My Intelligent Shopping Agent – Part 1

I’m still waiting for my intelligent shopping agent, but alas, it’s still nowhere to be found.

Back in 2006, I wrote the following description of the system that I thought would be prevalent by now:

In my vision of the shopping (and a lot of other activities) in the future, I will have an intelligent agent which understands my preferences, knows the marketplace (price trends, consumer sentiment, etc.) and is always on the lookout for products, deals, reviews, recommendations from friends (this is where social networks/communities become really valuable), etc. which I’d be interested in. My agent understands the competitive landscape and makes sure that my buying decision is well informed. My agent would have the authority to haggle with a dealer/distributor/merchant and make purchases according to criteria that I set or that my agent learned over time. It might take a while for the agent to understand my preferences and there would definitely be work involved with setting up such a system, but we will get there.

That was over 4 years ago. While this system might sound like science fiction (Snowcrash – if you want to know what will happen in the future, read the leading scifi writers), we have the platforms to enable this reality. There are a number of components that can come together through powerful APIs, but why not start with just querying users about simple preferences in a creative way.

While privacy will always be a hot button issue, ‘kids’ these days are way beyond this. And I don’t think I’m generalizing too much. With the rise of Facebook, people just share more information about themselves than they ever did before. And I think that if they’re willing to share with friends on Facebook, they’d be willing to share with a ‘secure’ intelligent shopping agent. You’re already seeing women express tastes through fashion 2.0 sites like (Google) and JewelMint, which require the user to go through a style analyzer to begin. The style analyzer is nothing more than a set of interests. The intelligent shopping agent could begin the same way. Another example would be Netflix. If you remember way back to when you first signed up, you expressed your likes and dislikes so the system could get a foundation for your movie viewing preferences. In shopping, there are a lot of factors which might be important: brands, styles, colors, etc. Asking for this basic information up front is a great start and probably not too intrusive.

But an individual isn’t going to want to go through 80 questions for the system to get to the bottom of his or her shopping taste. Luckily, you won’t have to. We’re all willing to share these days. Think Millions of people are willing to just give Mint access to credit cards, banks accounts, investment accounts, and more. The current equivalent in shopping is Blippy. Again, spurring all worries about privacy, individuals are giving Blippy access to all credit card transactions. Right now the reason to do so is to share purchases with friends and get feedback. But if we’re building an intelligent agent, why not just suck in all your past purchases? In this way, the intelligent agent will quickly understand your favorite stores, your location (more on this later), your demographic (income level), etc. And for you privacy freaks, with Blippy you don’t have to hook up your credit card transactions. Blippy will just scan your email for receipts or link to other accounts like Groupon or Etsy for more information. Not as powerful as accessing all your credit card purchases, but it’s a start.

Read Intelligent Shopping Agent – Part 2

4 Responses to My Intelligent Shopping Agent – Part 1

  1. […] in my last post, I re-introduced the concept of my intelligent shopping agent. The foundation for the agent could be built by querying the consumer and analyzing past buying […]

  2. Ahli says:

    Very shortly the company that I am involved in will launch its smart shopper technology. It remembers your searches, suggests items for you (not new) but will remember your birthday and suggest things to your significant other that you have been searching for. The tech is there, but everything is changing and evolving so quickly, I don’t think it stands a chance of keeping up!

  3. […] like the concept of Alfred because it mirrors parts of my Intelligent Agent. Amid talk of machine learning, Alfred’s Extraction Engine and Serendipity Engine gathers […]

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