Big Data. Big Decisions
InformationWeek
Special Coverage Series


How Kraft Foods Listens To Social Media

Your morning banter about bacon on Twitter? Kraft's using it to decipher consumer trends and develop product ideas.

14 Leading Social CRM Applications
Slideshow: 14 Leading Social CRM Applications
(click image for larger view and for slideshow)
The next time you see a new variety of Oscar Mayer bacon or cold cuts in the grocery store, there will be a chance it got there because of social media.

Paul Banas, a senior category insights manager in the Oscar Mayer division of Kraft Foods, won't say what new products have been created in response to social media research because some of them haven't been released yet, but he discussed how he uses social media as a research tool in an interview this week. His story shows how a marketer's use of social media monitoring is different from how a public relations manager or webmaster might use the same basic tools.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

While he can't claim to be in charge of the company's social media analytics efforts--which are distributed across the many divisions of the food conglomerate--Banas describes himself as "a passionate advocate."

Social media analytics "really got me jazzed as a researcher," Banas said. "It gives me a vast data set, bigger than any data set I ever had, and it's being refreshed constantly." Coming from a traditional market research background, he was used to working with relatively small survey panels and focus groups. And because social media allows him to tap into spontaneous conversations on the Web, it sometimes delivers different insights than he would get from those other tools.

"It's the difference between if I asked you a question, versus just listening to a conversation," Banas said.

His approach as a marketing strategist is different from the way the public relations and corporate communications teams within the company--who discovered social media monitoring long before he did--approach the data. "The thing I'm most interested in is a deeper understanding of the consumer, rather than putting out fires here and there," he said.

The kind of social media monitoring that tracks brand and product mentions tends to be less useful for his purposes, since about 95% of the conversations he cares about are unbranded--meaning that people are talking about bologna, but not necessarily about Oscar Mayer. A corporate communications specialist might want to be alerted to someone saying bad things about the brand or spreading a false rumor about its products. Banas is searching for longer-term trends, like changes in consumer tastes, and clues to how well the brand the company wants to project is reflected in consumer perception.

"What this research allows us to do is explore the fuzzy front end of basic user wants or needs, like what are the flavor trends, what are the usage trends," Banas said. To answer similar questions outside the digital world would require "some ethnography with a consumer, where we're going into someone's house, looking in the fridge, and asking 'Why did you buy this?'"

Banas works with MotiveQuest, a social media monitoring firm that delivers its analysis more through consultation than automated dashboards. Kraft makes use of some other social analytics tools such as NetBase as well, but Banas said he does not consider himself a power user of such analytic tools.

Instead, he looks for analytic help on a consulting basis "because I'm trying to take it beyond just tracking an individual keyword," and doesn't have time to learn how to invest in self-help tools. "I think I'm smart enough that I could probably figure it out myself, but I also have a lot of other responsibilities. I'd rather work with somebody who knows this soup-to-nuts, and can bring it to bear on my business issues," Banas said.

Keywords are still important for his research, and he works with the MotiveQuest consultants to improve their targeting over time, he said. "You know, I'm interested in conversations about bacon, but I'm not necessarily interested in conversations about Kevin Bacon."

Although he agreed to serve as a reference for MotiveQuest, Banas said he continues to experiment with other services, looking for those that can provide different insights. "I don't think anyone has figured out the best approach or the best uses for this--and on the vendor end, I don't think anyone's figured out the best business model to meet clients needs."

Banas believes social media monitoring techniques are getting better at "bringing actionable insights to the table, rather than focusing on levels of buzz," but the next step will be proving it in terms of a return on investment. "We need to take it beyond just a consumer understanding" and figure out how to translate that into sales, he said.

"We've gotten a bit of a pass so far, because we can say this is all brand new stuff, and we need to try new things," Banas said. "But at some point, folks are going to say, 'Yeah, but is this really all paying off for us?'"

Black Hat USA 2011 presents a unique opportunity for members of the security industry to gather and discuss the latest in cutting-edge research. It happens July 30-Aug. 4 in Las Vegas. Find out more and register.



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.