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Glossary Index

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Glossary term

Behavioral Segmentation

Quick definition

Behavioral segmentation is grouping — or segmenting — certain audiences of users based on actions those users have taken in their customer journey. A group of users with similar behavioral profiles is referred to as a segment.

Key takeaways

 

●     You can use behavioral segmentation to gain deep insights about customer behavior with your brand in order to more effectively market to certain types of groups and even make personalized connections with individuals.

●     The most common way to do behavioral segmentation is through web browsing behaviors, but you can also create segments using data from store-traffic reports, tracing content affinity, product engagement, and more.

●     Behavioral segmentation is important because it keeps your company from using valuable time and resources on an unnecessary marketing strategy. If you know how the people you’re targeting behave, you know when to stop marketing a certain product to them, for instance.

●     You can optimize your behavioral data by forming data partnerships with other companies, swapping behavioral data with each other to more successfully market to shared customers.

●     The best tools to use for behavioral segmentation would be a customer data platform (CDP), such as Adobe Real-time CDP, or a data management platform (DMP), such as Adobe Audience Manager. 


Q: What is behavioral segmentation?

A: Behavioral segmentation is grouping certain audiences of users based on actions those users have taken. A group or cluster of users with similar behavioral profiles is referred to as a segment. Doing behavioral segmentation means inferring something about a certain segment of users based on behaviors that you are aware of them taking.

The most common example of behavioral segmentation is web browsing behavior. Let’s say some new users who visit your e-commerce website from a social media ad put a few items in their cart and click to check out. Some of these users go through the purchase and place an order, but some users abandon their items. You would have one behavioral segment for those that purchased and another segment for those that didn’t, and you would use these segments to plan a different marketing experience for each of these groups.

Somebody in the group that purchased might receive an email showing other available products, based on their cart history. At that point, this group is no longer part of the segment of people who have not yet converted — they are part of the segment of those who have purchased products A, B, and C. Their segmentation will impact their experience with this brand. The group that abandoned their cart will be encouraged, through email, the web, or other means, to see their purchase through. They stay in the no-purchase segment until they are successfully converted.

Q: Why is behavioral segmentation efficient for a company?

A: Behavioral segmentation saves time and money from being wasted on already-converted, loyal customers — time and money that could be used on converting other potential customers. Going back to our e-commerce example, the customers that already purchased from the brand switch out of the non-converted segment into one reflecting the products they’re interested in. Because they are a new customer, the marketing campaigns targeting this group won’t need to be as aggressive as those for an almost-convert. Dividing customers into groups helps determine what types of marketing each group needs, so that the proper messaging reaches them.

Besides allocating time and budget properly, behavioral segmentation also helps companies to know what’s working, and what needs a tune up. For instance, a company notices that 50% of new customers brought to a certain landing page end up clicking away. Analyzing that segment helps the company know that something about the landing page doesn’t catch a potential customer’s attention. So not only does behavioral segmentation drive efficiency, it also drives better customer experiences because each customer is receiving personalized offers and messages from that brand.

Q: What is the difference between behavioral segmentation and psychographic segmentation?

A: Behavioral segmentation groups people based on how they act, but psychographic segmentation groups them based on how they think or feel.

For example, let’s say a news website sends out a survey to their readers, asking them what kind of news content they prefer. A huge group of readers responds and says that they prefer business content. But after the survey is conducted, the news website checks what content categories are frequented most, and in reality, the same readers that said they liked business content are checking on sport content most often. Maybe it’s true that the readers enjoy reading business content (psychographic data), but what they consume on this particular news site is sport content (behavioral data).

Though these types of data are different, marketers should consider both and how they overlap. Behavioral data can sometimes provide insights into psychographic data and vice versa.

Q: Can behavioral segmentation be used for other things besides determining purchases and non-purchases?

A: Behavioral segmentation can be used for many other purposes. For one, it can be used for determining content affinity, like we saw with the news website example. It can also be used to measure engagement about products or services, like somebody doing research to buy a car.

You can also use behavioral segmentation with your existing customers to determine loyalty and find deeper insights about their demographics. Or, say they’re searching how to unsubscribe from your company’s service. You can pinpoint that and market to them to convince them to do otherwise.

Q: How do you collect behavioral data, and what types of data should marketers focus on?

A: To collect behavioral data, you would use an analytics tool like Adobe Analytics. Then, you need a system that’s able to ingest that data alongside other data points.

As for what data you should pay attention to, some marketers might only use web analytics to do their segmentation, but not every customer approaches a brand by web. For example, a tech store might have a website and several physical store locations. That means they should keep track of web analytics data and store traffic data. Customers might browse online but purchase in store. This is where multi-channel data gathering comes into play, so this tech company can stop targeting customers for products viewed online but purchased in-store. Without store-traffic analytics, the company might continue marketing a product to a particular customer who already purchased it.

The most important things for marketers to think about are the different touchpoints where customers interact with their brand, like in-store, point of sale, web, and even call centers, and collect data from as many of those touchpoints as possible. You might even bring in data through CRM that was collected through event registrations or other engagement touchpoints.

Sophisticated marketers have developed data-sharing partnerships and collect data from their partners as well. An example of that would be a credit card company that has a relationship with an airline. If the credit card company has an airline points rewards system, then that data gets shared to both the credit card company and the airline company so that they can market to you with an offer that’s relevant for your travel interests.

Another example would be a travel board that’s running a campaign to encourage people to come to Italy as tourists. If the travel board partners with an airline, the travel board could share behavioral data about which pages on a site a user has browsed, such as “things to do in Rome, Italy.” If the travel board shares this data with the airline, the airline could market flights to Rome to that audience, and then convert these people to buy tickets. Then, once flights have been booked, the airline could tell the travel board which buyers booked flights and the travel board would stop targeting those people.

Q: How do you optimize the data you collect?

A: The most basic segment you could make would be binary — based on yes/no criteria — and rely on whether or not a user takes a certain action. If yes, then they’re in this segment, and if no, then they’re not. But as a marketer, you should make sure you’re building valuable customer segments from the data that you have. Adobe Real-time Customer Data Platform has a real-time customer segmentation service that allows you to create robust segments, which go way beyond a simple, binary segmentation. With Adobe Real-time CDP, you can build customer segments based on time-bound qualifiers, like taking action A, then action B, followed by action C, within X amount of time. This is a much more specific segment that can provide much deeper insight into potential marketing messages, and when you have specific data, you can deliver personalized offers that are more likely to make a sale.

Q: What is the boundary of privacy that companies should adhere to?

A: The level of personalization that companies choose to pursue is up to each company, but a good rule of thumb would be to stay away from personal information like health information, deep specifics about what somebody viewed while on a website (like products that didn’t even make it into the cart), or any type of direct targeting that presumes an established relationship between a customer and a brand, when such a relationship doesn’t exist yet.

Aggressive targeting toward only a potential customer, especially with personal information they did not provide, is definitely not a route that companies want to go. The goal of a company shouldn’t just be to make sales — it should be to establish a relationship of trust with their customers.

Q: How does behavioral segmentation improve customer loyalty?

A: When a brand uses behavioral segmentation, customers receive more personalized experiences, leading them to form stronger relationships with the brand. And if, as a customer, you receive personalized offers more often, you’ll be able to discover more products and services that are going to be relevant for you and your life circumstances.

Q: What are some drawbacks to behavioral segmentation, and how do you combat these drawbacks?

A: One drawback of behavioral segmentation is the danger of over-rotating toward your most engaged types of customers by only focusing on building relationships with that particular segment. If you only cater to what the people who fit that segment do to engage with your brand, you risk building something that doesn’t fit the needs of less-engaged customers, but could have been appealing to them as well. To combat this tendency, you can build lots of behavioral segments that span the life cycle of your customer base. Don’t just go big on one particular cohort of your customers. Instead, think about how you would build a behavioral segment for people who are newly engaging with your brand and how you could nurture and mature that audience as they move toward conversion, and eventually, loyalty.

Another potential drawback, especially if you’re creating a new product, entering a new market, or doing something that you don’t have a lot of behavioral data for yet, is not having enough data to make correct marketing decisions. In those cases, it’s a good idea to leverage other forms of segmentation, like psychographic segmentation and other forms of data collection.

Q: What tools are best for behavioral segmentation?

A: Customer data platforms, such as Adobe Real-time CDP, and data management platforms, such as Adobe Audience Manager, are fantastic tools to use for behavioral segmentation, because those specific systems not only ingest data from analytics, but they also ingest data from other tools like CRM, ad campaigns, internal customer systems, and a variety of data lakes. Marketers should perform behavioral segmentation using the tools that have the most sources of data to pick from and the most destinations available for activation of the data, so that they can have all of their segmentation in one place, not across several different systems.

Q: How will behavioral segmentation look in the future?

A: A large part of future behavioral segmentation will be the consent element. Behavioral segmentation will evolve, because consumers are more aware of privacy, and in some cases, they’re going to have to provide consent to collect and use their behavioral data. This will be a valuable opportunity to explain to your customers the value of allowing you to do personalization for them and why it will benefit them.

Another future evolution of behavioral segmentation will be the ability to combine behavioral data with a person’s attribute data, which will provide even deeper insights into personas and potential marketing choices than ever before. In the future, an audience segment won’t just be a group of device IDs and email addresses that you can target, but rather an insightful way to group people interacting with your brand, which can help you develop new campaigns, products, and services.

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