An Advanced Search Algorithm For Collaborative Marketplaces


An Advanced Search Algorithm For Collaborative Marketplaces photo

Which transaction workflows are best for service marketplaces?

Collaborative marketplaces, from big beasts like Airbnb to a local site for river boat rentals, has at its core a search and filtering engine to present the potential customer with the most relevant results based on his or her needs. But how do we ensure that this potential customer sees the results most likely to lead him or her to make a transaction, especially when the search, based on the strictly-defined filtering criteria the user has set, does not yield enough results?

To help answer this question, Roobykon Software have some insights from the team at Cocolabs, who created the awesome Cocorico engine for on-demand and service marketplaces – and made it available open source.

The majority of startups that decide to base their implementation upon the Cocorico engine naturally want to maximize the number of search filters available to their users, in order to help them obtain the most accurate possible results. But this is a mistake. What has been true in the economy of the web as we’ve known it so far with ecommerce doesn’t always work in the sharing (or ‘on-demand’) economy. The consumption habits of typical visitors to ecommerce sites cannot be applied to the sharing economy.

Is the problem a severe one? Not at all – we just have to do a little bit of math.

Let’s take as example a search based on geographical criteria. The user will naturally select the locations that he or she feels will be most convenient – but these locations may not be served by any suitable suppliers. Here, the Cocorico engine also looks for results that are outside of the specified areas but which are likely still be to accessible to the user.

The more the options there are for the user to add lots of search criteria, the more likely it becomes that no single available result will match all specified requirements.

Of course, in an infinite universe, it would be great to offer the user a result that corresponded to their exact desires – that, after all, would give the greatest likelihood of a transaction workflow. But in the finite universe that actually exists, giving too many options leads to a high chance of having nothing to offer at all.

There is a risk that automatic extension of the scope of the search could lead to results that aren’t relevant, and so compromise the reputation of the platform in the eyes of the suppliers using it. But as long as users are made aware that their results are being augmented with others that could be useful to them, the likelihood is that they will be pleased to receive additional, helpful suggestions.

Cocosearch – an advanced search algorithm by Cocolabs which seeks to provide the potential customer with the results most likely to lead to a transaction – therefore proposes to look at the problem for the opposite direction, rather than trying to live with an unsuitable approach. In order to maximize the probability of finding a satisfactory result for the user, the engine offers a range of choices of varying quality, and arranges them into a ‘virtuous circle’, with the most relevant results near the middle and less relevant ones towards the edge.

Isn't it great, this sharing economy!?

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