Posted by willcritchlow
Testing for only SEO or only CRO isn’t always ideal. Some changes result in higher conversions and reduced site traffic, for instance, while others may rank more highly but convert less well. In today’s Whiteboard Friday, we welcome Will Critchlow as he demonstrates a method of testing for both your top-of-funnel SEO changes and your conversion-focused CRO changes at once.
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Hi, everyone. Welcome to another Whiteboard Friday. My name is Will Critchlow, one of the founders at Distilled. If you’ve been following what I’ve been writing and talking about around the web recently, today’s topic may not surprise you that much. I’m going to be talking about another kind of SEO testing.
Over at Distilled, we’ve been investing pretty heavily in building out our capability to do SEO tests and in particular built our optimization delivery network, which has let us do a new kind of SEO testing that hasn’t been previously available to most of our clients. Recently we’ve been working on a new enhancement to this, which is full funnel testing, and that’s what I want to talk about today.
So funnel testing is testing all the way through the funnel, from acquisition at the SEO end to conversion. So it’s SEO testing plus CRO testing together. I’m going to write a little bit more about some of the motivation for this. But, in a nutshell, it essentially boils down to the fact that it is perfectly possible, in fact we’ve seen in the wild cases of tests that win in SEO terms and lose in CRO terms or vice versa.
In other words, tests that maybe you make a change and it converts better, but you lose organic search traffic. Or the other way around, it ranks better, but it converts less well. If you’re only testing one, which is common — I mean most organizations are only testing the conversion rate side of things — it’s perfectly possible to have a winning test, roll it out, and do worse.
So let’s step back a little bit. A little bit of a primer. Conversion rate optimization testing works in an A/B split kind of way. You can test on a single page, if you want to, or a site section. The way it works is you split your audience. So your audience is split. Some of your audience gets one version of the page, and the rest of the audience gets a different version.
Then you can compare the conversion rate among the group who got the control and the group who got the variant. That’s very straightforward. Like I say, it can happen on a single page or across an entire site. SEO testing, a little bit newer. The way this works is you can’t split the audience, because we care very much about the search engine spiders in this case. For the purposes of this consideration, there’s essentially only one Googlebot. So you couldn’t put Google in Class A or Class B here and expect to get anything meaningful.
So the way that we do an SEO test is we actually split the pages. To do this, you need a substantial site section. So imagine, for example, an e-commerce website with thousands of products. You might have a hypothesis of something that will help those product pages perform better. You take your hypothesis and you only apply it to some of the pages, and you leave some of the pages unchanged as a control.
Then, crucially, search engines and users see the same experience. There’s no cloaking going on. There’s no duplication of content. You simply change some pages and not change others. Then you apply kind of advanced mathematical, statistical analysis trying to figure out do these pages get statistically more organic search traffic than we think they would have done if we hadn’t made this change. So that’s how an SEO test works.
Now, as I said, the problem that we are trying to tackle here is it’s really plausible, despite Google’s best intentions to do what’s right for users, it’s perfectly plausible that you can have a test that ranks better but converts less well or vice versa. We’ve seen this with, for example, removing content from a page. Sometimes having a cleaner, simpler page can convert better. But maybe that was where the keywords were and maybe that was helping the page rank. So we’re trying to avoid those kinds of situations.
Full funnel testing
That’s where full funnel testing comes in. So I want to just run through how you run a full funnel test. What you do is you first of all set it up in the same way as an SEO test, because we’re essentially starting with SEO at the top of the funnel. So it’s set up exactly the same way.
Some pages are unchanged. Some pages get the hypothesis applied to them. As far as Google is concerned, that’s the end of the story, because on any individual request to these pages that’s what we serve back. But the critically important thing here is I’ve got my little character. This is a human browser performs a search, “What do badgers eat?”
This was one of our silly examples that we came up with on one of our demo sites. The user lands on this page here. What we do is we then set a cookie. This is a cookie. This user then, as they navigate around the site, no matter where they go within this site section, they get the same treatment, either the control or the variant. They get the same treatment across the entire site section. This is more like the conversion rate test here.
Googlebot = stateless requests
So what I didn’t show in this diagram is if you were running this test across a site section, you would cookie this user and make sure that they always saw the same treatment no matter where they navigated around the site. So because Googlebot is making stateless requests, in other words just independent, one-off requests for each of these of these pages with no cookie set, Google sees the split.
Evaluate SEO test on entrances
Users get whatever their first page impression looks like. They then get that treatment applied across the entire site section. So what we can do then is we can evaluate independently the performance in search, evaluate that on entrances. So do we get significantly more entrances to the variant pages than we would have expected if we hadn’t applied a hypothesis to them?
That tells us the uplift from an SEO perspective. So maybe we say, “Okay, this is plus 11% in organic traffic.” Well, great. So in a vacuum, all else being equal, we’d love to roll out this test.
Evaluate conversion rate on users
But before we do that, what we can do now is we can evaluate the conversion rate, and we do that based on user metrics. So these users are cookied.
We can also set an analytics tag on them and say, “Okay, wherever they navigate around, how many of them end up converting?” Then we can evaluate the conversion rate based on whether they saw treatment A or treatment B. Because we’re looking at conversion rate, the audience size doesn’t exactly have to be the same. So the statistical analysis can take care of that fact, and we can evaluate the conversion rate on a user-centric basis.
So then we maybe see that it’s -5% in conversion rate. We then need to evaluate, “Is this something we should roll out?” So step 1 is: Do we just roll it out? If it’s a win in both, then the answer is yes probably. If they’re in different directions, then there are couple things we can do. Firstly, we can evaluate the relative performance in different directions, taking care that conversion rate applies generally across all channels, and so a relatively small drop in conversion rate can be a really big deal compared to even an uplift in organic traffic, because the conversion rate is applying to all channels, not just your organic traffic channel.
But suppose that it’s a small net positive or a small net negative. What we can then do is we might get to the point that it’s a net positive and roll it out. Either way, we might then say, “What can we take from this? What can we actually learn?” So back to our example of the content. We might say, “You know what? Users like this cleaner version of the page with apparently less content on it.The search engines are clearly relying on that content to understand what this page is about. How do we get the best of both worlds?”
Well, that might be a question of a redesign, moving the layout of the page around a little bit, keeping the content on there, but maybe not putting it front and center to the user as they land right at the beginning. We can test those different things, run sequential tests, try and take the best of the SEO tests and the best of the CRO tests and get it working together and crucially avoid those situations where you think you’ve got a win, because your conversion rate is up, but you actually are about to crater your organic search performance.
We think this is going to just be the more data-driven we get, the more accountable SEO testing makes us, the more important it’s going to be to join these dots and make sure that we’re getting true uplifts on a net basis when we combine them. So I hope that’s been useful to some of you. Thank you for joining me on this week’s Whiteboard Friday. I’m Will Critchlow from Distilled.
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We talk a lot about local search and local search trends here at SEW and in the industry as a whole.
How have consumers changed the way they interact with local businesses? How can local businesses respond? And what can we anticipate about future trends?
Yext recently released some interesting findings on local search trends based on their internal data.
They analyzed a sample of more than 300,000 customer business locations active from January 1, 2017 to December 31, 2018.
What can we learn from this data about how consumer search behavior changed in 2018 versus 2017? And what might these changes tell us about the year ahead?
Key local search trends from their analysis include:
- Consumer interactions with businesses increased: New business reviews up 87% YoY.
- Businesses across industries saw more interactions via AI-enabled services than their own websites. Up to 2.7 times as much traffic on third-party sites.
- More consumers took action in search results: 20.1% increase in clicks to call, clicks for directions, and clicks to the website.
- Local pages saw increased consumer actions (i.e. pages for booking appointments, placing orders, etc.): Up 30.4% YoY.
We spoke with Zahid Zakaria, Yext’s Senior Director of Customer Insights and Analytics. Zahid leads the data team behind these new findings.
He’s been at Yext since August 2015, and spends nearly all of his time focused on client data. How can they unify data? What are the right metrics? How does an impression on a listing compare to an impression on a page? How can they understand the insights in local search trends?
These questions and more led them to this analysis. They’d seen that the local search market has been consistently growing, but wanted to find what insights demonstrated that growth.
First, about the data set and the approach
“We deal with tremendous data here at Yext,” Zahid said. “We power more than a million businesses globally. And we do quite a bit to ensure that all the work we do is based on a very complete data set.”
For these local search trends, the data set includes:
- More than 300,000 individual businesses
- Reviews for more than 150,000 business locations
- Actions on local pages for more than 59,000 business locations
Timing: Every data point included in this set remained live for the entirety of January 1, 2017 — December 31, 2018. So it wasn’t affected by clients opening new locations, etc.
Distribution: They examined business primarily located in the US, and also had significant representation of businesses in Western Europe (mainly the UK, Germany, and France).
In other words, quite a clean and thorough data set to work with.
They examined how metrics compared from the 2018 calendar year versus those same metrics for the same businesses for the 2017 calendar year.
So what did they find about local search trends?
The biggest takeaway was that consumers are interacting more with businesses via local search and local listings. Local interactions as a whole have increased.
Perhaps because search technology has gotten better, perhaps because SEOs are nailing it, but this rang true across the board, including Google, Alexa, and Siri.
As Zahid said, “There is unbelievable consumer interaction data happening on websites.”
What do those interactions look like?
1. New reviews per business location increased 87% in 2018 versus 2017
In other words, the volume of reviews per business nearly doubled this past year.
Whatever the reason, consumers seem to be feeling more comfortable treating an online business page as the representation of the business itself. And they seem to show little reserve in expressing their opinions there.
Beyond that, though, consumers take time and effort to leave a comment. They want to return the interaction.
And these brand interactions only increase the value of focusing on these listings.
2. More interactions via AI-enabled services than business’s own websites
“AI-enabled services” includes any consumer-based service powered by AI.
This could be traditional search, voice search, voice assistants, chatbots, Google, Alexa, Siri, Facebook, Yelp, Bing, etc.
Yext found that across nearly all industries, businesses have seen a greater proportion of their brand interactions happening via AI-enabled services rather than on their own websites.
73% percent of high-intent traffic occurs off a business’s own website.
Most businesses see 2.7 times the traffic on third-party sites verses on their own website.
(Caveat: these two stats were actually isolated to May 2017, in a survey of 20,107 business locations. We’re including them here as they represent a portion of the broader data set and local search trends as a whole.)
Consumers may find a business in an off-site interaction. They then would visit a business’s local page to take action.
This represents a fundamental shift in how consumers find out about and interact with a business.
Marc Ferrentino, Chief Strategy Officer at Yext, commented on this point:
“For twenty years, the brand website was the entry point for customers. People would go to the homepage and navigate to find the information they needed.
We’ve found that the customer acquisition funnel is no longer on the business website. Brand interactions in third-party AI-powered services are rising across the board as consumers engage with businesses off-site.
By the time they get to a business website, they’re ready to transact, and go straight to a local landing page to do so, often bypassing the homepage entirely.”
3. More consumers took action in search results
Within search results, there was a 20.1% increase in clicks to call, clicks for directions, and clicks to a business’s website.
Yext called these “Customer actions per business location.”
As we’ve seen since the beginning of local search, many consumers search in “micro-moments” of need. They’re often ready to make a purchase, walk into a store, place an order, etc.
Yext’s data shows that this trend is becoming even more prevalent.
4. Actions on transactional local pages saw increased 30.4%
Some businesses have “transactional” local pages, where consumers can book appointments, place orders, sign up for information, etc.
Increasingly, these pages are where the action is.
On this, Zahid elaborated, “When I as a consumer click the website link that shows up in a listing profile, what do I do? Surprisingly, it’s not get directions or make a phone call. It’s actually everything else.”
Consumers, it seems, increasingly want to complete their task — whatever they went searching for — via the page itself, without having to call or visit a location.
At the beginning of local search, we met consumers who wanted to make a phone call or get directions.
What we’re seeing as a trend, however, is that consumers don’t want to call to make an appointment, or get directions to a store to buy something.
They want to take those actions from the local page itself.
“Keeping that listing local is critical. A brand who takes a consumer from a local listing to their homepage just took that consumer from a local experience to a non-local experience.
For example, say I want to go get a haircut and the first thing I see when I land on that website is the exact wait time. It’s much better at capturing that micro moment of intent and turning it into a conversion.
That could be an online conversion, like in financial services, maybe requesting quotes. Or an offline conversion — maybe I just walked into the store, or made a phone call, booked that time to get my hair cut.”
Key takeaways for SEOs based on these findings
So we’ve seen the above local search trends. Customers interact more with local business pages. They leave reviews. They take actions — increasingly beyond just calling and getting directions. And they come through a different point of entry than they have for the last twenty years.
With that information, what can we do moving forward? Zahid pulled these four takeaways.
- “Obviously number one, ensure your listings data is accurate.”
- “Number two, think about your consumer journey. Think about the things you want to curate on a local landing page when a consumer hasn’t been able to find information on a local listing. Each industry is so different, depends on that consumer journey. Be there, do the best you can to answer consumer questions accurately.”
- “And third, when consumers are taking their time and effort to leave feedback, their expectation is to be heard. These are valuable interactions you need to cater to, especially as we’re seeing the whole search industry shift from “how many links” to listings management, knowledge cards, and conversational AI.”
- “Your local landing page is your visual merchandising for that locality. We do so much in the old world for visual merchandising. Treat your local landing page that way. Help people know why they should come to your store. Promote those interactions. Visually appealing, experience optimizing.
Based on these local search trends, how should we act in 2019?
Based on this data, what can we predict about the rest of the year? And what can we do with that information?
Zahid drew three primary conclusions.
1. Understand the interactions of local pages and listings — understand what works and what doesn’t
“So the algorithm updates? Analyze your listings data. See how that changed from your organic data. See how they interact.
From the the last update we had some really interesting stories of clients that won and clients that lost. It’s very interesting to see how some that won had made great use of things like schema. They’ve really gone above and beyond.
Looking at the interaction of what you do on your local page and how that impacts your listing visibility is incredibly important. These two properties work together. Optimize engagement not just on listings, but on landing pages. Think of them as one thing that you’re optimizing.
That’s one. Make sure you understand those interactions.”
2. Think about consumer questions and answer those
“Don’t forget about the world of voice and conversational AI as you think about your content strategy.
As we see the shift to voice assistants, think about how you’ll win here.
Answer the actual questions. Pull from inward sources. What are consumers looking for? What can we answer?
If you think from that perspective, you’ll be poised to win.”
3. Map data sources to answer future questions the right way
“Look inwardly at data hygiene and what you need to get that information out there
Think five years in advance. Make a roadmap of how all these answers sit. Think about it now to carve a strategy.”
What are your go-to methods for data analysis?
Given the general influx of data marketers have to deal with, and given that Zahid heads up a data team that has to deal with swarms of data points from millions of individual businesses — I couldn’t resist throwing in this question.
His answer? No secret sauce.
Like most of us, he first turns to Google Analytics and Google Search Console to look at his own website data and ask what trends are there.
Then he moves to other website sources: Google My Business, Facebook, etc. He’ll also use listings such as Yext’s own Intelligent Search Tracker, Brightedge, and various other rank trackers.
After that, he’ll look at third party industry level sources of information: Google Trends, publications.
Taking all of those things together, he’ll take a holistic look at what’s happening.
“Cleaning data is a lot like cooking,” he explained. “The first step is sourcing your ingredients. Source your data sources. Don’t just cook with one ingredient.”
One of the most challenging things?
“Merging a URL with a listing, and looking at a lot of different data sources together. A listing is not a URL. Some URLs are associated with a location or have UTMs directed to them. Tools like Yext help you unify that with the object as a core concept. Otherwise, you should do a mapping exercise. Where did all your data come from, what all do you have to look at?”
Final thoughts to keep in mind on this data set
In closing, Zahid gave one friendly caveat: These are trends, not benchmarks.
“What we know about this data is that it’s a reflection of a lot of things. Trends that are coming. For this data, all these customers were on Yext. They saw certain growth, certain increases. But we think it’s a pretty good reflection of the trends. Use this as a directional thing. Not the exact number — you don’t need to compare yourself exactly. Use it to indicate where you should be going.”
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