MIM Solutions develops algorithms to automate the calculation of behavioral clustering based on ML.
Our ML experts have developed a unique tool called Insight.MIM, which performs automatic behavioral segmentation of clients mainly from the broadly understood e-business and banking industry.
Insight.MIM performs fully automated behavioral segmentation of your clients. Profiling customer behavior based on their actual behavior, it provides an in-depth analysis of customer groups. This allows you to identify the current and future needs and interests of your customers. Thanks to the ML algorithm, we show how the segments change over time. Additionally, as part of the service, we recommend a set of products for each customer and define the segment of each new online user using our API.
In today’s digital world, understanding customer behavior is the key to success. When a brand speaks the language of the target audience, it resonates and increases brand loyalty.
There is a strong business case for using behavioral data in digital marketing, as it offers marketers granular behavioral insights that can help to create consumer segments that align a target audience with brand attributes. Businesses can then build clusters of consumers with similar attributes, and focus marketing efforts on the most promising segments by personalizing products and services and designing messages that connect with the target audience. When a brand speaks the language of the target audience, it resonates and helps increase brand loyalty.
Behavioral data can be developed by analyzing people’s core personality traits. Comprehensive insights about customers’ personalities, values, habits and preferences, can then help marketers set their strategy while understanding customers’ behavior on an individual level.
A typical application of behavioral segmentation is the personalization of the marketing message by online stores. For example, a grocery store can prepare a different newsletter for a partygoer, another for a housewife and another for a person buying organic products. For this purpose, the store has to solve two problems – identify the types (segments) of users and assign each user to a given segment. Until now, this type of segmentation was created with a very large participation of experts and required a lot of human work.
Thanks to our system, companies will get a tool that extracts user segments automatically on a mass scale, without human intervention. It is an absolutely innovative way that saves the company’s time and money, and above all, gives an in-depth knowledge of the actual customer behavior.
Thanks to the information provided by our system, a company is able to significantly improve the methods of communication with the client and improve the quality of content and offer presentation.