I need a Pattern-Based Super Search and Recommendation engine - who's on it?
I'm tired of searching - this is what I want - someone please build it for, or call me, and we'll build it together.
version 1 - this should be easy (Google 2.0)
I search Google all the time therefore it knows what I'm looking for and have looked for over the last 6 years. I want Google to recommend things to me that it should know I like based on my search activity. For example, Google should know that I recently searched for the following terms:
tablet hotels
soho
seth godin
soho house
Why aren't they recommending a killer airline deal on an airline, such as Virgin America, that has a look and feel of those things that I have searched? Why aren't they suggesting a 20% discount offer at 60 Thompson? Why don't they tell me that there is a signing party for someone that I should be interested in, if I have spare time during my visit to New York? Why can't someone package up my search history and recommend 10 things that might interest me?
version 2 - slightly harder - maybe Bing is trying to do this - perhaps Ask can do this (are they still around?)
Take all of the activity that I wish to share including a complete profile of my wants and capabilities, my event history, my Twitter feed, LinkedIn, Facebook, Dopplr, Slideshare, YouTube channel, etc and make KILLER recommendations? By KILLER, I mean that I act on these things > 25% of the time.
I want a daily list of suggestions based on all of these data sets. I want suggestions on where to stay, what to do, who to meet (yes, I'll upload my calendar availability), what to buy, etc. I also want to be able to drill down to understand why they thought I would like the suggestion, if I want to drill down, but the recommendations should be good enough that I don't need to. I want to know which of my 1 and 2 degree connections within my social sphere have recommended or commented on these things. If you give this to me, you will save me a ton of time and I suspect lots of money, while generating huge revenue from the vendors you recommend (take 7-12 % of every transaction - let's call it 10%).
Here's an example:
I'll spend about $1,900 on this 3 day trip and you will make $190 - not bad for a couple of recommendations. I'll be happy to use Super Search because you save me a couple hours per week and a bunch of cash and your vendors will love you for selling off their inventory.
Is this too much to ask? Does anyone else want this? Does anyone want to build it for me or with me? you can also ping me at @mwalsh.
I'm tired of searching - this is what I want - someone please build it for, or call me, and we'll build it together.
version 1 - this should be easy (Google 2.0)
I search Google all the time therefore it knows what I'm looking for and have looked for over the last 6 years. I want Google to recommend things to me that it should know I like based on my search activity. For example, Google should know that I recently searched for the following terms:
tablet hotels
soho
seth godin
soho house
Why aren't they recommending a killer airline deal on an airline, such as Virgin America, that has a look and feel of those things that I have searched? Why aren't they suggesting a 20% discount offer at 60 Thompson? Why don't they tell me that there is a signing party for someone that I should be interested in, if I have spare time during my visit to New York? Why can't someone package up my search history and recommend 10 things that might interest me?
version 2 - slightly harder - maybe Bing is trying to do this - perhaps Ask can do this (are they still around?)
Take all of the activity that I wish to share including a complete profile of my wants and capabilities, my event history, my Twitter feed, LinkedIn, Facebook, Dopplr, Slideshare, YouTube channel, etc and make KILLER recommendations? By KILLER, I mean that I act on these things > 25% of the time.
I want a daily list of suggestions based on all of these data sets. I want suggestions on where to stay, what to do, who to meet (yes, I'll upload my calendar availability), what to buy, etc. I also want to be able to drill down to understand why they thought I would like the suggestion, if I want to drill down, but the recommendations should be good enough that I don't need to. I want to know which of my 1 and 2 degree connections within my social sphere have recommended or commented on these things. If you give this to me, you will save me a ton of time and I suspect lots of money, while generating huge revenue from the vendors you recommend (take 7-12 % of every transaction - let's call it 10%).
Here's an example:
I like the beach, beer, wine, all tablethotels hotels, baseball, sushi, social networking, among other things. I have searched for things like these, not exactly, but similar to them.
When I visit LA, I want the Super Search and Recommendation engine to recommend that I stay at Shade Hotel (and offer a discount) in Manhattan Beach, have dinner at Club Sushi, make me aware of an art opening that night or a local TEDx event at the beach, and show me the connections whom have recommended these places. It should also let me know that Hennessey's on Hermosa Ave will be playing the game and the starting time of that game. It might also suggest that I try to meet Chip Conley who may be in Venice one of his newest hotels. Let me know that there is a store on Hermosa Ave that sells Nixon earphones and Billabong shorts, if I have time to stop by. Oh, you recommended that I fly either Virgin America or Southwest Airlines and provide the quote at the time of the recommendation. Though I like both airlines, I'll likely choose Virgin America because @PorterVA is awesome and I love the airline.I'll spend about $1,900 on this 3 day trip and you will make $190 - not bad for a couple of recommendations. I'll be happy to use Super Search because you save me a couple hours per week and a bunch of cash and your vendors will love you for selling off their inventory.
Is this too much to ask? Does anyone else want this? Does anyone want to build it for me or with me? you can also ping me at @mwalsh.
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