Insights as a Service

10 May 2017

So, you are a marketeer in an organisation that has a Marketing Intelligence group. You have a model by which certain customers are marked out as high-potential customers for a particular campaign, but how do you actually know what it was that led these customers to be considered relevant? And how can you then get a better view of these high-potential customers in order to also tailor communications and propositions for the target group? Asking an analyst every time takes a lot of time, and their findings often pose new questions, which also in turn take time. Preferably you would like to explore it, slice it and dice it yourself to extract these insights.

We are seeing a growing trend of simple analytical questions increasingly being answered by the person asking them. This in turn results in the role of the analyst/scientist changing: in addition to modelling, it is also becoming their responsibility to enable marketeers to answer their questions for themselves. On one of our current projects for an insurance company, energetic marketeers are revealing an insatiable hunger for information. We developed a number of churn, cross-selling and up-selling models for this insurance company. Every model we build automatically feeds into a dashboard. This dashboard presents all the information that marketeers need to put together business cases and determine optimal selection sizes. The marketeer is now free to exhaustively compare all the customer characteristics of their chosen selection with the rest of the base in order to build up a good picture of their high-potential customers.

We have seen this dashboard result in:

• More confidence in the models as insights deliver greater tangibility and transparency.
• Optimisation of selection sizes as they can make better supported business cases.
• Time saved as marketeers no longer need to ask analysts for information and wait for it.
• More refined propositions and communications in place as there is more control over who exactly has been selected.

To give you an idea of how this works, we have built this dashboard with a simulated dataset on sauna users.