Make me a match: How matchmaking in search can improve the sharing economy

Companies that have made a successful go of collaborative consumption — the concept of borrowing a product from or sharing it with peers rather than buying it — have done so by fostering trust in their users.  We use services like Uber, Airbnb and TaskRabbit because those startups have gone to great lengths to make providers of their services seem verified, trustworthy and responsible.

But what if they went one step further to match a person to you based not only on your needs, but your preferences and personality? Companies are exploring matchmaking as a feature that could make the experience of relying on a total stranger to serve your needs a bit more palatable.

Surabhi Gupta, an engineer for Airbnb, spoke on this topic during her talk, “Mastering Marketplace Matchmaking,” at the company’s OpenAir developer conference last Thursday in San Francisco. As Airbnb continues to improve its search algorithm, the company is working to better match hosts with guests, so both parties will walk away more satisfied with the overall experience.

A guest with allergies, for example, could filter potential rooms based on whether a host has cats.  The matching could  benefit the host as well: for example, someone who doesn’t like back-to-back bookings could request to be filtered out of search results for days before and after a confirmed booking.

Gupta didn’t say exactly when this type of ideal search will be made available to Airbnb customers, but the prospect sounds ideal — sophisticated search would make the service more efficient for both hosts and guests, and it’s likely that everyone will have a better time because of it.

But matchmaking doesn’t have to be limited to booking a vacation. It could help service providers develop a rapport with users. For example, ride-sharing services could prioritize drivers so those that you’ve rated highly before are more likely to pick you up. Or they could let users only select from drivers with hybrid vehicles.

Matchmaking can extend into more peer-to-peer collaborative sharing, as well, ensuring that users with similar schedules and interests can more easily swap items. That familiarity, enforced by repeated interactions, is likely to make the experience better for all parties involved, turning the service into a personalized ecosystem that better pushes users towards people they like doing business with.

This kind of sophisticated search is still just out of reach, though Gupta said in her talk that she is optimistic that it will be achievable in the near future. When it does happen, though, it could be a great way to put a human face on the collaborative consumption space.