The product selection you feature in your app is essential to its success. Here, we'll share some insights we've gained on how to optimize this.
Let's start with what we're trying to achieve. The goal of launching a guided selling app is to help users choose the product that's right for them. Aiden is built to help you achieve that goal. However, having the right set of products in place can definitely help.
In many cases the perfect product advice is a strong 'best match' followed by 1 or 2 good alternatives. From a psychological perspective this really helps customers to make up their minds. It's easier to pick a clear winner than to pick the best option out of 10 decent ones.
So, how can we optimize our product database to attain this goal? There are a couple of ways to go about this:
Not every single product within a category needs to be included in your app. If you have 200 products in an app with just a few questions and answers, this will lead to a lot of good matches in a lot of cases, with very little distinguishing factors between these products. "That's great!" you might think. But, actually, it isn't. Because we're not solving the product overload that customers experience in webshops, which stops them from buying.
So keep this in mind when selecting the products you want to feature in your application. The goal is to deliver a well-differentiated advice to every single customer. Do you really need your full product catalogue to do this, or can you cover the most likely advice scenarios with a subset of products?
This is a game of trial and error: simply exclude/include the desired products in your feed manager or CSV file. It's best to start with a small batch of products, match them in Matching, then run through a couple of customer scenario's. Do you get the feeling that the product offering isn't optimal in some scenarios? Add a few more products to your data source until you reach the sweet spot.
Added benefit: it's faster to match a small number of products than a large number!
Some catalogues may feature the same product in different colors, quantities or sizes. For instance: