Personally I think there is too much positive feedback in the App Store. The popular marketed stuff is downloaded, rises to the top of the charts, and that's reinforced by apples recommendations or charts. It might be worth apples time showing the less popular stuff in any category, maybe even randomly some of the least popular in a More To Try. That would change every day as the subsequent downloads would exclude those apps from the least popular but would keep the long tail churning.
say you are a 35 year old mother who lives in Minneapolis who is interested in apps to keep the kids busy, but she's also interested in hockey and flight simulators. She should have some way of manually setting these interests by keyword
Keywords would be a good idea. I think they'd have to be linked though. So for example, someone could choose tags 'baking', 'cooking', 'flying'. However, flying on its own might bring up flight checkers so it would have to be linked to games so they'd need linked tags 'games'-'flying' and inverse tags for exclusion so 'games'-!'flying' (it would be inverted colors or something) would mean no flying games. If you didn't want to see kids games, you'd set 'games'-!'children' and the system interpreting tags would know similar terms like kids/children etc.
These tags would be found by Apple using a search of app categories, titles and descriptions for frequency and excluding any offensive terms and then present them to the user in iTunes as building blocks. This could be a split view with a tag cloud up top that had a list of tags on the left in a long list that narrowed down by typing terms. You'd then drag the tags over into the tag cloud and could link them together, maybe even like the way iOS does folders so you can have one tag alone as a rounded square but drag two together and it make a folder of tags. Hovering over each tag would show an invert icon. Invert tag groups that exclude a lot of apps can have a small warning bubble, like if you accidentally inverted the whole games category.
You would even be able to add favorite developers as tags. There would then be a page dedicated solely to presenting the best apps that match your tag cloud and excluding apps adds an exclusion tag, which can be removed later. Individual exclusions could be grouped in a single tag folder.
The bottom part of the split view (on iPad and Mac) would then be your personal recommendation section showing apps. The tag cloud can also be helped automatically with Genius filters based on past purchases and apps you've rated. The tag cloud on the iPhone might be tricky to manage but they can split the tag view and tag list and then show the apps on a separate page.
I think Marvin and others who mentioned tagging and metadata are thinking along the right path for much better search models. You could point these ideas into the realm of faceted classification systems and come up with a pretty decent system. This strategy is actually quite old and dates back to Shiyali Ramamrita Ranganathan, an Indian master of library science. Faceted classification is computationally expensive but delivers a much more focused experience. A good example of this model is the Kayak travel site. You can also visualize it if you've seen those used car commercials where there is a huge matrix of candidates and as the customer provides more conditions, or facets, if what he or she is interested in the number of candidates is reduced.
I think a faceted classification system with some sort of Apple Genuis inspired adaptive learning influence would move this along quite well. Use the mass computational power of the internet of things, big data, search, and adaptive learning about what kinds of things the searcher "likes" and you get a more productive and personalized user experience focused on discovering apps or other content that you might like.
What makes this computationally intensive is having to provide indexing not only for every facet but for relationships between each facet. It's a big data problem. If I had to guess about who has the wherewithal to conceptualize the scale of the problem and bring the required processing model to bear I'd say Google and IBM and Amazon before I'd say Apple. This is not a knock on Apple, it's just the companies like Google and IBM are knee deep in this sort of thing as infrastructure providers as a primary focus while Apple is a product focused company with very large infrastructure needs due to their enormous success in product innovation.
You could say that had Google and Apple teamed up around this problem we as customers would be served unlike we've ever been served. Unfortunately egos, jealousy, and shareholders sometimes get in the way of solving real world problems. If Apple is going to do this on their own they'll have to learn and acquire some knowledge that's traditionally been outside of their core domain expertise. You can also flip this around and say that Google's foray in the product domain has been a distraction from solving the really big problems that they are well positioned to solve.
Apple may also want to think along the lines of curated app lists. I'd like to see extensive app lists from people like Oprah, Leo Laporte and other personalities or tech luminaries with large followings...possibly even a "New York Times Top Apps List" of sorts.
Comments
Keywords would be a good idea. I think they'd have to be linked though. So for example, someone could choose tags 'baking', 'cooking', 'flying'. However, flying on its own might bring up flight checkers so it would have to be linked to games so they'd need linked tags 'games'-'flying' and inverse tags for exclusion so 'games'-!'flying' (it would be inverted colors or something) would mean no flying games. If you didn't want to see kids games, you'd set 'games'-!'children' and the system interpreting tags would know similar terms like kids/children etc.
These tags would be found by Apple using a search of app categories, titles and descriptions for frequency and excluding any offensive terms and then present them to the user in iTunes as building blocks. This could be a split view with a tag cloud up top that had a list of tags on the left in a long list that narrowed down by typing terms. You'd then drag the tags over into the tag cloud and could link them together, maybe even like the way iOS does folders so you can have one tag alone as a rounded square but drag two together and it make a folder of tags. Hovering over each tag would show an invert icon. Invert tag groups that exclude a lot of apps can have a small warning bubble, like if you accidentally inverted the whole games category.
You would even be able to add favorite developers as tags. There would then be a page dedicated solely to presenting the best apps that match your tag cloud and excluding apps adds an exclusion tag, which can be removed later. Individual exclusions could be grouped in a single tag folder.
The bottom part of the split view (on iPad and Mac) would then be your personal recommendation section showing apps. The tag cloud can also be helped automatically with Genius filters based on past purchases and apps you've rated. The tag cloud on the iPhone might be tricky to manage but they can split the tag view and tag list and then show the apps on a separate page.
I think a faceted classification system with some sort of Apple Genuis inspired adaptive learning influence would move this along quite well. Use the mass computational power of the internet of things, big data, search, and adaptive learning about what kinds of things the searcher "likes" and you get a more productive and personalized user experience focused on discovering apps or other content that you might like.
What makes this computationally intensive is having to provide indexing not only for every facet but for relationships between each facet. It's a big data problem. If I had to guess about who has the wherewithal to conceptualize the scale of the problem and bring the required processing model to bear I'd say Google and IBM and Amazon before I'd say Apple. This is not a knock on Apple, it's just the companies like Google and IBM are knee deep in this sort of thing as infrastructure providers as a primary focus while Apple is a product focused company with very large infrastructure needs due to their enormous success in product innovation.
You could say that had Google and Apple teamed up around this problem we as customers would be served unlike we've ever been served. Unfortunately egos, jealousy, and shareholders sometimes get in the way of solving real world problems. If Apple is going to do this on their own they'll have to learn and acquire some knowledge that's traditionally been outside of their core domain expertise. You can also flip this around and say that Google's foray in the product domain has been a distraction from solving the really big problems that they are well positioned to solve.