Data Science Led Insights

Data Science & Machine Learning

Developing sales and marketing strategies relies on uncovering the hidden, intricate patterns in customer behaviours, needs and motivations.

With the volume of data generated by today’s complex customer journeys, which can be overwhelming for the people tasked with analysising it.

Acrotrend’s Data Science and Machine Learning led insights services provide you with the capability to quick, dig deep into the data generated from multiple business systems. We empower you to apply advanced analytical methods, data science techniques and Machine Learning approaches to generate the answers and hidden insights you’re looking for.

Customer Analytics Reference Architecture for Machine Learning

What are the Benefits?


Inform critical business decisions with real time, predictive insights 


Predict and score likely outcomes based on customer intents and behaviours

Identify leading indicators of success or risk in your business
Personalise and guide your cross channel customer experience

Get Results Faster

Accelerator for Machine Learning & Data Science
Amazon AWS select consulting partner
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Steps to Success

1. Discovery

Understand business objectives and agree on advanced analytics use cases.

2. Customer Analytics Pilot

Execute selected use case to deliver customer analytics outcomes and recommendations on business case development for ongoing customer analytics as a service initiative.

3. Customer Analytics as a Service

Managed services for executing various customer analytics use cases on set frequencies and experiment with new use cases.


Our data science and machine learning based customer analytics services are powered by our technology accelerators, including a ready-to-use library of data science models for customer analytics use cases, data preparation and analysis framework and data science implementation methodology.

We provide solutions to the following complex customer analytics problems:

Advanced Customer Segmentation based on a combination of customer demographics and behaviours, along with their key features and profile highlights

Customer Life Time Value Predictions based on historic purchasing trends and length of stay with your brand to create specific treatment plans for each customer micro-segment

Customer Churn Predictions based on past churn trends and current customer behaviours, with advice on intervention strategies per micro-segment to design retention campaigns

Recommendations and Matchmaking Engines, based on collaborative, content-based or hybrid approaches to design and drive your cross-sell and upsell campaigns

Buying Propensity Scores for specific products and brands, based on content and product affinities for you to design personalised and targeted campaigns

Business Hypothesis Modelling based on your current challenges, business questions and specific use cases, for you to experiment and learn more about your data and customers.

Location Analysis and ROI Prediction use historical data to identify similar locations or scenarios and predict likely outcomes for demand, footfall or utilisation so you can choose the most profitable opportunities or maximise efficiency.

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