Looking Beyond Keywords: How to Drive Conversion with Visual Search & Search by Camera

Posted by Jes.Scholz

Let’s play a game. I’ll show you an image. You type in the keyword to find the exact product featured in the image online. Ready?

Google her sunglasses…

What did you type? Brown sunglasses? Brown sunglasses with heavy frame? Retro-look brown sunglasses with heavy frame? It doesn’t matter how long-tail you go, it will be difficult to find that exact pair, if not impossible. And you’re not alone.

For 74% of consumers, traditional text-based keyword searches are inefficient at helping find the right products online.

But much of your current search behavior is based on the false premise that you can describe things in words. In many situations, we can’t.

And this shows in the data. Sometimes we forget that Google Images accounts for 22.6% of all searches — searches where traditional methods of searching were not the best fit.

Image credit: Sparktoro

But I know what you’re thinking. Image SEO drives few to no sessions, let alone conversions. Why should I invest my limited resources into visual marketing?

Because humans are visual creatures. And now, so too are mobile phones — with big screens, multiple cameras, and strong depth perception.

Developments in computer vision have led to a visual marketing renaissance. Just look to visual search leader Pinterest, who reported that 55% of their users shop on the platform. How well do those users convert? Heap Analytics data shows that on shopping cart sizes under $199, image-based Pinterest Ads have an 8.5% conversion rate. To put that in context, that’s behind Google’s 12.3% but in front of Facebook’s 7.2%.

Not only can visual search drive significant conversions online. Image recognition is also driving the digitalization and monetization in the real world.

The rise of visual search in Google

Traditionally, image search functioned like this: Google took a text-based query and tried to find the best visual match based on metadata, markups, and surrounding copy.

But for many years now, the image itself can also act as the search query. Google can search for images with images. This is called visual search.

Google has been quietly adding advanced image recognition capabilities to mobile Google Images over the last years, with a focus on the fashion industry as a test case for commercial opportunities (although the functionality can be applied to automotive, travel, food, and many other industries). Plotting the updates, you can see clear stepping stone technologies building on the theme of visual search.

  • Related images (April 2013): Click on a result to view visually similar images. The first foray into visual search.
  • Collections (November 2015): Allows users to save images directly from Google’s mobile image search into folders. Google’s answer to a Pinterest board.
  • Product images in web results (October 2016): Product images begin to display next to website links in mobile search.
  • Product details on images (December 2016): Click on an image result to display product price, availability, ratings, and other key information directly in the image search results.
  • Similar items (April 2017): Google can identify products, even within lifestyle images, and showcases similar items you can buy online.
  • Style ideas (April 2017): The flip side to similar items. When browsing fashion product images on mobile, Google shows you outfit montages and inspirational lifestyle photos to highlight how the product can be worn in real life.
  • Image badges (August 2017): Label on the image indicate what other details are available, encouraging more users to click; for example, badges such as “recipe” or a timestamp for pages featuring videos. But the most significant badge is “product,” shown if the item is available for purchase online.
  • Image captions (March 2018): Display the title tag and domain underneath the image.

Combining these together, you can see powerful functionality. Google is making a play to turn Google Images into shoppable product discovery — trying to take a bite out of social discovery platforms and give consumers yet another reason to browse on Google, rather than your e-commerce website.

Image credit: Google

What’s more, Google is subtly leveraging the power of keyword search to enlighten users about these new features. According to 1st May MozCast, 18% of text-based Google searches have image blocks, which drive users into Google Images.

This fundamental change in Google Image search comes with a big SEO opportunity for early adopters. Not only for transactional queries, but higher up the funnel with informational queries as well.

kate-middleton-style.gif

Let’s say you sell designer fashion. You could not only rank #1 with your blog post on a informational query on “kate middleton style,” including an image on your article result to enhance the clickability of your SERP listing. You can rank again on page 1 within the image pack, then have your products featured in Similar Items — all of which drives more high-quality users to your site.

And the good news? This is super simple to implement.

How to drive organic sessions with visual search

The new visual search capabilities are all algorithmically selected based on a combination of schema and image recognition. Google told TechCrunch:

“The images that appear in both the style ideas and similar items grids are also algorithmically ranked, and will prioritize those that focus on a particular product type or that appear as a complete look and are from authoritative sites.”

This means on top of continuing to establish Domain Authority site-wide, you need images that are original, high resolution, and clearly focus on a single theme. But most importantly, you need images with perfectly implemented structured markup to rank in Google Images.

To rank your images, follow these four simple steps:

1. Implement schema markup

To be eligible for similar items, you need product markup on the host page that meets the minimum metadata requirements of:

  • Name
  • Image
  • Price
  • Currency
  • Availability

But the more quality detail, the better, as it will make your results more clickable.

2. Check your implementation

Validate your implementation by running a few URLs through Google’s Structured Data Testing Tool. But remember, just being valid is sometimes not enough. Be sure to look into the individual field result to ensure the data is correctly populating and user-friendly.

3. Get indexed

Be aware, it can take up to one week for your site’s images to be crawled. This will be helped along by submitting an image XML sitemap in Google Search Console.

4. Look to Google Images on mobile

Check your implementation by doing a site:yourdomain.cctld query on mobile in Google Images.

If you see no image results badges, you likely have an implementation issue. Go back to step 2. If you see badges, click a couple to ensure they show your ideal markup in the details.

Once you confirm all is well, then you can begin to search for your targeted keywords to see how and where you rank.

Like all schema markup, how items display in search results is at Google’s discretion and not guaranteed. However, quality markup will increase the chance of your images showing up.

It’s not always about Google

Visual search is not limited to Google. And no, I’m not talking about just Bing. Visual search is also creating opportunities to be found and drive conversion on social networks, such as Pinterest. Both brands allow you to select objects within images to narrow down your visual search query.

Image credit: MarTech Today

On top of this, we also have shoppable visual content on the rise, bridging the gap between browsing and buying. Although at present, this is more often driven by data feeds and tagging more so than computer vision. For example:

  • Brahmin offers shoppable catalogs
  • Topshop features user-generated shoppable galleries
  • Net-a-Porter’s online magazine features shoppable article
  • Ted Baker’s campaigns with shoppable videos
  • Instagram & Pinterest both monetize with shoppable social media posts

Such formats reduce the number of steps users need to take from content to conversion. And more importantly for SEOs, they exclude the need for keyword search.

I see a pair of sunglasses on Instagram. I don’t need to Google the name, then click on the product page and then convert. I use the image as my search query, and I convert. One click. No keywords.

…But what if I see those sunglasses offline?

Digitize the world with camera-based search

The current paradigm for SEOs is that we wait for a keyword search to occur, and then compete. Not only for organic rankings, but also for attention versus paid ads and other rich features.

With computer vision, you can cut the keyword search out of the customer journey. By entering the funnel before the keyword search occurs, you can effectively exclude your competitors.

Who cares if your competitor has the #1 organic spot on Google, or if they have more budget for Adwords, or a stronger core value proposition messaging, if consumers never see it?

Consumers can skip straight from desire to conversion by taking a photo with their smartphone.

Brands taking search by camera mainstream

Search by camera is well known thanks to Pinterest Lens. Built into the app, simply point your camera phone at a product discovered offline for online recommendations of similar items.

If you point Lens at a pair of red sneakers, it will find you visually similar sneakers as well as idea on how to style it.

Image credit: Pinterest

But camera search is not limited to only e-commerce or fashion applications.

Say you take a photo of strawberries. Pinterest understand you’re not looking for more pictures of strawberries, but for inspiration, so you’ll see recipe ideas.

The problem? For you, or your consumers, Pinterest is unlikely to be a day-to-day app. To be competitive against keyword search, search by camera needs to become part of your daily habit.

Samsung understands this, integrating search by camera into their digital personal assistant Bixby, with functionality backed by powerful partnerships.

  • Pinterest Lens powers its images search
  • Amazon powers its product search
  • Google translates text
  • Foursquare helps to find places nearby

Bixby failed to take the market by storm, and so is unlikely to be your go-to digital personal assistant. Yet with the popularity of search by camera, it’s no surprise that Google has recently launched their own version of Lens in Google Assistant.

Search engines, social networks, and e-commerce giants are all investing in search by camera…

…because of impressive impacts on KPIs. BloomReach reported that e-commerce websites reached by search by camera resulted in:

  • 48% more product views
  • 75% greater likelihood to return
  • 51% higher time on site
  • 9% higher average order value

Camera search has become mainstream. So what’s your next step?

How to leverage computer vision for your brand

As a marketer, your job is to find the right use case for your brand, that perfect point where either visual search or search by camera can reduce friction in conversion flows.

Many case studies are centered around snap-to-shop. See an item you like in a friend’s home, at the office, or walking past you on the street? Computer vision takes you directly from picture to purchase.

But the applications of image recognition are only limited by your vision. Think bigger.

Branded billboards, magazines ads, product packaging, even your brick-and-mortar storefront displays all become directly actionable. Digitalization with snap-to-act via a camera phone offers more opportunities than QR codes on steroids.

If you run a marketplace website, you can use computer vision to classify products: Say a user wants to list a pair of shoes for sale. They simply snap a photo of the item. With that photo, you can automatically populate the fields for brand, color, category, subcategory, materials, etc., reducing the number of form fields to what is unique about this item, such as the price.

A travel company can offer snap-for-info on historical attractions, a museum on artworks, a healthy living app on calories in your lunch.

What about local SEO? Not only could computer vision show the rating or menu of your restaurant before the user walks inside, but you could put up a bus stop ad calling for hungry travelers to take a photo. The image triggers Google Maps, showing public transport directions to your restaurant. You can take the customer journey, quite literally. Tell them where to get off the bus.

And to build such functionality is relatively easy, because you don’t need to reinvent the wheel. There are many open-source image recognition APIs to help you leverage pre-trained image classifiers, or from which you can train your own:

  • Google Cloud Vision
  • Amazon Rekognition
  • IBM Watson
  • Salesforce Einstein
  • Slyce
  • Clarifai

Let’s make this actionable. You now know computer vision can greatly improve your user experience, conversion rate and sessions. To leverage this, you need to:

  1. Make your brand visual interactive through image recognition features
  2. Understand how consumers visually search for your products
  3. Optimize your content so it’s geared towards visual technology

Visual search is permeating online and camera search is becoming commonplace offline. Now is the time to outshine your competitors. Now is the time to understand the foundations of visual marketing. Both of these technologies are stepping stones that will lead the way to an augmented reality future.

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!

Reblogged 2 weeks ago from tracking.feedpress.it

Pinpoint vs. Floodlight Content and Keyword Research Strategies – Whiteboard Friday

Posted by randfish

When we’re doing keyword research and targeting, we have a choice to make: Are we targeting broader keywords with multiple potential searcher intents, or are we targeting very narrow keywords where it’s pretty clear what the searchers were looking for? Those different approaches, it turns out, apply to content creation and site architecture, as well. In today’s Whiteboard Friday, Rand illustrates that connection.

Pinpoint vs Floodlight Content and Keyword Research Strategy Whiteboard

For reference, here are stills of this week’s whiteboards. Click on it to open a high resolution image in a new tab!

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re going to chat about pinpoint versus floodlight tactics for content targeting, content strategy, and keyword research, keyword targeting strategy. This is also called the shotgun versus sniper approach, but I’m not a big gun fan. So I’m going to stick with my floodlight versus pinpoint, plus, you know, for the opening shot we don’t have a whole lot of weaponry here at Moz, but we do have lighting.

So let’s talk through this at first. You’re going through and doing some keyword research. You’re trying to figure out which terms and phrases to target. You might look down a list like this.

Well, maybe, I’m using an example here around antique science equipment. So you see these various terms and phrases. You’ve got your volume numbers. You probably have lots of other columns. Hopefully, you’ve watched the Whiteboard Friday on how to do keyword research like it’s 2015 and not 2010.

So you know you have all these other columns to choose from, but I’m simplifying here for the purpose of this experiment. So you might choose some of these different terms. Now, they’re going to have different kinds of tactics and a different strategic approach, depending on the breadth and depth of the topic that you’re targeting. That’s going to determine what types of content you want to create and where you place it in your information architecture. So I’ll show you what I mean.

The floodlight approach

For antique science equipment, this is a relatively broad phrase. I’m going to do my floodlight analysis on this, and floodlight analysis is basically saying like, “Okay, are there multiple potential searcher intents?” Yeah, absolutely. That’s a fairly broad phase. People could be looking to transact around it. They might be looking for research information, historical information, different types of scientific equipment that they’re looking for.

<img src="http://d1avok0lzls2w.cloudfront.net/uploads/blog/55b15fc96679b8.73854740.jpg" rel="box-shadow: 0 0 10px 0 #999; border-radius: 20px;"

Are there four or more approximately unique keyword terms and phrases to target? Well, absolutely, in fact, there’s probably more than that. So antique science equipment, antique scientific equipment, 18th century scientific equipment, all these different terms and phrases that you might explore there.

Is this a broad content topic with many potential subtopics? Again, yes is the answer to this. Are we talking about generally larger search volume? Again, yes, this is going to have a much larger search volume than some of the narrower terms and phrases. That’s not always the case, but it is here.

The pinpoint approach

For pinpoint analysis, we kind of go the opposite direction. So we might look at a term like antique test tubes, which is a very specific kind of search, and that has a clear single searcher intent or maybe two. Someone might be looking for actually purchasing one of those, or they might be looking to research them and see what kinds there are. Not a ton of additional intents behind that. One to three unique keywords, yeah, probably. It’s pretty specific. Antique test tubes, maybe 19th century test tubes, maybe old science test tubes, but you’re talking about a limited set of keywords that you’re targeting. It’s a narrow content topic, typically smaller search volume.

<img src="http://d1avok0lzls2w.cloudfront.net/uploads/blog/55b160069eb6b1.12473448.jpg" rel="box-shadow: 0 0 10px 0 #999; border-radius: 20px;"

Now, these are going to feed into your IA, your information architecture, and your site structure in this way. So floodlight content generally sits higher up. It’s the category or the subcategory, those broad topic terms and phrases. Those are going to turn into those broad topic category pages. Then you might have multiple, narrower subtopics. So we could go into lab equipment versus astronomical equipment versus chemistry equipment, and then we’d get into those individual pinpoints from the pinpoint analysis.

How do I decide which approach is best for my keywords?

Why are we doing this? Well, generally speaking, if you can take your terms and phrases and categorize them like this and then target them differently, you’re going to provide a better, more logical user experience. Someone who searches for antique scientific equipment, they’re going to really expect to see that category and then to be able to drill down into things. So you’re providing them the experience they predict, the one that they want, the one that they expect.

It’s better for topic modeling analysis and for all of the algorithms around things like Hummingbird, where Google looks at: Are you using the types of terms and phrases, do you have the type of architecture that we expect to find for this keyword?

It’s better for search intent targeting, because the searcher intent is going to be fulfilled if you provide the multiple paths versus the narrow focus. It’s easier keyword targeting for you. You’re going to be able to know, “Hey, I need to target a lot of different terms and phrases and variations in floodlight and one very specific one in pinpoint.”

There’s usually higher searcher satisfaction, which means you get lower bounce rate. You get more engagement. You usually get a higher conversion rate. So it’s good for all those things.

For example…

I’ll actually create pages for each of antique scientific equipment and antique test tubes to illustrate this. So I’ve got two different types of pages here. One is my antique scientific equipment page.

<img src="http://d1avok0lzls2w.cloudfront.net/uploads/blog/55b161fa871e32.54731215.jpg" rel="box-shadow: 0 0 10px 0 #999; border-radius: 20px;"

This is that floodlight, shotgun approach, and what we’re doing here is going to be very different from a pinpoint approach. It’s looking at like, okay, you’ve landed on antique scientific equipment. Now, where do you want to go? What do you want to specifically explore? So we’re going to have a little bit of content specifically about this topic, and how robust that is depends on the type of topic and the type of site you are.

If this is an e-commerce site or a site that’s showing information about various antiques, well maybe we don’t need very much content here. You can see the filtration that we’ve got is going to be pretty broad. So I can go into different centuries. I can go into chemistry, astronomy, physics. Maybe I have a safe for kids type of stuff if you want to buy your kids antique lab equipment, which you might be. Who knows? Maybe you’re awesome and your kids are too. Then different types of stuff at a very broad level. So I can go to microscopes or test tubes, lab searches.

This is great because it’s got broad intent foci, serving many different kinds of searchers with the same page because we don’t know exactly what they want. It’s got multiple keyword targets so that we can go after broad phrases like antique or old or historical or 13th, 14th, whatever century, science and scientific equipment ,materials, labs, etc., etc., etc. This is a broad page that could reach any and all of those. Then there’s lots of navigational and refinement options once you get there.

Total opposite of pinpoint content.

<img src="http://d1avok0lzls2w.cloudfront.net/uploads/blog/55b1622740f0b5.73477500.jpg" rel="box-shadow: 0 0 10px 0 #999; border-radius: 20px;"

Pinpoint content, like this antique test tubes page, we’re still going to have some filtration options, but one of the important things to note is note how these are links that take you deeper. Depending on how deep the search volume goes in terms of the types of queries that people are performing, you might want to make a specific page for 17th century antique test tubes. You might not, and if you don’t want to do that, you can have these be filters that are simply clickable and change the content of the page here, narrowing the options rather than creating completely separate pages.

So if there’s no search volume for these different things and you don’t think you need to separately target them, go ahead and just make them filters on the data that already appears on this page or the results that are already in here as opposed to links that are going to take you deeper into specific content and create a new page, a new experience.

You can also see I’ve got my individual content here. I probably would go ahead and add some content specifically to this page that is just unique here and that describes antique test tubes and the things that your searchers need. They might want to know things about price. They might want to know things about make and model. They might want to know things about what they were used for. Great. You can have that information broadly, and then individual pieces of content that someone might dig into.

This is narrower intent foci obviously, serving maybe one or two searcher intents. This is really talking about targeting maybe one to two separate keywords. So antique test tubes, maybe lab tubes or test tube sets, but not much beyond that.

Ten we’re going to have fewer navigational paths, fewer distractions. We want to keep the searcher. Because we know their intent, we want to guide them along the path that we know they probably want to take and that we want them to take.

So when you’re considering your content, choose wisely between shotgun/floodlight approach or sniper/pinpoint approach. Your searchers will be better served. You’ll probably rank better. You’ll be more likely to earn links and amplification. You’re going to be more successful.

Looking forward to the comments, and we’ll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!

Reblogged 2 years ago from tracking.feedpress.it

8 Ways Content Marketers Can Hack Facebook Multi-Product Ads

Posted by Alan_Coleman

The trick most content marketers are missing

Creating great content is the first half of success in content marketing. Getting quality content read by, and amplified to, a relevant audience is the oft overlooked second half of success. Facebook can be a content marketer’s best friend for this challenge. For reach, relevance and amplification potential, Facebook is unrivaled.

  1. Reach: 1 in 6 mobile minutes on planet earth is somebody reading something on Facebook.
  2. Relevance: Facebook is a lean mean interest and demo targeting machine. There is no online or offline media that owns as much juicy interest and demographic information on its audience and certainly no media has allowed advertisers to utilise this information as effectively as Facebook has.
  3. Amplification: Facebook is literally built to encourage sharing. Here’s the first 10 words from their mission statement: “Facebook’s mission is to give people the power to share…”, Enough said!

Because of these three digital marketing truths, if a content marketer gets their paid promotion* right on Facebook, the battle for eyeballs and amplification is already won.

For this reason it’s crucial that content marketers keep a close eye on Facebook advertising innovations and seek out ways to use them in new and creative ways.

In this post I will share with you eight ways we’ve hacked a new Facebook ad format to deliver content marketing success.

Multi-Product Ads (MPAs)

In 2014, Facebook unveiled multi-product ads (MPAs) for US advertisers, we got them in Europe earlier this year. They allow retailers to show multiple products in a carousel-type ad unit.

They look like this:

If the user clicks on the featured product, they are guided directly to the landing page for that specific product, from where they can make a purchase.

You could say MPAs are Facebook’s answer to Google Shopping.

Facebook’s mistake is a content marketer’s gain

I believe Facebook has misunderstood how people want to use their social network and the transaction-focused format is OK at best for selling products. People aren’t really on Facebook to hit the “buy now” button. I’m a daily Facebook user and I can’t recall a time this year where I have gone directly from Facebook to an e-commerce website and transacted. Can you remember a recent time when you did?

So, this isn’t an innovation that removes a layer of friction from something that we are all doing online already (as the most effective innovations do). Instead, it’s a bit of a “hit and hope” that, by providing this functionality, Facebook would encourage people to try to buy online in a way they never have before.

The Wolfgang crew felt the MPA format would be much more useful to marketers and users if they were leveraging Facebook for the behaviour we all demonstrate on the platform every day, guiding users to relevant content. We attempted to see if Facebook Ads Manager would accept MPAs promoting content rather than products. We plugged in the images, copy and landing pages, hit “place order”, and lo and behold the ads became active. We’re happy to say that the engagement rates, and more importantly the amplification rates, are fantastic!

Multi-Content Ads

We’ve re-invented the MPA format for multi-advertisers in multi-ways, eight ways to be exact! Here’s eight MPA Hacks that have worked well for us. All eight hacks use the MPA format to promote content rather than promote products.

Hack #1: Multi-Package Ads

Our first variation wasn’t a million miles away from multi-product ads; we were promoting the various packages offered by a travel operator.

By looking at the number of likes, comments, and shares (in blue below the ads) you can see the ads were a hit with Facebook users and they earned lots of free engagement and amplification.

NB: If you have selected “clicks to website” as your advertising objective, all those likes, comments and shares are free!

Independent Travel Multi Product Ad

The ad sparked plenty of conversation amongst Facebook friends in the comments section.

Comments on a Facebook MPA

Hack #2: Multi-Offer Ads

Everybody knows the Internet loves a bargain. So we decided to try another variation moving away from specific packages, focusing instead on deals for a different travel operator.

Here’s how the ads looked:

These ads got valuable amplification beyond the share. In the comments section, you can see people tagging specific friends. This led to the MPAs receiving further amplification, and a very targeted and personalised form of amplification to boot.

Abbey Travel Facebook Ad Comments

Word of mouth referrals have been a trader’s best friend since the stone age. These “personalised” word of mouth referrals en masse are a powerful marketing proposition. It’s worth mentioning again that those engagements are free!

Hack #3: Multi-Locations Ads

Putting the Lo in SOLOMO.

This multi-product feed ad was hacked to promote numerous locations of a waterpark. “Where to go?” is among the first questions somebody asks when researching a holiday. In creating this top of funnel content, we can communicate with our target audience at the very beginning of their research process. A simple truth of digital marketing is: the more interactions you have with your target market on their journey to purchase, the more likely they are to seal the deal with you when it comes time to hit the “buy now” button. Starting your relationship early gives you an advantage over those competitors who are hanging around the bottom of the purchase funnel hoping to make a quick and easy conversion.

Abbey Travel SplashWorld Facebook MPA

What was surprising here, was that because we expected to reach people at the very beginning of their research journey, we expected the booking enquiries to be some time away. What actually happened was these ads sparked an enquiry frenzy as Facebook users could see other people enquiring and the holidays selling out in real time.

Abbey Travel comments and replies

In fact nearly all of the 35 comments on this ad were booking enquiries. This means what we were measuring as an “engagement” was actually a cold hard “conversion”! You don’t need me to tell you a booking enquiry is far closer to the money than a Facebook like.

The three examples outlined so far are for travel companies. Travel is a great fit for Facebook as it sits naturally in the Facebook feed, my Facebook feed is full of envy-inducing friends’ holiday pictures right now. Another interesting reason why travel is a great fit for Facebook ads is because typically there are multiple parties to a travel purchase. What happened here is the comments section actually became a very visible and measurable forum for discussion between friends and family before becoming a stampede inducing medium of enquiry.

So, stepping outside of the travel industry, how do other industries fare with hacked MPAs?

Hack #3a: Multi-Location Ads (combined with location targeting)

Location, location, location. For a property listings website, we applied location targeting and repeated our Multi-Location Ad format to advertise properties for sale to people in and around that location.

Hack #4: Multi-Big Content Ad

“The future of big content is multi platform”

– Cyrus Shepard

The same property website had produced a report and an accompanying infographic to provide their audience with unique and up-to-the-minute market information via their blog. We used the MPA format to promote the report, the infographic and the search rentals page of the website. This brought their big content piece to a larger audience via a new platform.

Rental Report Multi Product Ad

Hack #5: Multi-Episode Ad

This MPA hack was for an online TV player. As you can see we advertised the most recent episodes of a TV show set in a fictional Dublin police station, Red Rock.

Engagement was high, opinion was divided.

TV3s Red Rock viewer feedback

LOL.

Hack #6: Multi-People Ads

In the cosmetic surgery world, past patients’ stories are valuable marketing material. Particularly when the past patients are celebrities. We recycled some previously published stories from celebrity patients using multi-people ads and targeted them to a very specific audience.

Avoca Clinic Multi People Ads

Hack #7: Multi-UGC Ads

Have you witnessed the power of user generated content (UGC) in your marketing yet? We’ve found interaction rates with authentic UGC images can be up to 10 fold of those of the usual stylised images. In order to encourage further UGC, we posted a number of customer’s images in our Multi-UGC Ads.

The CTR on the above ads was 6% (2% is the average CTR for Facebook News feed ads according to our study). Strong CTRs earn you more traffic for your budget. Facebook’s relevancy score lowers your CPC as your CTR increases.

When it comes to the conversion, UGC is a power player, we’ve learned that “customers attracting new customers” is a powerful acquisition tool.

Hack #8: Target past customers for amplification

“Who will support and amplify this content and why?”

– Rand Fishkin

Your happy customers Rand, that’s the who and the why! Check out these Multi-Package Ads targeted to past customers via custom audiences. The Camino walkers have already told all their friends about their great trip, now allow them to share their great experiences on Facebook and connect the tour operator with their Facebook friends via a valuable word of mouth referral. Just look at the ratio of share:likes and shares:comments. Astonishingly sharable ads!

Camino Ways Mulit Product Ads

Targeting past converters in an intelligent manner is a super smart way to find an audience ready to share your content.

How will hacking Multi-Product Ads work for you?

People don’t share ads, but they do share great content. So why not hack MPAs to promote your content and reap the rewards of the world’s greatest content sharing machine: Facebook.

MPAs allow you to tell a richer story by allowing you to promote multiple pieces of content simultaneously. So consider which pieces of content you have that will work well as “content bundles” and who the relevant audience for each “content bundle” is.

As Hack #8 above illustrates, the big wins come when you match a smart use of the format with the clever and relevant targeting Facebook allows. We’re massive fans of custom audiences so if you aren’t sure where to start, I’d suggest starting there.

So ponder your upcoming content pieces, consider your older content you’d like to breathe some new life into and perhaps you could become a Facebook Ads Hacker.

I’d love to hear about your ideas for turning Multi-Product Ads into Multi-Content Ads in the comments section below.

We could even take the conversation offline at Mozcon!

Happy hacking.


*Yes I did say paid promotion, it’s no secret that Facebook’s organic reach continues to dwindle. The cold commercial reality is you need to pay to play on FB. The good news is that if you select ‘website clicks’ as your objective you only pay for website traffic and engagement while amplification by likes, comments, and shares are free! Those website clicks you pay for are typically substantially cheaper than Adwords, Taboola, Outbrain, Twitter or LinkedIn. How does it compare to display? It doesn’t. Paying for clicks is always preferable to paying for impressions. If you are spending money on display advertising I’d urge you to fling a few spondoolas towards Facebook ads and compare results. You will be pleasantly surprised.

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!