Most of the civilized world, by this time, has heard about Apple’s fumble with their new mapping and local search capabilities in iOS. Apple replaced Google’s application – which is possibly the largest investment in cartography, imagery and local data ever made – with a home grown solution reportedly rolled out of maps from a number of providers including TomTom and local data from providers including Yelp.
As Apple has realised, there is a lot to learn for an entrant in this space. The hardest lesson they are learning now is actually not about data sources but about metrics and how to assess the quality of the product – something which they don’t appear to have invested in in a manner fitting to their global user base.
Apple will soon learn another lesson. Once the fog has lifted over the state of their entity data set (e.g. fixing the location of cities and ensuring coverage for local businesses), Apple will have to start worrying about ranking search results. When a user asks for , which of the many sushi places ought they to return? They will be presented with a choice between specialized providers – with whom they will actually be in competition – or creating the resources required for relevance ranking themselves.
A key aspect of providing appropriate indexing and ranking features is the association of content with the entities. Where does this content come from? The web. How is it acquired? Through large scale crawling, understanding and indexing.
Apple will likely find that as they pull on the thread of local search, their scope will have to open up to quite a different world, another world which – like local – they haven’t yet the expertise in.
