Can marketeers ignore AI and thrive?

“Artificial intelligence is that activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment.”

Without wanting in any way to dismiss AI, which can be incredibly useful in many different arenas like driverless cars, we believe that its role for marketers has been exaggerated. Indeed most of what we need is barely within the spectrum of technology normally defined as AI.

For most cases where marketers want to execute one to one personalisation, the area where AI could most appropriately be applied, the conventional propensity model is all that is required.

What is most often meant by personalisation is the means to carry out selections of customers for communications based on their expected response or their particular needs.

Here are some examples where personalisation is often used:

– Targeting apparently dormant customers (e.g. those who in fact have a high probability of being reactivated) with offers to reactivate them
– Making a relevant offer (e.g. based on customer characteristics that imply a higher than average probability of purchasing in a particular product category) of a specific item
– Responding to risk (e.g. predicting which customers are likely to cancel policies or stop ordering) so that they can be presented with good reasons not to abandon their policy or purchase

In each case a conventional predictive model can be built, using an historic set of customer data, where a target customer population can be distinguished from the remainder who have not evidenced reactivation, response, or reduced risk of lapsing.

The key point is that we are not asking for this kind of model to be adaptive to rapidly changing circumstances; instead it relies on past customer behaviour to inform what is likely to happen in the present or near future. And this is because human behaviour in most situations where we are reacting to propositions put to us by marketers tends to remain reasonably constant.

We have even tested propensity models on historic data going back four years and found them to work well.

However, to build and apply these conventional propensity models there are some essential requirements:

– a single customer view to provide the greatest possible depth of customer data
– the ability to update model scores each time new data about an individual arrives
– the availability of data scientists armed with tools like R, SPSS, or SAS

A typical predictive model will take the form of an algorithm which will attribute a probability score to each member of a customer base; we judge the success of these models by the extent to which these scores are differentiated from random in the way they can be used to predict customers’ behaviour.

Looking at a recent model we built for the reactivation of dormant customers, the top customer decile had an index of 330,compared to the bottom decile’s 17.

In another case, a model for product category preference had a top decile index of 601 and bottom decile index of 11.

For most of us marketers these results will be seen as providing a huge improvement on random and quite fit for purpose. However, the methodology used does not in our opinion qualify the models to be correctly described as AI.

If you would like to talk to us about developing propensity models for you, or providing the technology for a single customer view, then please do email us back


UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.


Just how personal do you want to get?

There is a lot of interest amongst marketers in personalisation. And yes, we all like to be recognised for what we are. But we suspect that people are becoming wary of trivial personalisation or ‘personalisation lite’.

For example, recognising what I last looked at on a website is reminding me of the blindingly obvious.

However, telling me about a local retail event in the near future that is connected to what I was looking at on a website is much more likely to catch my attention.

And, for a full version of personalisation, understanding that I am a longstanding and loyal customer, rewarding me for my loyalty, and telling me about something that is actually of interest to acquire, really does hit the spot.

So, what is required to make this deeper level of personalisation actually work in practice?

Well, the first item needed is an effective personalisation engine. A tool that decides what kind of personal experience I should receive based on the information it knows about me. These engines work by the marketer setting rules or conditions which if satisfied mean that the customer will be sent a specific version of an email, or see a particular image, or offer on a website.

But next you will need to have joined together the online and offline data worlds. That allows the personalisation engine to know both that you are a loyal customer and that you are interested in a particular kind of merchandise or customer experience.

Most personalisation engines deliver ‘personalisation light’ because they ignore the history of your relationship with the company and just focus on what you have been browsing in the last 24 hours or so.

We have teamed up with Fresh Relevance (see www.freshrelevance.com) as our personalisation engine partner to allow you to give your customers full personalisation.

We manage this by sending Fresh Relevance a nightly feed of customers’ characteristics – factors like loyalty, spend, and long-term merchandise category purchases, so that these can be used in combination with their immediate online activities and behavioural triggers.

UniFida and Fresh Relevance can deliver in combination personalisation that really makes a difference.

To find out more, please email us suggesting a time that would be good for you to have a chat.


UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.


Are you losing customers to your competition?

Are you leaving the competition an open door through which they can capture your best customers?


Most organisations will protest that they are not, and a sizeable proportion of these will be wrong!

The reason is the gap that often exists between how customers expect that they should be treated, and the reality of what actually happens.

Let us give you some examples:

  • We know of one company that sends its entire customer file an identical email a hundred times a year
  • and a second that takes at least a month between recruiting a new customer and sending them a welcome catalogue
  • a third that gives up on customers who have not been active in the last two years
  • a fourth that can’t distinguish between a currently dormant but previously valuable customer who is browsing on their website, and an unknown punter
  • and a fifth who doesn’t understand the longer-term value provided by customers from different recruitment channels

To start to put things right we usually find that all areas of the organisation that have responsibility for some aspect or another of looking after customers need to put their hands up, and agree that things are not going as well as they might.

At this point, with luck, a consensus will start to emerge that something needs to be done to fix the problem; this will usually involve introducing some kind of technology that takes an holistic view of customers and how they are interacting with you.

If you feel the need to mobilise your organisation in this direction, and make it properly customer centric, then we are here to help.

For a start we can offer you a free copy of our short and readable book ‘The Marketers Customer Data Platform Resource Book’; to be sent this we just need you to email us back with your postal address. Alternatively, simply sign up for our mailing list and we’ll send you the download link.

And we would welcome the opportunity to have a chat; just give us a call on 0203 960 6472 and ask for Julian Berry. He is here to help.


UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.