We all know that customer analytics refers to the processes and technologies that give organisations the customer insight necessary to deliver offers that are anticipated, relevant and timely.

As the backbone for all marketing activities, customer analytics comprises techniques such as predictive modelling, data visualisation, information management and segmentation.

We also all know that when we have bought a pair of shoes online, we are also offered more shoes in the days after or even a refrigerator because that is what someone else bought as well. Clearly someone is missing the point here.

The importance of customer analytics

Customer analytics is becoming critical. Why? Because customers are more empowered and connected than ever, and becoming more so.

Customers have access to information anywhere, any time – where to shop, what to buy, how much to pay, etc. They want what they want, they want it now, and they want is as cheaply as possible. That makes it increasingly important to predict how customers will behave when interacting with your organization, so you can respond accordingly.

The deeper your understanding of customers' buying habits and lifestyle preferences, the more accurate your predictions of future buying behaviours will be – and the more successful you will be at delivering relevant offers that attract rather than alienate customers.

Offer the right product, at the right time, through the right channel, using the right message.

It is safe to assume that most companies have a certain inclination of how their customer behaves. This is mostly based on purchasing behaviour, app use or any other sort of historic quantitative data collected through the interaction between your customer and you. There is absolutely nothing wrong with that. But what if you could add a lot more to that?

Now what would happen if we could help you out with a real insight in customer behaviour?

A picture of your customer that would show their development, culture and profile.No, not a profile based on econometrics, purchase behaviour, time series, or some sort of categorization of customer relationships and their communities like so many use. We are talking about a real behavioural profile! (Like the one you probably encountered during your job interview).

Allow us to elaborate, our analytic engine has the ability to extract key data points from the interactions between you and your client or between user groups on social media or any variety thereof. By interactions we mean text (i.e. email, voice, social media etc.). Our analysis will then show you what sort of culture your client has developed, what level their development is at (from a soft skill perspective) and what kind of personality they show. We can show you the real behaviour of your client. Depending on your data we can give you up to 350 elements.

What would be the benefits for your organisation? Well, imagine that every marketing message with which you approach your client, is setup in such a way that it would automatically appeal to them.

Your chances of selling shoes together with a refrigerator would increase dramatically.

Can you imagine what a system like this would mean for your targeted content marketing, your customer engagement, - retention and - loyalty?

Let's talk!

Marc Peter Geytenbeek

Rob Agterberg

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