What is behavioural segmentation?
Behavioural segmentation is one type of market segmentation within the field of behavioural marketing. This looks at exploring groups, audiences, prospects, and customers by their actions and behaviours. Where demographic and psychographic segmentation study who makes up your customer base, behavioural segmentation looks at what your customers do.
There are different types of marketing segmentation to consider, and behavioural segmentation doesn’t happen in isolation. It works in partnership with demographic, psychographic, and geographic segmentation to build up a complete customer profile. Where other segmentation data suggest potential interactions with your brand, behavioural can confirm them.
Customer behaviour can be grouped by the interactions with your brand, product, or service, such as:
- Customer attitudes towards it
- How customers use it
- Customers’ overall knowledge and awareness of it
- How customers buy it
In the world of ecommerce, segmenting customers can happen by examining online customer behaviour:
- How long do they browse your website (dwell time)?
- How rapidly do they click off your site (bounce rate)?
- Are they new or returning customers?
- What do they add to their basket or playlist?
- How frequently do they abandon their cart?
Effective, data-informed behavioural segmentation has been made possible by the development of artificial intelligence. Powerful AI marketing analysis platforms can help deliver accurate and fast behavioural market segmentation. An all-in-one platform could, for example, collect behavioural data, create segment-based behaviour graphics and help deliver tailored content reports for each consumer segment.
Benefits of behavioural segmentation
- Better targeting accuracy: You’ll be able to take advantage of different behaviours, and, knowing those, direct your marketing messages. For example, newer customers may be attracted to great introductory offers, while long-standing loyal customers may enjoy benefits from loyalty programs like an invitation to join an exclusive VIP club.
- More personal experiences: The days of blanket-bombing your email marketing lists with the same generic message are thankfully long gone. By identifying your audience’s needs, wants, concerns, and the type of messages they notice, you can connect with each one personally, making relevant offers and suggestions that they are more likely to take up.
- Filter the interested from the uninterested to find high customer engagement: By separating the most engaged customers from the least, you can target your product or services at people who need or want them the most.
- Cost-effectiveness: You can target your budget at your most interested, engaged, and valuable audiences, rather than waste it on cold leads and the uninterested.
- Trackable: You can track metrics within each segment, take action and improve results.
- Increase brand loyalty: Customers who feel special will stick with the brand that makes them feel that way. Customer loyalty increases customer lifetime value, and hence revenue for your business.
Types of behavioural segmentation
There are many ways your customers will interact with your brand, product or service. You’ll need to understand these behavioural variables to help create a behavioural segmentation strategy that is effective and sustainable.
AI-powered platforms can analyse all these behaviours along the customer journeys, identifying trends and patterns that will help you predict which customers are most likely to make which purchases.
The main ones are:
1. Purchasing behaviour
How do customers behave on their journey to purchase?
Purchasing behaviour can be segmented into four categories:
- Complex: Imagine the work that goes into making a purchasing decision to buy a new home. Customers are highly involved, research in-depth, and eventually buy something that is a one-off or infrequent purchase.
- Dissonance-reducing: Do you worry that you might regret your purchase? You’ve been highly involved in the purchasing process, but you’ve found it hard to choose between brands. Customers will seek follow-up reassurance that they made the right choice.
- Habitual buying: Every week you go to the grocery store and buy whichever products are cheapest or on special offer. You have no brand loyalty: this is your habit.
- Variety-seeking: You’re bored with citrus-scented shower gel, so you choose a cedarwood-scented one. The citrus one cleaned your body just fine, but you fancied variety.
2. Usage behaviour
How often do customers use your product/service and how?
This segment looks at the frequency of customer interaction with your business, and the nature of the interaction (what they do while interacting, which features they use, how long they spend, etc.). This can be further segmented into heavy, medium, and light users, and you can update your marketing strategy to target these segments accordingly.
3. Benefits sought
Which particular benefit is a customer seeking when they decide to make a purchase?
Customers place higher value on one benefit over another when choosing a product. A classic example is toothpaste. Any toothpaste can contribute to good dental health, but customers may prefer to choose:
- Sensitivity relief
- Tartar control
- Cavity protection
- Gingivitis prevention
- Fresh breath confidence
- Gel or paste
- The cheapest
4. Occasion or timing-based
Which special occasions do customers buy for?
These include universal and personal occasions:
- Universal occasions: Such as Thanksgiving, Halloween, Holidays, when most people are likely to make specific, seasonal purchases.
- Recurring personal occasions: Such as birthdays, anniversaries, vacations, monthly, yearly, or quarterly purchases, daily purchases like newspapers or coffee.
- Rare-personal occasions: Such as weddings, baby showers, college graduations. These are harder to predict.
5. Customer journey stage
Where is the customer currently along their journey?
The customer journey is, at its most basic, the process from when a customer becomes aware of a product to the point where they’ve bought it and are telling others about it. There are five touchpoints along the customer journey stages:
- Awareness (Advertising, radio & TV, PR campaign)
- Consideration (reviews, blogs, direct mail, and email marketing campaigns, or social ads)
- Purchase (website, store, contact centre)
- Retention (loyalty program, community, newsletters)
- Advocacy (word of mouth, social media, reviews)
Segmenting the customer journey stage will reveal any pain points or sticking places where the customer cannot complete their journey. For example, at Purchase, the store may habitually run out of stock, highlighting a problem with supply.
6. Customer satisfaction
How happy are your customers?
Customers’ needs, wants, and experiences change in real-time as they progress through their purchase journey. The traditional Net Promoter Score alone doesn’t really cut it anymore as it doesn’t reach all customers, and there’s too much unmonitored between-survey time. Real-time behavioural data is a much more accurate and reliable measure of customer satisfaction.
7. Customer loyalty
Which customers are the most loyal?
The most loyal customers are your most valuable as they spend the most time connected with your brand. They are:
- Cheaper to retain
- Have the highest customer lifetime value
- Are your best brand advocates, contributing to brand equity
Once you’ve highlighted them, you need to find ways to maximise their value and bring in more customers like them. Behavioural segmentation gives you insights into their needs so you can retain them with special VIP privileges and rewards to strengthen the customer relationship.
What are your customers interested in?
If you can continually pique your individual customers’ interests, they’ll keep coming back for more. Keeping customers engaged makes it easier to increase their usage of your product or service, keep them loyal on your platform or in your store, and sell them other products.
9. Customer engagement level
Who are your most (and least) engaged customers?
Different companies will have different interpretations of ‘engagement’. But generally speaking, when customers have positive experiences with your brand and are willing to interact with it regularly, there’s a good chance this will lead to profitable outcomes.
10. User status
How do people use your business?
This is another way to behaviourally segment different customers by how much they use your business. These can include, but are not limited to:
- ‘Freemium’ users (consumers who use a free product but pay for add-ons or in-app purchases)
- Defectors (previous customers who’ve switched to a competitor)
11. Spending Habits
How do customers spend their money with you?
These tell you how customers spend their money, and where and when they generally buy. This segment may include:
- Buying online vs. in-store
- Buying with a store credit card vs. a regular credit card
- Using coupons vs. never using coupons
- Visiting during sales vs. non-sale times
12. Brand Interactions
How do customers engage across all your branded channels?
This kind of behavioural segmentation tracks all interactions with your brand, both online and off, and demonstrates how engaged a customer is with your brand. Think of the Disney brand, which covers movies, merchandising, dedicated stores, websites, theme parks, vacations.
- Frequency of store visits
- Frequency of website visits
- Web pages visited
- Interactions with your social media
- Content viewed on social media
- Frequency of purchase
- Previous purchases
Three case studies examples of behaviour segmentation
Some behavioural segmentation examples of businesses successfully working with their customer information include:
Case study 1: Olay
Olay, the US skincare brand, has a global customer base of young and older women. The brand used artificial intelligence in their mobile-friendly tool, Skin Advisor, which asked potential customers about their skin, their skincare routine, and what they wanted.
By collected their answers, the team at Olay were able to:
- Understand their target market’s usage behaviour and whether current products fit the customer needs
- Upsell products to the customers, based on their answers
- Build trust and increase knowledge by providing advice on their skin’s profile
Based on the results, Olay introduced fragrance-free products and Retinol24, a retinol-based product, which increased revenue.
Case study 2: Thirdlove
Thirdlove is an American company producing and selling bras, underwear, loungewear, and nightwear. They wanted to help women find the right bra for their shape and size so they created the FitFinder tool. This tool asks a number of questions on how often they purchase bras, what sizes are most in-demand, and the body types of its target market.
While the customer is able to find the right information to help them make the best buying decision, the tools also helped the company. By looking at the data and using behavioural segmentation, the company was able to see that the tool was a key channel towards customers making a purchasing decision: they were more likely to purchase, return and spend more, so they invested more into its development..
Case study 3: Netflix
This well-known entertainment streaming service brings TV series and movies to customers in a personalised way. They do this by using AI in an agile way, providing bespoke recommendations to the user, based on their previous viewing history.
Combining this usage data with AI algorithms means that predictions on behaviour can be made, which are then tested when shown to the user in their recommendations lists. The AI program learns from the results and continues to tailor information to the user’s profile.
The amount of data collected from all users means that Netflix can see how users consume the service and where they have trouble. This gives it the right insights to be able to update and improve its user experiences and create happier customers that stay on for longer.
Behavioural Segmentation vs. Personalisation Marketing
At first glance, behavioural segmentation and personalisation both seem to deal with the same thing. After all, they both involve tailoring a marketing message based on audience behaviour for better, precision targeting.
But their primary difference lies in their scope.
Behavioural segmentation is an approach that divides your market into several groups based on their behaviour patterns. One of the simplest examples of behavioural segmentation is people buying on certain occasions. For instance, flowers or chocolates tend to sell more during Valentine’s Day.
However, the scope of behavioural segmentation often ends with categorising and understanding your audience. Therefore, it doesn’t generally cover the strategies you’ll use to market to these behaviour groups. In addition, its focus is only on the behaviour of the group. In other words, there’s no guarantee that your marketing applies to every person in that segment.
Personalisation marketing, on the other hand, gets more granular by tailor-fitting your marketing to each individual. It uses a combination of automation, customer data, and even artificial intelligence to make the experience more engaging and memorable. In many ways, personalisation is the logical progression of behavioural segmentation.
One simple, core personalisation tactic is to use a person’s name. For instance, emails and even videos can address the person by name. Going beyond that, AI can also analyse a person’s purchase history and recommend products to them.
As you can see, behavioural segmentation and personalisation are vastly different approaches. However, that doesn’t mean you should use only one of them exclusively. In fact, doing them in tandem can be an effective way to increase your brand’s relevance to your market.
In the end, both behavioural segmentation and personalisation have the same end goal – a targeted experience for every customer.
How to Improve Behavioural Segmentation
Behavioural segmentation used to be an imprecise process. The lack of robust data gathering and analytics meant that marketers had to make many assumptions to correctly classify a user’s behaviour.
But using artificial intelligence (AI) and machine learning (ML) allows organisations to get real-time insights that can power their behavioural segmentation efforts. In addition, with everything going digital, marketers can now also track what users are doing online, generating a wealth of marketing data. In other words, using AI and ML can give your behavioural segmentation strategies the ability to personalise.
For example, AI can analyse what a person has watched on a streaming platform such as Netflix. This allows you to suggest similar content that the user has a high chance of liking as well.
AI can also tailor ads and marketing offers to a person based on their past purchase history or behaviour. Doing this ensures you only present relevant products to someone, increasing conversion rates and reducing ad fatigue.
Finally, machine learning is also a powerful tool to “train” your customers to try out new behaviours. This is done by cross-selling them with a new offer that is still in line with their past behaviour. Doing this progressively can guide people to buy higher-priced products or purchase more often.
How to use behavioural segmentation to help your business
Automated brand experience management programs allow you to segment target customers, identify and develop your value proposition, conduct brand research, and personalise your communications. You can then track every behavioural brand metric that matters to your business, from awareness to loyalty and advocacy, picking up and resolving all the pain points as you go.
You will understand your customers better so you can enhance the experience of existing ones, and connect with new ones.