At the IAB conference, Frances Donegan-Ryan from Bing begins by reminding us of the history of online search.

NOTE: Live-blogging. Getting things wrong. Missing points. Omitting key information. Introducing artificial choppiness. Over-emphasizing small matters. Paraphrasing badly. Not running a spellpchecker. Mangling other people’s ideas and words. You are warned, people.

We all leave digital footprints, she says. Every time we search, data is recorded. The sequence of our searches gives especially useful information to help the engine figure out what you’re trying to find out. Now the engines can refer to social graphs.

“But what do we do with data?”

Bing Predicts
looks at all the data it can in order to make predictions. It began by predicting the winners and losers in American Idol, and got it 100% right. For this election year, it tried to predict who would win each state primary or caucus in the US. Then it took in sentiment data to figure out which issues matter in each state, broken down by demographic groups.

Now, for example, it can track a new diabetes drug through the places people visit when logged into their browser. This might show that there are problems with the drug; consider for example people searching for unexpected side effects of it. Bing shares the result of this analysis with the CDC. [The acoustics where I was sitting was poor. I’m not sure I got this right.]

They’re doing the same for retail products, and are able to tell which will be the big sellers.

Frances talks about Cortana, “the only digital system that works across all platforms.” Microsoft is working on many more digital assistants — Bots
— that live within other services. She shows a temporary tattoo
made from gold leaf that you can use as a track pad, and other ways; this came out of MIT.

She says that the Microsoft version of a Fitbit can tell if you’re dehydrated or tired, and then can point you to the nearest place with water and a place to sit. Those shops could send you a coupon.

She goes quickly over the Hololens since Robert Scoble covered it so well this morning.

She closes with a story about using sensor data to know when a cow is in heat, which, it turns out, correlates with them walking faster. Then the data showed at what point in the period of fertility a male or female cow is likely to be conceived. Then they started using genetic data to predict genetically disabled calves.

It takes enormous computing power to do this sort of data analysis.

Categories: big data, liveblog, marketing dw