Propensity Modelling

Propensity Modeling uses advanced machine learning algorithms to predict customer behavior. Propensity modeling is often critical in domains such as marketing, sales, e-commerce and CRM.

What is the Propensity Modelling?

The basis of propensity modeling is knowing whether a potential customer or existing customers will take an action under certain conditions. Propensity modeling means being able to predict who from your potential customers is most likely to buy, sign up for a service, respond to an offer, or leave. It allows you to target customers based on their possible behavior and focus on the right customer to promote the right product.

Challenges for Companies

Companies often deal with:
• Predicting customer behavior (like the probability of purchasing, leaving, returning to a campaign)

• Calculates the probability of acquiring potential customers. Modeling which customer segment will enter if a potential customer is acquired

• It aims to find out which customers are most likely to purchase a particular product and identify customers who are expected to reduce their spending.

Utility of Propensity Modelling

• You can take the action that will give the optimum result for the company by trying different scenarios on the trained propensity modeling.

• You can create targeted campaigns that increase customer engagement and provide better conversion rates.

• By using segmentation and propensity modeling together, it allows you to develop a more successful long-term sales strategy that responds to growth opportunities with proactive and timely cross-sell and up-sell campaigns.

Why do you Choose Trendify?

• Since not all segments have high propensity to buy, Trendify aims to reduce marketing efforts for segments of visitors that are less likely to buy.

• Predict customers behavior, actions and choices using Trendify. Increase marketing campaign revenue by X% with minimal campaign cost by delivering products to the right customers.

• With the Trendify product, your customer retention and acquisition strategies will result in a faster and higher return on investment and will save your brand time and money in the long term.

Related Blog Posts
Eren Retail goes beyond borders with cloud-based data warehouse project

Our "Modernization of Data Infrastructures and Analytical Applications" Project, which we started with Eren Retail, was crowned as a Success Read more

Product Segmentation for Inventory Management

Product Segmentation is the process of the parsing products into separate groups relationally with robust analytics and machine learning algorithms. Read more

Litigation Classification

Litigation Classification uses advanced machine learning algorithms to predict, if an insured person, who had an accident, is going to Read more

Trendify

Trendify