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SmartData Collective > Big Data > Data Mining > Honing in on the Value of Social Media Data
AnalyticsData MiningSocial Data

Honing in on the Value of Social Media Data

TeradataExperts
TeradataExperts
4 Min Read
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My colleague in Consumer Goods, Tim Shaw, recently passed along an interesting article from Deloitte titled “Making Sense of Social Data.” It raises a number of points applicable to consumer goods as well as other industries, but most interestingly concludes social media data’s greatest value is realized when connected “

My colleague in Consumer Goods, Tim Shaw, recently passed along an interesting article from Deloitte titled “Making Sense of Social Data.” It raises a number of points applicable to consumer goods as well as other industries, but most interestingly concludes social media data’s greatest value is realized when connected “very deeply into your operating model,” and is of an implicit nature. That’s not how most businesses employ social media data currently.

The article places social media within the context of three waves playing out in Big Data. Phase one has nothing to do with social media; rather it’s the traditional, transaction-based knowledge commonplace among retailers — but less so in consumer goods — in combination with the wealth of insights available in web analytics:

“…purchasing histories, demographics, measures of engagement—that make customer targeting more feasible.”

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That’s changing as CG adopts Demand Signal Repositories (DSR) that incorporate shopper and loyalty data, but it may be less actionable in a direct marketing sense, as it lacks consumer communication channel preferences and permission along with the ability to take action.

Phase two is a state many industries find themselves in today, where social media is a “bolt on” to some aspect of the business – think customer service, and marketing campaigns and promotions. Data generated is explicit, in that it’s volunteered by the consumer, but unlikely integrated with the aforementioned transaction, demographic and web data.

It’s the third phase where social media’s value is unleashed, when analytics blends with varied data sources to create an implicit understanding of consumers:

“In this wave, the focus shifts from the voice of the customer to the individual’s behavior. But more importantly, it looks at that behavior in the context of who is around them and how they interact. It gets below the curated, surface-level information we put out about ourselves online, to help understand what our digital trails and network really say about us.”

I say “varied sources,” because the article claims mobile will contribute even more to consumer understanding than social. Given the adoption of smartphones, it makes sense. Mobile is state based, real time and offers multiple channels to connect with consumers at the point of action. This is especially applicable to Consumer Goods, where the mobile channel presents an opportunity to connect with and influence shoppers independent of the retailer while at the point of purchase.

With so much data generated by so many sources, updated almost continuously, it will be important to isolate the most relevant information — much like settling on the key performance indicators (KPIs) and metrics important to your business amid all the possibilities.

“It doesn’t take all the data in the world, however. With so much data available, from so many different sources, it may actually be possible to build a 360 degree view of the customer; but for most companies, 15 degrees will do. The real challenge is making sure that you have the right 15 degrees.”

Teradata’s varied capabilities appear uniquely matched to all of challenges outlined in the article. Do you agree?

Gib Bassett

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