E-Commerce KPI Study: There’s (Finally) a Benchmark for That

Posted by ProfAlfonso

Being a digital marketer, I spend my day knee-deep in data. The time I don’t spend analysing it, I spend explaining its significance to a client or junior colleague or arguing its significance with a client or senior colleague.

But after many debates over the importance of bounce rate, time on site, mobile conversion rate and the colour grey for buttons (our designer partook in that last one), we’re never much closer to an agreement on significance.

Our industry is swimming in data (thanks Google Analytics), but at times we’re drowning in it.

Numbers without context mean nothing. Data in the hands of even the savviest marketer is useless without a context to evaluate its performance against competitors or the industry at large.

Which is why we need benchmarks.
Through benchmarking, marketers can contextualise data to identify under-performing elements and amplify what is over-performing. They can focus on the KPIs that are important, and recognise whether they are achievable.

Benchmarks also give context to those who aren’t familiar with data. One pain point that digital marketers face globally is communicating their performance upwards. There are very few ‘digital natives’ sitting in company boardrooms these days but plenty of executives who know their numbers inside out.

Industry benchmark data arms us with perspective and framework when we need to communicate upwards. It ensures we get pats on the back when deserved and additional budget released when required.

Google Analytics Benchmarking Reports

Google, you might argue, have already solved these problems.

The upgrade and roll-out of Google Analytics Benchmarking Reports has been met with plenty of excitement for these reasons. With its large data set and nifty options to chop up the data by geography and website size, for a minute it certainly seemed like the benchmarking of our dreams. And while we recognise its usefulness to benchmark against real-time data (comparing a surge of traffic from a particular location for example, or seasonal demands), it still left us short of the hard data insights we were looking for.

We wanted reliable KPI data that went beyond user behaviour. We wanted average conversion rates and average transaction values as well as ‘softer’ engagement metrics such as bounce rate and time on site.

Most importantly, we wanted to know which engagement metrics actually correlated with the conversion rate, so we could narrow our field of analysis and efforts in pursuit of a healthier bottom line.

Which is why we went out and got our own and generated this e-commerce KPI report.

Data and methodology

We analysed the 56 million visits and approximately $252 million (€214 million) in revenue that flowed through 30 participating websites between August 1, 2013 and July 30, 2014. The websites were in the retail and travel sectors and included both online-only and those with a physical store as well as an e-commerce site.

We averaged stats on a per-website basis, so that websites with high levels of traffic didn’t skew the stats. We had more retail participants than travel participants so the average e-commerce figures are not the midpoint between travel and retail but the average figure across all study participants. Revenue is attributed on a last-click basis.

Results

Here is a highlight of some of our most relevant and interesting findings. For all the data and results, download the full report on
WolfgangDigital.com.

Average KPIs: Bounce rate, time on site, and conversion rate

First, we calculated some averages across engagement KPIs and commercial KPIs. If you are an e-commerce website in the travel or retail business, you can use these numbers to evaluate how your website is performing when set against a broad swath of your industry peers.

Well, remember the conversion measured here is a sale. If your conversion rate is lower than the study average don’t fire your CMO straight away; check if your average transaction value (ATV) is higher. If they balance each other out you are all good – if they don’t, it’s time to start digging deeper. Does the 1.4% conversion rate give you a smug tingly feeling or a stab of panic?

We often break down conversion rate into two parts: website-to-basket and basket-to-checkout. Industry norms tell us expect about 5% CR on website-to-basket and 30% on basket-to-checkout. Check which one of these conversion rates is most out of kilter on your site, then focus your attention there. This exercise will often give greater visibility on where the hole in your bucket is, Dear Liza.

Another factor in this analysis is that online-only retailers tend to enjoy higher conversion rates as the consumer
must transact via the website. If you have an offline presence, a lower conversion rate comes with the physical territory as your site visitors may convert in store.

KPIs by device: Mobile under scrutiny

Next, we segmented the data by device: desktop, tablet and mobile.

We found that although mobile and tablet together accounted for nearly half of website traffic (43%), they contributed to just over a quarter of revenue (26%).

Mobile alone accounted for 26% of traffic but only 10% of revenue. This suggests that while mobile is a favoured device for browsing and researching, it’s the desktop where users are more likely to whip out the credit card.

When we looked at conversion rates by device, this confirmed it.

What data matters: The correlations

We wanted to know which engagement figures had an influence (if any) on commercial ones.

Then we’d know which behavioural metrics were worth trying to improve to lift conversion rate, and which metrics we could finally label insignificant.

We did this by calculating correlations. A correlation ranges from 0 to 1, so 0 indicates on no correlation at all, while 1 signifies a clear correlation. A negative correlation indicates that as one variable increases the other decreases.

Time on site (0.34) and pages viewed (0.35) both had positive correlations with conversion rate, so our advice is to look at how to improve these metrics for your site to benefit from a higher conversion rate.

We delved into the device data and found mobile was the only device with positive traffic (0.29) and revenue (0.45) correlations to overall conversion rate. In fact, that 0.45 correlation rate between mobile revenue % and conversion rate was actually the strongest correlation rate across all factors we measured.

We infer that while the mobile conversion rate is depressingly low, a mobile user is still somebody with purchase intent who is likely to convert later on another device. The lesson we took from this is to make sure your website is mobile-optimised, particularly for ease of research and browsing content.

Finally, the time came to talk about bounce rate. Our Excel wizard had converted the data to an ‘un-bounce rate’ (1 minus the bounce rate) for consistency with positive time on site and pages viewed metrics. We gathered round the spreadsheet.

He revealed
there is actually a negative correlation (-0.12) between un-bounce rate and conversion rate. This correlation signals that it couldn’t be less influential on conversion rate, so for those unable to sleep at night for bounce anxiety, we’re delighted to let you sleep easy.

Increasing your conversion rate may not be as complex a task as it seems.

Our KPI study shows that if you can increase pages viewed and time on site it will push up your conversion rate (content marketing for conversion optimisation anybody?).

We’ve also proved that mobile matters. Don’t be discouraged if your mobile conversion rate pales against desktop’s performance; keep driving mobile traffic and revenue (however minor) and you’ll see the difference in your bottom line.

Read the full results broken down by industry level by downloading from the Wolfgang Digital e-commerce KPI Study.

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Reblogged 3 years ago from moz.com

The Coming Integration of PR and SEO

Posted by SamuelScott

Earlier this year, I published a Moz post that aimed to introduce the
basic principles of public relations that SEOs and digital marketers, I argued, need to know. (Specifically, the post was on media relations and story-pitching as a means of getting coverage and “earning” good links.)

Following the positive response to the post, Moz invited me to host a recent Mozinar on the integration of PR and SEO. (
You can listen to it and download the slides here for free!) As a former print journalist who later became a digital marketer, I love to discuss this niche because I am very passionate about the topic.

In summary, the Mozinar discussed:

  • Traditional marketing and communications theory
  • Why both inbound and outbound marketing are needed
  • An overview of the basic PR process
  • How to use PR software
  • Examples of messaging and positioning
  • Where to research demographic data for audience profiles
  • How to integrate SEO into each step of the workflow
  • How SEO and PR teams can help each other
  • Why the best links come as natural results of doing good PR and marketing
  • “Don’t think about how to get links. Think about how to get coverage and publicity.”

At the end of the Mozinar, the community had some intriguing and insightful questions (no surprise there!), and Moz invited me to write a follow-up post to provide more answers and discuss the relationship between SEO and PR further.

Follow-ups to the PR Mozinar

Before I address the questions and ideas at the end of the Mozinar, I just wanted to give some more credit where the credit is certainly due.

People like me, who write for major publications or speak at large conferences, get a lot of attention. But, truth is, we are always helped immensely by so many of our talented colleagues behind the scenes. Since the beginning of my digital marketing career, I have known about SEO, but I have learned more about public relations from observing (albeit from a distance) The Cline Group’s front line PR team in Philadelphia over the years.

So, I just wanted to thank (in alphabetical order)
Kim Cox, Gabrielle Dratch, Caitlin Driscoll, Max Marine, and Ariel Shore as well as our senior PR executives Bill Robinson and DeeDee Rudenstein and CEO Josh Cline. What I hope the Moz community learned from the Mozinar is what I have learned from them.

Now, onto the three Mozinar Q&A questions that had been left unanswered.

  • Why do you use Cision and not Vocus or Meltwater or others?

I do not want to focus on why The Cline Group specifically uses Cision. I would not want my agency (and indirectly Moz) to be seen as endorsing one type of PR software over another. What I can do is encourage people to read these writings from 
RMP Media Analysis, LinkedIn, Alaniz Marketing and Ombud, then do further research into which platform may work best for them and their specific companies and needs.

(Cision and Vocus recently agreed to merge, with the combined company continuing under the Cision brand.)

  • Do you have examples of good PR pitches?

I’ve anonymized and uploaded three successful client pitches to our website. You can download them here: a
mobile-advertising network, a high-end vaporizer for the ingestion of medicinal herbs and a mobile app that helps to protect personal privacy. As you will see, these pitches incorporated the various tactics that I had detailed in the Mozinar.

Important caveat: Do not fall into the trap of relying too much on templates. Every reporter and every outlet you pitch will be different. The ideas in these examples of pitches may help, but please do not use them verbatim. 

  • Are there other websites similar to HARO (Help a Reporter Out) that people can use to find reporters who are looking for stories? Are the other free, simpler tools?

Some commonly mentioned tools are
My Blog U, ProfNet, BuzzStream and My Local Reporter. Raven Tools also has a good-sized list. But I can only vouch for My Blog U because it’s the only one I have used personally. It’s also important to note that using a PR tool is not a magic bullet. You have to know how to use it in the context of the overall public relations process. Creating a media list is just one part of the puzzle.

An infographic of integration

And now, the promised infographic!

I told the Mozinar audience we would provide a detailed infographic as a quick guide to the step-by-step process of PR and SEO integration. Well, here it is:

pr-seo-infographic-final.jpg

A second credit to my awesome colleague
Thomas Kerr, who designs most of The Cline Group’s presentations and graphics while also being our social media and overall digital wizard.

Just a few notes on the infographic:

First, I have segmented the two pillars by “PR and Traditional Marketing” and “SEO & Digital Marketing.” I hate to sound stereotypical, but the use of this differentiation was the easiest way to explain the integration process. The “PR” side deals with
people and content (e.g., messaging, media relations, and materials, etc.), while the “SEO” side focuses on things (e.g., online data, analytics, and research, etc.). See the end of this post for an important prediction.

Second, I have put social media on the online side because that is where the practice seems to sit in most companies and agencies. However, social media is really just a set of PR and communications channels, so it will likely increasingly move to the “traditional marketing” side of things. Again, see the end.

Third, there is a CMO / VP of Marketing / Project Leader (based on the structure of a company and whether the context is an agency or an in-house department) column between SEO and PR. This position should be a person with enough experience in both disciplines to mediate between the two as well as make judgment calls and final decisions in the case of conflicts. “SEO,” for example, may want to use certain keyword-based language in messaging in an attempt to rank highly for certain search terms. “PR” might want to use different terms that may resonate more with media outlets and the public. Someone will need to make a decision.

Fourth, it is important to understand that companies with numerous brands, products or services, and/or a diverse set of target audiences will need to take additional steps:

The marketing work for each brand, product, or service will need its own specific goal and KPI(s) in step one. Separate audience research and persona development will need to be performed for each distinct audience in step two. So, for a larger company, such as the one described above, parts of steps 3-8 below will often need to be done, say, six times, once for each audience of each product.

However, the complexity does not end there.

Online and offline is the same thing

Essentially, as more and more human activity occurs online, we are rapidly approaching a point where the offline and online worlds are merging into the same space. “Traditional” and “online” marketing are all collectively becoming simply “marketing.”

Above is our modern version of traditional communications and marketing theory. A sender decides upon a message; the message is packaged into a piece of content; the content is transmitted via a desired channel; and the channel delivers the content to the receiver. Marketing is essentially sending a message that is packaged into a piece of content to a receiver via a channel. The rest is just details.

As Google becomes smarter and smarter, marketers will need to stop thinking only about SEO and think more like, well, marketers. Mad Men’s Don Draper, the subject of the meme at the top of the page, would best the performance of any link builder today because he understood how to gain mass publicity and coverage, both of which have always been more important than just building links here and there. The best and greatest numbers of links come naturally as a
result of good marketing and not as a result of any direct linkbuilding. In the 2014 Linkbuilding Survey published on Moz, most of the (good) tactics that were described in the post – such as “content plus outreach” – are PR by another name.

At SMX West 2014 (where I gave a talk on SEO and PR strategy), Rand Fishkin took to the main stage to discuss what the future holds for SEO. Starting at 6:30 in the video above, he argued that there will soon be a bias towards brands in organic search. (For an extensive discussion of this issue, I’ll refer you to Bryson Meunier’s essay at Search Engine Land.) I agree that it will soon become crucial to use PR, advertisingand publicity to build a brand, but that action is something the Don Drapers of the world had already known to do long before the Internet had ever existed.

But things are changing

The process that I have outlined above is a little vague on purpose. The lines between SEO and PR are increasingly blurring as online and offline marketing becomes more and more integrated. For example, take this very post: is it me doing SEO or PR for our agency (while
first and foremost aiming to help the readers)? The answer: Yes.

In a Moz post by Jason Acidre on
SEO and brand building, I commented with the following:

Say, 10 years ago, “SEOs” were focused on techie things: keyword research, sitemaps, site hierarchy, site speed, backlinks, and a lot more. Then, as Google became smarter and the industry become more and more mature, “SEOs” woke up one day and realized that online marketers need to think, you know, like marketers. Now, I get the sense that digital marketers are trying to learn all about traditional marketing as much as possible because, in the end, all marketing is about
people — not machines and algorithms. What the f&*# is a positioning statement? What is a pitch? I just wish “SEOs” had done this from the beginning.

Of course, the same thing has been occurring in the inverse in the traditional marketing world. Traditional marketers have usually focused on these types of things: messaging documents, media lists, promotional campaigns, the 4 Ps, and SWOT analyses. Then, as more human activity moved to the Internet, they also woke up one day and saw an anarchic set of communications channels that operate under different sets of rules. Now, on the other end, I get the sense that traditional marketers are trying to learn as much as possible about SEO and digital marketing. 
What the f&^% is a rel=canonical tag? What is Google+ authorship? I just wish traditional marketers had done this from the start.

In fact, such a separation between SEO and PR is quickly dying. Here is a simplified version of the marketing and communications process I outlined at the beginning:

Traditional marketers and communications professionals have used this process for decades, and almost everything that (the umbrella term of) SEO does can fit into one of these boxes. A message can appear in a newspaper article or in a blog post. Content can be a sales brochure or an e-book. A channel can be the television or Facebook. A lot of  technical and on-page SEO is simply good web development. The most-effective type of off-page SEO is just PR and publicity. Public-relations executives, as I
have written elsewhere, can also learn to use analytics as yet another way to gauge results.

It all goes back to this tweet from Rand, which I cite in nearly every offline conversation with the marketing community:

SEO as an entity (sorry for the pun)
unto itself is quickly dying. The more SEO entails, the more the umbrella term becomes useless in any meaningful context. For this reason, it is crucial that digital marketers learn as much as possible about traditional marketing and PR.

So, in the end, how does one integrate public relations and SEO? By simply doing good
marketing.

Want more? Don’t forget to watch the Mozinar — I’d love to get your feedback in the comments below!

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Reblogged 4 years ago from feedproxy.google.com

Xtractor Demo del1 – SEO tool

Xtractor is a SEO tool with webanalysis, statisics, custom reports, KPI monitoring, ROI reporting, usability testing, digital visability and much more. SEO m…

Reblogged 4 years ago from www.youtube.com

Calculating Estimated ROI for a Specific Site & Body of Keywords

Posted by shannonskinner

One of the biggest challenges for SEO is proving its worth. We all know it’s valuable, but it’s important to convey its value in terms that key stakeholders (up to and including CEOs) understand. To do that, I put together a process to calculate an estimate of ROI for implementing changes to keyword targeting.

In this post, I will walk through that process, so hopefully you can do the same for your clients (or as an in-house SEO to get buy-in), too!

Overview

  1. Gather your data
    1. Keyword Data
    2. Strength of your Preferred URLs
    3. Competition URLs by Keyword
    4. Strength of Competition URLs
  2. Analyze the Data by Keyword
  3. Calculate your potential opportunity

What you need

There are quite a few parts to this recipe, and while the calculation part is pretty easy, gathering the data to throw in the mix is the challenging part. I’ll list each section here, including the components of each, and then we can go through how to retrieve each of them. 

  • Keyword data

    • list of keywords
    • search volumes for each keyword
    • preferred URLs on the site you’re estimating ROI
    • current rank
    • current ranking URL
  • Strength of your preferred URLs

    • De-duplicated list of preferred URLs
    • Page Authorities for each preferred URL
    • BONUS: External & Internal Links for each URL. You can include any measure you like here, as long as it’s something that can be compared (i.e. a number).
  • Where the competition sits

    • For each keyword, the sites that are ranking 1-10 in search currently
  • Strength of the competition

    • De-duplicated list of competing URLs
    • Page Authorities, Domain Authorities, 
    • BONUS: External & Internal Links, for each competing URL. Include any measure you’ve included on the Strength of Your Preferred URLs list.


How to get what you need


There has been quite a lot written about keyword research, so I won’t go into too much detail here. For the Keyword data list, the important thing is to get whatever keywords you’d like to assess into a spreadsheet, and include all the information listed above. You’ll have to select the preferred URLs based on what you think the strongest-competing and most appropriate URL would be for each keyword. 


For the
Preferred URLs list, you’ll want to use the data that’s in your keyword data under the preferred URL.

  1. Copy the preferred URL data from your Keyword Data into a new tab. 
  2. Use the Remove Duplicates tool (Data>Data Tools in Excel) to remove any duplicated URLs

Once you have the list of de-duplicated preferred URLs, you’ll need to pull the data from Open Site Explorer for these URLs. I prefer using the Moz API with SEOTools. You’ll have to install it to use it for Excel, or if you’d like to take a stab at using it in Google Docs, there are some resources available for that. Unfortunately, with the most recent update to Google Spreadsheets, I’ve had some difficulty with this method, so I’ve gone with Excel for now. 

Once you’ve got SEOTools installed, you can make the call “=MOZ_URLMetrics_toFit([enter your cells])”. This should give you a list of URL titles, canonical URLs, External & Internal links, as well as a few other metrics and DA/PA. 


For the
Where the competition sits list, you’ll first need to perform a search for each of your keywords. Obviously, you could do this manually, or if you have exportable data from a keyword ranking tool and you’ve been ranking the keywords you’d like to look at, you could use either of these methods. If you don’t have those, you can use the hacky method that I did–basically, use the ImportXML command in Google Spreadsheets to grab the top ranking URLs for each query. 

I’ve put a sample version of this together, which you can access here. A few caveats: you should be able to run MANY searches in a row–I had about 850 for my data, and they ran fine. Google will block your IP address, though, if you run too many, and what I found is that I needed to copy out my results as values into a different spreadsheet once I’d gotten them, because they timed out relatively quickly, but you can just put them into the Excel spreadsheet you’re building to make the ROI calculations (you’ll need them there anyway!).


From this list, you can pull each URL into a single list, and de-duplicate as explained for the preferred URLs list to generate the
Strength of the Competition list, and then run the analysis you did with the preferred URLs to generate the same data for these URLs as you did for the preferred URLs with SEOTools for Excel. 


Making your data work for you

Once you’ve got these lists, you can use some VLOOKUP magic to pull in the information you need. I used the
Where the competition sits list as the foundation of my work. 

From there, I pulled in the corresponding preferred URL and its Page Authority, as well as the PAs and DAs for each URL currently ranking 1-10. I then was able to calculate an average PA & DA for each query, and could compare the page I want to rank to this. I estimated the chances that the page I wanted to rank (given that I’d already determined these were relevant pages) could rank with better keyword targeting.

Here’s where things get interesting. You can be rather conservative, and only sum search volumes of keywords you’re fairly confident your site can rank, which is my preferred method. That’s because I use this method primarily to determine if I’m on the right track–whether making these recommendations are really worth the time to get implemented. So I’m going to move forward assuming I’m counting only the search volumes of terms I think I’m quite competitive for, AND that I’m not yet ranking for on page 1. 


Now, you want to move to your analytics data in order to calculate a few things: 

  • Conversion Rate
  • Average order value
  • Previous year’s revenue (for the section you’re looking at)

I’ve set up my sample data in this spreadsheet that you can refer to or use to make your own calculations. 

Each of the assumptions can be adjusted depending on the actual site data, or using estimates. I’m using very very generic overall CTR estimates, but you can select which you’d like and get as granular as you want! The main point for me is really getting to two numbers that I can stand by as pretty good estimates: 

  • Annual Impact (Revenue $$)
  • Increase in Revenue ($$) from last year

This is because, for higher-up folks, money talks. Obviously, this won’t be something you can promise, but it gives them a metric that they understand to really wrap their head around the value that you’re potentially brining to the table if the changes you’re recommending can be made. 

There are some great tools for estimating this kind of stuff on a smaller scale, but for a massive body of keyword data, hopefully you will find this process useful as well. Let me know what you think, and I’d love to see what parts anyone else can streamline or make even more efficient. 

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Reblogged 4 years ago from feedproxy.google.com