Customer Segmentation Analysis: A Guide

Customer Lifecycle Marketing|6 Minute Read

Customer Segmentation Analysis: A Guide

Customer segmentation analysis remains a highly critical task for companies today.

And now, there’s a simpler, far more efficient means to conduct this data analysis and better understand customers’ journeys.

When done carefully and thoroughly — and with the optimal tech (a vital component we’ll circle back on shortly) — this data examination of your various types of customers can transform your marketing program for the better, both immediately and in the long term.

With an improved customer segmentation strategy — and an advanced system that helps you unify and organize your first-party data sets and, in turn, more easily identify and interact with your ideal customers — you can take your engagement efforts to new heights.

In other words, you can routinely and extensively analyze each segment, get intricate insights about customers’ buying behaviors and patterns, and address any marketing pain points (e.g., ineffective personalized messaging).

Simply put, scrutinizing your target segments and evaluating the (hopefully) rich customer data that lives in their (hopefully) unified profiles (e.g., products and services bought, online engagement levels) is now the premier way to better understand and serve your audience.

So, how can you enhance your customer segmentation analysis — and, in turn, get on your way to perfecting your personalization approach and improving your marketing ROI?

The answer lies in a particular — and increasingly popular — data-driven marketing solution used by many enterprise brands today: the customer data platform (CDP).

customer segmentation

Customer segmentation analysis: Your key to better understanding your audience

We won’t highlight the (many) benefits of audience-based segmentation. Nor will we cover the (many) types of specific market segmentation businesses can implement. Or the (many) kinds of customer segmentation models (e.g., demographic, geographic, etc.).

You already know segmenting buyers and subscribers is a fundamental component of your marketing. It can also give you the ability to learn about customers’ behaviors.

Instead, let’s cover why customer segmentation analysis is just as critical as grouping individuals into distinct groups in your database ecosystem.

Any worthwhile market segmentation strategy requires constant, in-depth data analysis of each particular collection of customers so you can discern how to calibrate your promotional efforts accordingly to retain, upsell, and cross-sell those folks.

The rewards of regularly reviewing one’s customer base are many for marketers:

  • Customer segmentation and related persona analysis is deemed the second-most-effective tactic for organizations to grow lifetime value. — 2019 Econsultancy research
  • “The ability to dynamically segment audiences” was the top tactic for marketers when it comes to improving consumer experience. — 2018 Econsultancy report
  • Advanced analytics for robust segmentation and data consolidation to better understand customers are CMOs’ top marketing investments. — 2020 Merkle study

Whether you’re focused mostly on psychographic segmentation to determine buyers’ interests and motivations or geographic segmentation to distinguish shoppers by location, closely analyzing these clusters is what will help you evolve your customer engagement strategy and optimize your niche marketing efforts to those segments.

How to compare and contrast your segments with a customer data platform

What can enhance your marketing even more, however, is to compare your segments.

This is how leading companies figure out which groups of customers are worth allocating time, resources, and money to (e.g., high-CLV customers with high-cost subscriptions).

Similarly, it also informs which segments to focus on later (or not at all) with your messaging (e.g., inactive shoppers with low recency, frequency, and monetary value scores).

customer segmentation

BlueConic customers use our Segment Comparison insight to explore differences between segments. They can compare the sum or average of up to 10 number-, decimal-, and currency-oriented profile properties that pertain to those distinct segments.

By evaluating the average or sum associated with each segment, BlueConic customers get an at-a-glance view as to how all segments stack up against one another.

What’s more, they can easily and efficiently discover if one segment of customers spends more, has a higher average lifetime value score, and/or purchases more frequently.

For instance, if you’re a direct-to-consumer company and want to see how segments perform in terms of average order value (AOV), you could compare them based on:

  • Buying frequency: Do those who buy 1-2 times or 3-5 times have higher AOV?
  • CLV scores: Is there a group of customers with mid-range CLV scores with higher AOV?
  • Consent status: Do those who consent to personalized messaging have higher AOV?
  • Subscription level: How does your basic and premium subscribers AOV compare?
  • Engagement: How does the AOV compare for buyers with varying engagement scores?

Companies with our CDP in place can also use the Profile Distribution Graph insight. This helps them visualize a profile property’s distribution across a given customer segment and the relationship of said profile property to another for the same segment.

The sheer number of marketing segments companies can construct is substantial.

Suffice to say, with a feature like Segment Comparison, you have the opportunity to glean highly valuable customer insights that can educate you about all buyers in your database.

customer segmentation

Segmentation analysis simpler (and far more streamlined) with a leading CDP

Discovering which customer segments require your attention ASAP, is one thing. But the next step — adjusting your messaging to those segments accordingly — is just as vital.

For example, BlueConic customers who identify a segment via this comparison feature with both the highest momentum score (based on website activity in the last seven days) and propensity to buy (based on recent purchases) know right away that’s a prized audience.

BlueConic users can then use this new info about this niche portion of their customer base to see what past personalized messaging helps increase their engagement and buying behaviors and perhaps apply the same approach to other segments.

Conversely, BlueConic customers who pinpoint segments with a high propensity to churn can use that info to see what’s causing customer attrition rates to spike.

This sizable churn rate could be due to a lack of or too much messaging, use of the wrong marketing channels, poor customer service experiences, or something else entirely.

You and your team won’t know for sure, though, until you’ve unified all first-party data for every buyer and subscriber into a centralized database like a customer data platform.

Having just some customer data stored in disparate databases won’t give you the necessary insights into your target audiences or ability to liberate that data in cross-channel activities.

Nor will it give other teams at your company the opportunity to leverage said data for their work (e.g., informing product development or go-to-market strategies for new offerings).

It’s only when you consolidate every pertinent data point for your audience into a single source of truth like a CDP that you’ll be in a position to segment customers, compare them accordingly, and create an action plan that improves your lifecycle marketing strategy.

Watch our on-demand webinar today to learn about several specific CDP use cases — including multi-dimensional customer segmentation and segment analysis.

customer data platform use cases

See what BlueConic can do for you.

Whether you’re looking for operational efficiencies or improved marketing effectiveness through data activation, our customer data platform can help.