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How to Define Micro-Segments

We help our clients design relevant marketing strategies which optimize return on investment for each campaign. We do it thanks to a thorough knowledge of their customers’ needs, acquired using an advanced micro-segmentation methodology, based on the augmented analysis of internal and external data

Address the customer at the right moment, with the right message. Thanks to Machine Learning and automation, we identify micro-moments during which the customers are more likely to get in touch and engage with the brand. Then, we use micro-segmentation to address these different moments with a relevant and custom message, to allow the management of the customer relationship in real time.


Improve customer acquisition and loyalty. By leveraging internal and external data, it is possible to improve targeted marketing actions and therefore suggest relevant and custom content that is more engaging for customers.


Increase ROI per customer. We offer tools to increase our clients’ customer knowledge, to estimate the ROI of each customer and identify the products and services that could interest them. Pushing personalized offers to different customers, starting with the priority ones, enables you to significantly increase the ROI per customer.


Foresee the customer's needs. An in-depth knowledge of our clients’ own customers enables companies to anticipate their needs and to define a more relevant and efficient marketing strategy by adjusting brand positioning and adapting offers.

Our Work in the Energy Sector

Find out how we supported an energy leader in the development of a new customer micro-segmentation

As part of a customer knowledge-based approach which aims to design personalized offers and deliver an optimal customer relationship, we assisted a major energy company in building customer segmentation for each type of customer. Sia Partners offered a system composed of data scientists and experts in customer relations and energy in order to:

• cross-reference and enrich the client’s internal technical and commercial data, using open data

• compare expert opinions with statistical results

• formulate strategic recommendations on customer relations and on personalized pricing policy based on user behavior