My own definition of retention marketing is:

“Retention marketing is the art and science of converting someone twice without the pain and cost of acquiring them twice”

It’s not just about getting someone to buy again (or whatever the conversion action is) but using what you know about them to improve the chances of converting them again without having to go through the whole acquisition process again.

But somehow “retention optimisation” doesn’t quite sound right and I prefer to think of it in different terms. What we are trying to do once we have acquired a customer is to optimise their lifetime value and so I tend to think about this process as “customer optimisation”. How can I optimise the return on the investment that I have already made in acquiring that customer in the first place? What data, tool, technologies and processes do I need?

Classically we tend to think of email when it comes to retention marketing channels and used well it can be a powerful retention tool. However once you have transacted with a customer there are multiple touch points that can be used to increase the chances of them doing business with you again; the call centre, the store, the site etc and what is required is a view of the customer that straddles these multiple channels. This much easier said that done, especially for organisations with legacy systems that have been developed over the years. Often data on customers can sit in a number of disparate systems and it can take a huge data cleaning and integration effort to get the data into shape and fit for purpose.

So having good quality data is important but what you then do with it is pretty important as well. As I said earlier, what we are trying to do here is to increase the likelihood that the customer will transact with us again without the cost of repeated acquisition. What we want to improve is the “expected customer lifetime value”. The way to do that is to be in the right place at the right time by being relevant and timely.

Being relevant is about sending out the right kind of messages, whether it is in an email or on the site. Segmentation is a way of increasing relevance. Personalisation is a way of increasing relevance. These techniques, which may be manual or automated, are leveraging the insight that you have about someone to present them with more appropriate and relevant. These techniques do not necessarily have to be sophisticated to be effective, and in the early days of your customer optimisation programme being over elaborate can undermine the process. Remember, a key component of any optimisation programme is to have the ability to execute. That means that you need to ensure you have the processes and tools in place which allow you to act, measure and react.

For example, if you decide that you want to improve relevancy by having a segmented email marketing programme instead of having a single email that goes out every month then you’re probably on the right track. However, if your resources and processes are geared up around just sending out on version of one email every month, then it’s going to be a major step up to implement a segmented email marketing programme whereby different groups of customers will get different versions of different emails at possibly different times. You will need to have a more sophisticated email systems that can handle segmented email marketing programmes, your database will need to be more extensive and robust, you will need to invest in more copy and creative material and your processes will need to be more rigorous.

So it will pay to walk before you start to run and to look for the low hanging fruit. In terms of customer optimisation, I think that the most critical point is getting someone to make the second transaction. Generally there is a “friction curve” that needs to be managed. The steepest part of the curve is in the early days of your customer relationship. The more times that someone has transacted with you the more likely they are to do it again in the future; the friction isn’t as high. Getting them to repeat for the first time is the hardest part. So this is a special case in the programme and is when timing can be vitally important. The time when people are most likely to transact with you is just after they last transacted with you, so for this special group all about “recency”. The time to get them thinking about the next transaction is just after the first.

Ultimately profitable businesses are built on profitable customers and repeat customers tend to deliver the majority of the profit. Acquisition and conversion optimisation are essentially components of a success marketing programme but optimising long term customer value is key.

In fact, that’s not quite true. I know what engagement is (everyone does) but I don’t know what it means or how to explain it, let alone how to measure it. In the context of digital marketing I think it’s one of those words that everyone understands but can’t define. In that respect it’s similar to loyalty. Everyone understands the concept of loyalty but there are all sorts of ways that it gets defined (attitudinal loyalty, behavioural loyalty etc) and there are even more ways that it gets measured.

The web analytics blogosphere has been full of articles and comments on the whole subject of engagement over the last month or so with titles such as:

“Engagement” Is Not A Metric, It’s An Excuse”

Engagement is not an excuse, it’s a KPI

Is “Engagement” Physical or Emotional?

Customer Engagement Is Measurable

As you can see, there’s been quite a debate with a range of different views being expressed. On the one hand there are what you might call the “behaviouralists” who believe that engagement can be defined and encapsulated in simple site metrics or an equation to produce a complicated “engagement index”. There are others who hold the belief that engagement is a state of mind and therefore can’t be measured by using anything as blunt as clickstream data. So after some consideration, where do I sit in this debate?  I’ll tell you; Firmly on the fence!

For me (and that’s the point) engagement is a personal condition. It’s about me, it’s not about you. Engagement is all about the context that I am operating in. I can be on a site one day doing a series of activities, interacting in a certain way and feel “engaged”. I can also be there another day doing pretty much the same thing but not feel so “engaged”. The difference between the two sessions is more about me, my sense of expectations, what kind of day I’ve had and so on. It may be nothing to do with the website. Having said that, of course it is useful, if not essential, to define and measure the volume of valuable behaviour on your website and even to use those measures to predict future outcomes.

So, I do wonder whether this notion of engagement is actually very useful. If we can’t describe it or define it, what can we do about it? And does it actually add to what we already know or want to know. From the behaviouralist’s point of view, if we believe that there are sets of valuable behaviour that lead to beneficial outcomes, why dress this up and call it engagement? Why not just have a VBI (Valuable Behaviour Index) instead of an Engagement Index? At least then we know what it is and what it means. The new Score product from WebTrends is a way of doing just that – identifying behaviour that is considered valuable, giving it a subjective value and then tracking it.

And from an attitudinal perspective, we already have loads of measures that help us understand the visitor experience in their terms. Measures such as customer satisfaction, propensity to return and propensity to recommend have been around for ages. They are all measures of what you might call “engagement”, so do we need another one? I know what it means when someone says they are likely to recommend the site their friends. What does it mean though if someone says they were “fairly engaged” with the site?

I started writing this article feeling somewhat inadequate. I’ve been reading lots of lengthy and well-written blogs and articles on this whole subject and I wondered what I could add to the debate. However, I felt that the question “What is engagement?” was one that I had been avoiding for too long. The answer is still “I don’t know”. But now, nor do I really care. I don’t think that having a definition of “engagement” and then finding tortuous ways to measure it really adds anything to our understanding of how to improve the visitor experience at the moment. At a time when the online experience is still quite often a poor experience, I think we already have enough tools in our toolbox to help us figure out what needs to be done.

Following on from the tricky issue of looking to measure customer loyalty comes the issue of what to do about it. If you can look at the different aspects of customer loyalty through different metrics, then the question is: was do you do with this information? How do you act on it in a way that positively impacts on customers’ loyalty? How can you accelerate the building of loyalty when it’s in its ascendancy and how can you manage it when it’s beginning to decline?

On my customer loyalty dashboard I’m going to have a mixture of metrics. Some of them are going to be more strategic in nature, potentially even Key Performance Indicators (for example, a customer satisfaction index) and some of them are going to be more operational or tactical (such as recency or frequency measures). The strategic measures are going to be telling me how I am doing over the longer haul and the tactical measures are telling me what I need to do in the shorter term. The tactical measures are more likely to be behavioural metrics as, generally speaking, it’s easier to observe, react to and influence customer behaviour than customer attitudes.

RFM (Recency, Frequency, Monetary Value) analysis is often classically used to manage retention programmes. Customers are segmented according to how recently they have transacted, how frequently they have transacted and their value to the business. These segments can form the basis of differentiated retention and communication programmes depending on which segment the customer sites in. Customers who are in the top segment for recency, frequency and monetary value display loyal behaviour and are the ones that you don’t want to loose, and will probably deserve some special treatment.

A particular case of the RFM approach I think is the new customer, ie the customer who has just transacted for the first time. They’re a special case. It’s possible or even probable that you may not have made any money on them, you need to get them to transact again before you start to recoup your marketing costs. They are also at the steepest point on the “friction curve” which is the amount of effort required to get them to transact again. Retention is like momentum, once you get them started it’s easier to keep them going. In the case of the new customer, if you can get them to transact again, then they are more likely to transact a third time, and then a fourth and so on. So, customer retention, like conversion, is not one process but it’s a series of mini-events designed to move a customer from one state to the next.

The key advantage of RFM is its simplicity. It’s easy to do the analysis, create the segments and put together some specific customer communication. However, there are a couple of issues with it in my opinion. First of all, it’s assumes that people that behave the same on these dimensions will respond the same to particular communications. On it’s own it doesn’t help with the crafting of the retention marketing message. If you think of a multi-category retailer for example, different types of people will be buying different types of products. They may have similar shopping profiles but interested in completely different things. So, as well as knowing when to intervene, it’s also important to know how to intervene – what’s the trigger going to be?

The other issue is around recency. If you have a regular interaction in some way with your customers then by the time that you notice they’ve not been around for a while it may be too late. By the time they cancel the service, or stop visiting the site or whatever it is that means that they have stopped doing business with you, they could already be a lost cause. They might have stopped being attitudinally loyal some time earlier but it has taken a time to get to the point of being behaviourally disloyal.

So, we need to be able to anticipate changes in customer loyalty rather than just react to them. In many cases ,customers can give off signals or clues that their loyalty is shifting for the worse. They may change their patterns of behaviour, they may start calling customer services more often, and they may stop returning your calls. These are all indicators that changes are happening.

The role of predictive analytics in customer retention marketing is to give the marketer a heads up warning that something might be up with a customer. Predictive models look to identify customers who may be at risk based on the changes in other data. With all predictive models they will never be 100% accurate but if they are good enough they can at least reduce the risk of customers taking their business elsewhere. The inputs that go into these models will of course be specific to the individual business and the data that is available.

So, as markets become more competitive and retention becomes a more important facet of the digital marketer’s job description, it’s time to start thinking about customer loyalty seriously. What does loyalty mean in your business? Does it mean anything at all? If it does, how are you going to know if you’ve got it? What are the relevant measures? How can you impact those measures positively?

Lot’s of questions but they’re not necessarily difficult ones. The key thing I believe is to think them through carefully and build your customer loyalty dashboard accordingly. As the saying goes “Be careful what you measure, because what you measure is what you will get”.

At the same time, conversion optimisation is gaining momentum. There has been a lot more focus on what actually happens when someone gets to the site over the past couple of years, spawning the growth of web analytics and multi-variate testing services. There is still probably a lot of mileage to be gained for most organisations through site improvements but generally the process is underway.

However, from the work we have done with a number of organisations it seems to me that companies generally heave a sigh of relief when they make the sale as if the job is done. Having been through the effort of creating awareness, acquiring the traffic and converting it on the site, the important asset that has been created, ie the customer, is then neglected and the organisation sets off in pursuit of new ones. The result is most customer databases are littered with customers who have only transacted once. For more, the definition of retention marketing is converting someone twice without having to acquire them twice. You don’t want to have to go through all that heavy lifting again!

So as part of this increased focus on retention marketing there’s going to be an increased emphasis on customer loyalty. Over the next few weeks I’m going to be taking a look at issues around customer loyalty such as “what is customer loyalty?”, how do you measure loyalty and how can you use data and insights to manage the retention marketing process more effectively.

What do we mean by loyalty?
What do we mean by customer loyalty? For example is it a state of mind or it is a set of behaviours? How can we really establish whether a customer is loyal or not? In our multi-channel world is the notion of loyalty even valid or useful?

These are tough questions that have been debated for many years and, of course, there are arguments on all sides. If you look up the definition of loyalty is usually describes loyalty as being a “quality” which suggests it’s more attitudinal than behavioural. However in our marketing world we’re generally interested in outcomes, like someone buying something. But are behaviours actually always the best indicators of loyalty.

As part of my MBA I did a lot of research into store loyalty amongst supermarkets in the UK. I measured how much people spent in each of the grocery stores that they shopped in over a 12 week period and created a metric to measure how loyal they were to various retail brands. What I found was that most people spent most of their weekly shop in one supermarket. So you could argue that most people seemed to be “loyal”. But what is the context to this behaviour? Are they only loyal to that store because it happens to be the closest or the most convenient? Would they in fact rather shop somewhere else if it was more convenient?

Another example can be found in financial services. People can appear to be behaviourally very loyal to their bank. If I look at my own behaviour I have had my main account with my bank since I was a student. So I must be very loyal, right? Well if I was asked whether I considered myself to be a loyal supporter of my bank I would say that I wasn’t. I’m behaviourally loyal but I don’t consider myself to be a loyal customer. The problem is that the pain of switching accounts to another bank is just too high at the moment. There are inertia effects at work and there is a great deal of inertia in financial services.

Of course, the internet is a technology that can break down inertia. There is the famous saying that “your competitor is only one click away”. I can now choose to get my groceries delivered by whichever supermarket will deliver to my area. I am actively encouraged to use shopping comparison sites to get the best deal from a selection of stores.

However the technology can also create barriers to switching which means for example, that our household generally get’s all it’s online groceries from one supermarket chain because all our orders are stored there. Similarly Amazon get’s a significant chunk of my expenditure in certain categories mainly because it’s so easy to buy, not because they are necessarily the cheapest.

So how do we measure customer loyalty? Do we look at behavioural indicators or should we be concerned about what our customers think of us? Or both? This is something I’ll be looking at next time. Till then…