Product Recommendation Interpretation
Enhencer makes it unprecedentedly easy to analyze and predict customer journeys and customer behaviors by providing pre-defined templates for the whole process.
This is the Product Recommendation dashboard. It packs a handful of meaningful insights.
- Product Category: The Topmost drop down shows the list of product categories present in the data and the dashboard is the corresponding results of the chosen product category.
- Customer List: The table at the top left shows all the segments of customers that Enhencer automatically segments according to their likelihood to purchase a product from the chosen product category.
- Affordability Graph: The graph on the right shows automated segments of customers by their average basket size. This is very insightful since divides the customers according to their affordability. Segmentation using budget constraints has its own perks. It's not enough to predict a person is interested in buying a new phone. If you recommend an expensive phone to a customer with a lower budget then the recommendations are very likely to go to waste. Therefore, by using this sort of segmentation our recommendation algorithm decides which product is recommended for a given category and segment.
- Model Performance: The proportion of customers for marketing campaigns is a very handy tool that shows how well the model can uplift your purchase propensity for the product category. To put it simply, out of all the customers reaching out to 50% of the customers with the highest probability of purchase can lead to 1.65 times more sales than usual. Let's bring another perspective here. When taking marketing actions one has to reach out to a fraction of the whole customer pool in order to sell more of the products than the usual case.
- Customer Targeting: This area shows the customer targeting options. Among all the customers’ users can choose a portion of customers based on their likelihood of churn. For instance; 50% of the slider means the top 50% of the most highly likely customers are chosen for a campaigning purpose. This means when taking marketing actions one has to reach out to a fraction of the whole customer pool in order to retain a major proportion of customers who were highly likely to leave.
- Export Results: First, choose the number of products from different product categories to generate as recommendations before the sliders. Category Recommendations will export all the category recommendations for the customers. Product Recommendations will export the recommended products for the customers.
- Cost/Revenue Projections: This area represents the cost of marketing campaigns if these customers are targeted and the revenue that would be generated if the churn customers are retained. This in reality is a rough projection of how targeting the right customer would benefit the marketing campaigns. Get API Code option can be used to connect and implement the Enhencer outputs to your local system/platform.