Yelp announced the release of a brand new API called Fusion that allows greater developer access to native Yelp data and features on September 20. Fusion provides higher granularity filtering across Yelp data, greater access to photos and partner data, and 24 hour caching.
Yelp's Fusion API's main features involve data filtering when searching across large swaths of business data. With Fusion, developers now have the ability to filter by price level and open hours as well as receive autocomplete suggestions for business and keyword searches. The API documentation describes a relatively straightforward RESTful API for both search and autocomplete functionality. Standard HTTP gets with params are included for different respective filtering and autocomplete keywords. An important limitation, however, is that search results are limited to 1000 results. If companies are planning on doing their own analytics on Yelp data they may still be limited by the constraints put in place by the existing API.
Another large feature of the new Fusion API is caching and Yelp partner collaboration. 24 hour caching allows applications utilizing Yelp's data to be more performant. Because applications communicating with the Yelp API can keep a cache record of all client search results locally, applications can easily retrieve recent searches without having to make additional network calls to the Yelp API every time a user wants to search across Yelp data in their application. Yelp's collaboration with partner companies offering similar business data like ChowNow also means, at least in the food delivery category, there is more data to search against. While most general data around restaurant businesses is likely already in Yelp, data like business reviews that are often singular to a particular service can now be connected across Yelp and all its partner businesses in a potentially useful way for development.
In its early release the Fusion API has been primarily adopted by IOT (internet of things) applications. However, outliers like the popular dating site Coffee Meets Bagel, proves that there is a myriad of ways finer granularity of control over Yelp data can be adopted. Chad Richardson, senior vice president of business and corporate development at Yelp, writes "Their integration of the Yelp Fusion API will add a lot of value to the Coffee Meets Bagel community, and hopefully tee up the perfect setting for true love!" Co-founder of Coffee Meets Bagel, Dawoon Kang mentions Yelp's newest filtering additions as their biggest benefit from the new Fusion API, allowing them to produce more targeted results for dates. The main adopters of Fusion have primarily been applications, whether IOT or otherwise, which try and cater to the location-specific whims of users. Fusion's ability to combine location data, with high resolution photos and targeted reviews provides a uniquely robust context around individual businesses particular to very specific user locations.
Yelp has been careful to open up Fusion to the developer community while still keeping large amounts of data and functionality gated. For example, on the Yelp website you can get graphs of a business' rating over months and even years, whereas through the API you can only get the current rating. Also, while you can maintain a 24 hour cache, you can't externally store their API data. These safeguards prevent a competitor from stealing a large amount of Yelp's value while still opening the service up to greater development efforts. Richardson writes in the Fusion press release, "Consumer expectations for local content have been increasing, and to answer that need, we've decided to double down on our developer program and provide access to better tools and richer Yelp content and data." It's clear that with the boom of highly personalized data recommendations Yelp is making sure that developers are comfortable using their API as a driver.
