It is a form of data mining that looks at understanding how the customer behaves, predicts future actions and personalizes business interaction, enabling the company to attract a customer by providing particularly relevant content.

The main aim of user modeling is to find out the intention of the customer, look at their background, past activity and create a profile. Machine learning lends itself well to this type of activity but there are several different methods by which a user profile is created:

Search engines & Recommender systems – these are often used on social networking and present content and suggestions that the user can interact with. These user profiles are then used to create a relevant news feed on platforms like Facebook or Twitter or to enable stores like Amazon to recommend other products based on past purchasing behaviors.

Product or Knowledge Management – this aims to look at how a product is used, what needs improvement and what the users particularly like in order to target marketing appropriately.

Digital Marketing – also called Ad Tech, this creates user profiles to form a marketing campaign, then looks at how this was received and who interacted with it. This then leads to an adjustment of the original customer profiles.

Shopping Assistants – these are used in eCommerce to improve customer experience but they also adjust the service by looking at user preference and using this information to increase the likelihood of sales.

User modeling for healthcare – user data and health records can be combined for healthcare facilities for diagnosis and treatment. They can be used to collect health information, make relevant suggestions, create scenarios for simulating treatment and looking at outcomes. However, they are limited by potentially inconsistent patient data and the speed of healthcare developments.

Which User Modeling Approach is Appropriate?

There are 4 main approaches to choose from and each has its benefits; use case scenario would be the deciding factor for each.

Static User Modeling – information is gathered but not modified. Things like profiles for image boards and blogs commonly use this.

Dynamic User Modeling – information is updated over time and can include multiple sets of data. This is often used for digital marketing functions.

User Modeling via Stereotypes – this does not produce individual profiles but relies on generalizing from key characteristics. As new information arrives the stereotypes can be updated and it is useful when information does not need to be too personal. It also helps companies comply with the European General Data Protection Regulations by removing personal identification information.

Highly-Adaptive User Modeling – this gathers as much information about a user as possible, however, it is likely to become more and more unpopular in the face of increasing privacy concerns.

To conclude, successful marketing means knowing your audience and making sure you pick the right model for your own business. This will make a huge impact on outcomes when looking towards finding and converting new leads.

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