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
adam@alookanalytics.com or
kbcapp@alookanalytics.com. 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 :).
