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Big data personalizes retail, energy, finance

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Big data has become a buzzword, with increasing relativity as the use of the cloud allows for more and varied applications of it. Who is using this data, for what, and why, are questions that can elicit confusion for those unfamiliar with the concept.

Speakers from retail, finance and energy sectors spoke about the use of big data in their companies and industries at a recent MIT Enterprise Forum at the University of California San Diego.

“A lot of what I’m telling you is not futuristic; it’s happening today, we’re doing it,” said Meyar Sheik, co-founder and CEO of Certona, a San Diego-based retail personalization platform. “None of it is 'Minority Report' stuff.”

Certona has the ability to create OmniChannel personalized retail experiences for individual shoppers, without the person actually having to supply any data. Based on a computer IP address, Certona’s software is able to know a shopper’s location, and then tailor the online experience based on local trends, seasonality, weather and even the shopper’s browsing history.

This carries across laptops, mobiles, tablets and even into the in-store experience, where Sheik said associates are increasingly using tablets to improve shopping flow for customers. Using geofencing — a software program that uses GPS to define locations — Certona is able to pinpoint the closest store location for those browsing retail websites. Then the company can promote sales or offers to encourage shopping, or boost the total sale to a point that would qualify for free shipping, for example.

“OmniChannel is all about taking not only structured data with CRM [customer relationship management] from behind firewalls and retailers’ databases, but also things that are happening on Facebook, your location, weather, your browsing behavior — all this is a lot of data that we and others process to deliver this seamless, personalized experience,” Sheik said.

Ted Reguly, director of customer programs and assistance at San Diego Gas & Electric, said the energy sector got a late start in the big data game, but is trying hard to catch up to retail, as using this data to better understand and tailor to customers is key to companies’ survival against competition from rooftop solar panels and other alternative energy sources.

“By offering the right information to the right customers through the right channel at the right time — that’s what we’re trying to get to — but we’re nowhere near where retail is,” Reguly said.

“We’re just starting the segmentation, we’re just starting targeted messaging, and with the rollout of our smart meters we’re also being able to better understand how our customers use our commodity so that we can better target market what rate they would benefit from?”

Reguly said while the energy and electricity sector is behind other industries, SDG&E stacks up well in intra-industry comparisons. While most other utilities in the United States don’t yet have the technology to know when a transformer goes out, the implementation of smart meters in San Diego means the utility now has a view to the endpoint of the grid, and is using that information to run the electric distribution system and in offer targeted services to customers, based on when and how they use energy.

SDG&E is also using this data to target its programs more effectively, such as using dynamic pricing and Reduce Your Use, and pre-emptively altering the grid if necessary, based on the weather.

“We can really now do a low profile on any one of our transformers and then have it kick out at any time which ones are overloaded and why, so we can proactively go change out those transformers right away,” Reguly said.

“On the weather side, we’re using the weather data that we know — what the moisture content is, what the humidity and the wind velocity are anywhere in our service territory — and we predict out I think two weeks, so we can know two weeks in advance if we’ve got an issue, so we plan demand for those events.”

The goal in terms of customer data is to separate out the information and pinpoint for users exactly what is using energy, even down to problem appliances.

“Where the next step is, is disaggregation tools,” Reguly said. “We aren’t there yet, but that’s when it’s going to get really powerful — when we use the data … and we can say ‘Hey it looks like you have a pool pump — you didn’t reset your timer, it’s still running 12 hours a day in the middle of winter — turn your timer on.’ We’ve got the data, but it’s getting everything stuck together so that we can give the right answer to you. That’s sort of the direction we want to go, but we aren’t there yet.”

Mike Alfred, co-founder and CEO of San Diego's BrightScope, which collects and analyzes data to help consumers understand and compare retirement plans, said much of the data his company works with is actually publicly available in raw form, but is fairly meaningless without being organized and analyzed and, in his case, run through Monte Carlo simulations. This is one of the benefits of companies making use of big data — doing the complicated work so consumers don’t have to.

“A lot of companies want to do these sexy predicative analytics and forward-looking stuff, but the reality is most companies today are way down at the bottom. They’re still trying to get a data set big enough and with enough time series that they can even do interesting models,” Alfred said.

He said by analyzing companies’ plans and then making the scores publicly available, BrightScope isn’t only helping consumers better understand their options and push their employers for change, but also helping financial institutions compete and ultimately better serve the consumer.

Alfred said BrightScope uses the cloud to handle their high volume of calculations and storage, and said such a company couldn’t have existed 10 years ago, before the cloud.

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