Customer segmentation is a very powerful tool, but the reality is that few marketers use it properly.
It’s not enough to play with a few filters in Mailchimp or Salesforce. Customer segmentation is a complex process that requires a clear vision of the marketing objectives, the key personalization axes, the methodology for monitoring segmentation incremental impacts, etc.
First and foremost, you need to understand the state of the art.
Unless you work in a large company, or a very mature scaleup, the first step is to know the subject’s best practices and adapt them to your business.
We have prepared a complete article on customer segmentation, including 9 examples of classic customer segmentation to inspire you.
What makes a good customer segment?
A good segmentation should include these 6 characteristics:
- Relevant: it’s usually not profitable to target small segments – so a segment should be large enough to be potentially profitable.
- Measurable: Know how to identify customers in each segment, keep control of customer data, and measure their characteristics such as demographics or consumer behavior.
- Accessible: It sounds obvious, but your business should be able to reach these segments through different communication and distribution channels. For example, if your business targets young people, it should have Twitter and Tumblr accounts. You should also know how to use them to promote your products or services.
- Stable: To maximize the impact of your campaigns, each segment must be stable enough for an extended period. For example, the standard of living is often used as a means of segmentation, but this is dynamic and constantly changing. Therefore, it is not necessarily wise to make a segmentation based on this variable at the global level.
- Differentiable: People (or organizations in B2B marketing) in one segment should have similar needs, and these would be different from those of people in other segments.
- Actionable: This implies being able to deliver products or services to your segments. An American insurance company spent a lot of time and money identifying a segment and then realized it couldn’t find any customers for its insurance product in this segment. And it wasn’t able to devise a strategy to target them either.
The classic dimensions of customer segmentation
| Geography | Demographic (B2C) | Demographic (B2B) | Psychographic | Behavioral |
|---|---|---|---|---|
| Continent | Age | Sector | Social class | Usage |
| Country | Sex | Number of employees | Living standards | Loyalty |
| State | Annual revenue | Digital maturity | Values | Sensitivity to XYZ |
| Region | Socio-professional Category | Financial situation | Personality | Purchase frequency |
| Department | Marital status | Shareholding | Convictions | Payment method |
| City | Study level | Market capitalization | Social networks | Consumption habits |
| Ville | Job Title | Business model | Hobbies | |
| District | Language | Technologies used | ||
| Climate | Religion |
Customer segmentation is divided into 4 main categories:
- Geographic segmentation: It groups customers according to their location. Where they live, work, or go on vacation, for example.
- Demographic Segmentation: It groups customers using characteristics such as age, gender, income, or industry.
- Psychographic Segmentation: It groups customers according to their psychological characteristics, such as their interests, opinions, or social status.
- Behavioral Segmentation: It groups customers based on their buying behavior or customer journey stage. Customers who spend a lot, those who buy at a discount, or those who are at risk of changing their minds, for example.
9 exemples actionnables de segmentation client
1. SML segments (Small, Medium, and Large)
SML segmentation is based on Pareto’s law, which states that 20% of your customers generate 80% of your turnover. Therefore, you should primarily focus your efforts on this minority of customers.
This segmentation divides customers into three segments:
- Large customers: who represent a small part of customers but a high percentage of turnover.
- Average customers: who are few and represent a significant share of turnover.
- Small customers: the mass that represents only a moderate, even small part of your turnover.
Once these three segments have been determined, it is necessary to identify their commonalities and understand their expectations to fulfill them in a specific way. Your marketing strategy (message, communications frequency, promotional offers, etc.) will differ based on whether you are targeting small or large customers.
The more customers represent a significant part of your turnover, the more you will personalize your communication to offer them an exceptional customer experience using marketing automation software.
2. Promophilia
Promophilia designates the category of buyers responsive to promotions. The search for the right deal is their primary motivation. These are the famous “coupon lovers.”
This is a behavioral segmentation criterion. They spend a lot of time surfing the web to find the cheapest product. If you want to prioritize this type of consumer, you should set up loyalty programs.
The objective is to define segments based on responsiveness to promotional campaigns. For example, those who bought your product with a coupon in the last X days.
3. Stages in the customer journey
| Customer journey phase | Segment | Definition |
|---|---|---|
| Conversion | Potential customers | Contacts who have not yet made a purchase but have shown interest in one of your acquisition campaigns. |
| Growth | First-time buyers | Customers who have only bought once and who need to be turned into repeat buyers. |
| Loyalty | Repeat customers | Customers who have made at least two separate purchases over time. |
| Retention | Loyal customers | Customers who have purchased multiple times in a short period of time. |
| Re-conquest | Repeat customers at risk | Customers who have purchased several times but have not purchased anything for a long time. |
| Attrition | Inactive repeat customers | The loyal customers you have lost. |
You can thus create 6 different customer segments:
- Potential customers (prospects): these are contacts who have not yet made a purchase but have shown interest in one of your acquisition campaigns. You have to bring them to a first conversion with retargeting campaigns, coupons to play on FOMO to accelerate conversion, educational content to convince, etc.
- First-time buyers (the new “real” customers): these are customers who have only bought once and who need to be transformed into repeat buyers. You have to remind them of your existence via product recommendations, educational content, or a request for an opinion on the first product purchased.
- Customers who have purchased at least twice (repeat customers): these are buyers who have made at least two separate purchases over time. You have to nurture a dialogue to keep them and make them your ambassadors. Encourage those customers to make new purchases with offers on new products, a reorder form or even exclusive coupons.
- Loyal customers (your best customers): these are the customers who have purchased several times in a short period. Your ambassadors have demonstrated their attachment to your brand and its products. To maintain their loyalty, involve them in your product innovation process. You can give them early access to your new offers or send them requests for customer reviews.
- At-risk repeat customers: these are customers who have purchased several times but have not purchased anything for a long time. Recover them by sending them positive messages about your products, a coupon with a limited period of use, or even a questionnaire with an incentive.
- Inactive repeat customers: these are the loyal customers you have lost. You should reactivate the relationship and renew the dialogue by sending large product promotions or a questionnaire like: “How can I help you?”.
Source: Dolist
4. Customer satisfaction and NPS
The Net Promoter Score (NPS) is the indicator of customer satisfaction and loyalty. It measures the likelihood that your customers will recommend your brand, products, or services. According to the score given by the customer, the latter is classified into one of the following 3 categories:
- Promoters (score of 9 or 10)
- Passives (7 or 8)
- Detractors (0 to 6)
The NPS segmentation induces homogeneity between each segment of customers, but this is not always the case. Not all detractors are equal. A detractor of 0 may not necessarily ruin your reputation, but they may be likelier to complain about your business than the customer who gave you a 6 rating.
This also applies to your promoters and passives. Not all of your promoters are promoting, and some passives may not be so passive after all. A study revealed that customers who give ratings of 8, 9, or 10 were all similar in terms of recommendation probability.
So focus on passives who give you an 8 rating to boost customer recommendations. On the other hand, there is a significant difference between a rating of 7 and 8, or between 6 and 7 in terms of recommendation probability.
You can develop different strategies for detractors who have given you a rating of 6 to convert them into promoters. Pay attention to satisfying your passives to give them the little nudge necessary to become promoters. Use NPS to boost customer recommendations.
5. RFM Segments (Recency, Frequency, Monetary value)
RFM segmentation is one of the most popular customer scoring systems based on previous purchases. Direct marketers use it to score each customer and predict each segment’s reaction to future marketing campaigns.
From the RFM analysis, we can draw 6 segments:
| Customer segment | RFM | Description | Marketing action |
|---|---|---|---|
| The hardcore - Your best customers | 111 | Highly engaged customers who have purchased your products recently, most often, and generated the most revenue. | Focus on loyalty programs and new product launches. These customers have proven they are willing to pay more, so don't offer discounts to generate additional sales. Instead, focus on high value actions by recommending products based on their previous purchases. |
| The loyal - Your most loyal customers | X1X | Customers who buy most often from your store. | Loyalty programs are effective for these repeat visitors. Engagement programs and evaluations are also common strategies. Finally, consider rewarding these customers with free shipping or other such perks. |
| The whales - Your highest paying customers | XX1 | Customers who generated the most revenue for your store. | These customers demonstrated a strong willingness to pay. Consider premium offers, subscription levels, luxury products, or value-added cross-selling or upselling to increase total added value. Don't lose your margin with discounts. |
| The Promising - Loyal customers | X13, X14 | Customers who come back often, but don't spend a lot. | You have already succeeded in creating loyalty. Focus on increasing monetization through product recommendations based on past purchases and incentives tied to spend thresholds (set based on your store's average added value). |
| The recruits - Your newest customers | 14X | New buyers visiting your site for the first time. | Most customers never become loyal. Having clear strategies for new buyers, such as welcome emails, will pay off. |
| The unfaithful - Once faithful but now gone | 44X | Great old customers who haven't bought in a long time. | Customers leave for a variety of reasons. Depending on your situation, suggest price offers, new product launches, or other loyalty strategies. |
6. Customer (in)activity
At a minimum, most companies classify customers into two categories: active customers and inactive customers. These categories indicate when a customer last made a purchase or engaged with you for the last time. For non-luxury products, active customers are those who have purchased in the last 12 months (and vice versa for inactive customers).
To segment the customer base according to the level of activity or commitment, we sometimes use a Recency Frequency Engagement scoring, like an RFM. Here, transactions are replaced by all forms of contact points (pages visited, email opening, email click, ..). We associate several points, for example, +1 email opening, +3 website visit, +5 email click, etc.
7. Purchase frequency
Active customers are your loyal customer base and brand ambassadors. They are more likely to share your posts, encourage others to buy your products, and leave comments.
Target these loyal customers with exclusive discount codes or a loyalty program to ensure your organic growth and multiply your organic reach online.
Loyalty programs are a great way to improve purchase frequency, as they effectively draw customers away from the competition by focusing their attention on your offers. By distributing loyalty points to customers, you motivate them to increase purchase frequency.
8. Customer value
This can lead to or be based in part on the RFM segmentation program.
The value of a customer is strictly determined by their cumulative spending. An LTV (Life Time Value) scale can be used to determine eligibility for offers, loyalty rewards, promotions, and other unique campaigns.
Building a customer score by giving a high or low value to each segment can help understand how high-value customers find you in general. Therefore, you can know how to direct your acquisition strategies.
9. Acquisition sources
In their buying journey, potential customers are likely to interact with your company through multiple acquisition channels, especially when developing an omnichannel customer relationship.
Analyzing these results allows you to be strategic and invest where it pays off. In addition, the source of acquisition can be very structured in explaining customer behavior thereafter.
We can even go so far as to segment by acquisition cohort to observe the behaviors induced by certain campaigns in the medium term.
Referred customers are 4x more likely to refer others to your brand. Segmenting your audience based on whether they were recommended or not is an effective approach to improving your referral sales.
Target your current customers who have joined your referral program and develop campaigns to turn them into super fans.
From segmentation to personalization
Source: Formation
Segmentation is a solid foundation, but it doesn’t offer everything you need to develop personalized offers and build strong relationships with your current customers.
Segmentation is an excellent working basis for customer data, but it only offers a general view of the customer. You should personalize your loyalty offers or messages even further. It will help you target and tailor messages and offers to different customers based on their unique wants, motivations, and needs.
This is why segmentation is often referred to as stage 1. Personalization (into 1-10 segments) and micro-segmentation (10-30 segments) as stage 2.
Many brands get stuck at these basic stages and thus limit their ability to develop deeper and more profitable relationships with their customers. To move to step 3, you have to go beyond segmentation’s limits to find the best alternatives.
Marketing teams must leverage artificial intelligence (AI) and machine learning (ML) algorithms to achieve true personalization. These advanced technologies help to continuously capture and analyze every interaction a customer has with your brand. With these analytics, businesses can individualize offers and messages to specific customers at scale.
For example, Starbucks, which has more than 30,000 stores and nearly 19 million active members of its rewards program, aims to be the most personalized brand globally. The company currently uses AI to continuously learn its customers’ preferences and desires based on purchases and interactions.
AI and machine learning capabilities have enabled Starbucks to create individualized loyalty offers at scale. The results have been phenomenal: 10x the speed of marketing execution and three times the one-to-one marketing and sales drive.
Therefore, segmentation alone is far from providing the value of true personalization and information with the same level of sophistication or detail. Nor can it deliver targeted, personalized messages to a huge volume of unique customers.