In one of the recent articles, we’ve covered how self-learning search works and uncovered how search optimizes order and suggests more relevant items for a visitor. It’s a very efficient technique that brings interesting items to the visitor first. But Kea Labs search makes a step further – it focuses on your profit first.  It ranks products based on the chance of the purchase and the potential profit of the transaction. Let’s unveil some of the algorithms behind it and learn how search can increase profit.

Kea Labs combines various calculated metrics to keep the balance between the profit and the chance of the purchase. It is not a straightforward task, and the importance of each coefficient is getting tuned based on your historical sales performance.

How smart search can increase profit

Shortly speaking, profit is the difference between earning and costs. On the level of an individual product, we may look on the following formula:

margin = product price – product farm price

But it will be incorrect to pull only high-margin products on top. As search will be unrepresentative and prices may be higher than competitors have.

Furthermore, the search doesn’t keep relations between product margins. It’s very often when accessories have a huge margin, but the general item has a very low (and sometimes negative) margin. For example, a mobile phone and a suitcase or screen protection glass.

Having a low margin on the general product helps in keeping the price competitive, while the profit is coming from the accessories. Kea Labs profit-first search may detect relations between a group of products and smooth the way it pushes high or low-margin products.

Unfortunately, farm price is not available by default on many platforms, including Shopify, so please contact us if you need any help with exporting it.

Popularity and trends

Thanks to a product comparison algorithm used by Kea Labs Advanced Recommendations, Kea Labs Search detects popularity not only for individual items but also for a group of similar items.

As a result, Kea Labs Search detects trends and promotes even new, or not so popular items of the group. This solves the problem when new products lack visibility because no one has purchased it yet.

Trends automatically detects which group of products needs to have higher priority. For example, if a visitor searches for ‘jacket’ in winter, search detects the rising interest for warmer jackets and pulls them up.

Quality of content

It’s simple, but many stores are forgetting that search needs to know the quality of product content. One of the key goals of the search is to take the user’s attention and show attractive products. And the quality of content, like the presence of a picture or video, detailed description, product attributes, affects the impression. Search needs to evaluate the quality of the content and pull up the most attractive products.

Number of available products

Based on the historical transaction search evaluates an average number of bought items per product, and checks how many items are left. Based on this, the search may either push the product to be sold out or promote other alternatives. If the product is not available, it’ll have a higher priority than alternatives available for purchase or for preordering.

Your marketing goals

Algorithms are good, but no one better than you may know the goals of your business. Having control over the algorithms and the ability to implement your marketing strategy is vital. Kea Labs Search is totally controllable and it’s a powerful tool for your marketing team. We’ll cover the marketing features in one of the nearest articles.