Consider search engines.  How many of you actively decide which search engine to use for a given search you have in mind vs. just using the one that is habitual for you (Google for 2/3rds of us)?  “I don’t even think about it” is often the predominant factor in behavior yet we don’t really study this.

Do you think it’s easier to get someone to try a new restaurant in their neighborhood or to switch search engines?  In one case we are actively seeking, and in the other case, we are sensing…responding to cues in an automated and unconscious way as Dave Lundahl, founder of InsightsNow, Inc. might say.  The ability to gain trial for something new is clearly easier when someone is already “seeking” so the degree to which habits drive pre-existing behaviors is key to understanding the potential for a new offering.

Even in your business life, you are governed by habits and rituals.  Think about how you check e-mail in the morning and how you get your daily briefing.

Now, consider how most concept testing and choice experiments work.  We throw all of that insight about habit out the window.  We put people into choice and decision-making mode whether they are ever there in real life or not.  We force people to tell us if they are interested in a particular new product idea without measuring if they are interested in any new product idea at all for a given situation.  Yet, the key for new product adoption is disruption of existing habits and rituals.

We need to  break the concept testing habit and start researching new product adoption in ways that are closer to how people really decide.

Behavioral economists like Dan Ariely understand this.  They understand that people have heuristics, “little tricks”, that allow them to decide in non-fully compensatory ways…basically, the reality is exactly the opposite from how choice experiments and traditional concept testing work!

Traditional concept testing does not study how people decide, it merely gets at purchase interest IF they were deciding.  Usually less than half of those who say “definitely would buy” ever buy for this reason; we are forcing people into active decision-making mode when many are not there in real life.  This unnatural situation is what creates such poor individual-level predictive validity for purchase intent.

First and foremost, a new product must disrupt existing behaviors or leverage behaviors that are already disrupted to be “seen” by the consumer.

In real life, disruption is all around us in an age where digital technology is producing bone-rattling change in everyday life.  Imagine location-aware offers, brand stories, and payment all converging at point of purchase via your smart phone; this is already happening in parts of Asia.  As touchpoints emerge (weekly it seems), marketing and research approaches need to constantly evolve.

We need to start studying how people decide and how to break habits. I have developed a strategic partnership with InsightsNow to create a next generation of innovation development and testing methods that will get at this concept of disruption. Hopefully, we can induce marketers to align lean forward research methods with contemporary marketing thinking and break the traditional concept testing habit.  Maybe then, finally, CPG will do better than the 80% new product failure rate.

Please attend the webinar on this subject on May 25^th, at 2PM Eastern time.

If so, Marketers are missing powerful insights into brand health and growth strategies, especially in a digital marketing age.  

Brand health. Brand equity is your biggest asset. So it follows that brand health is your most important analysis because it is about understanding if that equity is poised to grow or decline over time and what you can do about it. Like the beautiful symmetry of a baseball diamond, there is a certain geometry to a brand.  If that geometry is intact, the brand is healthy.  If the geometry is broken, it looks just as wrong as having different distances between the bases. The geometry includes relationships such as the following. The market leader must have the highest repeat rate, and the greatest number of buyers. The geometry encompasses attitudinal patterns, where attribute ratings for a leading brand are always higher across the board, referred to as the “halo effect”.  Brand geometry relationships can be modeled with a high degree of statistical accuracy. When that geometry is broken, your brand’s market share is going to move back to an equilibrium point.  For example, if a leading brand’s repeat rate is not commensurately higher, or if it does NOT have commensurately higher attribute ratings its share will almost certainly decline over time.

Segmenting your buyers based on loyalty. To direct optimal strategies in digital, the most targetable of all media, we need to first extend these “macro” relationships between loyalty and market share to the micro or individual level because different loyalty groups require different marketing approaches. Let’s segment your buyers by loyalty level into, say, 4 groups based on their probability of purchase towards your brand.  Let’s make the top group those consumers who buy your brand 75% of the time.  The next group buys you 50-75% of the time.  The third group buys you 25-50% of the time and the fourth group buys you a small percent of the time probably because they are loyal to some other brand.  Where does a higher repeat rate for a market leader come from?  It comes from having disproportionately more of its buyers being in the top two loyalty groups vs. a smaller brand.  Again, if this is not the case, a leader will decline.

Brand loyalty and digital brand growth strategies. Now, let’s apply loyalty segmentation to digital behaviors.  With this loyalty segmentation in mind, what do you think the distribution of fans to your brand’s Facebook page is proportionately distributed?  Probably not; it is unlikely that someone who rarely buys your brand will friend or follow you.  How about the middle two groups?  Are they more likely to be visiting the coupon-related shopping sites? What do people search for that leads them to visit your brand microsite?  Are the referring search terms different for loyal vs. marginal buyers?  Probably there is more trademark search for loyal buyers and more discounts, comparison, and issue-related searches for less loyal buyers.  Have you optimized search with this in mind? What does each loyalty segment say about you in social media conversation?  Is it the same pool of comments or are they saying very different things? (I bet they are.)

Some marketers, in the era of engagement thinking might believe that you don’t have to care so much about the less loyal buyers except how to make them “engaged”.  This is actually a mathematical mistake.  If you analyze the sales changes from the four loyalty groups of a growing brand you will see a remarkable thing.  Sales actually must increase from every one of the loyalty groups!  (For the readers who are a bit wonky, as I proudly am, I am happy to describe this one on one if you contact me.) In other words, your brand growth marketing strategies must have a customized component that addresses each group, even the less loyal buyers.

Brand loyalty analysis proves that approaches which are exclusively based on building brand engagement are incomplete. I hope to bring back brand loyalty analysis for a digital marketing age.  It’s throwback, but with a modern marketing twist.

Let me illustrate with simple arithmetic why the click is a red herring measure of digital advertising effectiveness.  Click rates, on average, are around 0.1% (one tenth of one percent) on a good day. However, Gian Fulgoni, President of Comscore who was the lead author on an article (JAR, 2009) entitled “Whither the click?” showed an average lift of 1.4% percentage points (off of a base of 2.1%), test vs. control in visitation to the advertiser’s home page in the first week after ad exposure.  That suggests that the total effect of digital advertising (view through plus click through) is about 10 times greater than can be accounted for by the click!

Let’s create some sample math from Gian’s article to understand this.

• Propensity to visit the home page without an ad: 2.1%
• Say, 0.1% click on the ad and assume that takes them to the home page, so propensity to visit the home page after clicking is 100%
• This implies that the propensity to visit the home page if you do not click but are exposed to an ad is approximately 3.4% (an increase of 1.3%/99.9%)

Okay, so now let’s see where the leverage is.

If you can double the click through rate to .2% (hey doubling ad effects is really good), the increase in effect is about 1.4 to 1.5 or 7%.  However, if you can double the view-through effect (which presumably is like good old advertising effectiveness), the impact is close to double because over 90% of the lift in home page visitation was coming from the branding effect of display advertising in the first place.

Clearly, the leverage is in understanding and amplifying the effect on behavior of those exposed but who do not click on the ad.

When I look at dashboards of advertising effectiveness like from Double-click, click rate is most prominent.  If there is a conversion metric, it is still the percent of those who clicked that then matched to a conversion pixel.  The digital analytics infrastructure is not geared to report on the pathway by which 90% of digital advertising effect occurs!

To address this, advertisers must define what a conversion is (I believe that most do not, especially when sales occur offline) and then put the conversion pixel into the conclusion of that action.  It is not always a sale and perhaps should NOT be the sale but some behavior that is a highly correlated marker for sales.  It can be downloading a coupon, signing up for a database, requesting a price quote, sharing an asset, etc.  Then we must start tracking conversions based on exposures not only clicks. Important words for digital…behavior…highly correlated to sales.

None of this is beyond the realm of possibility because digital is all about behavior and gives us the opportunity to track this.  We CAN fully account for the effectiveness of digital display; Advertisers just need to start requiring the ecosystem and their chosen partners to start measuring the right thing, and start doing it in real time for digital advertising to fulfill its promise.

Consider the following comment from the head of digital at Pepsico beverages, Shiv Singh as part of a roundtable discussion:

“Another challenge facing brands is the pace of marketing. We’re living increasingly in a world of real-time marketing where reputations are built and broken in seconds. Marketing programs succeed and fail in that time span too. Unfortunately, most marketing organizations are structured for annual or semi-annual planning, budgeting, and executing. That tension is only going to grow…business models, staffing structures, and processes are aligned for a much slower world.”

So what does a commitment to real time sensing look like?  Here is an example from Gatorade of a mission control center.  Note how they bring together multiple streams of insights for instant feedback.

So what can we learn from these leaders about real time marketing?  Here are eight guidelines for what will it take.

1.       You are creating culture change so this must be immersive.  Screens everywhere and big hoopla with the launch.  The whole organization must be aligned to putting the human at the center of the marketing action.

2.       There are no boundaries or borders.  Everyone (all employees, partner organizations) should have access to insights instantly and simultaneously

3.       It is integrative. There is no one source that gives all the answers.  You must integrate the signals and find the common thread

4.       Real time insights must connect to real time action.  In digital marketing, ad serving rules and search keywords can be changed daily or even hourly.  Create real time sensing systems about what is working that lead to real time optimization of brand communication efforts and bidding.

5.       Real time marketing is becoming as much about place as it is about time.  As smart phone penetration increases, the opportunity for location-aware offers, messaging, and consumer metrics will go to a completely different level.

6.       Marketing should become hyper-granular.  As we learn about the preferences and need state changes of people in real time, we must act in ways that are as relevant as possible before the moment passes.  For example. as I begin digitally signaling that I am considering buying a new car, say by sharing content with friends in Facebook or Twitter, you want to address relevant car messages to me at that point and feature relevant content.  The week before, those messages and content would have been much less relevant. Real time feedback on brand communication will become infinitely granular to fulfill the promise of digital advertising with real-time networks and ad serving.

7.       Marketing will move from integrated to vertically integrated. Think about the ability for Starbuck’s to build a community and via smart phone apps and location-aware social tools, activate those relationships when someone is in the vicinity of a Starbucks or a supermarket and even right at the point of purchase.

8.       All research and insights programs should be either designed to be real-time or not; “fast” is not good enough.  If you are building a sensing program to replace a traditional research method that used to take 8 weeks, 2 week turnaround sounds good but is still way too late.  To be clear, there is a role for non-real time research; for example, strategic learning research, concept testing, and product testing certainly do not need to be real time

Get ready for real time marketing now.  If you blink, you might find yourself permanently trying to catch up.

Marketers should want their bought, owned, and earned media to do four things:

1. create brand led shopping so you are not only in the consideration set, you start in the pole position
2. guide people through the pre-shopping process to reinforce your pole position as they  move from pre-shopping to shopping
3. seal the deal through smart shopper marketing (which now includes mobile) because most shoppers are still considering options at point of purchase
4. Reinforce and help shape brand experience

Here is a personal example of how advertising can create brand-led shopping that will illustrate the concept.  I don’t NEED a new car.  My BMW X5, which I got new in 2003, still has low mileage and works fine.  But then I started seeing ads for the Lincoln MKX and MyFord Touch technology and, well, I got the itch.  So what did I do next?  In yesteryear, I might have bought an auto magazine.  Today, I googled Lincoln to go to their website, and then I went to MSN.com to compare Lincoln MKX to Cadillac and, of course, BMW, since I still love my X5.  Behavioral Economists will be happy to note that I did NOT bother to check out the other 10 or so brands that MSN told me were comparable.  I have yet to test drive, but those are the three showrooms…Lincoln, Caddy, BMW…I plan to go to.

Lincoln’s advertising got me started in my shopping process, and put their brand in the pole position of consideration.  It is Lincoln’s game to lose at this point. However, the advertising did not make this a done deal.  If I don’t like the driving experience, or if it just doesn’t feel like me as much as one of the others, or if the dealership is rude, I will probably buy something else.

This view of media gives advertising an integrate shopper and consumer purpose.  Touchpoints must be used strategically as they are unlikely to be interchangeable. The special contribution of a mass medium like TV is probably to create brand led shopping while digital display, search, and owned media probably influence the pre-shopping stage more.  Shopper marketing, including mobile, becomes essential to win the purchase irrespective of how the shopping process got initiated.  Social media create a post-purchase community.

Finally, the measurement guy inside me notes that I didn’t use the word “awareness” once in creating a shopper-based view of how advertising works.  It really is time for a new set of shopper-based brand metrics.