Customer segmentation groups customers depending on certain characteristics, such as demographics or behavior metrics, using online or offline data sources.
Customer segmentation lets companies define specific target audiences that may be interested in products, services, and content.
It reduces the risks that brands will spend money on marketing to customers that are not interested in specific products.
Segmentation lets businesses increase personalization, which is becoming increasingly important to fostering engagement and customer loyalty.
Businesses that are able to use customer segmentation to better understand the buyer's journey can take action to increase engagement and conversion rates.
Most tools businesses are using have some customer segmentation functionality.
The biggest obstacles to using customer segmentation property include lack of knowledge, resources and data.
Learn more about customer segmentation in this Q&A with Danielle Doolin, senior product marketing manager for Adobe Analytics. Danielle has been with Adobe for three years and worked for leading analytics companies prior to that. Her experience includes work in the entertainment niche, which relies heavily on customer segmentation for success.
Q: What is customer segmentation?
A: I would define customer segmentation as the ability to group customers into specific subgroups depending on certain characteristics and using online or offline data sources. With customer segmentation, we're looking at things like demographic characteristics, engagement characteristics and the types of interests they have. Are they interested in food or sports, for example?
And then other types of lifestyle information are also considered. Like, what is their salary, what is their job, how many children do they have? So, it's just really being able to segment your customers into groups with common characteristics so you can utilize those groups for other purposes.
Q: How is customer segmentation different from market segmentation?
A: They're very similar in the types of criteria considered to be able to segment customers. I'd say the major difference between customer and market segmentation is that customer segmentation is probably a fairly new term because of the fact that customer experience and customer journey is so important to businesses today. It's about looking at actual customer experiences versus answer questions like "Can I get more sales regardless of who the customer is?"
Q: Why has customer segmentation become more important today?
A: Today, it's all about being able to provide the best possible experience for that user or customer. Because it's not just about engaging with new customers. It's also about engaging and keeping customers loyal. You want to be able to target customers effectively by giving them personalized experiences, showing that you care about them and giving them content or product recommendations that they're interested. It's really all about the theme of personalizing that customer's experience because that enables them to really become engaged and helps you retain them longer. It extends the customer lifecycle.
Q: How do you target the right customers?
A: There are different ways. A lot of times, companies use DMPs (data management platforms) or CRMs (customer relationship management) tools to collect customer data. They use their own first-party data or leverage other sources to be able to segment customers into certain attributes they want to target.
So, a company takes specific pieces of data about customers, establishes goals as far as what types of customers they want to reach, and uses that information to be able to act via personalization tools like recommendation engines, search engines, or marketing and ad targeting.
Really, the only way to be able to understand how your customer segmentation is working is to have some type of analytics tool to evaluate performance and understand who you're reaching and if it's the right target market.
For example, say you know there's a group of females in a certain age range that come to your site and you want to do a promotion to them for a sale. You know that somebody comes back on a daily basis on your site and purchases versus someone else, who comes back on a monthly basis and purchases. But you want to get those monthly visitors so they are coming back and making purchases more often. You may be more likely to promote to just that segment of users that are monthly visitors. So that's where the joint data come together.
This type of customer segmentation requires pairing two types of data: data about the visit and data about the visitor.
Visit characteristics related to the person's engagement with the brand or service. For example, when did they visit the site, what did they look at, did they make a purchase, how long were they there?
Visitor characteristics related to everything about the customer's demographics and lifestyle, such as who they are and what they do.
Q: What are some of the most important types of customer segmentation in use today?
A: I think engagement pattern is super important. Not only looking at when they purchased something, but also what they do after and what they've done before. How often have they purchased a product? What are they purchasing? It's important to really understand the engagement with the brands they are purchasing.
Another important factor is interest – understanding what types of things they're interested in. That helps you ensure you're serving relevant marketing to specific interests, whether it be food or sports or a certain team.
One of the greatest features through analysis is being able to look at cohort analysis. That allows you to look at groups and sections of users and what their retention and loyalty is. You can see if they're coming back on a daily, weekly or monthly basis. You can segment to understand what products they're looking at and what are their interests, and really use that to be able to target. At the same time, cohort analysis helps you with churn analysis to understand when certain types of users aren't likely to come back. That's important for remarketing and retargeting.
Fall and out flow analysis are methods for understanding what the customer journey really is. Because no customer is the same. Having specific segments of customers that you can group separately in terms of how they interact with the brand or product during the journey is important for marketing and conversions.
Q: What are the biggest challenges in customer segmentation?
A: One common challenge is that companies don’t have first-party data, or they have limited data on their customers to be able to really segment based off of certain characteristics.
There's also an issue of aged data. So, think in terms of not consistently updating the customer segments or iterating on them. If you don't keep up with your customer segments, you could have groups of customers that originally were single users age 18 to 24, but now they're married users age 35 to 49.
The challenges tend to be making sure the customer segments are up-to-date, making sure you have enough data via first, second or third parties, and also making sure you have the resources and tools – some type of analytics program that allows you to understand how those kinds of segments are performing, provides actional insights and helps you take action.
Most companies understand what customer segmentation is. I just don't know that they all use it as much as they could in terms of analyzing and acting on the data. Sometimes I hear from companies that they haven't used customer segments or attributes to look at their data, and I feel this is a real weakness for their strategy. You can't just look holistically at all customers and create them equally, because everyone has their own unique interests. It's hugely important — especially in today's day and age, with customer experience being such a high level of standard.
Q: Why don't brands have some of this information?
A: They don't have their customer demographic because they don't have first-party data. They don't have authentication. They aren't collecting age, gender, etc. — they're just getting a purchase. Or, they don't subscribe to a service that may be able to provide it this information to them.
Most companies have visitation data. They can see page visits. But unless you combine it with something like audience analytics, it's going to be more difficult to target your users effectively. You could risk spending marketing dollars on users that wouldn't be interested in this specific product even though they visited your page. It's definitely important to have both components to be able to target better.
Q: Why aren't some companies using the data?
A: It could be they lack the resources – the data scientists and analysts – to be able to effectively look at the data. They might just be scrambling to pull reports for high level views for the management team. Or, they might not know how to use the functionality in the tools they already have — they don’t know how to segment the data themselves.
Most of the tools people have can do this stuff. It's the inexperience of the analyst or marketing team, lack of resources, or lack of data that is often a challenge.
Q: What are some ways companies can use customer segmentation to make improvements?
A: I think one of the big topics that has come up is all about the customer journey and understanding where they are in their path to purchase and how they're interacting with a brand across devices. If you're able to segment customers who look up your product on one device and later purchase it on another, you can use that segment to target them more effectively.
It's definitely about using customer segments no matter what device they're on to be able to better target. It's also about personalizing that experience for them based off of what they have shown interest in. Targeting and personalization can definitely be improved upon in the future.
In terms of improving the product and service itself, it's about understanding where there are issues. It's about discovering where there are customers that are likely to churn and being able to use that as a segment to reengage with that customer, improving their experience and reaching out to provide them with help.
Q: Where is the future of customer segmentation?
A: I think with customer segmentation, there are a lot of enhancements that have come about through cohort analysis as well as attribution, flow and fall-out analyses. Those are all things available today.
I think the future will hold a lot more AI machine learning capabilities that make it possible to increasingly analyze that data and the customer segment, providing you with smart segments or new segments that you wouldn't have otherwise put together. Also, the technology will provide critical insights on how to use those customer segments — recommendations on how to act on these specific segments. Plus, really doing it all in a privacy-friendly manner.
Q: Can you over segment?
A: Yes, you don't want your segments to be too small. If you layer on more and more data points, it could get to a really small reach of customers. You could be missing out on other opportunities because you've narrowed it down too small.