How to better engage the user on the website and what data-driven method can be used for that?

To properly engage or encourage a user to take action, you first need to identify your audience, analyze the types of users the site reaches, conduct analyses for each user type to fully understand their needs, and, as a result, develop a strategy for encouraging the user to perform the desired actions and achieve the goals set for the selected user profile.

The interpretation of ‘goals’ can vary greatly: from subscribing to a newsletter, increasing time spent on a page, deepening scroll depth, or purchasing products or subscribing to digital content. For each type of user, it is necessary to define a ‘real’ goal, meaning one that can be realistically achieved based on their actions on the site.

There are many different evaluation models for identifying users that work based on collected user data (clicks, pages viewed, visit frequency and duration, etc.).

An effective method for identifying users is the use of the RFV model, which tracks several criteria at once and assigns the user to the appropriate group. User groups can be either custom or generally accepted.

What is the RFV model and what data is it based on?

The RFV model is a method of segmenting users based on three metrics:

• Recency — the time since the user’s last purchase or article read.
• Frequency — the number of purchases or articles read by the user over a specific period.
• Value — the total amount spent or the total time spent by the user over a certain period.

This model allows businesses to assess the value of users, identify their behavior, and determine which users are the most loyal, active, or promising. The RFV model helps understand which clients have the highest value to the business and require more attention, enabling more efficient resource allocation and maximizing profits. The model is used to optimize marketing campaigns, increase conversions, improve customer retention, and set priorities for working with different user groups.

At this stage, we already know how to identify a user, but the question arises:

Where/How can we effectively use the obtained results?

Results from the RFV model can be applied in various business areas to improve user interaction and enhance marketing strategy efficiency. Here are a few examples of where and how they can be applied:

1. Identification of Loyal Users: Identifying users who frequently buy or spend significant amounts allows for the creation of special loyalty programs, personalized discounts, or bonuses for them.
2. Activation of “Dormant” Users: Creating special offers for users who haven’t made purchases for a long time to re-engage them.

3. Priority Service: RFV model results help identify which users are most valuable to the business. This allows for providing them with priority service, such as expedited delivery or a dedicated support line.

4. New Product Development: Analyzing the behavior of different user segments helps better understand their needs and requirements, which can aid in the development of new products or services.

5. Growth Strategy Development: RFV analysis results assist in decision-making regarding expansion into new markets, product assortment improvement, or pricing policy changes.

Thus, using the RFV model, users can be segmented into different groups, such as:

• “Valuable Users” (those who buy frequently and spend large sums),
• “Potentially Valuable Users” (those who buy but do not spend large sums),
• “Users Who Are Moving Away” (those who haven’t made a purchase for a long time),
• “New Users”, etc.

The size of the segments themselves can also be adjusted by assigning them unique characteristics, such as:

• Additional demographic characteristics (age, gender, location, etc.)
• Behavioral characteristics (visitation, duration of stay, click frequency)
• Time frames (periods of user activity or inactivity)
• Product type or category (grouping users by the type of products they most frequently purchase, such as electronics, clothing, food, etc.). This allows for more targeted offerings.

By adjusting characteristics, more precise segments can be created that match their business goals and strategies, providing more effective targeting and personalization.

RFV model calculations can be run in different modes: from monthly updates (for monitoring changes in user loyalty) to real-time calculations (for integrating results with the site/app).

The most effective use of the RFV model is the direct integration of its results with the website/application (integration via third-party services). This allows for changes and personalization of the site/app structure, including or excluding special functions to encourage selected user segments to take action.

At People More, we specialize in creating comprehensive analytical models (including RFV models), from collecting the necessary data and developing the model to integrating the model results with required third-party services.