Closed Beta: This capability is currently in Closed Beta and may not be available to all customers. For information beyond this article, please reach out to your Customer Success Manager.

Product or Game Affinity in Target Group Discovery enables marketers to build precise Target Groups based on predicted customer interest in a specific item or game. This approach helps marketers target customers most likely to engage with or purchase a particular product, optimizing campaigns for better performance and relevance.

Product or Game Affinity introduces a different approach to segmentation. Instead of starting from KPIs like lifecycle stage or purchase behavior, marketers can start from a specific product, game, brand, or category, and identify the customers whose behavior is most closely aligned with it. This enables more intent-driven targeting, grounded in actual customer interactions.

How It Works

Predicting Product or Game Interest
AI analyzes historical behavioral signals, including:

Past purchases
Interaction frequency
Category affinity patterns
Engagement with similar products or games
Recency and intensity signals

Using this data, the AI calculates a predicted interest score for each customer, reflecting their likelihood to engage with or purchase the selected product or game. This data empowers marketers to target the most relevant customers with confidence.

The affinity score represents how closely a customer’s behavior aligns with the selected product or game. It is not a purchase probability, but a relevance ranking, helping marketers identify which customers are the best fit for a campaign.

The model leverages different types of behavioral signals with varying strength, such as product views, add-to-cart actions, and purchases, with purchases being the strongest indicator of affinity.

Affinity can be calculated at multiple levels, including product, brand, or category, allowing flexibility depending on data availability. For newer products with limited data, the model can rely on broader signals like category or brand affinity.

Group Size Slider

Unlike Deposit/Purchase Affinity, which segments customers into two predefined groups, Product or Game Affinity uses a group size slider. This slider enables marketers to adjust the optimal audience size based on predicted affinity levels, from high to low interest. Optimove AI suggests an ideal group size, but clients can customize it based on their campaign goals. Whether they want to target a narrow, high-conversion group or expand their reach to include more customers with medium or lower affinity, the slider offers the flexibility to do so.

Marketers can use this to select a top set of customers based on affinity, for example targeting the top few hundred or thousand customers most aligned with a product, depending on campaign constraints such as budget or channel capacity.

The goal of adjusting the audience size is to define the right Target Group for improving campaign effectiveness, such as refining targeting and offers.

Key Consideration

After the Target Group is created and saved, the customer list is not automatically recalculated with each campaign execution. This tool is designed to be optimized for ad hoc campaigns.

Use Cases

Decrease Churn Risk by Targeting Customers Likely to Engage with a Specific Game

A marketer is focused on reducing churn risk by targeting customers who are most likely to re-engage with a game like Blackjack Live. With Product & Game Affinity, the marketer can easily identify high affinity customers based on their past behavior, ensuring the campaign targets those most likely to play the game. This approach drives session starts, repeat gameplay, and monetization by focusing on the most engaged players.

By combining game affinity with churn risk, marketers can target customers who are at risk of leaving but still have a high likelihood of engaging with the game. After creating the initial Target Group from the Target Group Discovery page, marketers can refine the targeting to include customers with churn risk as a key segmentation criterion. They can then add more layers, such as engagement frequency or spending behavior, ensuring that the campaign targets the most relevant and high-value customers with tailored offers. This powerful combination of predictive targeting and churn mitigation enhances engagement and drives retention.

Increase Conversion Probability for New Leads

A retailer faces the challenge of converting new leads who have engaged with the brand but have yet to make a purchase. Instead of sending broad promotions, Product or Game Affinity enables marketers to identify leads who are most likely to purchase a specific product, like Wireless Headphones, based on their predicted interest.

Using Product or Game Affinity, the marketer can initially refine the targeting to focus on new leads with high predicted likelihood to engage with a specific product they might like. By targeting these leads, marketers can send personalized incentives, such as welcome offers or exclusive discounts, to increase conversion rates.

Marketers can further enhance the Target Group by adding additional criteria like browsing behavior or similar product interests, ensuring they are reaching the most relevant leads with the right message. This AI-driven approach increases the chances of converting prospects into paying customers, ultimately boosting sales and customer acquisition.