Customer segmentation has always been important. But now that orchestrating journeys that reflect a customer’s overall experience, rather than their most recent interaction within a siloed touchpoint, is integral to enterprise success today, effective segmentation is an absolute must.

But according to a recent Forrester report, only 33% of companies using customer segmentation say they find it significantly impactful. According to the report, the main reason companies fail is that they are still using traditional customer segmentation approaches, without leveraging the breadth of customer data and advanced analytics techniques available today.

In other words, they are not using a modern behavioral segmentation approach.

In this post I’ll bring you up to speed with an in-depth overview of 10 different approaches to behavioral segmentation that can be used to better understand your customer’s and their goals, in order to maximize journey success and achieve business outcomes.

What is Behavioral Segmentation?
Traditional approaches to segmentation focused mainly on who customers are and segments were based on demographic attributes such as gender or age, and firmographic attributes like company size or industry. But as I discussed in my previous post on customer behavior data, just understanding who your customers are is not enough anymore.

Earlier this week we asked our Twitter followers what they think happened to organic traffic when we added a 2-step email signup component to pages.

Almost 64% of those who answered thought this change would have no detectable impact on organic traffic while almost 32% thought this would result in a negative impact to SEO.

Well, majority of the guesses were incorrect. In fact, this particular test resulted in a negative impact to SEO (and conversion rates). Read on to learn more!

The Case Study
Email is a powerful marketing channel, but there can be trade-offs between different approaches toward capturing users’ email addresses and permissions. In our latest case study, we explore how one approach to email capturing impacted SEO.

We tested adding a signup component that involved two steps: it appeared at the bottom of the page, encouraging users to sign up for email updates. Once clicked, it expanded to a larger component and centered itself in the middle of the page so that users could input their email address. Our goal was to begin capturing email addresses on these pages without obscuring the whole page with an immediate overlay.

We tested this change full funnel and hoped that by only showing the larger email capture pop-up to those users that had already indicated they were happy to submit their email, we would avoid negative impacts on users who didn’t want to subscribe. Below are examples of how the 2-step component appeared on both desktop and mobile devices.

This week we asked our Twitter followers what they thought happened when we added a confidence banner to a travel client’s website (this test was run pre-COVID). The test was a full funnel experiment, so we measured the impact on user metrics (conversion rate and bounce rate) and on organic traffic.

We asked our Twitter followers what they thought the impact of this test was on organic traffic, 37% guessed positive impact, 17% guessed negative impact, 46% guessed no detectable impact.We asked our twitter followers what they thought the impact on conversions was for this test, 68% guessed a positive impact, 12% guessed a negative impact, 20% guessed it had no detectable impact.
The consensus from our followers was that this experiment had no detectable impact on organic traffic and was positive for conversion rate. This was partly correct – this test was positive for both organic traffic and conversion rate. Read below for the full case study:

The Case Study
Can trust signals impact SEO performance? That’s what our client set out to answer with this test. Our client tested adding confidence messaging below their search bar and measured the impact on user metrics (conversion rate and bounce rate) at the same time as measuring the impact on organic traffic. They tested this on three different domains, Spain, Russia and France.

Mockup of changes to the page where confidence message was added saying: ‘No hidden fees’, among other benefits.Mockup of changes to the page where confidence message was added saying: ‘No hidden fees’, among other benefits.
In our previous case study, testing page layout changes, we shared a test where moving the search widget on a travel client’s page had a negative impact on organic traffic. This case study of ours is one of many that we believe support the increasing importance of user signals for rankings.

In addition to user signals, many in the industry argue that the August 2018 core algorithm update placed further importance on E-A-T (Expertise, Authoritativeness and Trustworthiness), especially for Your Money Your Life (YMYL) websites.

In this week’s #SPQuiz, we asked our Twitter followers what they thought the outcome in organic traffic was when we added a new keyword to the H1 of a customer’s product pages.

Here’s what people thought:

The majority of our followers believe adding additional keywords to the H1 would positively impact traffic. In contrast, almost 30% and 7% believe this change would either not have a noticeable impact or have a negative impact on organic traffic, respectively.

In this case, the majority were correct…sort of – read the full case study below!

The Case Study
The H1 is one of the oldest known ways to improve relevancy as H1s are used to highlight the page’s main topic, contributing to the overall user experience. While the H1 has been standard in SEO best practice for years, its significance as a ranking factor has often been questioned and debated.

In early 2020, Google’s John Mueller took time to explain Google uses headings to understand page content better, and that this can result in ranking improvements, or in ranking for new searches.

We decided to experiment with the H1 of a customer’s website to see if it would allow Google to improve our rankings for a broader set of keywords. We ran this experiment with an ecommerce company that offers customizable products by adding the keyword “Custom” to the front of the H1 of the product pages. Note: “custom” already appeared elsewhere on the page, in the title, and in other headings.

FAQ schema is a form of structured markup that can get rich snippets in search results. It was released in 2019 and allows web pages to mark up FAQ content on their web pages so that it appears for users in the SERP (Search Engine Results Page). When implemented, it can transform your web page’s search result to look like this:

Example of FAQ rich snippet

Not only can these rich snippets readily provide informative content to users, they also created quite a buzz in the industry when SEOs discovered they could be used to take up more real estate on the SERP, pushing competitors further down the page.

In August last year we shared our first case studies from testing FAQ schema, where we reported that we had seen uplifts in organic traffic ranging from 3% to 8% despite the concerns of ourselves and others that this new search feature was going to negatively impact organic click-through-rates.

They were exciting results, but a lot has changed since then. First, since we published that case study Google made some changes to FAQ schema implementation. Gone are the days where you can go wild on the SERP with price, and review, and FAQ schema and get rich snippets for all of them. Today, aside from some rare edge cases, Google only allows you to have either price and review snippets or FAQ snippets:

FAQ Only

This week, we asked our Twitter followers what they thought happened to the organic traffic of pages when we replaced microdata markup with the equivalent JSON-LD structured data.

This was what they thought:

Twitter poll showing 61% of voters believing that the test had no detectable impact on organic traffic, 33% thought this change had a positive impact, 5% thought negative impact
It turns out those 61% of people were correct! This change had no measurable impact on organic traffic, despite JSON-LD being Google’s preferred way of adding structured data to a page.

The Case Study
We have run hundreds of tests implementing different schema to win various rich snippets over the years. While there’s never a universal answer for every website on whether a specific type of schema will improve organic traffic or not, implementing schema to win rich snippets generally generates good results for organic traffic.

From review schema to win review star snippets, to FAQ schema to soak up real estate on the SERP, we can generally accept that the rich results produced from schema implementation benefit users and improve organic click-through-rates.

Yet, there’s not one universal way to mark up data on your website. On schema.org, a collection of shared vocabularies for data markup understood by the major search engines. There are two widely used formats for structured data: microdata and JSON-LD.

With JSON-LD, a JavaScript object is inserted into the HTML of your page to define data, whereas microdata uses HTML tags and attributes to define data. In its structured data guidelines, Google states that it recommends JSON-LD over microdata for web content.

So we know that Google prefers JSON-LD, but does that preference translate to improved organic traffic if we change our structured data markup from microdata to JSON-LD? That was the question we sought to answer for this test.

The test was run on a client’s website in the travel sector (in January 2020, before any traffic drops related to the COVID-19 pandemic). The client in question had various schema on its website implemented with microdata. This included breadcrumb, review, and offer schema.

We didn’t change any of the schema other than removing all the microdata tags and attributes, and instead inserting script elements containing JSON-LD objects after the opening body tag.

Table of Contents
Buttons
Tactic 1: Choose a Contrasting Button Color
Tactic 2: Increase the Amount of Whitespace
Tactic 3: Convey Depth Through a Border, Bevel, or Shadow
Tactic 4: Convey Movement With an Arrow
Tactic 5: Alter Your Button on Hover
Tactic 6: Orient Gazes Toward Your CTA
Tactic 7: Repeat Your Primary CTA
Tactic 8: Use 1st Person Wording
Tactic 9: Change Your Button During a Visit
Tactic 10: Force Visitors to Accept / Reject Your CTA
Create an Account
Tactic 11: Use a Two-Step Opt-In
Tactic 12: Let Visitors Create Tangible Progress
Tactic 13: Don’t Require Credit Cards for Free Trial
Tactic 14: Emphasize Their Progress Within Your Funnel

For this edition of the #SPQuiz, we asked our Twitter followers what they expected to have happened when we replaced numbers with emoji in meta descriptions. The response was mixed:

Result of Twitter poll on emoji meta descriptions

No answer gained an overall majority of votes, but the largest group thought that this change wouldn’t have a significant impact on organic traffic. Only one in four of our Twitter followers thought that this change would be negative. In this case, it turns out that the minority was correct. As you’ll read below, this change was negative for organic traffic in this case, a fact that 75% of people got wrong!

The Case Study

The use of emoji can be a divisive topic in SEO, especially in the context of trying to get them shown in search results. On the one hand, they can be eye-catching, and an easy way to get people to notice your result and potentially click on it. On the other hand, they can come across as gimmicky, and some searchers may be put off from clicking because it looks unprofessional.

Before we get into the details of this particular test, a bit of background information on emoji and how they can be used for SEO purposes. Emoji are characters that form part of the Unicode standard for text, alongside letters, numbers, punctuation and all other characters in a wide range of writing systems.

Since they are just Unicode characters, they can be used within HTML elements the same way as any other character. As such they can be included in title tags, meta descriptions and even structured data markup. In general, Google will pull these characters through into the search results as it would for any other character. Note that the emoji will be displayed in the default font of a user’s browser, and as such may be displayed differently to how you might expect.

In this particular test (launched in July 2020), we wanted to test replacing the number of items listed in a website’s category page meta descriptions with the equivalent numerical emoji. For example, 125 would be replaced with 1️⃣2️⃣5️⃣. Below is an example of how this would look in an analogous website’s Search Engine Results Page (SERP) snippets.*

In this week’s #SPQuiz, we asked our Twitter followers what they thought the impact on organic traffic was when we reordered title tags to include brand names at the start, especially if you are a household name.

Here is what they thought:

While it was close, the majority of followers that responded believed the brand name in the front had a positive impact on organic traffic. Although it was a small sample size of followers, the majority were correct!

This change had a positive impact on organic traffic – read on for the full case study!

Decisions about where to include brand keywords in title tags have been around as long as title tags themselves, and there are good arguments for leading with the brand and good arguments for leading with more generic keywords. Many industries have this tension, but local search is a fascinating example to investigate – with some people looking for their nearest store of a particular type, and some people searching for a specific retailer.

There is a theoretical tradeoff between a better click-through rate at a high level when the brand is presented more prominently and potentially worse rankings for generic queries. The only way to be sure which effect wins out is to test it.

While title tag tests are straightforward, they can often yield surprising results regarding their impact on organic traffic. The powerful effect on both rankings and click-through rate is the main reason why our SearchPilot customers love to test their title tags.

Our case study this week goes back to the basics as we look at localized search queries. We recently tested adding the brand name to the beginning of the title tags on city level pages.

This enabled marketing and sales teams to carve out inch-perfect strategies that specifically target requiting audiences based on the psychological factors they consider dear. The resultant success of B2C psychographics further led to another proposition — B2B psychographics. As traditional wayward methods of sales targeting eroded with the rise of data driven sales intelligence, it was only wise to turn the tables around and use tools such as psychographics on businesses themselves — employees, managers, key personnel, members of management.

Fast forward to today, psychographics allow marketing and sales teams to target only the prospects that have the highest probability of reciprocating the demand for your product or service. Integrating extrapolated psychographic data into your market strategies can help you improve your deal conversion rates and reach out to the right target audience. Psychographics enable your business to assemble inclusive campaigns, strategies and content that dramatically boost conversions. But first:

What is Psychographic Segmentation?