aLook Analytics App

Getting actionable insights from data is usually more discussed than actually implemented. In order to succeed in this task, you need to combine three completely different worlds. Data, analytics and business. Practically, it means creating a team that consists of someone who knows the data, someone with the relevant analytical skill-set (call it data science, machine learning or predictive modelling) and someone with the domain knowledge. These people often speak different languages and use different tools.

Thanks to Keboola and the new aLook Analytics app, the main integration and collaboration issues are gone. The beauty of the solution at hand lies in a simple integration of custom analytics into the standard data processes. All the issues around data processing, data transfer and model deployment have been already sorted out, and therefore the primary focus really is on solving the business problem. No middle-man needed. Your data guy will deal with data processing, our data scientist will train the best possible model in R and finally your business person will make sure that you will be able to make more money using this new information.

Predictive modelling embedded in data processes

The job of aLook Analytics is to provide the client with tailor-made predictive models developed in R that directly support their KPIs. Some specific examples of these models are:

  • Propensity models – predicting, which customers are likely to buy a product, start using a product, decrease their activity or even churn completely
  • Recommendation engines – providing a personalized product offer for each customer
  • Direct campaign optimization – models indicating who to target, when, with which offer and through which channel

We have expertise in building such models in various industries – retail banking and e-commerce, but also behavioral talent analytics and sport.

The setting step for the end-user of aLook Analytics app in Keboola Connection is very simple. It includes just mapping of input and output tables. Any other extra configurations need to be added only in case when multiple complex models are used in parallel.

All models are kept in our private repository on Bitbucket and their management is very easy. We can develop a new version of a model and switch it to production in no time.

If you want to give it a try, start by contacting us at or The process is fairly straightforward. After initial check-in of what the business problem is, we put together a solution plan, exchange a data sample to develop an initial model and after a few very quick iteration loops [days] we can deploy the model into your standard data processes to start acting upon it. It’s easy and fun. You will see :).