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I got a DVR five or six years ago.  I wasn’t exactly an early adopter, but I must say I love it.  I record everything, often watching a program a mere 20 minutes after it starts to avoid the commercials.  I know I’m not alone.

Don’t get me wrong.  Good advertising I really like.  But so much of it is bad – or stupid.  The DVR lets me watch commercial-free if I want to.

Among DVR owners in Nielsen markets (37%), Nielsen recently reported that 40-50% of commercials are watched during playback, up from earlier estimates of 30-40%.  (Source:  MediaDailyNews, 8/5/10)

I’m not sure what to believe about this:  Commercial viewership up among DVR owners?  Really?  Or did Nielsen change how they’re measuring things? One hypothesis I had was that more recent DVR adopters could be less sophisticated/less comfortable using the fast forward/jump feature on their remote controls.  But Nielsen says that DVR playback is happening more among younger and higher-income viewers, so I can’t imagine my hypothesis is true.

While DVR viewership isn’t universal, these “facts” got me asking a few questions:

• Who’s not watching ads – consistently?  Do they have any identifiable characteristics that we can plan around?
• What are the best, most effective ways to reach these ad-skippers in other media and/or via other ways on TV (e.g., product placement, sponsorships, etc.)?
• What defines “stopping power” in a TV ad today, and how is it measured, particularly among DVR viewers?   I would think that the first and last ads in a pod would have the highest viewership, yet is this reflected in the numbers agencies are getting to calculate impressions?  Related to this, for researchers/account planners, is there a method out there for testing ads in a program-embedded clutter and letting people skip as they would at home, to get at stopping power and ad effectiveness?  Plus, can ads be tested at fast-forward speed to assess their stopping power?
• What impact is all this having on brand awareness or brand image?  Have any tracking studies been done among ad-skippers vs. those who fast-forward through ads vs. ad-watchers to see what impact ad viewing behavior has on these critical brand measures?

As I write these questions from my logical left brain, I have to remind myself that how we take in information isn’t very well understood.  I might not “know” the latest musical phenom, but I always seem to have heard the tune before I learn the artist’s name or see their face – and this is without kids at home.  What goes on around us seems to sink in and have an impact.

I don’t know the answers to the questions above, and maybe I’ll dig around to learn a bit more.  Yet it’s clear that whether TV ads are skipped or seen, consumers continue to form impressions of brands.  And since no matter how hard we try, not everything that impacts them will be known or measurable, I feel more strongly than ever that having consistent brand values which shine in all we do – and being present where our target lives – is the best foundation for the relationships we want to have with them.

While I do a lot of qualitative research in Los Angeles (where I’m based), getting a good cross-section of the client’s target takes me to other cities.  We pick those cities with care, yet often there are major-market favorites. For example, Chicago gets picked far more often than St. Louis or Kansas City.

A project last week reminded me once again how nice it is to include even smaller markets in the mix.  I drove to Bakersfield from Los Angeles, only an hour and a half drive.  (Bakersfield is much smaller than Kansas City, with slightly less than 400,000 in the urban area.)  The client picked the market as it’s a good market for them.  There isn’t a focus group facility in the area and there is no longer a recruiter based in the market.  But I got great respondents (using my LA recruiter) who didn’t have prior research experience, who showed up on time (a good incentive strategy worked!), and who really helped to give us the needed insights.

I had a similar experience many years ago when I had a client who loved the Atlanta market, yet after three projects in a row where we had “dud” groups, we both decided to drive up to Chattanooga, TN.  The facility was in someone’s house.  Again, the respondents were great, candid, and while not as sophisticated, they gave us a perspective that we hadn’t heard before.  (And what a lovely city!)

Online qualitative research does afford us the opportunity to include more of these participants in the mix, but a lot of the smaller markets may still experience some problems with Internet connection speeds.

BTW, I’m not recommending that small markets always be included in market selection – that depends on the client and the target.  However, if you’re going to three or more markets, you might want to consider one of the smaller gems to add perspective to your exploratory undertaking.

Last week, Ad Age published an article where the following comment was made about the convergence of shopper marketing with digital technologies:

“The killer app of mobile media may yet be in the store, as more consumers use their mobile devices to scan barcodes and get product reviews, coupons, or other promotional offers.”

Think about that for a moment.  When the Internet came along, it had a tremendous impact on shopper behavior; we did much of our researching and browsing online (even if we didn’t always purchase online).  Now, in a short time, with our mobile phones, we’ll be able to can scan a barcode and get reviews, coupons and other offers?  Wow.

As stores move to visually de-clutter (a big move of late), imagine creating your shopping list using a special app and then walking into a store where the app would scan the store and the store would send you all the specials in the categories of your choice.  Any manufacturers coupons that week?  Send those too.  Oh, and to save you time, we’ll tell you what aisle to find the merchandise – maybe even map a shopping plan for the store to save you time.  Finally, at check out, your mobile device would send the correct coupon information to the register via Wi-Fi or IR; other promotional offers could be sent to your phone if you’d like.

How to get that killer app to market fast?  Also last week, Mob4Hire announced the first “crowd-sourced mobile market research” service.  They have more than 20,000 application testers (mobsters) operating in 105 countries.  How this works is that when a new application is ready to be tested on the more than 330 mobile network carriers around the world, the mobsters download the test app to their mobile phone, test it on their network, and provide feedback to the developer.  Fast, comprehensive, and very cost efficient relative to how this is typically done today.

Where does this take your imagination?

When the focus is on metrics or statistics, there are really three things that marketers must know to use them effectively.

#1: Observed and Expected

Statistics typically are based on a simple equation:  “Observed minus Expected.”

Ex 1:  Comparing the target audience (the Observed) against the total population (the control or Expected).  High or low indices can inform marketing strategies and tactics.

Ex 2:  Assessing company sales performance, where the actual sales (Observed) are compared against prior sales (Expected).

Even as statistics get more complex, we see this.  An “average” (aka “mean”) is another way of saying “Expected.”  Conjoint (trade-off) analysis, a complex multivariate technique, works under the assumption that at the start, all attributes have an equal chance of being selected.

Most marketers don’t know it, but they “talk” in “Observed minus Expected” all the time:  “If we do A, I hope to see B change by X.”  Measuring that goal becomes the foundation for designing research, for the statistics used in analysis, and for seeking unexpected insights.

(For those of us into social media/discourse analysis and data mining, a special note:  there often isn’t an “Expected” with these methods, which is one reason why they’re harder to analyze.  The goal, moving forward, is to start establishing benchmarks against which findings can be assessed – or it will always be difficult to separate new, critical insights from the undefined norm.)

#2:  Correlation vs. Causation

Because two things are related doesn’t mean that one thing caused another.  We know that over-eating (unfortunately) causes most people to gain weight.  However, most smokers – some say 90% of them – don’t get lung cancer.  Smoking doesn’t cause cancer, but it’s clearly a (correlated) high risk behavior because many more of those who smoke will get ill when compared with those who don’t.

How does this impact marketers?  You can’t really assume that doing A will cause B to happen.  However, business models built on connections between operations, consumer attitudes, behaviors, etc. are very powerful in finding ways to reach business goals.

#3:  Compound Findings

Independent facts can’t be compounded or strung together to simplify the “story” being shared with others.

Does this example tell us that our target should be women, age 25-34, who participate in outdoor sports?  Not necessarily.

Assuming a perfectly distributed sample, we’d estimate that the target is 25% of our population (65% x 65% x 60%).  But what if all the men – this is a hypothetical! – said they were into outdoor sports?  That would mean that only 25% of the women said the same – reducing our estimated target size to 11% (65% x 65% x 25%).

While compounding or grouping results makes for a clearer story, marketers need to know that the story may not be accurate.

I’m a consumer advocate.  To advocate for them – to give them voice in the business decision-making process – I must know the best ways to learn from them.

As new techniques are developed, I can embrace them, refine them, reject them, or even create something else that will work better for my clients.  I want a large arsenal of effective tools.  And, when needed, I want to be able to combine approaches to address the client’s objectives in the best way possible.

The current trends in marketing research highlight four rather distinct quadrants in which work is conducted.  A simplified overview is shown below.

Historically, most marketing research has fallen into what I’m calling the Sociologic quadrant – participants know they’re in a test environment and they often interact with an interviewer/moderator + other participants; additionally, verbal skills often have a prominent role.

Physiologic testing has been around for years.  It measures a physical response to test stimulus, such as  eye tracking when conducting a copy test or website evaluation.

Ethnographic (or observational) research, with its roots in anthropology, has become quite popular in recent years.  In its purist form, participants don’t know they’re being observed and less emphasis is placed on verbal responses.

Discourse Analysis is the newest approach, and is currently the hottest topic in marketing circles.  These methods analyze social media, such as postings on Facebook, Twitter and personal blogs, by studying the language used.

In the coming weeks, I’ll take a closer look at each quadrant in more detail.  In the meantime, I’d enjoy hearing your initial thoughts about this concept and how it might be used to help clients understand why different methods are being recommended.