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more effective cross-sell, upsell, and offers

The secret to higher sales at higher margins in e-commerce apps is not a secret at all. More effective cross-sell/up-sell, and better optimized offers are techniques employed by all major e-commerce powerhouses. At the core of these techniques is:

Pre-AI Approach:

rule-based segments

The what/who/when/how-much of targeted merchandising is often solved by segmenting users based on manually crafted rules and building offer pairings based on domain knowledge. For instance, an offer rule could look like:

Rule-based segmentation is a powerful tool, particularly for early e-commerce apps, as it allows product owners to incorporate their domain knowledge into the offer system. However, as the user base and app complexity grows, the rule systems tend to mushroom into unmaintainable tangled spaghetti, significantly limiting the opportunities for more complex and data-driven targeting.

Better with Haro:


With Haro, the what/who/when/how-much of up-sells, cross-sells, and offers can be determined by predictions based on user behavior. A Haro-driven offer would look like:

This single prediction-driven offer can generate personalized and optimized offers for every single user, and is more powerful than hundreds of hand-crafted segmentation rules.

By unchaining your app from the guesswork of rule-based cross-sell/up-sell and intuition-based offers, Haro enables your app to have higher sales at higher margins.

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