Ordering the Needles After Finding them in Haystacks

Finding just a few bits of useful information within a vast sea of data is a pretty neat trick. Here at WhoDoYou we specialize in filtering out the millions of posts across social networks that have nothing to do with local business recommendations. The good news is, out of all that hay, we’re able to come up with hundreds of thousands of needles – high quality bits of advice shared between friends.

But believe it or not, it can be difficult to display the resulting information in a logical and ordered way that meets the needs of a person searching WhoDoYou. I’m sure many of you can identify with times when you are most interested in ordering search results by price. At other times, quality is your first criterion, and when searching on mobile, often proximity is the primary variable. WhoDoYou introduces a social layer on top of these considerations, not to mention the precision of the user’s search and the category we have stored (e.g. CPA versus accountant, HVAC vs plumber).

So there are indeed many calculations to factor in when thinking about how best to display the most fitting results to each user, to ultimately help in making a hiring or purchasing decision. We’ve been working on this problem and are excited to soon be rolling out a whole new way of ordering our results – in a way that we believe will make it much quicker and easier for users to choose the business that best fits their needs.

Funny enough, it turns out we’re not the only ones that have been working hard to address this issue. In fact, one of the Internet’s most mature verticals, travel, is still working to make the user experience better when searching for flights, hotels and complex itineraries. Recently the New York Times did a story on ‘How to Choose an Air Travel Search Site.’ They compared the old guard – www.expedia.com, www.orbitz.com, and www.travelocity.com with a handful of newer companies.

The site I found most interesting is www.routehappy.com. They are doing a wonderful job in trying to present useful results in an order that’s meaningful to its users. Try a search and you’ll find they have a ‘Happiness Index’ which attempts to balance the price, schedule and trip duration components (as well as seat recline, in-flight entertainment, etc.). Essentially these are the primary variables used to make a purchase decision, and Routehappy is doing its best to remove most of the work for the person searching.

Coming back to WhoDoYou, our goal is to help people find dentists, plumbers, painters, movers and hundreds of other types of local professionals. Today it’s very difficult on other sites to choose between a list of unknown providers. At WhoDoYou, we give you trusted opinions, and will soon go beyond the bits of advice to showing a more ordered list based on the factors that seem to correlate most with choosing a local service provider.

We hope you’ll like what you see, and as always, we welcome your comments and feedback.

Thanks in advance,

Yoav

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Sick of hearing about big data? Try some small data, you may never go back

So, have you heard the latest crack about big data?

“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it….” Dan Ariely, Professor at the Center for Advanced Hindsight (and Duke).

Kudos to Prof. Ariely for making light of possibly the most overused cliché of our age – big data (with apologies to “The Cloud”). There are a lot of good reasons that industry folks are pretty excited about big data. Crunching massive amounts of information to generate actionable, predictive conclusions certainly has great promise. Indeed I recently attended a conference where a company that builds in-store technology tools to measure shopper behavior said that they collect 10,000 data points for every unique store visit. And, they have already captured more than 600 million visits. I’m not a mathematician, but if you multiply 600,000,000 x 10,000 you get a really large number. That’s probably useful for big data purposes.

But, for all those non-industry folk, who have no idea what to do with 600 gazillion data points, WhoDoYou has something for you. Specifically, we are using small data to give you as much insight and power as the big boys have with large data. To be really specific, we’re talking about making the everyday decisions around which professionals to use. When searching for an accountant or a mechanic, you know that many of your friends and people you know have already done a similar search. Even better, many of them have quality professionals they’ve been using for years. The problem is, YOU don’t know who they’ve been using, and to capture the information from your friends, or from trusted locals in your area, can be difficult or unpleasant (broadcasting messages via social media, not knowing who to ask, not wanting to bug all your friends every time you need some professional). While this is a pain point that people feel every day, no big data solution that does trend analysis on hundreds of millions of inputs will help you solve what seems like a pretty basic question: who’s the best pediatrician in town?

The good news is, this data exists within your friends and locals’ networks. It’s just called small data, and it turns out to be pretty hard to find and catalogue it. That’s what WhoDoYou is here for – we search for the needles in your many haystacks, and the little nugget of gold in the mass of rocks and dirt. There is so much data and so many conversations happening all around you – none of which help when you want an answer to a very specific question, as in, who is the best piano teacher for your daughter, or what’s the best dentist for cheap, yet high quality care.

You see we specialize in capturing the small data, just the bits you really need. On a typical day across social networks people use common category terms (plumber, lawyer, notary) literally millions of times. But it turns out that only a tiny fraction of those mentions include people asking their friends for help, and fewer still of these public conversations result in a high quality recommendation. But when they do, we’re there for you, capturing, cataloging, and storing the information for when you need it most. That’s why we call it small data, and it’s the reason that our solution – although rooted in big data and deeply technical machine learning algorithms – works so well for people like you, just trying to find basic answers to really important questions.

So the next time you hear people talking about big data and wonder what the heck they’re trying to say, just relax, and think about small data. You know, the stuff that helps you answer the questions you really need, without all the hyper-fad-buzzwordery.

As always, if you have any questions or comments, we love hearing from you. So please be in touch.

Yoav and the WhoDoYou team