Two-way marketplaces exist to create a match between supply and demand. However, these marketplaces are often inundated with new item submissions, which can lead to a couple of problems. Firstly, the data in these item submissions is frequently disorganized or irrelevant, especially from user-generated text fields. Secondly, when a supply-side user submits a new item, how do you determine who it’s relevant for and how they discover it? To successfully pair supply with demand, you need to understand each item the moment it’s submitted.
Simply put, gathering high-quality inventory data is the baseline for enhanced recommendations and high-quality discovery. The more you know about the specifics of the items that make up your inventory, you can use that data to start proactively recommending it to the right audience. That way,end users will find items they love sooner, leading to a better customer experience and higher conversion rates.
Over a third of consumers stop visiting websites that recommend items they don’t care about. (Source: Salesforce)
The consequences of poor personalization and discovery mechanisms are serious. . As more suppliers and items are added to your marketplace, the likelihood of customer churn increases, due to irrelevant item suggestions. 76% of consumers find it frustrating when a business has mediocre personalization (source: McKinsey), while over a third of consumers say they stop visiting sites that recommend things of no interest to them (source: Salesforce), which can have a devastating impact on conversions.
Look at your inventory with a critical eye and parse out the high-quality data tied to each of your items. Think things like size, color, category, and so forth. Once you do this, you can leverage the collaborative filtering technology of a recommendation solution much more efficiently in order to achieve the best results for end users.
Here are some tips to help you understand and prepare your marketplace catalog for enhanced recommendations and faster item discovery.
Doing this preparation prior to feeding the data to your recommendation solution will help you enable faster discovery of items that are most relevant and interesting to your users. It’s worth investing some time upfront so you can maximize your conversion potential right out of the gate, as well as prevent negative customer experiences.