Customer Segmentation in 2025 – How to Do It Right

Not so long ago, businesses could put out a product or service at regular intervals throughout the year, promote it using a one-size-fits-all approach, and then wait expectantly for sales to come flooding in.

Marketing has come a long way since then. Consumers have different needs and wants, with personalisation a key driver for where and when they choose to spend their money.

Based on insights from our State of the AI Connected Customer report (surveying more than 16,000 consumers and business buyers worldwide), 73% of customers feel that businesses treat them as a unique individual rather than a number, which plays a significant role in customer retention and trust.

Customer segmentation is one of the key strategies that has allowed businesses to achieve this. With this approach, businesses are better equipped to use target messaging on certain groups at certain times, dramatically increasing the chances of securing sales, while saving money on wasted marketing efforts.

In this article, we’ll take a look at what customer segmentation is and how it works. We’ll highlight some of the common challenges associated with segmentation, and we’ll also explore how technology powers customer segmentation efforts for modern businesses.

• What is customer segmentation?
• Customer segmentation vs. market segmentation
• Why should you segment your customers?
• 7 successful ways to segment your customers
• How to segment your customers (step-by-step)
• How to solve common segmentation challenges
• How technology powers customer segmentation
• No matter how you slice it, customer segmentation is essential

Customer segmentation means splitting your customer base into groups so you can customise your sales strategies based on their specific needs, pain points, objections and affinities. Instead of one campaign for everyone, you can create a more personalised touch that fits each audience. This ultimately leads to more effective selling, with relatable, relevant messaging and offers for each segment.

Customer segmentation is applied to your own customer base, helping refine your sales strategies. For example, there might be an entire market of computer buyers, but you make powerful laptops for playing video games. Within this gamer audience of potential customers, you could segment them into casual players who just need a basic laptop and enthusiasts who need the top-of-the-line hardware.

While there is certainly crossover between customer segmentation and market segmentation, it’s best not to use the two terms interchangeably, as their focal points are quite different.

Customer segmentation relates to a business’s existing customer pool and how they can separate it based on shared characteristics. Marketing segmentation, on the other hand, is when businesses examine their entire market with the intention of finding fresh entry points via new products or services.

By honing in on specific areas of the target market that might resonate with the business’s products and services, there is a much better chance of attracting new customers as opposed to targeting the market as a whole.

One-size-fits-all isn't a strategy for long-term success. In our State of the AI Connected Customer report , we found that 65% of customers expect companies to adapt to their changing needs and preferences, but 61% felt that most companies treated them as a number. Eighty-one per cent of customers expect faster, more tailored service as technology advances.

As salespeople, we have to meet and exceed customer expectations to win business and build loyalty. Competitors can easily use superior services to steal our hard-won customers.

As well as catering to what the modern consumer expects from a business, there are several other benefits of customer segmentation that companies can take advantage of. These include:

• Gaining a better understanding of existing customers: With detailed customer segmentation, businesses are able to gain valuable insights into who is buying their products, which market segment they can be found in, and how they behave. This makes tailored messaging much simpler.
• Keeping up with changing needs: With segments in place, you’re better able to monitor and react to change. Some segments are likely to be very stable, whereas others are more malleable. If you are able to identify these changes, particularly if they are negative, you’ll be able to investigate what’s causing them much more easily.
• Improving customer lifetime value and loyalty: CLV is a measure of how much the business expects a customer to spend with your company long-term. Segmentation helps you identify which groups tend to have higher CLV. Your sales team can then target these groups more actively.
• Better customer experience (CX) and sales: As mentioned, tailored customer experiences resonate with modern consumers. Your goal is to turn these first-time buyers into long-term customers, which will result in an increased level of recurring revenue.

Customer segmentation is something that FedEx recognised as being a key component of their own sales and marketing approach. By segmenting and targeting inactive B2B customers with a tailored follow-up strategy, they were able to quickly boost reactivations and shipping conversions, resulting in increased ROI and revenue.

Segmentation methods fall into several types that can be used alone or together to create broad or narrow customer groups. They each have their own purpose and many require different methods of data collection. The types are:

Let’s take a look at the seven main types.

Demographics are set traits based on who a person is, some of which are changeable and some of which aren't. They include attributes such as gender, age, marital status, income and occupation. You'd use this form of segmentation to identify basic trends and buying habits that correlate with these shared traits.

Example: Parents of children aged 5-10 who earn at least $80,000 AUD per year.

Geographic traits are those based on things like preferred language, physical location and transportation methods (which advertisers can use for things like billboard or radio advertising). They help confirm to your sales team that customers within this segment can feasibly buy or receive the product.

Example: English speakers who live in Sydney.

These are traits based on what kinds of technology customers use and prefer. They include things like device type, web browser and origin source (where a user came from to get to your website or landing page, such as social media, email, or text). These can be good for sending targeted messaging to the preferred method of outreach for different customers.

Example: Smartphone users on the Chrome browser who were directed by an SMS campaign.

This type of customer segmentation model delves deeper into personalisation and the specific needs of different sectors. It is related to factors such as product features, service needs, and delivery methods. Businesses need to have a firm grasp on common pain points that their product or service can solve in order for this segmentation to be effective.

Example: Customers who frequently visit two different product pages on your app might require an intuitive comparison tool.

This segmentation strategy focuses on separating customers by economic value to the business. Measures include the number of purchases, average purchase value, and customer satisfaction (CSAT) scores. You'd segment this way to maximise the return on investment for different levels of sales team resources.

Example: Customers opting for high-value subscription package plans may require more effort to maintain.

Psychographics are less about inherent traits and more about interests, values, and broader personalities. Researchers can infer some of these, but they often have to be learned through surveys, focus groups, and one-on-one interviews. Businesses can combine these segments with demographics to create ideal buyer personas and effective messaging.

Example: Fashion enthusiasts who follow any social media influencers and cite ‘shopping’ as a hobby.

Behavioural segmentation groups customers by what they do, especially around your business. These might be actions such as interacting with customer service reps, leaving a review, returning items, visiting certain pages on your website, leaving a shopping basket with items in it or frequently buying items. Sales teams can use these segments to create just-in-time sales messages, and also group for specific playbooks based on the ways customers behave.

Example: Customers who visited your pricing page more than once and previously downloaded your white paper.

Like all marketing strategies, customer segmentation is only effective if you understand the key steps necessary in order to make it happen. The good thing about this approach is that it is generally a universal process, regardless of which industry your business happens to be in.

The five steps for customer segmentation are:

1. Set your segmentation goals
2. Collect customer data
3. Segment your customers
4. Sell to your new customer segments
5. Analysis and continuous improvement

Let’s take a look at each of these in a little more detail.

Businesses should not carry out segmentation just for the sake of it. There needs to be a thesis behind it. What is it that you’re trying to achieve by segmenting your audience?

Perhaps you have an idea for a new product and want to be certain that there is an audience segment for it. Or maybe you want to discover who your most loyal customers are and set up some form of exclusive loyalty or reward scheme for them.

These goals should dictate the structure and prioritisation of your segmentation.

You should always have a deep knowledge of who your audience is, where they’re coming from, and why they’re engaging with your business. You can develop this through examining direct first-party data or via third-party data analytics providers.

Common sources of customer data might include:

• Internal customer surveys (questionnaires, post-transaction)
• Signup forms
• External customer reviews
• Customer support interactions (ideal for understanding common pain points)
• Focus groups
• Social media engagement
• Purchase history
• Website behaviour metrics – like CLV, click-through-rates (CTRs), churn rate, cart abandonment, etc.

Analyse the data you've collected and the goals you set to decide the right types of segmentation to use. Machine learning and artificial intelligence (AI) can help you create connections and associations, and suggest segments for you to use. Ultimately, the segments you create should help meet the goals you set.

For example, a clothes retailer might identify three distinct groups related to buying behaviour based on the data: frequent high spenders, occasional bargain hunters, and one-time buyers. Each of these will require a slightly different approach when it comes to messaging and advertising.

With your new segments in hand, you can build brand positioning, messaging, go-to-market (GTM) strategies, and more for your sales team to use in their outreach and prospecting. That way, they can reach the goals you set at the start of the segmentation process.

You should consider implementing a trial period or a limited run in the first instance. While data-driven customer segmentation will often yield positive results, it is not infallible. You’ll want to be sure your segmentation is accurate before applying it across all of your marketing efforts.

Your customer base is never fully static. Customers will come and go, and the makeup of your base will experience periods of transition. That’s why it’s vital to consistently maintain your customer segmentation analysis to make sure that it accurately represents your customer base at all times. This is particularly the case if you use AI to help with segmentation, as its success is dependent on the data it’s fed remaining relevant.

Collect feedback from customers experiencing your new outreach, and the teams you put together at the start. Compare your new segment's performance with the business goals that led you to create it, and evaluate whether you are segmenting this target accurately from your broader customer list.

Segmentation can go wrong very easily. There are a lot of moving parts and technologies at play, all at a massive scale to meet modern customer demands. Here are the common challenges of segmenting your customers (and how you can overcome them):

Segmentation is one of those things that all businesses feel they should be doing. But many fall into the trap of segmenting just for the sake of it, without any real purpose or strategy.

A business might choose to segment by gender without having any appreciation of how men and women react to different forms of messaging, across different platforms. They may opt to segment by spending amounts without having a strategy ready to reward those high-spending customers, or to further encourage lower spenders.

Solution: The way to overcome this is to follow the implementation guide and work with your marketing team to establish the personas your business works with. Start conducting first-party research to create a working strategy.

Another common mistake is jumping into segmentation poorly. Putting a customer in the wrong segment, either manually or automatically, can have significant negative consequences. If your enterprise subscribers are getting flagged by automated processes as free users, they'll get masses of ‘upgrade now’ emails. At best, you'll look like you don't know what you're doing; at worst, customers will cancel. Plus, you may misalign your resources.

Solution: The way to overcome this is with regular and thorough audits of your strategy and implementation, with sample customers running through the process to see where gaps or mistakes are made.

The final segmentation error lies in poor data sources. If the information going into your machine is incomplete or outdated, the segmentation may not be accurate. You may get the wrong buying signals, pull in out-of-date decision-makers, or have an entirely incorrect organisational payoff.

Solution: The only way to overcome this is through much more deliberate data collection using your CRM at the start, with higher-quality sources. It might take more time and cost more upfront investment, but the payoff is more than worth it.

Most customer segmentation tactics are only possible thanks to features of modern software platforms. Here are a handful of features and capabilities that can scale up your strategy.

• Automated data preparation: Customer segmentation is now more powerful than ever, thanks to automated data retrieval. Most businesses have data scattered throughout numerous sources and channels. Dynamic software such as Salesforce Data Cloud unifies customer data across systems in real time, creating a single source of truth for segmentation.
• Calculated insights: Take advantage of AI modelling features found within technologies such as Salesforce CRM Analytics to analyse and evaluate your segmentation. Use these vital insights to make data-driven decisions on marketing strategies and direction.
• Targeted prospecting: Divide lead lists by known attributes such as demographics and behaviour, and your historical data about messages that have appealed to these different segments. With Salesforce Sales Cloud, your team is equipped with lead scoring, segmentation insights, and pipeline prioritisation tools.
• Sales personalisation: Integrate your marketing and sales tools so you can talk to prospects more effectively. Pull in data from recent customer actions on your sites, apps, emails, and social accounts, as well as interactions with service, marketing, and sales reps. Our Marketing Cloud software powers hyper-personalised engagement, aligning sales and marketing outreach.
• Customer journey orchestration: Build personalised journeys that work across omnichannel avenues, satisfying the marketing team's needs and feeding into the sales team, as well. Tap into the power of our Marketing Cloud Personalisation tools to enable real-time journey orchestration across channels.
• Email productivity tools: Help sales teams access segmentation data from within their CRM platform. These sales engagement tools help to identify which stage along the buying journey customers are in and utilise data-driven guidance on the right email to send at the right time.