Paul M. Banas on Consumer Insights, Marketing Research, and the Digital Media Landscape

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Social Media Listening: What To Listen For In Social Media

In my previous post on the need to focus on insights versus observations when engaged in social media listening, I mentioned three areas in particular that researchers should be focusing their listening on: passion, tension, and the context of the conversation which surrounds them.

As a second part to my posts outlining the themes I covered at the Advertising Research Foundation event last week on “Putting Listening To Work”, I want to go into these three areas in more detail.

Several weeks ago, Annie Pettit, who writes the excellent market research blog LoveStats, had a brief post entitled “The Lost Art Of Qualitative Research”.  In it, she makes the link between the need for more academic focus on qualitative research and the imminent rise of social media research.

As someone who has spend more than his fair share of time behind the glass at focus groups or tromping through people’s home in ethnographic research, I can see directly how knowing what to listen for in traditional qualitative research can truly improve the quality of insights one gets from social media listening.

As most qualitative researchers or ethnographers know, there are key emotions and phrases we listen and watch for that help distill all those hours of people talking by pinpointing the beginnings of actionable insights.

Tension:

One of the first things to listen for is tension in the conversation.  By using natural language processing and linguistic analysis, one can hone in the tension or pain points that people express, which are locaters for unmet needs:

“…Dinnertime is tough in our household because of all the picky eaters…”

“…making lunches for three kids in the morning is extremely difficult when…”

“…I wish there were more fast food menu choices that weren’t so high in sodium…”

By looking at verbatims filled with tension in social listening, one can focus on “white space” opportunities for new product development or innovative equity messaging.

Passion:

Another rich source of insights is looking for where people’s passions lie within their online conversations.  When people express either positive or negative passions, they are providing locations for key points of emotional leverage, much like following tendrils of smoke can lead to where the fire is hottest.

“…I absolutely love the way my clothes smell after I take them out of the dryer…”

“…now that it’s the middle of winter, I am truly craving chocolate…”

“…everything tastes awesome with bacon it it…”

People don’t change behavior unless the have a strong motivation for doing so.  Passion, either negative or positive, can lead to points of emotional leverage.  Since all effective marketing is predicated on a change in behavior, focusing on a passion is the quickest way to more effective marketing communication.

Context:

Unlike the first two areas, Context is not a what, it’s more about the who or the where that occurs around conversations containing passion and tension.  It provides the linkages that help us in the chain of understanding that goes from what people say to what people do.

An example would be that all the online conversations about something like burgers are very different, depending on who is doing the talking: moms with a family to feed, guys talking about tailgating, or foodies talking about their favorite gourmet burger.

The flipside to this is that a single person may have multiple personas: they can be moms, business owners, someone with a health condition, etc.  The emotions and tension points they have as a mom will probably be different in a context where they are talking about their own personal health issues.

Better Listening Insights:

Social Media Listening is currently one of the hottest topics in consumer research today.  However, as a discipline, it’s still in its infancy.  If we are going to take it from providing a random assortment of facts or observations in the digital space, we need push past the buzz on the surface to get to the raw emotions and tension points in the conversation.  And by understanding the contextual who and where of these expressed emotions, we can then make the linkages to the actionable insights we are all trying to find.

January 27, 2010   2 Comments

Social Listening: Focusing On Insights

January 2010 is shaping up to be a very busy month for me: in addition to kicking off the strategic planning season in my brand research role at Kraft Foods, I have a couple of opportunities to speak publicly over the next couple of weeks about social media, social listening, as well as other ways to lever the digital space for consumer insights.

At the end of the month, I’m honored to be presenting at the Advertising Research Foundation’s Industry Leader Forum  on “Putting Listening To Work” in San Francisco.  I’ll be speaking on ways to ask more from social listening as a research methodology, by focusing on insights, rather than settling for simple observations.

In the run up to these talks, I’m going to try to outline some of the thoughts and themes I’m thinking about sharing on this exciting new phase for marketing research.

Insights Versus Observations:

The first theme is the concept of focusing on insights versus observations when analyzing data coming in from social listening efforts.

Said simply, an observation is a fact without wings.  Something like “the brand mentions for Brand X were 45% positive during the last 12 months” or “the level of buzz around Category Y has increased 28% versus the prior year”.  While both true, these observations don’t take me anywhere and they don’t lead to any implications that I can build a business idea on.

Unfortunately, many researchers are settling for summary reports from social listening efforts that are full of these type of simple findings.

Just because you observe something in the digital space versus traditional research, doesn’t make it any more interesting or valid.  And just as in traditional research, meaningful insights need to be the goal of any impactful  social listening effort.

Impactful insights are findings that are unexpected and can readily lead you to new ideas and new opportunities.  Many times they provocatively challenge the status quo, mostly by looking at the broader context of the findings, whether by highlighting new voices (people) or new angles on old problems.  They generally are built on hardcore emotions, those that are brimming with passions and tensions.

Finally, impactful insights are generally found after sifting through several levels of “Why?”. If you’re still scratching your head on why consumers are saying what they are saying in the social space, you need to dig even deeper.

The great opportunity that social listening provides is that digging deeper is infinitely possible, with millions upon millions of conversations occurring over time that we can continuously mine for insights.  This means moving from simply tracking brand mentions, to understanding the underlying insights in a broader conversation.

One of the smartest people I’ve had a chance to work with in the social listening space, someone who truly understands the concept of insights versus observations, is Dan Neely of Networked Insights. In this blog post, Dan challenges researchers do go beyond mere brand mentions, and to focus on the broader context of the conversation through advanced text analytics in order to identify impactful insights.

His post also references this very relevant quote by Malcolm Bastien, who states that:

“Just like the enemy of web analytics is measurement of page views and visitors, the enemy of social media listening is listening only for brand mentions.”

In my next post I’ll show how by focusing social listening efforts on conversations that highlight passions, tension, and and the context around them, researchers can move their social listening efforts beyond simple observations to true, business building consumer insights.

January 18, 2010   6 Comments

Forecasting The Obvious With Google Insights For Search

Recently, Google announced a new forecasting feature for their useful Google Insights for Search.  At first blush, it would seem to be a great way to peer into the future and reach that nirvana of any good marketing researcher, the predictive insight.

However, after playing with the tool a bit, it’s not very clear that the utility of the forecasts is really anything more than a clearly laid out progression of obvious seasonality.

Here is a historical look at search behavior behind the term hot dogs, with the dotted line representing a forecast of future search behavior.

Google Insights For Search Hot Dogs

Based upon a quick look at previous years, though, you would see that you don’t need a sophisticated model to predict that there should be a big spike in searching on the term “hot dogs” coinciding with the start of the grilling season around Memorial Day, peaking at 4th of July, and then tailing off through the rest of the summer.

That’s not to say that understanding seasonality isn’t important in search.  In fact, it can be critical to providing a baseline in identifying deviations from the forecast, which is where the true insight lies.

What would be a more interesting tool from Google would be something that clearly laid out the historical trend in search, and then showed where search patterns began to deviate from traditional seasonality, say a spike in “Hot Dog” searches in February that were the result of a particularly effective Superbowl ad.

One really shouldn’t look a gift horse in the mouth, especially when it’s one of the many excellent free tools that Google provides for better digital insights.  However, researchers need to be cognizant that just because an observation comes to a brand digitally, doesn’t mean that it’s automatically innovative and insightful.

Forecasting data that moves beyond the obvious should always be the goal.  Unfortunately, it’s not always easy, as Nobel Prize winning physicist Niels Bohr so humorously captured:

“Prediction is very difficult, especially of the future.”

September 27, 2009   2 Comments

Twitter As The New Focus Group

The past week has seen a tipping point for Twitter, with the cultural touchstone being Oprah starting her twitter career @oprah on Friday, and by Monday morning having over 400,000 followers.

Twitter itself has seen tremendous adoption growth in the past couple of months, most driven by the cult of celebrity that has grown up around people such as Ashton Kutcher and Shaquille O’Neal.

twitter-growth

And according to this ComScore post by Sarah Radwanick, this growth is occurring across a wide swath of US demographics:

twitter-demographics

What this broad demographic representation means is that Twitter may now be set to become the new holy grail for researchers looking for insights into what a wide range consumers are thinking and talking about.

The first application is monitoring the Twitter conversation around brands and ideas, which can be done very cheaply and efficiently.

The next level will be to approach Twitter as a focus group.  Tropicana found this out the hard way, with consumer feedback on Twitter coming fast and furious in the wake of its recent package change.

As Peter Shankman points out in this New York Times article on the Tropicana package change:

“Twitter is the ultimate focus group,” Mr. Shankman said. “I can post something and in a minute get feedback from 700 people around the world, giving me their real opinions.”

However, in the case of marketers like Tropicana, the trick will be to harness the insight power of Twitter before the product, package, or advertising makes it way into broader distribution.

April 21, 2009   No Comments

Monitoring Brands Across Social Media And Twitter

“One of these days, your boss will wander into your office and say “I assume you’re keeping track of which brands in our category are using Twitter””.

This is a very real world situation that marketers and marketing researchers will soon find themselves in, according to this post from Tom Cunniff at the iCPG blog.

This applies to social media in general as well.  For broader monitoring, I wanted to build on a social media monitoring approach that I’ve blogged about before and that recently Chris Brogan did a good job outlining as well.

But rather than using Google Blog Search, I’d suggest using the new RSS feed functionality that Google Alerts rolled out a couple of months ago, in order to aggregate the significant amount of online content that exists outside of formal blogs.

1.)  Develop Key Words To Track

This could be a brand name (“Energizer”) or a specific topic “homemade barbecue sauces”.  Start by typing the word or phrase in quotes in Google to see how relevant results are with the phrase.

If your brand name is also a word with multiples meanings such as “Tide”, you may need to add something like the word detergent to keep from capturing conversations on surfing or beach combing.

You can also track:

  • A URL for a Website
  • A person’s name or online nickname

2.)  Getting the search feeds:

Once you have the keywords, it’s simply a matter of setting up a search feed with different social media monitoring tools.  For the three listed below, that means adding your keywords to their search box and then clicking on the RSS subscription button to get the auto-link:

  • Google Alerts – for online news, videos, images, and other sources
  • Technorati – for monitoring blog postings
  • Twitter Search – for brand chatter on the Twitter micro-blogging platform

3.)  Aggregating Feeds In Google Reader

By collecting these feeds into one folder on Google Reader, you can monitor all your brand related mentions from social media in one convenient place.

Another good aggregation tool would be Friendfeed, especially for those who are trying to distribute their monitored content to a far flung group.

That way you can send your boss the link, and he’ll never even get to ask if you’re on top of social media and your brand.

March 31, 2009   No Comments

Modeling Search Data For Predictive Insights

hitwise-logo

A great presentation last week by Bill Tancer of Hitwise Intelligence has broken me out of the winter posting doldrums.

His topic on levering search data for consumer insights is one of my key interest areas on the bleeding edge of marketing research, and he did a great job of demonstrating the predictive power of modeling search data trends.

One of his most compelling talking points, reflecting the current state of the economy, showed an updated chart from this older analysis on the correlation of unemployment website visits with actual unemployment claims.

Google has gone here before as well, with their demonstration of the Google Flu Trends application, and how search data can be predictive of CDC confirmation of regional flu outbreaks by a couple of weeks.

Both of these examples illustrate how the modeling of aggregated search queries can be an incredible source of insights into consumer intent.

There are a couple of white space areas for marketing research with search data, and all worthy of further pursuit.  For me these include:

  • Analyzing search terms associated with digital marketing campaigns at the metro area level in order to link digital behavior to a store level or DMA based marketing mix model.
  • Identifying the most predictive search terms (“grocery coupons”) that best correlate with widely tracked consumer attitude and behavior metrics (Conference Board’s Consumer Confidence Index) in order to understand where consumer sentiment is heading before the competition does.

For a better understanding of the modeling technique behind Google Flu Trends, download the PDF and Excel files that illustrate their method as it appeared in the February 19th issue of Nature.

March 30, 2009   No Comments

Social Media Impact On Consumer Behavior

While brands are beginning to reach out to consumers in social media in significant ways, the question remains on whether or not consumers will be receptive to their outreach.

According to a study entitled “The Impact of Social Media on Purchasing Behavior” done by OTX Research on behalf  DEI Worldwide, the answer is yes.

The study confirms that consumers currently use social media as a top resource for information on brands, companies, or products:

where-do-consumers-search-for-information

What it also concludes is that social media outreach by brands and companies, especially if this outreach is done by a personal online representative, can be much more influential on consumer behavior than ads or other promotional devices.

In fact, 2/3rds of consumers are likely to pass the information they receive from these representatives on to others and over half are likely to take action on this information.

Attitudes towards information they receive from online brand representatives

  • Likely to pass this information on to others – 67%
  • Likely to share their opinions – 63%
  • Value information more than ads – 62%
  • Likely to take action – 57%

Currently, most companies are viewing social media as something to manage or handle damage control, like many of the top brands involved with Twitter.

However, by using social media as a proactive outreach to share valued information, the impact of social media on consumer behavior can be significantly stronger.

December 31, 2008   2 Comments

Motrin Wins Social Media Marketing Campaign Of The Year

On Saturday, Motrin posted the ad below:

YouTube Preview Image

What followed was a viral social media response that most marketers can only dream about.

In just 48 hours they had:

Additionally, they had the undivided attention of many of the leading pundits in the digital marketing blogosphere, including Seth Godin, Jeremiah Owyang, Brand Flakes, Adfreak, ReadWriteWeb, Hard Knox Life, David Armano, Frank Martin, The Consumerist, Adrants, Mashable, Viral Blog, Peter Kim, Adverganza, Brand Experience, Rogue Agency, and many more.

Now to the fine print:

This social media marketing campaign was all a big, unintended mistake.  And as you may guess, the overwhelming response was negative.

Motrin is now backpedaling, pulling the ad from their site, posting apologies all over the place, and they and their agencies are probably in an all points scramble mode.

Which is all too bad, because, if you just looked at the response numbers, Motrin had a lock on social media marketer of the year with this one.

November 17, 2008   1 Comment

Search Engine Research 2.0

With the announcement of its innovative use of search data to track the spread of the common flu, Google Flu Trends has allowed Google to lever the enormous potential of search analysis in order to track the most viral (pardon the pun) of trends.

Search Engine Optimization 2.0 and Search Engine Marketing 2.0 as concepts have dominated digital media over the last couple of years.  And now with Google Flu Trends the concept of Search Engine Research 2.0 is truly coming into its own.

Google Flu Trends is based upon the aggregation and analysis of the search behavior of people who type the flu symptoms they are experiencing into Google in order to confirm their self diagnosis and to look up potential treatment options.

Google has found there is a close relationship between the amount of people searching on flu symptom related keywords and the amount who actually have the flu itself.

In the chart above you can see how Google Flu Trends has been well correlated with data from the Center of Disease Control on the level of flu cases being reported in the US over the past several years.

The advantage with Google Flu Trends is that the data is available a couple of weeks ahead of what the CDC compiles and announces.

Google Flu Trends is a good demonstration of the potential of the large and relatively untapped potential of levering search data for marketing research and consumer insights.

I look at what Google is doing with its Flu Trends tracker as bit of kicking the tires and taking their data for a test drive around the block.

When researchers finally take this information out on to open road and push things to the limit, that’s when we will really start realizing the full potential of search engine research.

November 14, 2008   No Comments

Insights Into A Data Driven Election

With the 2008 Presidential election now almost a week behind us, the media is filled with backwards looking punditry on what lessons this campaign will inform history with.

But of all the unique aspects of this campaign, one thing that stood out was the use of data and how that influenced strategy, especially with the Obama campaign.

His unique electoral strategy of looking outside the typical swing states into areas where Republicans have always been strong (Colorado, North Carolina, Virginia) was driven by statistical analyses that showed how changing demographics in these typically Republican areas provided opportunities for a Democrat willing to take advantage of them.

I tend not to be very politically minded, but one site that fascinated me throughout the election season was Nate Silver’s FiveThirtyEight.com blog (538 being the number of electors in the Electoral College).

Throughout the campaign, he aggregated all the available polls and then analyzed them using regression analyses to find out what their outlier tendencies tended to be.

He then weighted the polls and re-simulated the election 10,000 times per update in order to, in his words, “provide a probabilistic assessment of electoral outcomes based on a historical analysis of polling data since 1952″.

And his accuracy throughout the election process was remarkable.  According to this New York Times article entitled “This Math Whiz Called It For Obama Months Ago”, in the primary election versus Hilary Clinton, Silver “projected Senator Obama would win 833 Super Tuesday delegates, which was within about a dozen of the actual vote estimates”.

Additionally, when the returns came in on election night, it was found that “Mr. Silver had predicted the popular vote within one percentage point, predicted 49 of 50 states’ results correctly, and predicted all of the resolved Senate races correctly”.

What will be interesting to see is how this new approach to the analysis of polling data will have an effect on future elections.  What is certain is that the data driven approach to election strategy is probably here to stay.

November 10, 2008   No Comments