Brand equity refers to the size of a brand.  A brand with high brand equity has lots of customers, big market share, and a presence in the marketplace that leads one to believe that it will stay big.  Take two brands—Microsoft and Apple.  Both have lots of brand equity and because the corporate name is the brand, we can think of market cap as reflective of brand equity.  I am an outsider to both firms but I think the marketplace would believe that the trajectory of the two brands is somewhat different at this point.  Their brand health is different.

So, let’s think about brand health.  When David Meer and I worked together at The NPD Group, we had an impromptu “Synectics-style excursion” one day to explore the meaning of brand health by thinking about how you can tell if your dog is healthy.

Signs your dog is healthy

• Has a normal appetite
• Comes when you call it
• Looks like the breed it is
• Heals fast
• Puppies need to grow into their paws to normal size
• Has a bright, shiny coat
• Doesn’t have accidents in the house
• Cold, wet nose

So, following the metaphor, here are the signs that your brand is healthy

So, we’re not talking about the size of the dog, we’re talking about if it’s healthy.  Brand health is critical to understand and measure because it is predictive of the future.  A big brand that is unhealthy won’t stay that big for long.

OK, that brings me to my final point.  At the ARF Research Transformation initiative, we talk about “The River”.   Today in our digital society there is a constant river of information that is fed by numerous tributaries.  The river is flowing continuously so conversation about your brand and people’s needs don’t happen on your schedule but on theirs.  Someone can search for your brand (or a competitor) anytime they choose to. Today, tracking surveys alone are not enough to fully understand brand health.   We must also look in the river and consider ALL the signs and signals in a digital age to see if your brand has a cold wet nose.

Cass Sunstein, co-author of Nudge, created this idea which is about deciding how we are going to decide.  As an example (mine, not his), let’s say you want to buy a smart phone but know there are an overwhelming number of options.  You might manage this by doing a lot of research ahead of time (online, ask friends, observe what others have) to make it easier to decide when you get to the store.  That decision STRATEGY is your second order decision and what you actually buy when you get to the store is your first order decision.

Shoppers can be segmented and targeted based on their second-order decision strategies. When we can repeatedly observe how a shopper decides, like in packaged goods, it is likely that a shopper mostly exhibits the same path to purchase for a given type of product, as their underlying decision strategy is likely to be very stable for a given product category. For example, if you know there are sales to be had on bottled water and you wait until an acceptable brand is on sale, you are a “system beater” (a term I helped to create in 1994).  That strategy of searching for sales becomes the core of the shopper’s second-order decision. The first-order decision becomes greatly simplified with that strategy (buy/not buy, how much).  Not all shoppers are system beaters (for example, some are highly brand loyal) suggesting that shoppers can be segmented on their decision strategies and marketed to in that way.

Second-order decision making can be affected by marketing and the economy.  During the recession, I believe that many shoppers changed their second-order decisions.  People’s shopping patterns were greatly affected (more planned purchases and acceptance of store brands increased.) imagine the heuristic at point of purchase becoming “see if a national brand is on sale; compare price to the store brand”.  Dramatic increase in the use of coupons has been documented (highly intensive second-order decision-making/searching for sales that then simplifies the first order decision).  It is the changes in second-order decision strategies that have challenged the value proposition for national marketers. 

Do you want the brand decision in or out of the store? A national marketer with strong brands wants the brand decision to be made at the time the shopping trip is being planned, not in the store.  In other words, they have a strong preference for people using a PARTICULAR second-order decision. What are marketers doing to encourage the second-order strategy that benefits them?  How are their packaging and website encouraging consumers to simply use habit and replenishment as their decision strategy? If you are the new brand or a price brand, how are you DISCOURAGING people from doing that and encouraging shoppers to be more explorative?

What type of second-order decision do you want people to use? I imagine that AT&T and iPhone do not want people to have a high-effort second-order decision strategy.  They want people to just go to the AT&T store and get the leading smart phone (iPhone).  Verizon and Motorola Droid should want people to get curious and to engage in much more information search; a highly engaged second-order decision approach.  In other words, the marketing battle needs to be fought on shaping people’s strategies for deciding and targeting those who have the preferred second-order decision strategy.

One way to get people to engage in a more evolved second-order decision process starts with the realization that it is a coping mechanism when people perceive many available choices.  This idea turns the Schwartz Paradox of Choice concept on its head.  Choice is NOT bad; people want choice to reflect their individuality (that’s why there is a long-tail of choices.) However, when there is a lot of choice, people cope by employing heuristics and second-order decisions to simplify the first-order decision.  Hence, more PERCEIVED choice leads to involved pre-planning. That is what iPhone COMPETITORS should want; get people to see the choices out there.  On the other hand,Apple should want to convince people there is really only one choice.  The battle is waged over the second-order decision strategy.

How can Apple (or any market leader) take a marketplace where there are many choices and make it one with few perceived options? Own the one thing that people should really care about. Taversky pioneered the concept of “elimination by aspects”; all items that don’t possess a certain desired feature are immediately put out of consideration. Dr.  Gerd Gigerenzer has documented many simplifying heuristics that people use, including “take the best” which describes an approach of focusing first on the attribute that is both the most important AND that differentiates the choices. We become blind to other choices.  That’s why Schwartz’ Paradox of Choice is misleading for marketers. 

How do we recognize? The final point I want to make today is the importance of understanding how we recognize things.  When the second-order decision carries the entire load, the planned purchase becomes a foregone conclusion.  Then, the retailer and manufacturer challenge shifts from influencing decisions to influencing recognition.  Gregory Bern, in his book “Iconoclast” talks about perception as a predictive system, where low level visual stimuli are interpreted via retained images and concepts. What cues will best connect your brand to this “predictive system” that people use to recognize things?

Behavioral economics has given us a new path to marketing opportunity.  Let’s study how people decide.

This is the second of two posts on applying behavioral economics to marketing issues.  The first posting is here.

1. Mobile. Not mentioned in 1995 because it wasn’t thought of as an advertising or entertainment medium. Now mobile is at the top of everyone’s list to understand and measure better.

2. Set top box data. A compelling opportunity to get the granularity needed for media properties on the long-tail

3. Social media. Nuff said

4. The human. In 1995, we were focused on the consumer. As Stan Stanunathan from Coca-Cola says, when you focus on consumers you get incremental ideas. When you focus on humans you get breakthroughs.

5. Listening. Not a term the research community was using. Today it is central to generating future-focused insights and there were numerous presentations that leveraged the concept of listening.

6. Insights. In the 1995 brochure the word “insights” appeared only 4 times while the word “research” appeared 179 times. In 1995, we were still focused on the activities and craft of research.

7. Storytelling. This was the agency domain and only recently became a part of research impact

8. Sub-conscious mind. Especially on the biometrics panel, the idea that certain feelings, reactions, etc. are simply not accessible via the conscious mind. How do people make decisions? The model of the rational consumer has been forever overthrown.

9. Shopper. Shopper insights and shopper marketing are important parts of driving brand growth. They weren’t talked about at an advertising research event 15 years ago.

10. Long-tail. Amazon was just being founded in 1995 and before that, physical stores had limits to the choice they could offer. Unlimited choice via online retailers and media has created a level of market fragmentation never before seen.

11. Online research data quality. Online research didn’t really exist in 1995. Online research is such a dominant mode that the quality of the data must be beyond question.

12. We research. In 1995, each respondent was still a separate entity and not encouraged or even allowed to talk with anyone else. Now, firms are attempting to capture the dynamics of social interaction on individual choice in both quantitative research and communities.

13. Online and mobile video. Barely touched on in 1995 but now is a major force that every TV network needs to integrate into a 360 experience with their media properties. At first thought to be a threat to TV, now online and mobile video are thought to actually enhance engagement with the media property and increase TV viewing.

14. Multicultural is the new mainstream. We WERE talking in 1995 about how to conduct valid research among Hispanics but now it is mission critical. Non-Hispanic whites will be the minority in the US in 30 years and this has already happened in a number of major markets.

15. New business giants have emerged since 1995 that have changed the way people live their lives. The list includes: Google, Facebook, Twitter, My Space, LinkedIn, Flickr, Apple iTunes/iPhone/iPad/stores, Hulu, Youtube, Foursquare, Huffington Post, Techcrunch, Zappos, Fox News, Skype, Wikipedia, Firefox, DirecTV, Tivo, XM radio, NetFlix, Pandora.

Our lives are forever changed and are forever changing…truly there is a constantly changing new normal where the past is less and less predictive of the future. Marketers must use new approaches and adopt a new corporate culture to become fast-learning organizations, or they will find their opportunities in the new normal defined by a future that is not of their own making. Please take a minute to look at the video the ARF prepared, with the help of Thinktopia, entitled, “Inspiring Better Brands”.

As the ARF continues to release results, we want to share more insight on that important question here.

As can be seen in the two tables below, there is no clear pattern of RDD providing the more accurate answer vs. the average result from internet panel research on a series of benchmarking questions and demographics. The biggest failures of RDD are in age of respondents and cell phone usage probably due to an increasing percentage (20% currently) of people in the US only having mobile phones and not having landlines.

While a research supplier can weight data (also called “post-stratification”), the demographic imbalances from RDD are problematic. The more skewed the sample is, the more extreme the weights, the lower the “RIM efficiency”. This is an important statistic as it tells you the effective sample size. For example, an ending sample of 1,000 and a RIM efficiency statistic of 40% implies that your sample has the variability of a sample of 400.

Clearly all modes have their challenges and require their own custom-tailored best practices to produce trustworthy information. Even in the world of political polling, RDD interviewing methods can produce very different results and might not be as accurate as well-designed online research. Professor Costas Panagopoulos from Fordham’s Political Science Dept analyzed the accuracy of 23 presidential polls regarding the 2008 presidential election. While nearly all polls use RDD telephone methods, the one poll I recognize as an online poll actually finished third in accuracy (ahead of 20 or so RDD-based polls). Also, 17 of 23 polls OVERESTIMATED Obama’s margin of victory, indicating a clear bias from RDD polling. Interestingly, some of the best known polls (e.g. from the original national networks and Gallup finished at the bottom of the list.

Recently an old 2004 study that also compares online to RDD research managed out of Stanford University has resurfaced with some re-analysis of the 5 year old dataset. Due to the rapid rise of cell-phone only individuals and the apparent failure to employ what would be considered best practice today regarding pre-stratification of online samples, this study is of limited relevance today. (See pollster.com.)

Our evidence from Foundations of Quality is that online research can produce comparable, consistent, and accurate data if proper practices are implemented. If not, for example, if we do not control for sample source, a project can yield data that are not useful. On Sept 29^th, the ARF will share a process we have co-created with industry leadership that will allow buyer and seller to work collaboratively to produce online research that can be used with confidence to inform marketing decision making. This meeting is open to all, including the press.

Joel: Can stories be used to convey quantitative research findings too?
Michael Perman: Yes, but it’s a matter of focusing on a small number of facts that are truly meaningful. Maybe even on specific metric about consumption or equity. Too many reports try to cover too much ground and people lose sight of the big ideas. Also, facts sometimes need to be validated with human connections…not always the other way around.

Joel: Can you describe the training you do at Levi Strauss and how it impacts the organization?
Michael Perman: We’ve trained more than 7,000 employees around the world on developing innovation from insights. We’ve taught them how to observe and listen to consumers, how to tell stories about their experiences and how to synthesize cogent themes. Empathy is a company value. That ethos helps us get grounded in the reality of our consumers’ lives.