Recently, there have been a number of announcements regarding the redesign of Bing's main search experience. The key difference is the use of three parallel zones in the SERP. Along with the traditional page results area, there are two new results columns: the task pane, which highlights factual data and the social pane which currently highlights social information from individuals (I distinguish social from 'people' as entities - for example a restaurant - can have a social presence even though they are only vaguely regarded as people).
These three areas can be seen below:
The example above shows another key part of Bing's exploration of the search experience. The results for the query {sushi in seattle} are no longer displayed as a block of structured data inserted somewhere in the stream of blue link web pages. Rather, they are integrated into the results in a manner that leverages both the web presence of the entity (for local entities this generally means the home page of the business) and associates with it the structured data that identifies and characterizes the entity.
The task pane - which appears when the arrow tab is interacted with - holds more detail about the entity and provides affordances for learning more. There are options to compute directions to the location, view the streetside imagery or read reviews.
In addition, for local queries Bing now provides an aggregate view of results.
My team, along with a number of other teams in Bing, have been hard at work bringing this evolution to fruition. Here are some comments on the process:
- When we provide flat structured data (as Bing did in the past), while we continued to strive for high quality data, there is no burning light focused on any aspect of the data. However, when we require to join the data to the web (local results are 'hanging off' the associated web sites), the quality of the URL associated with the entity record becomes a critical issue.
- The relationship between the web graph and the entity graph is subtle and complex. Our legacy system made do with the notion of a URL associated with an entity. As we dug deeper into the problem we discovered a very rich set of relationships between entities and web sites. Some entities are members of chains, and the relationships between their chain home page and the entity is quite different from the relationship between a singleton business and its home page. This also meant that we wanted to treat the results differently. See below for the results for {starbucks in new york}
- The structure of entities in the real world is subtle and complex. Chains, franchises, containment (shop in mall, restaurant in casino, hotel in airport), proximity - all these qualities of how the world works scream out for rich modeling if the user is to be best supported in navigating her surroundings.
It proved to be a lot of fun and technically challenging to get deep into the problem of local search (not to mention the need to throw in some philosophical underpinnings regarding the semantics).
Here is another example of a search result which highlights Bing's understanding of chains of local entities {starbucks in new york}: