Episode 25 - Actions speak louder than words: Why Behavioural Segmentation is powerful at driving customer value


Are you value-sensitive or time-sensitive? Active or dormant? Proactive or a procrastinator? These questions are at the heart of Behavioural Segmentation, an approach to segmentation that makes nudges significantly more effective at influencing behaviour. The integration of behavioural science into customer insight is proving to be a powerful accelerator for businesses to understand their customers and, more importantly, use that insight to drive value for them and their customers alike. 

To discuss how putting these approaches helped Sage increase customer satisfaction and reduce churn, host Freddie Martin is joined in the studio by Suresh Natarajan, who leads the PwC Behavioural Economics practice, and Brian Wall, Director of retention at Sage.

Listen on: iTunes  Spotify


Freddie Martin:

Hello, I am Freddie Martin, and welcome to a new episode of the Economics in Business podcast. Today, we are looking again at behavioural economics, and more specifically behavioural segmentation, and how it can transform the way businesses operate and deliver customer value. This podcast is a follow up to a previous podcast of ours, episode 8, titled, ‘How can companies benefit from behavioural economics?’ We would recommend going back and giving that one a listen to brush up on the basics first. We’ve put a link in the description of the episode, or you can find us on iTunes and Spotify.

Now, back to today, to talk about behavioural segmentation, we're joined in the virtual studio by Suresh Natarajan, the lead of our Behavioural Economics practice in UK and Europe; and special guest speaker, Brian Wall, director of retention at Sage, US. Sage is a multinational enterprise software company on the FTSE100 and has recently completed some relevant work with the PwC team. Welcome to you both.

Suresh Natarajan:

Hey, nice to be here.

Brian Wall:

Hi, thank you for having me.


Suresh, it's great to have you back on the podcast. In that previous episode, you going into a lot of detail about what is behavioural economics and what we can do with it. Just now, it'd be nice to know and understand why is it important to be talking about behavioural economics now?


Thanks Freddie. I think pretty much everyone who is listening to this podcast has heard of nudging and behavioural economics before, so I am not going to prove the point that it's important to those who've already heard about it, but it's been around for a while. It's increasingly used by the organisations that we think are successful. So the Googles, Amazons, Facebooks of the world are using all the data they have with behavioural techniques to drive different kinds of behaviour. Increasingly, approaches like behavioural segmentation and microtargeting are being used to drive business and customer value. For better or worse, it is being used right now and it's proven to be powerful, but we need to make sure we use it carefully.


Thanks for giving that useful context on behavioural economics as a whole, but today, we're discussing behavioural segmentation specifically, so what exactly is behavioural segmentation? Can you give us a brief explainer?


Yeah, I'll avoid the long-winded academic answer, so it’s what it says on the tin right. It's about behaviours rather than just about demographic attributes. Most organisations, they'll hear segmentation, and they'll have in their mind what we call customer segmentation, which is backwards looking. It describes who someone is, based on the features that are observable of who they are. Behavioural segmentation is more about their behaviours. What is it that they do, what is the information that you can gather from the way they interact with you, and how can you use that to drive a different type of segmentation that allows for a different series of levers and tools that changes their behaviour. Customer segmentation helps you understand who they are, but doesn't help you to change who they are. Behavioural segmentation describes that behaviour and helps you to focus on the kinds of things that will change their behaviours in their future. It's really looking at the kinds of things around how much they know, what do they think, how do they do things, or their response to a product or service. Those segments from there allow for a much more effective use of tools such as nudging and process change.


Okay, that sounds quite intuitive really, as you say, it’s segmenting people on behaviours, not other attributes. Could you go into a bit more detail about exactly what behavioural segmentation brings for businesses, but also to their customers as well?


We've got loads of information about our customers, and we need to use that to prioritise, personalise, and target our customers in a more effective way. When you have a behavioural segmentation model, we looked at all the types of information around how often the customers are using the service, how many tickets they're raising, and how much satisfaction they are getting from it, what is their patterns of usage and patterns of behaviour. We take those and create loads of different segments, like a dissatisfied user, a value sensitive user, a procrastinator, a dormant user, etc. We use that information to help unlock specific strategies for each of those groups. A dormant customer, someone who's not using it, hasn't used it for a while, aren't getting as much value from Sage as they should be, that's the problem. We can identify that based on their usage patterns nine months ahead of the time that they might make the next purchase decision. We use that in a timely way, change their likelihood of improving their usage, improving their access, improving the value that they get, that increases satisfaction in the short term, that increases usage in the medium term, and that increases their willingness to stay with Sage, and their willingness to use these kinds of products in the future in the long term. That's the kind of power, that we can predict nine months ahead of time, when normally you might be firefighting and say, ‘why don't our customers like us when it comes to a renewal, when that instead we can focus on the root causes based on the behaviours that we see.’

From there, we can then put a suite of different nudges alongside the processes, alongside the communications that really target those customers in different ways. The kind of customer who might be procrastinator, who needs a very different kind of thing, all about increasing the speed of response, speed of access, and you're focusing on messaging for them about how much time do they unlock and get to re-spend in other ways as a result of being with Sage, because that's what's valuable to them. That's very different to someone who we might consider a value-sensitive customer. For them, value is more about the dollar sign, how do they make sure that every dollar that they spend is going to be worth it for them. For them, it is really about trying to make the message about how does this unlock the critical enabling activities to run in their business. What are the benefits that they gain from being a customer that we should be highlighting? Those are different set of tools, a different set of nudges that can only be unlocked by having a better sense of who those customers are, and the behaviours that would likely be receptive to the things that we have.

From there, we then apply loads of different things around battle cards, talk tracks, making conversations more effective, making those nudges in every single critical part of the journey that they have. Whilst no simple thing is changing, every small process, every small interaction they have with Sage throughout the entire journey they have is a little bit better, little bit more effective, and collectively a lot more powerful.


It seems like that's a real win-win, where you're using types of data that's not been used in that way before in order to centre the customer experience, the customer wins, but then through that drive growth and value. That's been a really interesting introduction to behavioural segmentation in theory, but Brian, given that you worked with the actual team, could you talk to us a bit more about how this works in practice? Also, thank you very much for joining us today.


Thanks for having me Freddie, I am glad to be here, and I would absolutely love to talk to you about it. At Sage, we have a Customer For Life team (CforL or retention), and that places customer experiences as the focus of everything we do. We're always looking for ways to innovate and give our customers a personalised experience that reflects who they are as a business and what they need from us at Sage. Now, if we do this well, our customers will trust us more, they will value their partnership with Sage, and they will remain customers for life. That's why my team is measured on customer churn. The better we serve our customers, the more likely they are to stay.

Behavioural segmentation is one innovation that we thought could help us serve customers better. Strategies are different, but we all want our customers to have a great experience, right. In order to do that, though, we needed to have a deeper understanding of our customers. We had to decide how we needed to serve them differently, and then we had to scale that strategy from theory to reality quickly. As a result, it would help us have better conversations with our customers and drive better outcomes for Sage and for the customer themselves.

Let me give you an example, for instance, if a sub-team or department at one of our customers aren't making the most out of the software they bought, that means potentially in three to six months’ time, they're going to collectively feel like they're not getting the value for their investment. Knowing what might make them unhappy before they're unhappy is the key to the success of this program.


Okay so an easy problem to solve then! Suresh, faced with that challenge of knowing when people are unhappy, before they know themselves, how did you go about tackling that?


Well, it's a number of different things. Speaking to the stuff that Brian was saying, there's a whole load of data that we have about customers. How often do they use the service? How many tickets have they raised due to problems that they're facing? What kinds of users do they have? Do they have lots of users that use it a lot, or do they have pockets of users who use it for lot of activities, and some who don't use it for any at all? There's a whole richness in the data that we have, and what we try to use all of that data to come to is to create this behavioural segmentation model that we use, effectively grouping those into those behavioural segments. Dissatisfied users, value sensitive users, procrastinators, customers who might be what you call a dormant user, and all of that helps us to personalise, predict and prioritise our efforts in how we improve customer satisfaction for all those different types of segments.

For example, a dormant user, they weren't, maybe, fully utilising the Sage product suite. We identified them by all of this information that suggests that they are not using it as much as another customer might, they're not getting as much value potentially as a result. If they weren't getting as much value, and they weren't realising the full potential of the product, that's not going to help them, and they're not going to help Sage when it comes to the time of renewal, they say, ‘have I got good value for my money? Possibly not as well as I could have done.’ Getting that richness of data, making sure we're really identifying who those customers are way in advance, can then change the strategy to hold on to them. We're looking six months in the future, nine months in the future, and say, ‘if we can change the behaviours now, it's going to take that much time to make those new kind of improvements, new kind of usage pattern stick.’ That will make their experience better, and they'll get more for the money they've already paid, and they're going to love Sage in the process.

Based on all of that, we can also then prioritise which of these groups we target as well. So, nine months from down the line, you might want to talk about dormant customers. In the last month, you're going to really want to focus on and prioritise procrastinators or customers who might be more value sensitive. We need to change the way that we work on them, given they're going to leave things to the last minute, they're going to be procrastinating, they might be time poor. The kind of things that we need to help them with is, how does this unlock the time they need to run their business, and how do we take this as a headache they no longer have to worry about. For a value sensitive customer, which we take a lot of different information to get us there as well, this helps us to drive the messaging and behavioural change techniques around how does this serve as a critical enabler, the software, to the work that they do, how do we highlight the benefits that they gained for them. Again, a whole series of different psychological techniques, that's then better informed by knowing who they are, what they're most receptive to, and really driving home the value in a way that speaks to them rather than just a generic message for everyone.

On top of that, those are all the more automated processes, we then designed battle cards, talk tracks about how do service agents, customer satisfaction managers, help improve the experience of the people that they speak to. Giving the right strategies to deal with these kind of customers, to accompany that with proactive messaging, the whole series and suite of nudges and process designs, so that every single point of the customer journey is optimised incrementally just a little bit, and every conversation is made just a little bit sharper, a little bit faster, and a little bit more tailored to the person that they're speaking to. All diverse things combine together off the back of this behavioural segmentation data that really makes a big difference when you group them all together.


It's really interesting to hear the different strategies you have to target these customers. What I find particularly interesting about that is most of this is borne of data that companies are already collecting themselves, about when and how customers raise complaints and issues with a service, for example. I mean, Brian, with all that information, how did the project go? What was the impact of this for Sage?


Well, it went very well Freddie. Sage already had a strong customer retention rate but reducing churn by a further 2 to 3 percentage points, that was a huge success. One of the oldest questions in business is how do you make a great team better? Well for us behavioural segmentation was the answer. Keeping the customer at the centre of everything we do is critical, but understanding our customers better before we spoke to them and knowing what would drive them to action, that was the plan. I'll give you one amazing outcome was a double digit increase in percentage points converting first contact calls into committed renewals for future months. That was huge. Knowing which customers to contact as a prioritised list based on the segmentation we were given was a key driver to our success.


That’s amazing, these impacts are enormous, and it's great to hear you be so enthusiastic about it, particularly because the types of interventions that are recommended by PwC, they don't seem like these huge transformational things of writing up battle cards, and prioritising which customers to target and so on, but the use of data and those new techniques means that you can have these enormous impacts, without necessarily the same enormous level of investment. For me, whenever I hear about behavioural economics, that's always the power of behavioural economics, knowing which small changes to make to really drive that value.


That's exactly right, Freddie. This is really showing how behavioural economics and the applications of it is evolving over time. Several years ago, people were just saying, sprinkle a few nudges and see what happens, now it's using all of this data to drive a whole meaningful series of changes to drive some really powerful impacts at speed.


Sadly, that's all that we have time for, for this episode, but thank you so much to our wonderful guests Suresh and Brian, it's been great having you on. It's clear that behavioural economics is only going to become more and more important for businesses going forward. It's been really exciting to see the work going on in this area already.

As mentioned at the top of the show, please check out the episode description for a link to our previous behavioural economics episode. There is also a link to the PwC behavioural economics site, where you can learn more about how PwC helps clients to use behavioural insights to improve decision making and drive value. As always, if you like the podcast, please make sure to subscribe on iTunes or Spotify to get notified of future episodes. Thank you for listening.

Contact us

Follow us