This episode of the Leading Learning Podcast looks at why and how learning businesses can and should segment their audience—what it looks like in practice and how it can lead to more engagement, better learning outcomes, and, yes, better business results.
If you’re already segmenting learners, the episode will provide food for thought and an opportunity to reassess your approach. If you’re new to segmentation, then you’ll walk away with how to start.
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Celisa Steele: [00:00:03] If you want to grow the reach, revenue, and impact of your learning business, you’re in the right place. I’m Celisa Steele.
Jeff Cobb: [00:00:10] I’m Jeff Cobb, and this is the Leading Learning Podcast.
Celisa Steele: [00:00:17] Jeff, have you ever had one of those moments where you’re scrolling through a streaming service, and it suggests a show that’s so spot-on, it’s almost creepy how well it knows what you’d like?
Jeff Cobb: [00:00:27] Definitely. It’s like, “Hey, Jeff, we know you love rock and roll and satirical comedy, so here’s a series where Stephen Colbert comments on biopics about musicians à la Mystery Science Theater.”
Celisa Steele: [00:00:38] And you’d watch that series, right? Because it fits your interests.
Jeff Cobb: [00:00:42] And I now have questions about whether I should be happy about my viewing options or deeply concerned that an algorithm understands me better than some of my friends do. But I digress.
Celisa Steele: [00:00:53] That kind of personalization is what makes companies like Netflix or Spotify so good at what they do. And they do it through segmentation. They analyze behavior, preferences, patterns, and then they serve up the right content for the right person at the right time.
Jeff Cobb: [00:01:11] Of course, achieving the level of personalization of a Netflix or Spotify might be a stretch for most learning businesses, but many learning businesses aren’t doing even basic segmentation well. They offer the same courses, the same marketing messages, and the same learning experiences to everyone—whether they’re a brand-new professional or a 30-year veteran, whether they’re highly engaged by the subject or just trying to fulfill their CE requirements.
Celisa Steele: [00:01:37] Which is a problem, because learners—who are also entertainment consumers—are expecting more personalized experiences. If we don’t take the time to understand and segment our learners, we risk losing them to providers who do that segmentation.
Jeff Cobb: [00:01:54] So we want to spend this episode talking about why and how learning businesses can and should segment their audience—what it looks like in practice and how it can lead to more engagement, better learning outcomes, and, yes, better business results.
Celisa Steele: [00:02:10] If you’re already segmenting, great. We hope the episode will still provide you with some food for thought and an opportunity to reassess your approach to segmentation. You might walk away with a new dimension you want to segment on or a new idea to try for how you leverage the segments you have in place. Of course, if you aren’t yet doing segmentation, then we hope this episode starts you down that road.
Why Segmentation Matters: The Business Case
Jeff Cobb: [00:02:33] Let’s start off with why segmentation matters: the business case for segmentation. And we’ll say, out of the gate, segmentation isn’t just a nice-to-have—it’s essential if you want that engagement, retention, and revenue that so many learning businesses are seeking.
Celisa Steele: [00:02:52] Learning businesses compete for attention, and personalized experiences help cut through all the noise. We’ve talked about awareness. We’ve talked about attention many times before on the podcast. Segmentation is a way to help you make your messaging more tailored, more personalized, which is then going to hopefully help it, once it does get someone’s attention, keep that attention.
Jeff Cobb: [00:03:15] We’ve made comparisons between learning and marketing before. That’s familiar ground with us. Segmentation happens all the time in marketing—e-mail campaigns, for example, or in ads. You can set up all sorts of segmentation around running digital ads. And learning businesses need to be doing the same. They need to be doing that as part of their own marketing promotions, but they also need to be doing it as they’re thinking about their portfolio and their product development.
Celisa Steele: [00:03:42] The danger of not segmenting or not segmenting well is that you waste hard-earned attention and awareness, and then you make it even harder to get that back. If you’re sending that same e-mail about a beginner’s course to seasoned professionals, when they tune in, they’re going to be like, “Hey, that’s not for me. That doesn’t interest me.” So the next time they see your e-mail, even if it does tout an offering that is more appropriate to them as a seasoned professional, they might be less likely to open it.
Jeff Cobb: [00:04:11] In that case, it might be much better to have different learning paths that are based on career stage and then promote the appropriate one to the appropriate person. We’ve brought this up before. You can’t stress enough, at this point, how important getting attention is and how hard it is to get attention. I think we all know that. And, once you’ve got it, you better be delivering something that’s relevant and interesting to that particular person, or you’re going to lose them, and you may not get them back.
Celisa Steele: [00:04:39] If we know that segmentation is really important, critical in fact, then the next big question is how to do that segmentation. Because not all segmentation is created equal.
Jeff Cobb: [00:04:51] You don’t want to split people into new versus experienced or member versus nonmember and then call it a day. We’ve done our job. There are different approaches to segmentation, and the trick is finding what actually matters for your learners and your learning business.
Different Ways to Segment Learners
Celisa Steele: [00:05:10] We’re going to talk about some different ways to segment learners, and there are lots of ways to slice and dice an audience. Before we jump into different ways to segment learners, we’re going to say up front that less is more and that it’s really important to also be asking why as you think through your segmentation.
Jeff Cobb: [00:05:31] You can segment in so many different ways, but it’s a lot easier to manage a handful of meaningful segments or meaningful personas. Businesses like to talk about personas a lot, but you can’t have 80 of those and serve them effectively. You can’t even have 30 of those and serve them effectively. You’ve got to get it down to the ones that matter most for your particular business.
Celisa Steele: [00:05:57] That’s around that less is more. Part of it’s being able to keep them in mind, being able to meaningfully serve them. That’s why less is more effective in this case. In terms of that importance of asking why, it’s about what will you do with that segment? What will you do with that piece of data you’re thinking about segmenting along? And the real takeaway here is don’t collect that data if you don’t really have a plan to use it. You’ve got to get people’s attention to collect data often in the first place, and then you don’t want to overwhelm them with too many asks, especially if you’re not going to do anything with it. So the data you’re trying to collect and determine about individual learners, make that important; make that relevant. Make sure you know why you’re collecting it and what you’re going to do with it.
Jeff Cobb: [00:06:43] A part of that why and a part of that relevance is the size of the segments that you define. We just talked about not having too many different segments because that gets to be hard to manage, and oftentimes, if you have too many segments, you start getting them down to sizes that don’t really work from a business standpoint because we are, after all, talking about the learning business. It’s pretty easy to slice down to segments that are so small that there’s just no way you’re going to be able to offer a financially viable product. Now, if you’re a mission-driven organization, as many learning businesses are, you may make the decision to offer something to that segment anyway and offset the loss somewhere else. But, let’s face it, you can only do so much of that.
Celisa Steele: [00:07:25] Those are some upfront caveats or upfront thoughts to think about as you’re thinking about what segmentation might make sense for your audience, for your learners. What we can do now is talk about some typical ways to segment learners and different ways to think about that. Demographic segmentation is a very big, typical way to segment an audience. This might have you looking at things like what career stage is that individual in? What industry, or what job role? Are they a member or nonmember? Maybe you want to do things like collect geographical location, if you offer synchronous learning opportunities, whether those are in-person or online, and you want to be able to offer that at appropriate times to those learners. Maybe you want to use that geographic location to also make some assumptions around language support or localization needs.
Jeff Cobb: [00:08:16] Demographic is definitely a standard one. In a lot of ways, it’s often the easiest one for learning businesses to work with. Particularly if you’re within, say, a member organization, a lot of times you’re going to have some of that data about your learners, or you can get it relatively easier. Other types of data might not be as easy. Relative to any segmentation, you want to form some solid ideas about the segmentations you want as early as possible so you can plan for it because it’s going to be pretty rare that you’re going to be able to push a button and have your segmentation data. You’re going to have to collect it over time. You’ve got to be thinking about the things that you really want to have in terms of segmentation data.
Jeff Cobb: [00:08:56] A second one we’ll mention is behavioral segmentation—things like preferences for in-person offerings versus online or preference for mobile-friendly learning or short form (microlearning) versus deep dive or more immersive opportunities, what the engagement patterns are of your learners, their past participation, their tech access and savviness. These reflect ways that they behave. But, again, you’ve got to have a plan for figuring out how you’re going to get that. Are you going to get that through a survey? Are you tracking your LMS data? How are you getting that?
Celisa Steele: [00:09:29] Buried in some of what you were saying is this idea of engagement. How engaged are these segments? How engaged are these learners? Are they coming back to you, and what are they coming back to you for? This is perhaps a bit of a side note, but a potential, useful distinction or segmentation could be around who do you consider alumni? Who has come and learned from you before? Maybe that’s a useful segmentation because the messaging to those folks is a little bit different than to folks who’ve never learned with you before or haven’t learned with you in this type of offering. They haven’t yet gone to the big place-based conference, or they haven’t yet tried the mobile-friendly course offerings that you have, things like that, and that distinction of “Who is an alumni?” in this case.
Jeff Cobb: [00:10:16] These are great things to brainstorm about within your learning business. What are these different types of segmentation that really matter? Again, going back to that why. Another one is needs-based segmentation—knowing pain points of particular groups of learners, knowing learning goals of particular groups of learners, the urgency of skill acquisition for particular segments within your audience.
Celisa Steele: [00:10:37] Then there’s also the potential to segment around competitive offerings, i.e., where does this segment of your learners tend to go to learn if they’re not going to learn from you? In some cases, that might be they’re going nowhere, and that might be your competitive landscape with them, which then would lead to a certain type of messaging. For others, you may know that there’s another offering in the field that is competitive with yours, and they have enough money and enough wherewithal to get themselves to that place-based offering. That’s going to be what you’re alluding to in some of your marketing messaging, for example.
Jeff Cobb: [00:11:12] Or configuring your advertising against keywords that relate to that competitor—back to the personalization and marketing. Another one is what’s typically referred to as psychographic segmentation. What do you know about the mindset of the different segments within your audience, the motivations, the barriers to learning? How can you speak to those, both in how you promote and in what you provide in terms of learning experiences?
Celisa Steele: [00:11:35] That ties back to the needs-based segmentation that you mentioned earlier, Jeff, around pain points, learning goals, and the urgency of skill acquisition. A lot of those then tie into things like mindset and motivation. But, again, the more fully you understand the drivers and the barriers for your learners, the more effective you’re going to be able to be in how you design your learning offerings and also how you talk about them, how you promote them.
Jeff Cobb: [00:12:00] You can imagine a Venn diagram around some of this stuff, where some of these different segments, these different categories overlap. You’re looking for that sweet spot where you’re capturing the most of these characteristics within a particular segment, which can be very powerful in terms of positioning and messaging. One we’ll mention that we find a lot of organizations don’t tend to focus on as much as they could is ability and willingness to pay and, related to that, the learners’ or members’ or customers’ role relative to decision-making for learning. Are they making training decisions for others? And, if you know you’ve got a segment of your population that is making training decisions for others or if you know you’ve got a particular segment of your population that is showing a particular willingness and ability to pay for whatever an offering is, that’s very valuable data.
Celisa Steele: [00:12:49] Related to that, we could call this the firmographic segmentation. If you’re thinking about firms, if you are a learning business that’s selling B2B, what do you know about those firms that make really good B2B customers in terms of company size or industry focus or any of that? Having that segmentation and that data for your B2B customers can also be extremely valuable.
Jeff Cobb: [00:13:13] That’s one of those classic overlap areas. If you’re trying to target organizations of a certain size, and you want to get to the person who makes training decisions within that organization, that’s a great segment to be able to have data on.
Celisa Steele: [00:13:23] And the last segmentation idea or category we’ll talk to is around strategic importance or strategic relevance. When you think about your learning business, your mission, your goals for the next two or three years, how important are particular segments to helping you achieve those goals, achieve that mission?
Jeff Cobb: [00:13:47] We’ll tie a bow around this by saying, again, that be sparing (less is more), and why is very important. You want to consider all of these different types of segments, but whittle it down to the ones that are important for your learning business and know why they are important.
How to Gather Segmentation Data
Celisa Steele: [00:14:05] We’ve talked a little bit about the business case for segmentation, for why segmentation matters at that high level. We’ve just talked through some different ways that you can think about segmenting learners. Now it feels like it would be worthwhile to touch, at least briefly, on how do you get that segmentation data? How do you get that data that’s going to allow you to segment your audience?
Jeff Cobb: [00:14:26] We referenced this a little bit earlier, saying you need a plan. You need to make some decisions as early as possible about the types of segmentation and that segmentation data that you want to collect because it’s not going to magically appear for you in most cases. But, as you have that plan, then you’re going to have to go through the process of getting, maintaining, and updating the data. One classic method around this is surveying and getting learners to self-identify in some of these segment choices that we’ve talked about. We know from hard experience ourselves, and most of our clients know, that surveying is getting tougher and tougher (to get people to respond to surveys). But it still needs to be a tool in your toolset, and it also needs to be something that you’re repeating with some regularity over time. Running the survey once every five or ten years is probably not going to give you the level of segmentation data that you really need.
Celisa Steele: [00:15:16] Surveys and learner self-identification may be a proactive way of getting some of this data. Another proactive way would be around using some other qualitative methods. Maybe you do interviews. You pick up the phone and call some people who you deem to be representative of some of these segments that you’ve identified. Maybe you do focus groups where you bring in more than one from that sample segment and talk through key issues with them and uncover things like some of those psychographic needs around mindset and motivation or getting a little bit around the competitive landscape for those folks. Those would be more proactive ways to get some of the data or to update data. If you think you already have some of this or if you’ve collected it in the past, maybe it needs to be refreshed. But, in addition to proactive, there’s data that already exists, and it’s going to be then more a matter of pulling that together, looking through it, and assessing that.
Jeff Cobb: [00:16:12] It’s somewhat more passive—or automated data is the way to put it. The types of things that you’re getting through your learning management system. Learning management systems are collecting all sorts of data, which often does not get used as well as it could. Your Web site data, through your Google Analytics and other types of data that you’re collecting there. Your e-mail, those open rates and click rates and engagement rates with your e-mail—a wealth of data. You’ve got so many different data sources you can tap into, and you’re going to do this over time. This isn’t a static one-point-in-time thing. You’re going to be continually refining this segmentation data. I’ll note that a lot of what we’re talking about here aligns completely with our Market Insight Matrix tool, which we have an episode dedicated to that. We’ve talked about that tool a lot. I don’t think we’ve talked about it a lot as a path to segmentation, but it absolutely is because it’s all about getting different types of data that you can then use in how you’re going to market your offerings.
Celisa Steele: [00:17:07] This is a great place to leverage artificial intelligence or other analytic tools to help you dig through some of that data, like you were saying, Jeff. If you’re going to have this wealth of individual points of data about individual learners from your learning management system, you’re probably going to need some tools to help you make sense of that volume of data, to see some of the patterns and see some of the takeaways around your segmentation from that. Just be thinking about AI and other analytical tools to help you find some of those insights into your audience.
Jeff Cobb: [00:17:40] Yes, those can be extremely powerful. Those are things we’re using ourselves in thinking about our own segments right now. Maybe we should turn to how to use all of this wonderful segmentation data that we’ve been talking about here.
How to Use Segmentation Data
Celisa Steele: [00:17:54] A clear place where you can use this segmentation data is in your promotions. We started out near the beginning of our conversation talking about how common it is for promotions in the marketing world to make use of segmentation so that they can better personalize the message that’s being received. That’s something for learning businesses to do. You can be thinking about, “Okay, what is the message in the e-mail for this segment going to be? How can we speak to them and hit on some of their pain points or hit on some of their aspirations and really target it to that segment?”
Jeff Cobb: [00:18:31] We’ve talked before on a number of occasions about learner engagement, about how engagement begins during that promotional cycle (the early stages of marketing), getting to the right learners with the right message, and engaging the motivations of those learners as you bring them towards the actual offering and move them into the actual offering. You want to, again, as you’re saying, Celisa, tailor that message and put them on a path towards learner engagement in your offerings. You can also do things when you’re promoting, like configuring specific offers to specific groups. You might do things like free courses to previously unengaged members or customers to try to move the needle or a special follow-on deal for folks who enrolled in a specific course or seminar.
Celisa Steele: [00:19:18] And then you can also potentially use segmentation data to determine the cadence or the frequency or the timing of your promotional messages. If you know that seasoned professionals tend to be much more harried, and they’re going to only want to see, at most, one e-mail a week from you, then maybe they want it at a certain time of day. This is where you can begin to play with “When do we send it? How frequently do we send it?” to also go along with that tailored messaging and also potentially those tailored, specific offerings to your particular segments.
Jeff Cobb: [00:19:54] Yes, and this is definitely a place to leverage AI. You can supply information about a particular offering and information about the audience segments, and, for example, have AI write different e-mails emphasizing different features for different segments, asynchronous for mid-career-ers who are likely to have school-age kids, that sort of thing. All of these things we’re talking about we do in our own learning business. For example, in the run-up to the most recent Learning Business Summit, we did this, fed a bunch of data into ChatGPT, and had it help generate a series of different e-mails for marketing that particular event. That’s a starting point, we should say. In my experience so far, ChatGPT still does not come up with the perfect thing, but it can help to jog your thinking and get you on a clear path that you can then configure and customize to truly fit your audience and the different segments within it.
Celisa Steele: [00:20:47] Promotion is a very clear, fairly obvious way to use segmentation data. Another big way to use segmentation data is for product development.
Jeff Cobb: [00:20:58] Yes, definitely. Being able to leverage content in different ways, in different formats, and for different audiences. Of course, you have to have the segmentation data to do that in the first place. You don’t want to just be proliferating content without, again, that why in the background, having identified specific audiences that different permutations of content can be used for. We had an interesting example come up in our mastermind not too long ago, where one of the members in a trade association was approached by a member company who wanted to use that organization’s core training, or one of its core trainings, to create more targeted, specific training for its own employees internally. They were able to take the core training of the organization, run it through Synthesia (one of the AI video tools), and, based on their segment data for their particular set of employee learners, were able to convert it into content to fit their audience. A content reuse story but tailored based on segmentation data and leveraging AI to make that happen.
Celisa Steele: [00:22:04] You can use the segments to create different versions of the same products. This is a different spin or a slightly larger view of what you were just sharing there, Jeff, in that example. But we know that there have been learning businesses in the past that have put in the time and energy and effort to standardize the set of materials that they have for their trainings, for their learning experiences, and so they have those standard materials, whether it’s in person or online. Once you have those segments, and you realize, “Okay, who’s going to benefit more from the in-person? Who’s going to benefit more from the online?,” then you can again tailor the promotion of that correct product to that user. And, as you’re saying, Jeff, you’re setting them up on the way in to come into a product that’s most likely to align with their needs and their preferences, and then they have that good experience there, and that all leads to greater engagement. That starts very early on in the process, and it ties to both the promotion and to the specific flavor of the offering that that learner, that that segment is presented with.
Jeff Cobb: [00:23:10] This is one of the great arguments for being able to chunk your content as much as possible into small components so that those can be reconfigured in different ways for those different paths and different audiences. This kind of segmentation is fundamental to personalization and to adaptive learning experiences that we know so many organizations want to make part of their approach to learning right now. AI has big promise around this. But, if you don’t have that segmentation data in the first place, it’s hard to leverage the opportunities for personalization and adaptive learning experiences and getting the most out of AI.
Celisa Steele: [00:23:51] One approach to adapting a learning experience can be around having different tiers or different levels of the offering. Maybe there’s a free offering that goes to a certain segment. Maybe there’s a shorter version (microlearning piece) that might go to a different segment. Maybe there’s the deeper dive that might go to a third segment. You could imagine that both the free and the micro and then the fuller offering are all based on some of the same assets, the same content, but pulled together differently for different segments.
Jeff Cobb: [00:24:26] The last thing we’ll say about using segmentation data around product development—and there’s certainly plenty more that could be said—is it can be a great tool for strengthening community around your learning offerings and, as a result, strengthening learner retention as well. If you’ve got good data on your learners, then you’re able to connect learners with true peers, whether it’s for peer-to-peer learning or accountability, whatever’s going to be productive in that experience. Or connecting them with mentors, so you can see that early-career person, and you can see that later-career person based on the data, and you can see other commonalities between them and be able to arrive at the decision that this is a great match, that this person is going to be a great mentor to this person.
Measuring Use of Segmentation Data
Celisa Steele: [00:25:09] We have talked about why, the business case. We’ve talked about different, typical bits of data that you can use to segment. We’ve talked a little bit about how to get some of that segmentation data. We were just talking about how to use segmentation data. So the last area that we’ll touch on is around the idea of measurement, the idea of looking at the impact of all of this.
Jeff Cobb: [00:25:30] Measurement is always a good thing and knowing that you are having an impact with what you’re doing. If you’re just starting out with doing this, then getting a baseline now is important. You know where you’re starting from and have an idea of where you’re trying to move to and then see if segmentation of messaging helps, for example, in increasing open rates or click-throughs. And then does it help with the real test, which is purchases?
Celisa Steele: [00:25:57] That reminds me of your conversation with Alaina Szlachta—she was at the Learning Business Summit earlier—that idea of having a hypothesis and that it’s really important because you want to have that hypothesis about, “Okay, now that we have this segmentation, yes, we should see higher open rates,” or “We should see higher click-through rates,” or “We should see greater sales revenue because of this.” So figure out what is that hypothesis that you have around what this segmentation is going to do for you, and then test it; see if it plays out.
Jeff Cobb: [00:26:26] Definitely true. All strategy basically comes down to having a hypothesis and testing that out.
Celisa Steele: [00:26:33] We talked about it a little bit on the promotion side—click-throughs and open rates. In terms of, once people engage in the learning experience itself, it might be looking at completion rates. Do those go up? Might be looking at evaluation results. Do those go up? Because then the right people are getting to the right offerings. But, again, be very clear. This goes back to that earlier comment about be clear on your why. We were talking about why for segmenting and what’s the end result of that why? Why are you segmenting, and what results are you looking for?
Recap and Final Thoughts
Celisa Steele: [00:27:25] If you enjoy the Leading Learning Podcast, please do us and a colleague the favor of sharing this show with that colleague, someone you feel would appreciate and get value from it.
Jeff Cobb: [00:27:35] To recap, we see segmentation as an important aspect of what any learning business should do in the marketing realm.
Celisa Steele: [00:27:42] If you’re already segmenting, revisit your segments. Are they still accurate? Are you leveraging them well, especially in the areas of product development and promotion?
Jeff Cobb: [00:27:51] If you haven’t yet segmented your audience, we encourage you to start small and identify two to five segments that matter the most and that you’re in a position to serve well or soon in the future.
Celisa Steele: [00:28:02] And, whether you’re starting fresh or already have segments in place, remember that you’ll need to continuously refine segments as learner behaviors evolve.
Jeff Cobb: [00:28:11] Thanks again, and see you next time on the Leading Learning Podcast.
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