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How to Boost Sales with Customer Segmentation Analysis

Boosting sales and fostering long-term relationships with your customer base is the goal of most businesses. Great products and customer service help. But how well do you actually know your target customers and what they want?

Conducting a customer segmentation analysis is an opportunity for your business not only to sort customers into segments, but to also better understand those segments. From delivering more relevant content to targeting specific demographics with new products, this strategy is a brilliant way of boosting sales. 

What is customer segmentation analysis?

Customer segmentation analysis is the process of separating your customer base into distinct groups based on shared characteristics or behaviors. 

Your customers come from different cities, have different jobs, cover a range of age brackets, and have a variety of interests and needs. Some want to know what the best parenting or productivity hacks are, others are searching for call center quality assurance tips

These differences are likely to impact what and how they make a purchase. So understanding and separating customers based on those differences means you can more effectively craft hyper-personalized messaging that’s more likely to result in conversions.

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Benefits of customer segmentation analysis

We’ll dive into how to segment consumers in a moment. But first, let’s explore why you should be doing it in the first place.

Targeted marketing

Dividing customers into discrete segments means you can focus marketing campaigns or social media ads on a particular group. 

So, if a new product is aimed at younger customers or those who have previously engaged with a particular theme like beauty, sponsored ads can be adjusted to target these users. 

Similarly, if your enhanced software subscription is typically purchased by clients working for large enterprises, you can funnel marketing emails about negotiating software contract renewals or software security measures to them. 

Enhanced product development

Once you have customer segmentation analysis in hand, you’ll have both an in-depth and snapshot view of essential customer information, including demographics and interests. This makes product development far easier and helps you foster ideas bent towards a specific customer base. 

Different customer groups prioritize and value different things, and these differences are relevant to what products or software ideas you develop next. In this way, you always have the right product-market fit and can meet existing customer needs rather than shooting in the dark. 

Cost efficiency

Casting a wide net has its benefits. But understanding customers and developing targeted products or services is far more cost efficient than trying to appeal to everyone. 

Analyzing customer segments can make your entire approach to marketing more cost efficient too. This helps you identify who the most profitable customer segments are. In this way, you can focus your marketing efforts (and time and money) on them, rather than unresponsive or low revenue boosting customers.

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6 steps to perform customer segmentation analysis

Customer segmentation can give you brilliant insights into your customers. But it’s crucial that you practice this method correctly for it to be effective. Here are the essential steps to follow.

1. Collect relevant data

There are two forms of customer segmentation data: demographic and behavioral. Demographic covers essential information, such as age, gender, and location. Behavioral is much broader. It can cover purchase history and past engagements with your brand as well as general interests and preferences. 

Segmentation is based on existing customer data and can (and should) be collected from various sources, including:

Tip: Don’t have the data you need? Encourage existing and new customers to provide data like demographics and interests by incentivizing them with offers like a discount on their next purchase. 

2. Prepare your data

Raw data can be overwhelming and unhelpful. So the next step is to clean and prepare gathered data before analyzing it. 

Here are some essential data preparation steps to take:

  • Audit: Identify any inconsistencies or errors in the data set and check for duplicates or incomplete records. Be sure to keep track of your results for future audits. 
  • Clean: Data cleaning covers removing duplicates and correcting errors as well as standardizing data in each field to fit a single format. 
  • Transform: Make sure that any data gathered from different sources is measured in the same way so that you can compare it accurately. Put everything in a format that is easy to analyze at a glance. For instance, if you’re collecting info about people’s interests, you could assign each interest a number or category. This way, you can analyze the data more effectively and spot patterns or trends. 
  • Integrate: You’ve probably collected data from multiple sources, so make sure everything is integrated into one data set in a spreadsheet or your chosen data collection software. Formatting should be identical across data sets as should any Excel rules you have in place. 

Tip: As you prepare data, read up on regional and national data security and privacy regulations, such as GDPR and HIPAA. If you’re collecting sensitive data, be sure to anonymize it so as to ensure confidentiality.

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3. Identify segmentation variables

Next, you need to figure out what criteria or variables you want to segment customers according to. These should be based on your business’s needs and customer type, so choose carefully rather than segmenting everything.

Some typical customer segmentation models include:

  • Demographic segmentation:
      • Age
      • Gender
      • Income
      • Location
  • Psychographic segmentation:
      • Lifestyle
      • Interests
      • Personal and political values
  • Behavioral segmentation:
      • Buying habits
      • Click-through rates
      • Website and social media user behavior
      • Brand loyalty
  • Transactional data:
    • Purchase history
    • Purchase frequency
    • Customer lifetime (how long they’ve been with your brand)
    • Average order value

Tip: Consider implementing real-time segmentation capabilities in your data system to segment customers based on their current interactions and behaviors.

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4. Turn segments into subsegments

Just because you know the geographic segmentation or marital status of a set of customers, doesn’t mean you can lump them together. Instead, you need to divide and collate variables with shared characteristics that make them useful target groups. For many businesses, this might involve creating buyer personas based on a range of segmentation data.

For example, let’s say you own a SaaS company that specializes in unified customer experience tools. Your customer segments may differ from those that focus on generational differences or gender, as company size and niche is more relevant. In this case, you might subsegment your variables into:

  • Small-to-medium businesses in niche A
  • Small-to-medium businesses in niche B
  • Enterprise businesses in niche A
  • Enterprises businesses in niche B

This takes several variables — company size and niche — and segments them into distinct groups that can be targeted with specific marketing and sales tactics.  

Tip: Predictive models and cluster analysis for customer segmentation analysis can be incredibly useful both for variable identification and subsegment analysis. Cluster analysis can quickly group similar customers based on shared attributes. Predictive models classify customers into segments based on their likelihood to perform certain actions, helping you stay one step ahead. 

5. Evaluate customer segments

Now you need to figure out what to do with each segment. This starts with some quantitative analysis based on how profitable or convertible a given segment is. Here are some metrics to include:

  • Revenue and profitability: Measure the revenue and profitability generated by each customer segment. Evaluate metrics such as average revenue per user (ARPU) and customer lifetime value (CLV) to assess the financial impact of each segment.
  • Growth potential: Analyze the growth trajectory of each segment by tracking changes in customer acquisition rates and predicted market statistics.
  • Customer behavior: Assess customer behavior within each segment, identifying those with better loyalty by measuring metrics such as purchase frequency, average order value, churn rates, and engagement metrics.

Tip: Analyze how your customer segments compare to competitors’ in terms of market share and profitability. This will help you identify opportunities for differentiation and competitive advantage. You may be able to identify an appeal you have to a different generation or locale.

6. Implement strategies for each segment

Now it’s time to think about your customer segmentation strategy. These might apply to your marketing plans or sales tactics. Let’s look at some of the approaches you might take to each segment.

Email marketing

You can divide your email subscriber list into segments based on data like demographics or purchase history. This way, you can send targeted emails with content that resonates with each segment’s interests, such as a ‘What is contact center technology’ guide for SaaS customers. 

Lifecycle email campaigns are also worth exploring. Create automated emails tailored to different stages of the customer lifecycle, such as welcome emails for new subscribers or renewal reminders for existing customers.

Social media campaigns

Developing a segmented content strategy for your social media channels means creating posts and campaigns that appeal to different audience segments. Tailor messaging and visuals to each segment and use social listening tools to better understand your customers.

Localized marketing

Create marketing materials and landing pages tailored to the language and preferences of geographic regions. Use local imagery and references to connect with audiences on a personal level.

You can also leverage geo-targeting features on social media and advertising platforms to display ads to users in specific locations. Make sure you adjust ad copy and calls-to-action based on regional context and relevance.


Implement dynamic website content and personalized recommendations based on user behavior and past interactions. These can serve personalized product recommendations and special offers for individual segments.

Boost sales with the power of segmentation

The many types of customer segmentation can all help you reach your ideal customer or even bring in new ones. Either way, customer segmentation is an essential tool for understanding who your customers are and adjusting your product offerings and marketing tactics accordingly. 

Whether you want to create more personalized marketing campaigns or guide product development, conducting a customer segmentation analysis is an effective way of boosting sales for any businesses.

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