Machine Learning Models

Anticipate your customers’ next move using machine learning models.

Predict the future,
using your data

Machine learning modelling is an analytical technique that allows you to explore large data sets by analysing smaller groups, observing their patterns and intelligence. Decisions on these sets can scale to the rest of the data and make inferences about patterns of behaviour.

Use modelling to predict what your customer needs next, or use what you know about one customer to build a better picture of another. Modelling can help you decrease churn, improve sales, and build a better relationship with your customer. Not to mention the insights it can offer when business forecasting.

Analytics modelling in more detail

Let us explain how it works

Identifying patterns and intelligence in your data is important because it can help you understand the cause of customer behaviours. Once you know the causes, or at least the indicators of a certain type of behaviour before it happens, you can do something about it.

Models can generally be put into these four categories:

  • Descriptive Analytics models, which describe what has happened in the past
  • Diagnostic Analytics models, which help you understand why things are happening
  • Predictive models, which look to predict future outcomes
  • Prescriptive analytics models, which use simulations to determine an overall goal

Our experts will be happy to recommend which modelling techniques would be best for your business goals.

Modelling is a tool which helps identify important characteristics within large data to make actionable decisions which can ultimately improve ROI. This can be through:

  • Optimising customer journey programs that generate longer tenures and identify where you could save on cost.
  • Enhancing segmentations with varied data bringing statistical analysis to back results and decisions.
  • Identifying prospects that are likely to be interested in your products and services through profiling.
  • Developing targeting models that identify customers who are most suited to cross-sell opportunities.
  • Track behavioural patterns that lead to customer churn, enabling you to be proactive in your retention strategy.

Our team of experts can build statistical models in FastStats, “R”, Python, SQL or SAS.

Useful Resources

Using Machine Learning Models for Better ROI

30 Jun 2022

It’s one thing correctly storing, processing and managing your data. But how do you translate that to…

Euler Achieves Microsoft Azure Gold Status in Data Analytics

31 Aug 2021

We’re delighted to announce that we have been awarded gold competency status for our expertise in data…

Case study
The Royal British Legion

22 Nov 2021

The Royal British Legion came to Euler to find new ways of using their data to reach…