphic of its impact on Berlin.

Buzzsumo

urlProfiler

This is another great tool for scraping urls for large sites that can return about every type of measurement you could want. For sites with 1000s of pages, this tool could save hours of data gathering and can spit out a lovely formatted CSV document that will allow you to sort by things like word count, page authority, link numbers, social shares, or about anything else you could imagine.

url profiler

4. Develop local content marketing tactics

This is how most of you look when marketing tactics are brought up.

monkey

Let me remind you of something with a picture. 

rolled up newspaper

Do not start with tactics. Do the other things first. It will ensure your marketing tactics fall in line with a much bigger organizational movement and process. With the warning out of the way, here are a few tactics that could work for you.

Local landing page content

Our initial concept of local landing pages has stood the test of time. If you are scared to even think about local pages with the upcoming doorway page update then please read this analysis and don’t be too afraid. Here are local landing pages that are done right.

Marriott local content

Marriot’s Burley local page is great. They didn’t think about just ensuring they had 500 unique words. They have custom local imagery of the exterior/interior, detailed information about the area’s activities, and even their own review platform that showcases both positive and negative reviews with responses from local management.

If you can’t build your own platform handling reviews like that, might I recommend looking at Get Five Stars as a platform that could help you integrate reviews as part of your continuous content strategy.

Airbnb Neighborhood Guides

I not so secretly have a big crush on Airbnb’s approach to local. These neighborhood guides started it. They only have roughly 21 guides thus far and handle one at a time with Seoul being the most recent addition. The idea is simple, they looked at extremely hot markets for them and built out guides not just for the city, but down to a specific neighborhood.

air bnb neighborhood guides

Here is a look at Hell’s Kitchen in New York by imagery. They hire a local photographer to shoot the area, then they take some of their current popular listing data and reviews and integrate them into the page. This idea would have never flown if they only cared about creating content that could be fast and easy for every market they serve.

Reverse infographicing

Every decently sized city has had a plethora of infographics made about them. People spent the time curating information and coming up with the concept, but a majority just made the image and didn’t think about the crawlability or page title from an SEO standpoint.

Here is an example of an image search for Portland infographics.

image search results portland infographics

Take an infographic and repurpose it into crawlable content with a new twist or timely additions. Usually infographics share their data sources in the footer so you can easily find similar, new, or more information and create some seriously compelling data based content. You can even link to or share the infographic as part of it if you would like.

Become an Upworthy of local content

No one I know does this better than Movoto. Read the link for their own spin on how they did it and then look at these examples and share numbers from their local content.

60k shares in Boise by appealing to that hometown knowledge.

movoto boise content

65k shares in Salt Lake following the same formula.

movoto salt lake city content

It seems to work with video as well.

movoto video results

Think like a local directory

Directories understand where content should be housed. Not every local piece should be on the blog. Look at where Trip Advisor’s famous “Things to Do” page is listed. Right on the main city page.

trip advisor things to do in salt lake city

Or look at how many timely, fresh, quality pieces of content Yelp is showcasing from their main city page.

yelp main city page

The key point to understand is that local content isn’t just about being unique on a landing page. It is about BEING local and useful.

Ideas of things that are local:

  • Sports teams
  • Local celebrities or heroes 
  • Groups and events
  • Local pride points
  • Local pain points

Ideas of things that are useful:

  • Directions
  • Favorite local sports
  • Granular details only “locals” know

The other point to realize is that in looking at our definition of scale you don’t need to take shortcuts that un-localize the experience for users. Figure and test a location at a time until you have a winning formula and then move forward at a speed that ensures a quality local experience.

5. Create a content calendar

I am not going to get into telling you exactly how or what your content calendar needs to include. That will largely be based on the size and organization of your team and every situation might call for a unique approach. What I will do is explain how we do things at Nifty.

  1. We follow the steps above.
  2. We schedule the big projects and timelines first. These could be months out or weeks out. 
  3. We determine the weekly deliverables, checkpoints, and publish times.
  4. We put all of the information as tasks assigned to individuals or teams in Asana.

asana content calendar

The information then can be viewed by individual, team, groups of team, due dates, or any other way you would wish to sort. Repeatable tasks can be scheduled and we can run our entire operation visible to as many people as need access to the information through desktop or mobile devices. That is what works for us.

6. Launch and promote content

My personal favorite way to promote local content (other than the obvious ideas of sharing with your current followers or outreaching to local influencers) is to use Facebook ads to target the specific local personas you are trying to reach. Here is an example:

I just wrapped up playing Harold Hill in our communities production of The Music Man. When you live in a small town like Burley, Idaho you get the opportunity to play a lead role without having too much talent or a glee-based upbringing. You also get the opportunity to do all of the advertising, set design, and costuming yourself and sometime even get to pay for it.

For my advertising responsibilities, I decided to write a few blog posts and drive traffic to them. As any good Harold Hill would do, I used fear tactics.

music man blog post

I then created Facebook ads that had the following stats: Costs of $.06 per click, 12.7% click through rate, and naturally organic sharing that led to thousands of visits in a small Idaho farming community where people still think a phone book is the only way to find local businesses.

facebook ads setup

Then we did it again.

There was a protestor in Burley for over a year that parked a red pickup with signs saying things like, “I wud not trust Da Mayor” or “Don’t Bank wid Zions”. Basically, you weren’t working hard enough if you name didn’t get on the truck during the year.

Everyone knew that ol’ red pickup as it was parked on the corner of Main and Overland, which is one of the few stoplights in town. Then one day it was gone. We came up with the idea to bring the red truck back, put signs on it that said, “I wud Not Trust Pool Tables” and “Resist Sins n’ Corruption” and other things that were part of The Music Man and wrote another blog complete with pictures.

facebook ads red truck

Then I created another Facebook Ad.

facebook ads set up

A little under $200 in ad spend resulted in thousands more visits to the site which promoted the play and sold tickets to a generation that might not have been very familiar with the show otherwise.

All of it was local targeting and there was no other way would could have driven that much traffic in a community like Burley without paying Facebook and trying to create click bait ads in hope the promotion led to an organic sharing.

7. Measure and report

This is another very personal step where everyone will have different needs. At Nifty we put together very custom weekly or monthly reports that cover all of the plan, execution, and relevant stats such as traffic to specific content or location, share data, revenue or lead data if available, analysis of what worked and what didn’t, and the plan for the following period.

There is no exact data that needs to be shared. Everyone will want something slightly different, which is why we moved away from automated reporting years ago (when we moved away from auto link building… hehe) and built our report around our clients even if it took added time.

I always said that the product of a SEO or content shop is the report. That is what people buy because it is likely that is all they will see or understand.

8. In conclusion, you must refine and repeat the process

local content strategy - refine and repeat

From my point of view, this is by far the most important step and sums everything up nicely. This process model isn’t perfect. There will be things that are missed, things that need tweaked, and ways that you will be able to improve on your local content strategy and marketing all the time. The idea of the cycle is that it is never done. It never sleeps. It never quits. It never surrenders. You just keep perfecting the process until you reach the point that few locally-focused companies ever achieve… where your local content reaches and grows your target audience every time you click the publish button.

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Moz’s 2014 Annual Report

Posted by SarahBird

Moz has a tradition of sharing its financials (check out 2012 and 2013 for funzies). It’s an important part of TAGFEE.

Why do we do it? Moz gets its strength from the community of marketers and entrepreneurs that support it. We celebrated 10 years of our community last October. In some ways, the purpose of this report is to give you an inside look into our company. It’s one of many lenses that tell the story of Moz.

Yep. I know. It’s April. I’m not proud. Better late than never, right?

I had a very long and extensive version of this post planned, something closer to last year’s extravaganza. I finally had to admit to myself that I was letting the perfect become the enemy of the good (or at least the done). There was no way I could capture an entire year’s worth of ups and downs—along with supporting data—in a single blog post.

Without further ado, here’s the meat-and-potatoes 2014 Year In Review (and here’s an infographic with more statistics for your viewing pleasure!):

Moz ended 2014 with $31.3 million in revenue. About $30 million was recurring revenue (mostly from subscriptions to Moz Pro and the API).

Here’s a breakdown of all our major revenue sources:

Compared to previous years, 2014 was a much slower growth year. We knew very early that it was going to be a tough year because we started Q1 with negative growth. We worked very hard and successfully shifted the momentum back to increasingly positive quarterly growth rates. I’m proud of what we’ve accomplished so far. We still have a long ways to go to meet our potential, but we’re on the path.

In subscription businesses, If you start the year with negative or even slow growth it is very hard to have meaningful annual growth. All things being equal, you’re better off having a bad quarter in Q4 than Q1. If you get a new customer in Q1, you usually earn revenue from that customer all year. If you get a new customer in Q4, it will barely make a dent in that year, although it should set you up nicely for the following year.

We exited 2014 on a good flight path, which bodes well for 2015. We slammed right into some nasty billing system challenges in Q1 2015, but still managed to grow revenue 6.5%. Mad props to the team for shifting momentum last year and for digging into the billing system challenges we’re experiencing now.

We were very successful in becoming more efficient and managing costs in 2014. Our Cost of Revenue (COR), the cost of producing what we sell, fell by 30% to $8.2 million. These savings drove our gross profit margin up from 63% in 2013 to 74%.

Our operating profit increased by 30%. Here’s a breakdown of our major expenses (both operating expenses and COR):

Total operating expenses (which don’t include COR) clocked in at about $29.9 million this year.

The efficiency gains positively impacted EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) by pushing it up 50% year over year. In 2013, EBITDA was -$4.5 million. We improved it to -$2.1 million in 2014. We’re a VC-backed startup, so this was a planned loss.

One of the most dramatic indicators of our improved efficiency in 2014 is the substantial decline in our consumption of cash.

In 2014, we spent $1.5 million in cash. This was a planned burn, and is actually very impressive for a startup. In fact, we are intentionally increasing our burn, so we don’t expect EBITDA and cash burn to look as good in 2015! Hopefully, though, you will see that revenue growth rate increase.

Let’s check in on some other Moz KPIs:

At the end of 2014, we reported a little over 27,000 Pro users. When billing system issues hit in Q1 2015, we discovered some weird under- and over-reporting, so the number of subscribers was adjusted down by about ~450 after we scrubbed a bunch of inactive accounts out of the database. We expect accounts to stabilize and be more reliable now that we’ve fixed those issues.

We launched Moz Local about a year ago. I’m amazed and thrilled that we were able to end the year managing 27,000 locations for a range of customers. We just recently took our baby steps into the UK, and we’ve got a bunch of great additional features planned. What an incredible launch year!

We published over 300 posts combined on the Moz Blog and YouMoz. Nearly 20,000 people left comments. Well done, team!

Our content and social efforts are paying off with a 26% year-over-year increase in organic search traffic.

We continue to see good growth across many of our off-site communities, too:

The team grew to 149 people last year. We’re at ~37% women, which is nowhere near where I want it to be. We have a long way to go before the team reflects the diversity of the communities around us.

Our paid, paid vacation perk is very popular with Mozzers, and why wouldn’t it be? Everyone gets $3,000/year to use toward their vacations. In 2014, we spent over $420,000 to help our Mozzers take a break and get connected with matters most.

PPV.png

Also, we’re hiring! You’ll have my undying gratitude if you send me your best software engineers. Help us, help you. 😉

Last, but certainly not least, Mozzers continue to be generous (the ‘G’ in TAGFEE) and donate to the charities of their choice. In 2014, Mozzers donated $48k, and Moz added another $72k to increase the impact of their gifts. Combining those two figures, we donated $120k to causes our team members are passionate about. That’s an average of $805 per employee!

Mozzers are optimists with initiative. I think that’s why they are so generous with their time and money to folks in need. They believe the world can be a better place if we act to change it.

That’s a wrap on 2014! A year with many ups and downs. Fortunately, Mozzers don’t quit when things get hard. They embrace TAGFEE and lean into the challenge.

Revenue is growing again. We’re still operating very efficiently, and TAGFEE is strong. We’re heads-down executing on some big projects that customers have been clamoring for. Thank you for sticking with us, and for inspiring us to make marketing better every day.

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​Inbound Lead Generation: eCommerce Marketing’s Missing Link

Posted by Everett

If eCommerce businesses hope to remain competitive with Amazon, eBay, big box brands, and other online retail juggernauts, they’ll need to learn how to conduct content marketing, lead generation, and contact nurturing as part of a comprehensive inbound marketing strategy.

First, I will discuss some of the ways most online retailers are approaching email from the bottom of the funnel upward, and why this needs to be turned around. Then we can explore how to go about doing this within the framework of “Inbound Marketing” for eCommerce businesses. Lastly, popular marketing automation and email marketing solutions are discussed in the context of inbound marketing for eCommerce.

Key differences between eCommerce and lead generation approaches to email

Different list growth strategies

Email acquisition sources differ greatly between lead gen. sites and online stores. The biggest driver of email acquisition for most eCommerce businesses are their shoppers, especially when the business doesn’t collect an email address for their contact database until the shopper provides it during the check-out process—possibly, not until the very end.

With most B2B/B2C lead gen. websites, the entire purpose of every landing page is to get visitors to submit a contact form or pick up the phone. Often, the price tag for their products or services is much higher than those of an eCommerce site or involves recurring payments. In other words, what they’re selling is more difficult to sell. People take longer to make those purchasing decisions. For this reason, leads—in the form of contact names and email addresses—are typically acquired and nurtured without having first become a customer.

Contacts vs. leads

Whether it is a B2B or B2C website, lead gen. contacts (called leads) are thought of as potential customers (clients, subscribers, patients) who need to be nurtured to the point of becoming “sales qualified,” meaning they’ll eventually get a sales call or email that attempts to convert them into a customer.

On the other hand, eCommerce contacts are often thought of primarily as existing customers to whom the marketing team can blast coupons and other offers by email.

Retail sites typically don’t capture leads at the top or middle of the funnel. Only once a shopper has checked out do they get added to the list. Historically, the buying cycle has been short enough that eCommerce sites could move many first-time visitors directly to customers in a single visit.
But this has changed.

Unless your brand is very strong—possibly a luxury brand or one with an offline retail presence—it is probably getting more difficult (i.e. expensive) to acquire new customers. At the same time, attrition rates are rising. Conversion optimization helps by converting more bottom of the funnel visitors. SEO helps drive more traffic into the site, but mostly for middle-of-funnel (category page) and bottom-of-funnel (product page) visitors who may not also be price/feature comparison shopping, or are unable to convert right away because of device or time limitations.

Even savvy retailers publishing content for shoppers higher up in the funnel, such as buyer guides and reviews, aren’t getting an email address and are missing a lot of opportunities because of it.

attract-convert-grow-funnel-inflow-2.jpg

Here’s a thought. If your eCommerce site has a 10 percent conversion rate, you’re doing pretty good by most standards. But what happened to the other 90 percent of those visitors? Will you have the opportunity to connect with them again? Even if you bump that up a few percentage points with retargeting, a lot of potential revenue has seeped out of your funnel without a trace.

I don’t mean to bash the eCommerce marketing community with generalizations. Most lead gen. sites aren’t doing anything spectacular either, and a lot of opportunity is missed all around.

There are many eCommerce brands doing great things marketing-wise. I’m a big fan of
Crutchfield for their educational resources targeting early-funnel traffic, and Neman Tools, Saddleback Leather and Feltraiger for the stories they tell. Amazon is hard to beat when it comes to scalability, product suggestions and user-generated reviews.

Sadly, most eCommerce sites (including many of the major household brands) still approach marketing in this way…

The ol’ bait n’ switch: promising value and delivering spam

Established eCommerce brands have gigantic mailing lists (compared with lead gen. counterparts), to whom they typically send out at least one email each week with “offers” like free shipping, $ off, buy-one-get-one, or % off their next purchase. The lists are minimally segmented, if at all. For example, there might be lists for repeat customers, best customers, unresponsive contacts, recent purchasers, shoppers with abandoned carts, purchases by category, etc.

The missing points of segmentation include which campaign resulted in the initial contact (sometimes referred to as a cohort) and—most importantly—the persona and buying cycle stage that best applies to each contact.

Online retailers often send frequent “blasts” to their entire list or to a few of the large segments mentioned above. Lack of segmentation means contacts aren’t receiving emails based on their interests, problems, or buying cycle stage, but instead, are receiving what they perceive as “generic” emails.

The result of these missing segments and the lack of overarching strategy looks something like this:

My, What a Big LIST You Have!

iStock_000017047747Medium.jpg

TIME reported in 2012 on stats from Responsys that the average online retailer sent out between five and six emails the week after Thanksgiving. Around the same time, the Wall Street Journal reported that the top 100 online retailers sent an average of 177 emails apiece to each of their contacts in 2011. Averaged out, that’s somewhere between three and four emails each week that the contact is receiving from these retailers.

The better to SPAM you with!

iStock_000016088853Medium.jpg

A 2014 whitepaper from SimpleRelevance titled
Email Fail: An In-Depth Evaluation of Top 20 Internet Retailer’s Email Personalization Capabilities (
PDF) found that, while 70 percent of marketing executives believed personalization was of “utmost importance” to their business…

“Only 17 percent of marketing leaders are going beyond basic transactional data to deliver personalized messages to consumers.”

Speaking of email overload, the same report found that some major online retailers sent ten or more emails per week!

simplerelevance-email-report-frequency.png

The result?

All too often, the eCommerce business will carry around big, dead lists of contacts who don’t even bother reading their emails anymore. They end up scrambling toward other channels to “drive more demand,” but because the real problems were never addressed, this ends up increasing new customer acquisition costs.

The cycle looks something like this:

  1. Spend a fortune driving in unqualified traffic from top-of-the-funnel channels
  2. Ignore the majority of those visitors who aren’t ready to purchase
  3. Capture email addresses only for the few visitors who made a purchase
  4. Spam the hell out of those people until they unsubscribe
  5. Spend a bunch more money trying to fill the top of the funnel with even more traffic

It’s like trying to fill your funnel with a bucket full of holes, some of them patched with band-aids.

The real problems

  1. Lack of a cohesive strategy across marketing channels
  2. Lack of a cohesive content strategy throughout all stages of the buying cycle
  3. Lack of persona, buying cycle stage, and cohort-based list segmentation to nurture contacts
  4. Lack of tracking across customer touchpoints and devices
  5. Lack of gated content that provides enough value to early-funnel visitors to get them to provide their email address

So, what’s the answer?

Inbound marketing allows online retailers to stop competing with Amazon and other “price focused” competitors with leaky funnels, and to instead focus on:

  1. Persona-based content marketing campaigns designed to acquire email addresses from high-quality leads (potential customers) by offering them the right content for each stage in their buyer’s journey
  2. A robust marketing automation system that makes true personalization scalable
  3. Automated contact nurturing emails triggered by certain events, such as viewing specific content, abandoning their shopping cart, adding items to their wish list or performing micro-conversions like downloading a look book
  4. Intelligent SMM campaigns that match visitors and customers with social accounts by email addresses, interests and demographics—as well as social monitoring
  5. Hyper-segmented email contact lists to support the marketing automation described above, as well as to provide highly-customized email and shopping experiences
  6. Cross-channel, closed loop reporting to provide a complete “omnichannel” view of online marketing efforts and how they assist offline conversions, if applicable

Each of these areas will be covered in more detail below. First, let’s take a quick step back and define what it is we’re talking about here.

Inbound marketing: a primer

A lot of people think “inbound marketing” is just a way some SEO agencies are re-cloaking themselves to avoid negative associations with search engine optimization. Others think it’s synonymous with “internet marketing.” I think it goes more like this:

Inbound marketing is to Internet marketing as SEO is to inbound marketing: One piece of a larger whole.

There are many ways to define inbound marketing. A cursory review of definitions from several trusted sources reveals some fundamental similarities :

Rand Fishkin

randfishkin.jpeg

“Inbound Marketing is the practice of earning traffic and attention for your business on the web rather than buying it or interrupting people to get it. Inbound channels include organic search, social media, community-building content, opt-in email, word of mouth, and many others. Inbound marketing is particularly powerful because it appeals to what people are looking for and what they want, rather than trying to get between them and what they’re trying to do with advertising. Inbound’s also powerful due to the flywheel-effect it creates. The more you invest in Inbound and the more success you have, the less effort required to earn additional benefit.”


Mike King

mikeking.jpeg

“Inbound Marketing is a collection of marketing activities that leverage remarkable content to penetrate earned media channels such as Organic Search, Social Media, Email, News and the Blogosphere with the goal of engaging prospects when they are specifically interested in what the brand has to offer.”

This quote is from 2012, and is still just as accurate today. It’s from an
Inbound.org comment thread where you can also see many other takes on it from the likes of Ian Lurie, Jonathon Colman, and Larry Kim.


Inflow

inflow-logo.jpeg

“Inbound Marketing is a multi-channel, buyer-centric approach to online marketing that involves attracting, engaging, nurturing and converting potential customers from wherever they are in the buying cycle.”

From Inflow’s
Inbound Services page.


Wikipedia

wikipedia.jpeg

“Inbound marketing refers to marketing activities that bring visitors in, rather than marketers having to go out to get prospects’ attention. Inbound marketing earns the attention of customers, makes the company easy to be found, and draws customers to the website by producing interesting content.”

From
Inbound Marketing – Wikipedia.


Larry-Kim.jpeg

Larry Kim

“Inbound marketing” refers to marketing activities that bring leads and customers in when they’re ready, rather than you having to go out and wave your arms to try to get people’s attention.”

Via
Marketing Land in 2013. You can also read more of Larry Kim’s interpretation, along with many others, on Inbound.org.


Hubspot

“Instead of the old outbound marketing methods of buying ads, buying email lists, and praying for leads, inbound marketing focuses on creating quality content that pulls people toward your company and product, where they naturally want to be.”

Via
Hubspot, a marketing automation platform for inbound marketing.

When everyone has their own definition of something, it helps to think about what they have in common, as opposed to how they differ. In the case of inbound, this includes concepts such as:

  • Pull (inbound) vs. push (interruption) marketing
  • “Earning” media coverage, search engine rankings, visitors and customers with outstanding content
  • Marketing across channels
  • Meeting potential customers where they are in their buyer’s journey

Running your first eCommerce inbound marketing campaign

Audience personas—priority no. 1

The magic happens when retailers begin to hyper-segment their list based on buyer personas and other relevant information (i.e. what they’ve downloaded, what they’ve purchased, if they abandoned their cart…). This all starts with audience research to develop personas. If you need more information on persona development, try these resources:

Once personas are developed, retailers should choose one on which to focus. A complete campaign strategy should be developed around this persona, with the aim of providing the “right value” to them at the “right time” in their buyer’s journey.

Ready to get started?

We’ve developed a quick-start guide in the form of a checklist for eCommerce marketers who want to get started with inbound marketing, which you can access below.

inbound ecommerce checklist

Hands-on experience running one campaign will teach you more about inbound marketing than a dozen articles. My advice: Just do one. You will make mistakes. Learn from them and get better each time.

Example inbound marketing campaign

Below is an example of how a hypothetical inbound marketing campaign might play out, assuming you have completed all of the steps in the checklist above. Imagine you handle marketing for an online retailer of high-end sporting goods.

AT Hiker Tommy campaign: From awareness to purchase

When segmenting visitors and customers for a “high-end sporting goods / camping retailer” based on the East Coast, you identified a segment of “Trail Hikers.” These are people with disposable income who care about high-quality gear, and will pay top dollar if they know it is tested and reliable. The top trail on their list of destinations is the
Appalachian Trail (AT).

Top of the Funnel: SEO & Strategic Content Marketing

at-tommy.jpg

Tommy’s first action is to do “top of the funnel” research from search engines (one reason why SEO is still so important to a complete inbound marketing strategy).

A search for “Hiking the Appalachian Trail” turns up your article titled “What NOT to Pack When Hiking the Appalachian Trail,” which lists common items that are bulky/heavy, and highlights slimmer, lighter alternatives from your online catalog.

It also highlights the difference between cheap gear and the kind that won’t let you down on your 2,181 mile journey through the wilderness of Appalachia, something you learned was important to Tommy when developing his persona. This allows you to get the company’s value proposition of “tested, high-end, quality gear only” in front of readers very early in their buyer’s journey—important if you want to differentiate your site from all of the retailers racing Amazon to the bottom of their profit margins.

So far you have yet to make “contact” with AT Hiker Tommy. The key to “acquiring” a contact before the potential customer is ready to make a purchase is to provide something of value to that specific type of person (i.e. their persona) at that specific point in time (i.e. their buying cycle stage).

In this case, we need to provide value to AT Hiker Tommy while he is getting started on his research about hiking the Appalachian Trail. He has an idea of what gear not to bring, as well as some lighter, higher-end options sold on your site. At this point, however, he is not ready to buy anything without researching the trail more. This is where retailers lose most of their potential customers. But not you. Not this time…

Middle of the funnel: Content offers, personalization, social & email nurturing

at-hiker-ebook.png

On the “What NOT to Pack When Hiking the Appalachian Trail” article (and probably several others), you have placed a call-to-action (CTA) in the form of a button that offers something like:

Download our Free 122-page Guide to Hiking the Appalachian Trail

This takes Tommy to a landing page showcasing some of the quotes from the book, and highlighting things like:

“We interviewed over 50 ‘thru-hikers’ who completed the AT and have curated and organized the best first-hand tips, along with our own significant research to develop a free eBook that should answer most of your questions about the trail.”

By entering their email address potential customers agree to allow you to send them the free PDF downloadable guide to hiking the AT, and other relevant information about hiking.

An automated email is sent with a link to the downloadable PDF guide, and several other useful content links, such as “The AT Hiker’s Guide to Gear for the Appalachian Trail”—content designed to move Tommy further toward the purchase of hiking gear.

If Tommy still has not made a purchase within the next two weeks, another automated email is sent asking for feedback about the PDF guide (providing the link again), and to again provide the link to the “AT Hiker’s Guide to Gear…” along with a compelling offer just for him, perhaps “Get 20% off your first hiking gear purchase, and a free wall map of the AT!”

Having Tommy’s email address also allows you to hyper-target him on social channels, while also leveraging his initial visit to initiate retargeting efforts.

Bottom of the funnel: Email nurturing & strategic, segmented offers

Eventually Tommy makes a purchase, and he may or may not receive further emails related to this campaign, such as post-purchase emails for reviews, up-sells and cross-sells.

Upon checkout, Tommy checked the box to opt-in to weekly promotional emails. He is now on multiple lists. Your marketing automation system will automatically update Tommy’s status from “Contact” or lead, to “Customer” and potentially remove or deactivate him from the marketing automation system database. This is accomplished either by default integration features, or with the help of integration tools like
Zapier and IFTTT.

You have now nurtured Tommy from his initial research on Google all the way to his first purchase without ever having sent a spammy newsletter email full of irrelevant coupons and other offers. However, now that he is a loyal customer, Tommy finds value in these bottom-of-funnel email offers.

And this is just the start

Every inbound marketing campaign will have its own mix of appropriate channels. This post has focused mostly on email because acquiring the initial permission to contact the person is what fuels most of the other features offered by marketing automation systems, including:

  • Personalization of offers and other content on the site.
  • Knowing exactly which visitors are interacting on social media
  • Knowing where visitors and social followers are in the buying cycle and which persona best represents them, among other things.
  • Smart forms that don’t require visitors to put in the same information twice and allow you to build out more detailed profiles of them over time.
  • Blogging platforms that tie into email and marketing automation systems
  • Analytics data that isn’t blocked by Google and is tied directly to real people.
  • Closed-loop reporting that integrates with call-tracking and Google’s Data Import tool
  • Up-sell, cross-sell, and abandoned cart reclamation features
Three more things…
  1. If you can figure out a way to get Tommy to “log in” when he comes to your site, the personalization possibilities are nearly limitless.
  2. The persona above is based on a real customer segment. I named it after my friend Tommy Bailey, who actually did write the eBook
    Guide to Hiking the Appalachian Trail, featured in the image above.
  3. This Moz post is part of an inbound marketing campaign targeting eCommerce marketers, a segment Inflow identified while building out our own personas. Our hope, and the whole point of inbound marketing, is that it provides value to you.

Current state of the inbound marketing industry

Inbound has, for the the most part, been applied to businesses in which the website objective is to generate leads for a sales team to follow-up with and close the deal. An examination of various marketing automation platforms—a key component of scalable inbound marketing programs—highlights this issue.

Popular marketing automation systems

Most of the major marketing automation systems can be be used very effectively as the backbone of an inbound marketing program for eCommerce businesses. However, only one of them (Silverpop) has made significant efforts to court the eCommerce market with content and out-of-box features. The next closest thing is Hubspot, so let’s start with those two:

Silverpop – an IBMⓇ Company

silver-pop.jpeg

Unlike the other platforms below, right out of the box Silverpop allows marketers to tap into very specific behaviors, including the items purchased or left in the cart.

You can easily segment based on metrics like the Recency, Frequency and Monetary Value (RFM) of purchases:

silverpop triggered campaigns

You can automate personalized shopping cart abandonment recovery emails:

silverpop cart abandonment recovery

You can integrate with many leading brands offering complementary services, including: couponing, CRM, analytics, email deliverability enhancement, social and most major eCommerce platforms.

What you can’t do with Silverpop is blog, find pricing info on their website, get a free trial on their website or have a modern-looking user experience. Sounds like an IBMⓇ company, doesn’t it?

HubSpot

Out of all the marketing automation platforms on this list, HubSpot is the most capable of handling “inbound marketing” campaigns from start to finish. This should come as no surprise, given the phrase is credited to
Brian Halligan, HubSpot’s co-founder and CEO.

While they don’t specifically cater to eCommerce marketing needs with the same gusto they give to lead gen. marketing, HubSpot does have
an eCommerce landing page and a demo landing page for eCommerce leads, which suggests that their own personas include eCommerce marketers. Additionally, there is some good content on their blog written specifically for eCommerce.

HubSpot has allowed some key partners to develop plug-ins that integrate with leading eCommerce platforms. This approach works well with curation, and is not dissimilar to how Google handles Android or Apple handles their approved apps.

magento and hubspot

The
Magento Connector for HubSpot, which costs $80 per month, was developed by EYEMAGiNE, a creative design firm for eCommerce websites. A similar HubSpot-approved third-party integration is on the way for Bigcommerce.

Another eCommerce integration for Hubspot is a Shopify plug-in called
HubShoply, which was developed by Groove Commerce and costs $100 per month.

You can also use HubSpot’s native integration capabilities with
Zapier to sync data between HubSpot and most major eCommerce SaaS vendors, including the ones above, as well as WooCommerce, Shopify, PayPal, Infusionsoft and more. However, the same could be said of some of the other marketing automation platforms, and using these third-party solutions can sometimes feel like fitting a square peg into a round hole.

HubSpot can and does handle inbound marketing for eCommerce websites. All of the features are there, or easy enough to integrate. But let’s put some pressure on them to up their eCommerce game even more. The least they can do is put an eCommerce link in the footer:

hubspot menus

Despite the lack of clear navigation to their eCommerce content, HubSpot seems to be paying more attention to the needs of eCommerce businesses than the rest of the platforms below.

Marketo

Nothing about Marketo’s in-house marketing strategy suggests “Ecommerce Director Bob” might be one of their personas. The description for each of
their marketing automation packages (from Spark to Enterprise) mentions that it is “for B2B” websites.

marketo screenshot

Driving Sales could apply to a retail business so I clicked on the link. Nope. Clearly, this is for lead generation.

marketo marketing automation

Passing “purchase-ready leads” over to your “sales reps” is a good example of the type of language used throughout the site.

Make no mistake, Marketo is a top-notch marketing automation platform. Powerful and clean, it’s a shame they don’t launch a full-scale eCommerce version of their core product. In the meantime, there’s the
Magento Integration for Marketo Plug-in developed by an agency out of Australia called Hoosh Marketing.

magento marketo integration

I’ve never used this integration, but it’s part of Marketo’s
LaunchPoint directory, which I imagine is vetted, and Hoosh seems like a reputable agency.

Their
pricing page is blurred and gated, which is annoying, but perhaps they’ll come on here and tell everyone how much they charge.

marketo pricing page

As with all others except Silverpop, the Marketo navigation provides no easy paths to landing pages that would appeal to “Ecommerce Director Bob.”

Pardot

This option is a
SalesForce product, so—though I’ve never had the opportunity to use it—I can imagine Pardot is heavy on B2B/Sales and very light on B2C marketing for retail sites.

The hero image on their homepage says as much.

pardot tagline

pardot marketing automationAgain, no mention of eCommerce or retail, but clear navigation to lead gen and sales.

Eloqua / OMC

eloqua-logo.jpeg

Eloqua, now part of the Oracle Marketing Cloud (OMC), has a landing page
for the retail industry, on which they proclaim:

“Retail marketers know that the path to lifelong loyalty and increased revenue goes through building and growing deep client relationships.”

Since when did retail marketers start calling customers clients?

eloqua integration

The Integration tab on OMC’s “…Retail.html” page helpfully informs eCommerce marketers that their sales teams can continue using CRM systems like SalesForce and Microsoft Dynamics but doesn’t mention anything about eCommerce platforms and other SaaS solutions for eCommerce businesses.

Others

There are many other players in this arena. Though I haven’t used them yet, three I would love to try out are
SharpSpring, Hatchbuck and Act-On. But none of them appear to be any better suited to handle the concerns of eCommerce websites.

Where there’s a gap, there’s opportunity

The purpose of the section above wasn’t to highlight deficiencies in the tools themselves, but to illustrate a gap in who they are being marketed to and developed for.

So far, most of your eCommerce competitors probably aren’t using tools like these because they are not marketed to by the platforms, and don’t know how to apply the technology to online retail in a way that would justify the expense.

The thing is, a tool is just a tool

The
key concepts behind inbound marketing apply just as much to online retail as they do to lead generation.

In order to “do inbound marketing,” a marketing automation system isn’t even strictly necessary (in theory). They just help make the activities scalable for most businesses.

They also bring a lot of different marketing activities under one roof, which saves time and allows data to be moved and utilized between channels and systems. For example, what a customer is doing on social could influence the emails they receive, or content they see on your site. Here are some potential uses for most of the platforms above:

Automated marketing uses

  • Personalized abandoned cart emails
  • Post-purchase nurturing/reorder marketing
  • Welcome campaigns for the newsletter (other free offer) signups
  • Winback campaigns
  • Lead-nurturing email campaigns for cohorts and persona-based segments

Content marketing uses

  • Optimized, strategic blogging platforms, and frameworks
  • Landing pages for pre-transactional/educational offers or contests
  • Social media reporting, monitoring, and publishing
  • Personalization of content and user experience

Reporting uses

  • Revenue reporting (by segment or marketing action)
  • Attribution reporting (by campaign or content)

Assuming you don’t have the budget for a marketing automation system, but already have a good email marketing platform, you can still get started with inbound marketing. Eventually, however, you may want to graduate to a dedicated marketing automation solution to reap the full benefits.

Email marketing platforms

Most of the marketing automation systems claim to replace your email marketing platform, while many email marketing platforms claim to be marketing automation systems. Neither statement is completely accurate.

Marketing automation systems, especially those created specifically for the type of “inbound” campaigns described above, provide a powerful suite of tools all in one place. On the other hand, dedicated email platforms tend to offer “email marketing” features that are better, and more robust, than those offered by marketing automation systems. Some of them are also considerably cheaper—such as
MailChimp—but those are often light on even the email-specific features for eCommerce.

A different type of campaign

Email “blasts” in the form of B.O.G.O., $10 off or free shipping offers can still be very successful in generating incremental revenue boosts — especially for existing customers and seasonal campaigns.

The conversion rate on a 20% off coupon sent to existing customers, for instance, would likely pulverize the conversion rate of an email going out to middle-of-funnel contacts with a link to content (at least with how CR is currently being calculated by email platforms).

Inbound marketing campaigns can also offer quick wins, but they tend to focus mostly on non-customers after the first segmentation campaign (a campaign for the purpose of segmenting your list, such as an incentivised survey). This means lower initial conversion rates, but long-term success with the growth of new customers.

Here’s a good bet if works with your budget: Rely on a marketing automation system for inbound marketing to drive new customer acquisition from initial visit to first purchase, while using a good email marketing platform to run your “promotional email” campaigns to existing customers.

If you have to choose one or the other, I’d go with a robust marketing automation system.

Some of the most popular email platforms used by eCommerce businesses, with a focus on how they handle various Inbound Marketing activities, include:

Bronto

bronto.jpeg

This platform builds in features like abandoned cart recovery, advanced email list segmentation and automated email workflows that nurture contacts over time.

They also offer a host of eCommerce-related
features that you just don’t get with marketing automation systems like Hubspot and Marketo. This includes easy integration with a variety of eCommerce platforms like ATG, Demandware, Magento, Miva Merchant, Mozu and MarketLive, not to mention apps for coupons, product recommendations, social shopping and more. Integration with enterprise eCommerce platforms is one reason why Bronto is seen over and over again when browsing the Internet Retailer Top 500 reports.

On the other hand, Bronto—like the rest of these email platforms—doesn’t have many of the features that assist with content marketing outside of emails. As an “inbound” marketing automation system, it is incomplete because it focuses almost solely on one channel: email.

Vertical Response

verticalresponse.jpeg

Another juggernaut in eCommerce email marketing platforms, Vertical Response, has even fewer inbound-related features than Bronto, though it is a good email platform with a free version that includes up to 1,000 contacts and 4,000 emails per month (i.e. 4 emails to a full list of 1,000).

Oracle Marketing Cloud (OMC)

Responsys (the email platform), like Eloqua (the marketing automation system) was gobbled up by Oracle and is now part of their “Marketing Cloud.”

It has been my experience that when a big technology firm like IBM or Oracle buys a great product, it isn’t “great” for the users. Time will tell.

Listrak

listrak.jpeg

Out of the established email platforms for eCommerce, Listrak may do the best job at positioning themselves as a full inbound marketing platform.

Listrak’s value proposition is that they’re an “Omnichannel” solution. Everything is all in one “Single, Integrated Digital Marketing Platform for Retailers.” The homepage image promises solutions for Email, Mobile, Social, Web and In-Store channels.

I haven’t had the opportunity to work with Listrak yet, but would love to hear feedback in the comments on whether they could handle the kind of persona-based content marketing and automated email nurturing campaigns described in the example campaign above.

Key takeaways

Congratulations for making this far! Here are a few things I hope you’ll take away from this post:

  • There is a lot of opportunity right now for eCommerce sites to take advantage of marketing automation systems and robust email marketing platforms as the infrastructure to run comprehensive inbound marketing campaigns.
  • There is a lot of opportunity right now for marketing automation systems to develop content and build in eCommerce-specific features to lure eCommerce marketers.
  • Inbound marketing isn’t email marketing, although email is an important piece to inbound because it allows you to begin forming lasting relationships with potential customers much earlier in the buying cycle.
  • To see the full benefits of inbound marketing, you should focus on getting the right content to the right person at the right time in their shopping journey. This necessarily involves several different channels, including search, social and email. One of the many benefits of marketing automation systems is their ability to track your efforts here across marketing channels, devices and touch-points.

Tools, resources, and further reading

There is a lot of great content on the topic of Inbound marketing, some of which has greatly informed my own understanding and approach. Here are a few resources you may find useful as well.

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Moving 5 Domains to 1: An SEO Case Study

Posted by Dr-Pete

People often ask me if they should change domain names, and I always shudder just a little. Changing domains is a huge, risky undertaking, and too many people rush into it seeing only the imaginary upside. The success of the change also depends wildly on the details, and it’s not the kind of question anyone should be asking casually on social media.

Recently, I decided that it was time to find a new permanent home for my personal and professional blogs, which had gradually spread out over 5 domains. I also felt my main domain was no longer relevant to my current situation, and it was time for a change. So, ultimately I ended up with a scenario that looked like this:

The top three sites were active, with UserEffect.com being my former consulting site and blog (and relatively well-trafficked). The bottom two sites were both inactive and were both essentially gag sites. My one-pager, AreYouARealDoctor.com, did previously rank well for “are you a real doctor”, so I wanted to try to recapture that.

I started migrating the 5 sites in mid-January, and I’ve been tracking the results. I thought it would be useful to see how this kind of change plays out, in all of the gory details. As it turns out, nothing is ever quite “textbook” when it comes to technical SEO.

Why Change Domains at All?

The rationale for picking a new domain could fill a month’s worth of posts, but I want to make one critical point – changing domains should be about your business goals first, and SEO second. I did not change domains to try to rank better for “Dr. Pete” – that’s a crap shoot at best. I changed domains because my old consulting brand (“User Effect”) no longer represented the kind of work I do and I’m much more known by my personal brand.

That business case was strong enough that I was willing to accept some losses. We went through a similar transition here
from SEOmoz.org to Moz.com. That was a difficult transition that cost us some SEO ground, especially short-term, but our core rationale was grounded in the business and where it’s headed. Don’t let an SEO pipe dream lead you into a risky decision.

Why did I pick a .co domain? I did it for the usual reason – the .com was taken. For a project of this type, where revenue wasn’t on the line, I didn’t have any particular concerns about .co. The evidence on how top-level domains (TLDs) impact ranking is tough to tease apart (so many other factors correlate with .com’s), and Google’s attitude tends to change over time, especially if new TLDs are abused. Anecdotally, though, I’ve seen plenty of .co’s rank, and I wasn’t concerned.

Step 1 – The Boring Stuff

It is absolutely shocking how many people build a new site, slap up some 301s, pull the switch, and hope for the best. It’s less shocking how many of those people end up in Q&A a week later, desperate and bleeding money.


Planning is hard work, and it’s boring – get over it.

You need to be intimately familiar with every page on your existing site(s), and, ideally, you should make a list. Not only do you have to plan for what will happen to each of these pages, but you’ll need that list to make sure everything works smoothly later.

In my case, I decided it might be time to do some housekeeping – the User Effect blog had hundreds of posts, many outdated and quite a few just not very good. So, I started with the easy data – recent traffic. I’m sure you’ve seen this Google Analytics report (Behavior > Site Content > All Pages):

Since I wanted to focus on recent activity, and none of the sites had much new content, I restricted myself to a 3-month window (Q4 of 2014). Of course, I looked much deeper than the top 10, but the principle was simple – I wanted to make sure the data matched my intuition and that I wasn’t cutting off anything important. This helped me prioritize the list.

Of course, from an SEO standpoint, I also didn’t want to lose content that had limited traffic but solid inbound links. So, I checked my “Top Pages” report in
Open Site Explorer:

Since the bulk of my main site was a blog, the top trafficked and top linked-to pages fortunately correlated pretty well. Again, this is only a way to prioritize. If you’re dealing with sites with thousands of pages, you need to work methodically through the site architecture.

I’m going to say something that makes some SEOs itchy – it’s ok not to move some pages to the new site. It’s even ok to let some pages 404. In Q4, UserEffect.com had traffic to 237 URLs. The top 10 pages accounted for 91.9% of that traffic. I strongly believe that moving domains is a good time to refocus a site and concentrate your visitors and link equity on your best content. More is not better in 2015.

Letting go of some pages also means that you’re not 301-redirecting a massive number of old URLs to a new home-page. This can look like a low-quality attempt to consolidate link-equity, and at large scale it can raise red flags with Google. Content worth keeping should exist on the new site, and your 301s should have well-matched targets.

In one case, I had a blog post that had a decent trickle of traffic due to ranking for “50,000 push-ups,” but the post itself was weak and the bounce rate was very high:

The post was basically just a placeholder announcing that I’d be attempting this challenge, but I never recapped anything after finishing it. So, in this case,
I rewrote the post.

Of course, this process was repeated across the 3 active sites. The 2 inactive sites only constituted a handful of total pages. In the case of AreYouARealDoctor.com, I decided to turn the previous one-pager
into a new page on the new site. That way, I had a very well-matched target for the 301-redirect, instead of simply mapping the old site to my new home-page.

I’m trying to prove a point – this is the amount of work I did for a handful of sites that were mostly inactive and producing no current business value. I don’t need consulting gigs and these sites produce no direct revenue, and yet I still considered this process worth the effort.

Step 2 – The Big Day

Eventually, you’re going to have to make the move, and in most cases, I prefer ripping off the bandage. Of course, doing something all at once doesn’t mean you shouldn’t be careful.

The biggest problem I see with domain switches (even if they’re 1-to-1) is that people rely on data that can take weeks to evaluate, like rankings and traffic, or directly checking Google’s index. By then, a lot of damage is already done. Here are some ways to find out quickly if you’ve got problems…

(1) Manually Check Pages

Remember that list you were supposed to make? It’s time to check it, or at least spot-check it. Someone needs to physically go to a browser and make sure that each major section of the site and each important individual page is resolving properly. It doesn’t matter how confident your IT department/guy/gal is – things go wrong.

(2) Manually Check Headers

Just because a page resolves, it doesn’t mean that your 301-redirects are working properly, or that you’re not firing some kind of 17-step redirect chain. Check your headers. There are tons of free tools, but lately I’m fond of
URI Valet. Guess what – I screwed up my primary 301-redirects. One of my registrar transfers wasn’t working, so I had to have a setting changed by customer service, and I inadvertently ended up with 302s (Pro tip: Don’t change registrars and domains in one step):

Don’t think that because you’re an “expert”, your plan is foolproof. Mistakes happen, and because I caught this one I was able to correct it fairly quickly.

(3) Submit Your New Site

You don’t need to submit your site to Google in 2015, but now that Google Webmaster Tools allows it, why not do it? The primary argument I hear is “well, it’s not necessary.” True, but direct submission has one advantage – it’s fast.

To be precise, Google Webmaster Tools separates the process into “Fetch” and “Submit to index” (you’ll find this under “Crawl” > “Fetch as Google”). Fetching will quickly tell you if Google can resolve a URL and retrieve the page contents, which alone is pretty useful. Once a page is fetched, you can submit it, and you should see something like this:

This isn’t really about getting indexed – it’s about getting nearly instantaneous feedback. If Google has any major problems with crawling your site, you’ll know quickly, at least at the macro level.

(4) Submit New XML Sitemaps

Finally, submit a new set of XML sitemaps in Google Webmaster Tools, and preferably tiered sitemaps. While it’s a few years old now, Rob Ousbey has a great post on the subject of
XML sitemap structure. The basic idea is that, if you divide your sitemap into logical sections, it’s going to be much easier to diagnosis what kinds of pages Google is indexing and where you’re running into trouble.

A couple of pro tips on sitemaps – first, keep your old sitemaps active temporarily. This is counterintuitive to some people, but unless Google can crawl your old URLs, they won’t see and process the 301-redirects and other signals. Let the old accounts stay open for a couple of months, and don’t cut off access to the domains you’re moving.

Second (I learned this one the hard way), make sure that your Google Webmaster Tools site verification still works. If you use file uploads or meta tags and don’t move those files/tags to the new site, GWT verification will fail and you won’t have access to your old accounts. I’d recommend using a more domain-independent solution, like verifying with Google Analytics. If you lose verification, don’t panic – your data won’t be instantly lost.

Step 3 – The Waiting Game

Once you’ve made the switch, the waiting begins, and this is where many people start to panic. Even executed perfectly, it can take Google weeks or even months to process all of your 301-redirects and reevaluate a new domain’s capacity to rank. You have to expect short term fluctuations in ranking and traffic.

During this period, you’ll want to watch a few things – your traffic, your rankings, your indexed pages (via GWT and the site: operator), and your errors (such as unexpected 404s). Traffic will recover the fastest, since direct traffic is immediately carried through redirects, but ranking and indexation will lag, and errors may take time to appear.

(1) Monitor Traffic

I’m hoping you know how to check your traffic, but actually trying to determine what your new levels should be and comparing any two days can be easier said than done. If you launch on a Friday, and then Saturday your traffic goes down on the new site, that’s hardly cause for panic – your traffic probably
always goes down on Saturday.

In this case, I redirected the individual sites over about a week, but I’m going to focus on UserEffect.com, as that was the major traffic generator. That site was redirected, in full on January 21st, and the Google Analytics data for January for the old site looked like this:

So far, so good – traffic bottomed out almost immediately. Of course, losing traffic is easy – the real question is what’s going on with the new domain. Here’s the graph for January for DrPete.co:

This one’s a bit trickier – the first spike, on January 16th, is when I redirected the first domain. The second spike, on January 22nd, is when I redirected UserEffect.com. Both spikes are meaningless – I announced these re-launches on social media and got a short-term traffic burst. What we really want to know is where traffic is leveling out.

Of course, there isn’t a lot of history here, but a typical day for UserEffect.com in January was about 1,000 pageviews. The traffic to DrPete.co after it leveled out was about half that (500 pageviews). It’s not a complete crisis, but we’re definitely looking at a short-term loss.

Obviously, I’m simplifying the process here – for a large, ecommerce site you’d want to track a wide range of metrics, including conversion metrics. Hopefully, though, this illustrates the core approach. So, what am I missing out on? In this day of [not provided], tracking down a loss can be tricky. Let’s look for clues in our other three areas…

(2) Monitor Indexation

You can get a broad sense of your indexed pages from Google Webmaster Tools, but this data often lags real-time and isn’t very granular. Despite its shortcomings, I still prefer
the site: operator. Generally, I monitor a domain daily – any one measurement has a lot of noise, but what you’re looking for is the trend over time. Here’s the indexed page count for DrPete.co:

The first set of pages was indexed fairly quickly, and then the second set started being indexed soon after UserEffect.com was redirected. All in all, we’re seeing a fairly steady upward trend, and that’s what we’re hoping to see. The number is also in the ballpark of sanity (compared to the actual page count) and roughly matched GWT data once it started being reported.

So, what happened to UserEffect.com’s index after the switch?

The timeframe here is shorter, since UserEffect.com was redirected last, but we see a gradual decline in indexation, as expected. Note that the index size plateaus around 60 pages – about 1/4 of the original size. This isn’t abnormal – low-traffic and unlinked pages (or those with deep links) are going to take a while to clear out. This is a long-term process. Don’t panic over the absolute numbers – what you want here is a downward trend on the old domain accompanied by a roughly equal upward trend on the new domain.

The fact that UserEffect.com didn’t bottom out is definitely worth monitoring, but this timespan is too short for the plateau to be a major concern. The next step would be to dig into these specific pages and look for a pattern.

(3) Monitor Rankings

The old domain is dropping out of the index, and the new domain is taking its place, but we still don’t know why the new site is taking a traffic hit. It’s time to dig into our core keyword rankings.

Historically, UserEffect.com had ranked well for keywords related to “split test calculator” (near #1) and “usability checklist” (in the top 3). While [not provided] makes keyword-level traffic analysis tricky, we also know that the split-test calculator is one of the top trafficked pages on the site, so let’s dig into that one. Here’s the ranking data from Moz Analytics for “split test calculator”:

The new site took over the #1 position from the old site at first, but then quickly dropped down to the #3/#4 ranking. That may not sound like a lot, but given this general keyword category was one of the site’s top traffic drivers, the CTR drop from #1 to #3/#4 could definitely be causing problems.

When you have a specific keyword you can diagnose, it’s worth taking a look at the live SERP, just to get some context. The day after relaunch, I captured this result for “dr. pete”:

Here, the new domain is ranking, but it’s showing the old title tag. This may not be cause for alarm – weird things often happen in the very short term – but in this case we know that I accidentally set up a 302-redirect. There’s some reason to believe that Google didn’t pass full link equity during that period when 301s weren’t implemented.

Let’s look at a domain where the 301s behaved properly. Before the site was inactive, AreYouARealDoctor.com ranked #1 for “are you a real doctor”. Since there was an inactive period, and I dropped the exact-match domain, it wouldn’t be surprising to see a corresponding ranking drop.

In reality, the new site was ranking #1 for “are you a real doctor” within 2 weeks of 301-redirecting the old domain. The graph is just a horizontal line at #1, so I’m not going to bother you with it, but here’s a current screenshot (incognito):

Early on, I also spot-checked this result, and it wasn’t showing the strange title tag crossover that UserEffect.com pages exhibited. So, it’s very likely that the 302-redirects caused some problems.

Of course, these are just a couple of keywords, but I hope it provides a starting point for you to understand how to methodically approach this problem. There’s no use crying over spilled milk, and I’m not going to fire myself, so let’s move on to checking any other errors that I might have missed.

(4) Check Errors (404s, etc.)

A good first stop for unexpected errors is the “Crawl Errors” report in Google Webmaster Tools (Crawl > Crawl Errors). This is going to take some digging, especially if you’ve deliberately 404’ed some content. Over the couple of weeks after re-launch, I spotted the following problems:

The old site had a “/blog” directory, but the new site put the blog right on the home-page and had no corresponding directory. Doh. Hey, do as I say, not as I do, ok? Obviously, this was a big blunder, as the old blog home-page was well-trafficked.

The other two errors here are smaller but easy to correct. MinimalTalent.com had a “/free” directory that housed downloads (mostly PDFs). I missed it, since my other sites used a different format. Luckily, this was easy to remap.

The last error is a weird looking URL, and there are other similar URLs in the 404 list. This is where site knowledge is critical. I custom-designed a URL shortener for UserEffect.com and, in some cases, people linked to those URLs. Since those URLs didn’t exist in the site architecture, I missed them. This is where digging deep into historical traffic reports and your top-linked pages is critical. In this case, the fix isn’t easy, and I have to decide whether the loss is worth the time.

What About the New EMD?

My goal here wasn’t to rank better for “Dr. Pete,” and finally unseat Dr. Pete’s Marinades, Dr. Pete the Sodastream flavor (yes, it’s hilarious – you can stop sending me your grocery store photos), and 172 dentists. Ok, it mostly wasn’t my goal. Of course, you might be wondering how switching to an EMD worked out.

In the short term, I’m afraid the answer is “not very well.” I didn’t track ranking for “Dr. Pete” and related phrases very often before the switch, but it appears that ranking actually fell in the short-term. Current estimates have me sitting around page 4, even though my combined link profile suggests a much stronger position. Here’s a look at the ranking history for “dr pete” since relaunch (from Moz Analytics):

There was an initial drop, after which the site evened out a bit. This less-than-impressive plateau could be due to the bad 302s during transition. It could be Google evaluating a new EMD and multiple redirects to that EMD. It could be that the prevalence of natural anchor text with “Dr. Pete” pointing to my site suddenly looked unnatural when my domain name switched to DrPete.co. It could just be that this is going to take time to shake out.

If there’s a lesson here (and, admittedly, it’s too soon to tell), it’s that you shouldn’t rush to buy an EMD in 2015 in the wild hope of instantly ranking for that target phrase. There are so many factors involved in ranking for even a moderately competitive term, and your domain is just one small part of the mix.

So, What Did We Learn?

I hope you learned that I should’ve taken my own advice and planned a bit more carefully. I admit that this was a side project and it didn’t get the attention it deserved. The problem is that, even when real money is at stake, people rush these things and hope for the best. There’s a real cheerleading mentality when it comes to change – people want to take action and only see the upside.

Ultimately, in a corporate or agency environment, you can’t be the one sour note among the cheering. You’ll be ignored, and possibly even fired. That’s not fair, but it’s reality. What you need to do is make sure the work gets done right and people go into the process with eyes wide open. There’s no room for shortcuts when you’re moving to a new domain.

That said, a domain change isn’t a death sentence, either. Done right, and with sensible goals in mind – balancing not just SEO but broader marketing and business objectives – a domain migration can be successful, even across multiple sites.

To sum up: Plan, plan, plan, monitor, monitor, monitor, and try not to panic.

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In-App Social & Contact Data – New in Open Site Explorer

Posted by randfish

Today I’m excited to announce the launch of a new feature inside 
Open Site Explorer—In-App Social & Contact Data. 

With this launch, you’ll be able to see the
social or email accounts we’ve discovered associated with a given website, and have one-click access to those pages.


Initially, the feature offers:

  1. Availability today on the inbound links tab and in Link Intersect on the “pages -> subdomains” view. In the future, if y’all find it useful, we hope to expand its presence to other areas of the tool as well.
  2. Email accounts will only be shown if they match the domain name (e.g. rand@moz.com would be shown next to moz.com, randfishkin@yahoo.com would not) and if they appear in standard format on the page (we don’t try to grab emails in JavaScript or that use alternate formats to obsfucate).
  3. We show Facebook, Twitter, Google+, and email addresses we’ve found on multiple pages of the site (we take a small random set and analyze whether these social/contact data pieces are uniform). If we find multiple accounts, you’ll see this:

Use cases

There are three major use cases for this feature (at least for me; you might have more!):

1) Link/Outreach prospecting

It can be a pain to visit sites, find social accounts/emails, and copy them into a spreadsheet or send messages (and recall which ones you have/haven’t done yet). By including social/contact data in the same interface where you’re doing link analysis, we hope to save you time and clicks.

2) Link/site trust and audience reach analysis

We’re actually using this data on the back end at Moz for our upcoming Spam Score feature (coming very soon), but you can use it manually to help with a quick mental filter for trustworthy/authoritative/non-spammy sites, and to get a sense for the size and reach of a site’s social audience.

3) At-a-glance analysis of social networks among a group

If you’re in a given space (e.g. travel blogs), it’s a process to determine which social networks are/aren’t being used by industry participants and influencers. Social/contact data in OSE can help with that by showing which social networks various sites are using and linking to from their pages:

We need your feedback

This first implementation is relatively light in the app—we haven’t yet placed this data anywhere/everywhere it might be useful. Before we do, we want to hear what you think: Is this useful and valuable to your work? Does it help save you time? Would you want to see the feature expanded and if so, in what sections would it provide the greatest value to you? Please let us know in the comments, and by getting back in touch with us after you’ve had a chance to try it out for yourself.

Thanks for giving social/contact data a spin, and look for more upgrades to Open Site Explorer in the very near future!

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