Forget your existing target market for a second.

Now think of all the possible people you could target.

That’s a lot of people, right? And you know it doesn’t make sense to target all of them.

That’s why, before you get down to creating buyer personas, you should divide the market up into useful pieces.

These pieces are known as segments.

But what’s implicit segmentation? And why should your organization use it?

Read on to discover… 👇

What is market segmentation?

Market segmentation is the practice of sorting members of a customer base into divisions based on shared characteristics. Such characteristics can be simple, including age, demographic, background, and language. Or, such characteristics can be more sophisticated, based on the customers’ needs and goals, or on past behavioral data.

Businesses use a market segmentation strategy to improve messaging specificity, to drive product differentiation to more closely match the needs of high-value or under-served market segments, and to generally improve marketing and product strategies. (Hint: if you're building a niche differentiation strategy, you'll want to know more about segmentation.)

What is implicit segmentation in marketing?

Implicit segmentation is the practice of using implied data to make assumptions about customers and categorize them. From there, you can predict future behavior, produce more targeted messaging, or provide a better customer experience. Segmentation is typically the first step in targeted, personalized marketing.

Implied data is data collected in the background, without asking customers to give specific information.

Implicit segmentation could include categorizing based on customer loyalty, implied interests (based on past activity and other data), the customer’s supposed engagement level, or their assumed stage in the customer journey.

Explicit vs implicit segmentation techniques in marketing

Struggling to understand implicit segmentation?

Let’s take a look at its opposite, explicit segmentation. 👀

Explicit data and segmentation

Explicit data is made up of information customers explicitly give you about themselves; your customers can then be grouped according to that information.

This could include things the customer has done, the information they’ve given, or simple facts like their location and age.

Explicit segmentation techniques make it easy to categorize customers, but the segments themselves are not always super useful, since they’re not specific. Their breadth can stop us from understanding different customer needs well enough, and from helping them to buy.

Some examples of explicit segmentation:

  • Florida residents.
  • People aged 25-34.
  • Businesses in the telecommunications industry.

You might be wondering, “Why not ask customers for specific information? Then it’s both explicit and specific.”

You can. But this requires you to survey customers, which carries certain risks depending on your survey design. You risk asking leading questions that encourage certain answers. Or, the answers you allow for in multiple choice segments might not match those the customer wants to give.

Implicit data and segmentation

Collecting implicit data is different.

You passively ‘listen’ to the actions of your customers, by using internet tracking cookies, or by looking at browser data, for example. This casts a wider net, so you can collect more data points, which allows for better analysis and segmentation.

Implicit segmentation (or ‘implied segmentation’) techniques use this ‘background’ data to draw conclusions about consumers. 🤔

As an example, instead of people aged “25-34”, your segment might be “people interested in basketball”. This is a more specific (and therefore arguably more useful) category for a business to look into.

But how would you assess whether a customer is part of that group if they don’t tell you?

Implicit segmentation has the answer: guess that an individual is part of a specific segment based on the data you do have.

Combining explicit and implicit techniques

In practice, it makes little sense to produce segments based on only explicit or implicit data. You’ll produce more useful, profitable segments if you combine both types of segmentation.

Here’s a use case for you.

Let’s say you own a business that sells computer parts to tech enthusiasts. You need to find potential customers to market to.

You might know from past buyer behavior that more than 50% of your buyers live in just three states (explicit data).

You might also know that this majority is most interested in graphics cards and CPUs since this is what your customers in these states buy most often (explicit data).

From internet browser data, perhaps you see that 70% of your website visitors are men aged between 16-34. And that the landing pages on your site with the highest click-through rates are blogs about installing this hardware in laptops.

You can take this information and combine it with your other data to create a high-value segment and, from there, build a solid buyer persona. You’ll be able to include details about where this persona spends their time and attention, and where you should be advertising in order to capture that attention.

Sources of implicit and explicit data

Before you can divide up your customer base, you need data. 👨‍💻

Of all the places you can go, it makes the most sense to start with those that are readily available and which contain a lot of useful information. Here are a few to get you started:

Email marketing campaigns

Your email campaigns are a great place to start. Open rates and click-through rates are great for learning about a customer’s possible engagement rate or level of interest.

Your sales platform

Sales platforms and CRMs like Hubspot are a goldmine. Right away you’ll be able to categorize leads according to what stage of the deal funnel they’re at. If you record conversations between customers and sales reps, even just as notes, you’ll have plenty of data that are both explicit and specific.

Social media platforms

LinkedIn, Facebook, and other social media platforms offer readily available demographic data like age and location, plus data on customer interests.

Where does segmentation fit into your marketing strategy?

You may have heard about the STP framework: Segmentation, Targeting, Positioning.

As we alluded to in our introduction, and as the STP framework implies, segmentation comes early in your marketing strategy.

In fact, it should probably come first.

Though you can market to anyone, you shouldn’t market to everyone. And determining the highest value groups of people interested in your product or service, and prioritizing those groups in your marketing strategy, is crucial for getting the most out of your marketing efforts.

So before you and your marketing team start creating buyer personas, collect some implicit and explicit data to segment your audience. Prioritize the highest value segments, then create buyer personas for these segments.

You’ll save time and achieve greater impact. 💪