We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Honing in on the Value of Social Media Data
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
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
Honing in on the Value of Social Media Data
Photo by jasongillman on Pixabay (https://pixabay.com/photos/knife-sharpening-whetstone-1267405/)
SHARE

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.”

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.

More Read

Real-Time Weather Forecasting
How Big Data Enables Hyper-Local Real-Time Weather Forecasting
Innovating the Practice of Performance Management
A Two-Stage Approach to Financial Return for Data Lakes
The Ever-Increasing Importance of Predictive Analytics
Can Predictive Analytics Help Improve Your Instagram Strategy?

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

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Technical architecture diagram and decision framework for ai-powered logo generation: design.com vs looka
AI-Powered Logo Generation: Design.com vs Looka
Artificial Intelligence Exclusive
Retailers Should Stop Treating Every Stockout as Equal -- AI-generated illustration
Retailers Should Stop Treating Every Stockout as Equal
Business Intelligence Exclusive
Best Vibe Coding Cleanup Specialists in the USA: Fix or Rebuild? -- AI-generated illustration
Best Vibe Coding Cleanup Specialists in the USA: Fix or Rebuild?
Development Exclusive
Using Warehouse, Transportation and Order Data to Plan Distribution-Center Capacity -- AI-generated illustration
Using Warehouse, Transportation and Order Data to Plan Distribution-Center Capacity
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Black Swans Causing a Rethink on Global Supply Chains?
AnalyticsBusiness IntelligenceDecision ManagementExclusiveModelingPredictive AnalyticsRisk Management

Black Swans Causing a Rethink on Global Supply Chains?

4 Min Read
The Big Data Uprising: It's Not About Big Or Data
AnalyticsBig DataBusiness IntelligenceCloud ComputingData MiningHadoopMapReducePredictive AnalyticsUnstructured Data

The Big Data Uprising: It’s Not About Big Or Data

12 Min Read
Is Analytics-Based Performance Management Art, Craft or Science?
AnalyticsCommentaryCulture/LeadershipExclusive

Is Analytics-Based Performance Management Art, Craft or Science?

7 Min Read
How Big Data and Hadoop Training Programs Can Make a Big Difference
AnalyticsBig DataExclusiveHadoopSoftware

How Big Data and Hadoop Training Programs Can Make a Big Difference

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

5 Great Tips for Using Data Analytics for Website UX
5 Great Tips for Using Data Analytics for Website UX
Big Data
ai chatbot
How AI Website Chatbots Improve Customer Support and Lead Generation
Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?