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Dear Dr. Jay—Brands Ask: Let's Stay Together?

Posted by Dr. Jay Weiner

Thu, Feb 11, 2016

 Dear Dr. Jay,

 What’s love got to do with it?

 -Tina T. 

DrJay_Thinking_about_love.pngHi Tina,

How timely.

The path to brand loyalty is often like the path to wedded bliss. You begin by evaluating tangible attributes to determine if the brand is the best fit for you. After repeated purchase occasions, you form an emotional bond to the brand that goes beyond those tangible attributes. As researchers, when we ask folks why they purchase a brand, they often reflect on performance attributes and mention those as drivers of purchase. But, to really understand the emotional bond, we need to ask how you feel when you interact with the brand.

We recently developed a way to measure this emotional bond (Net Positive Emotion Score - NPES). By asking folks how they felt on their most recent interaction, we’re able to determine respondents’ emotional bond with products. Typical regression tools indicate that the emotional attributes are about as predictive of future behavior as the functional benefits of the product. This leads us to believe that at some point in your pattern of consumption, you become bonded to the product and begin to act on emotion—rather than rational thoughts. Of course, that doesn’t mean you can’t rate the performance dimensions of the products you buy.

Loyalty is a behavior, and behaviors are often driven by underlying attitudinal measures. You might continue to purchase the same product over and over for a variety of reasons. In a perfect world, you not only create a behavioral commitment, but also an emotional bond with the brand and, ultimately, the company. Typically, we measure this path by looking at the various stages you go through when purchasing products. This path begins with awareness, evolves through familiarity and consideration, and ultimately ends with purchase. Once you’ve purchased a product, you begin to evaluate how well it delivers on the brand promise. At some point, the hope is that you become an advocate for the brand since advocacy is the pinnacle of the brand purchase hierarchy. 

As part of our Consumer Pulse program, we used our EMPACT℠: Emotional Impact Analysis tool to measure consumers’ emotional bond (NPES) with 30 brands across 6 categories. How well does this measure impact other key metrics? On average, Net Promoters score almost 70 points higher on the NPES scale versus Net Detractors. We see similar increases in likelihood to continue (or try), proud to use, willingness to pay more, and “I love this brand.”


What does this mean? It means that measuring the emotional bond your customers have with your brand can provide key insights into the strength of that brand. Not only do you need to win on the performance attributes, but you also need to forge a deep bond with your buyers. That is a better way to brand loyalty, and it should positively influence your bottom line. You have to win their hearts—not just their minds.

Dr. Jay Weiner is CMB’s senior methodologist and VP of Advanced Analytics. He has a strong emotional bond with his wife of 25 years and several furry critters who let him sleep in their bed.

Learn More About EMPACT℠

Topics: NPS, path to purchase, Dear Dr. Jay, EMPACT, emotional measurement, brand health and positioning

Dear Dr. Jay: Bayesian Networks

Posted by Dr. Jay Weiner

Thu, Jul 30, 2015

Hello Dr. Jay,

I enjoyed your recent post on predictive analytics that mentioned Bayesian Networks.

Could you explain Bayesian Networks in the context of survey research? I believe a Bayes Net says something about probability distribution for a given data set, but I am curious about how we can use Bayesian Networks to prioritize drivers, e.g. drivers of NPS or drivers of a customer satisfaction metric.


Dear Dr. Jay, Chadwick Martin BaileyDear Al,

Driver modeling is an interesting challenge. There are 2 possible reasons why folks do driver modeling. The first is to prioritize a set of attributes that a company might address to improve a key metric (like NPS). In this case, a simple importance ranking is all you need. The second reason is to determine the incremental change in your dependent variable (DV) as you improve any given independent variable by X. In this case, we’re looking for a set of coefficients that can be used to predict the dependent variable.

Why do I distinguish between these two things? Much of our customer experience and brand ratings work is confounded by multi-collinearity. What often happens in driver modeling is that 2 attributes that are highly correlated with each other might end up with 2 very different scores—one highly positive and the other 0, or worse yet, negative. In the case of getting a model to accurately predict the DV, I really don’t care about the magnitude of the coefficient or even the sign. I just need a robust equation to predict the value. In fact, this is seldom the case. Most clients would want these highly correlated attributes to yield the same importance score.

So, if we’re not interested in an equation to predict our DV, but do want importances, Bayes Nets can be a useful tool. There are a variety of useful outputs that come from Bayes Nets. Mutual information and Node Force are two such items. Mutual information is essentially the reduction in uncertainty about one variable given what we know about the value of another. We can think of Node Force as a correlation between any 2 items in the network. The more certain the relationship (higher correlation), the greater the Node Force.

The one thing that is relatively unique to Bayes Nets is the ability to see if the attributes are directly connected to your key measure or if they are moderated through another attribute. This information is often useful in understanding possible changes to other measures in the network. So, if the main goal is to help your client understand the structure in your data and what items are most important, Bayes Nets is quite useful.

Got a burning research question? You can send your questions to DearDrJay@cmbinfo.com or submit anonymously here.

Dr. Jay Weiner is CMB’s senior methodologist and VP of Advanced Analytics. Jay earned his Ph.D. in Marketing/Research from the University of Texas at Arlington and regularly publishes and presents on topics, including conjoint, choice, and pricing.

Topics: advanced analytics, NPS, Dear Dr. Jay

Dear Dr. Jay: The 3 Rules for Creating Truly Useful KPI

Posted by Dr. Jay Weiner

Thu, Jun 04, 2015

Dear Dr. Jay,

How can my organization create a Key Performance Indicator (KPI) that’s really useful?

-Meeta R., Seattle

Dear Meeta,

CMB, NPS, KPI, Dear Dr. Jay, Jay WeinerA key performance indicator (KPI) is often used to communicate to senior management how well the company is doing, with a single metric. It could be based on a single attribute in the questionnaire, e.g., the top two boxes of intent to continue using the brand. Another popular KPI is the Net Promoter Score (NPS), based on likelihood to recommend, where we take the percentage of customers who are promoters and subtract the percentage who are detractors.

Over the years, likelihood to continue, overall satisfaction, and likelihood to recommend have all been candidates for inclusion in creating a KPI. We find these measures are often highly correlated with each other.  This suggests that while any one measure might be a decent KPI, there is a unique piece of each that is not captured by the others. Likelihood to continue and likelihood to recommend both have a behavioral dimension to them, while overall satisfaction is most likely purely attitudinal. 

There are a few key things to consider in selecting (or creating) a KPI: 

  1. The number should be easy to explain and compute. 

  2. It must be tied to some key business outcome, such as increased revenue.

  3. Finally, it should be fairly responsive to future changes.

In the third consideration, a balance of behavioral and attitudinal measures comes into play. If you’re trying to predict future purchases, past purchases are a good measure to use. For example, if my past 10 credit card transactions were with my Visa card, there’s a very good probability that my next transaction will be made with that same card. Even if I have a bad experience on the 11th purchase with my Visa card, the prediction for the 12th purchase would still be Visa. However, if I include some attitudinal component in my KPI, I can change the prediction of the model much faster.

So what is the best attitudinal measure? Most likely, it’s something that measures the emotional bond one feels for the product, something that asks: is this a brand you prefer above all others? When this bond breaks, future behavior is likely to change.

A final word of caution—you don’t need to include everything that moves. As your mentor used to say, keep it simple, stupid (KISS). Or better yet, keep it stupid simple—senior management will get that.

Got a burning research question? You can send your questions to DearDrJay@cmbinfo.com or submit anonymously here.

Dr. Jay Weiner is CMB’s senior methodologist and VP of Advanced Analytics. Jay earned his Ph.D. in Marketing/Research from the University of Texas at Arlington and regularly publishes and presents on topics, including conjoint, choice, and pricing.

Watch our recent webinar to learn about the decision-focused emotional measurement approach we call EMPACT℠: Emotional Impact Analysis. Put away the brain scans and learn how we use emotion to inform a range of business challenges, including marketing, customer experience, customer loyalty, and product development.


Topics: advanced analytics, NPS, Dear Dr. Jay

Roses Are Red, Violets Are Blue, Is Your Customer Loyalty True?

Posted by Dr. Jay Weiner

Wed, Feb 18, 2015

“How do I love thee? Let me count the ways.” “You’re my favorite brand ever.” “You’ve taken such good care of me over the years we’ve been together.” “I can see myself spending the rest of my life with you.” How many of your customers would say such things about you?

Loyalty is a behavior, and behaviors often have underlying attitudes that drive them. We might continue to purchase the same product over and over for a variety of reasons. Don’t get me wrong: repeat business is almost always a good thing. But, if it comes at a negative margin, it may not be a good thing. If you frequently incentivize your customers, you might be buying loyalty (deal loyalty), but are you making money doing it? If your deal loyals are promoting you, are they promoting the deal or your brand? In a perfect world, we not only create a behavioral commitment, but also an emotional bond with the brand and, ultimately, the company.

Many companies track the Net Promoter Score (NPS) as a measure of loyalty. This adds another potential behavior to the mix—advocacy. If we look at a traditional purchase conversion ladder, advocacy or evangelism would be at the top of the pyramid. Promoters are certainly advocates, but are they also evangelists? Is promotion really enough? Don’t you really want to know what they’re saying?

Advocacy is attempting to influence decisions. Evangelism is relaying information about a particular set of beliefs to encourage conversion. Advocacy may encourage lexicographic information processing—buy cheapest, buy fastest, etc. Evangelism should encourage a more holistic view of evaluating the brand. The implication is that beliefs are probably more deeply rooted in brand performance. This creates a bond with the brand that transcends getting a good deal. You want folks that are proud to wear your logo and serve your product as well as folks who would gladly buy other goods/services from you if you want to extend the franchise.

In a recent survey, we found that about 60% of brands promoters love the brand. If they don’t love you, what are they saying about you? On the flip side, over 80% of those that love you are promoters.  Clearly promoters have value to the franchise in helping grow the brand. As a company, you not only want more promoters, you’d like to believe they are, in fact, promoting the brand and the company and not something else.

How can we improve on tracking the NPS score? We find a way to capture the emotional bond of your true loyals. Those customers who love you will clearly go out of their way to buy you, pay more for your product or service, and proudly share your brand with others. Growing this share of your customer base will certainly help you grow both the top line sales and bottom line net profits.

At CMB, we’ve been looking at the Emotional Fingerprints™ brands leave on their customers. We’ve developed a measure of the emotional bond customers have for brands. When we look across different segments of your loyal customers, we can clearly see that those that love you clearly are more bonded to your franchise.

jay loyalty

So, even if you forgot the roses this Valentine’s Day, don’t forget to send your favorite customers a forget-me-not. Let them know how much you appreciate their business and their love.

Dear Dr. Jay

Dr. Jay Weiner is the top digit-head at CMB. Starting next month, he’ll answer your burning market research questions in his new blog series: Dear Dr. Jay. You can send your questions to
DearDrJay@cmbinfo.com or submit anonymously here: http://forms.cmbinfo.com/dear-dr.-jay   





Topics: NPS, EMPACT, emotional measurement, customer experience and loyalty

What's Love (and NPS Scores) Got to Do with it?

Posted by James Kelley

Wed, Feb 11, 2015

NPS, or Net Promoter Score, is all the rage in market research. Most major corporations have a tracking program built around the statistic, and many companies also gauge their customer service and client relationships against this number. But what is NPS? 

At its root, NPS is a measure of advocacy. In terms of data collection, NPS is a single question usually included in a customer satisfaction or brand tracking survey. The question’s scale ranges from 0-10 but is grouped according to the graphic below. In the aggregate, an NPS score is the percentage of Promoters minus the percentage of Detractors.  


We did a recent study in which we took a deeper look at NPS and what how Promoters differ from Detractors. We surveyed customers from a wide array of industries (travel, eCommerce, telecom, etc.), and we uncovered quite a few statistics that might surprise you. 

What if I told you that only a slim majority (53%) of Promoters love the brands they do business with? Remember: this isn’t 50% of all consumers but 50% of Promoters. In fact, only 15% of all consumers use the “L word” at all. This isn’t to say that advocacy isn’t important—word of mouth is an essential part of advertising—but wouldn’t you rather your loudest advocates be your biggest loyalists? If these Promoters found a competitive brand more attractive, are they likely to advocate on that brand’s behalf?  

Here are some more fun facts: 4% of Promoters are only loyal customers during sales or when they have a coupon, and another 5% of Promoters would be happy to purchase from another brand if it were available. Consumers are fickle beasts. 

So, what does all this mean? Are we ready to throw NPS out the window? Certainly not. NPS is great in that provides a clear measure of how many advocates exist in comparison to Detractors. Think of it as a net tally of all the communications in the world. Scores above 0 mean you have more Promoters then Detractors, and negative scores mean the opposite. But for those companies out there that have the traffic on their side, it’s time to ask: is advocacy enough? Advocacy is great—it provides momentum, gets startups off the ground, and fuels growing brands. But love is better—love builds dynasties. 

James Kelley splits his time at CMB as a Project Manager for the Technology/eCommerce team and as a member of the analytics team. He is a self-described data nerd, political junkie, and board game geek. Outside of work, James works on his dissertation in political science which he hopes to complete in 2016.

Check out our new case study and learn how CMB refreshed Reebok’s global brand tracker, which gives the global fitness giant insight into how the brand is performing, its position in the global marketplace, and whether current brand strategies reach their targets.

Download Case Study Here

Topics: advanced analytics, NPS, customer experience and loyalty

The Dangers of Relying On A Single Market Research Question

Posted by Josh Mendelsohn

Wed, Sep 22, 2010

single question“Do you know what the secret of life is? One thing. Just one thing. You stick to that and the rest don't mean s**t.” – Curly (played by Jack Palance), in the 1991 classic City Slickers

Over the last few years there has been a lot of debate over the use of a single question in market research to make business decisions, but this is not actually a post about NPS.  (For the record, I believe in a beefed up version of NPS measurement as a key loyalty indicator.)

This post is about how looking at a single data point can lead to incorrect decisions (Sorry Curly).  Case in point, in our most recent consumer pulse report about consumer opinions of health reform we asked 1500 Americans who they thought should be responsible for providing the most information about healthcare reform, and only 14% cited pharmaceutical companies (the government at 74% and health insurance companies at 61% were the runaway leaders.)  If pharma company executives were only looking at this data point, they might think that they were not deemed responsible by consumers and had a limited role to play in driving clarity around the issues.    

But when asked what groups should be most responsible for lowering healthcare costs, 54% of respondents cited pharmaceutical companies.  That means that consumers expect these companies to take action and operate in a way that helps consumers, regardless of the fact that they are not high on the list for providing information.  Those two points could lead to the exploration of a very different set of actions and strategies than looking at either in a vacuum.

The point is that while brevity is important in questionnaire design, it is market researchers’ job to not let it get in the way of providing business leaders with a full enough picture to make smart decisions.

Posted by Josh Mendelsohn. Josh is our VP of Marketing and loves live music, tv, great food, market research, New Orleans, marketing, his family, Boston and sports. You can follow him on Twitter @mendelj2.

Topics: methodology, NPS, Consumer Pulse, research design

Love It or Hate It: the NPS Approach Works

Posted by Brant Cruz

Tue, Jun 17, 2008

NPS, or Net Promoter® Score, has generated quite a bit of controversy since its introduction in 2003. And it’s easy to see why. Proponents point to measurement of a single question, the likelihood that a customer will recommend a firm’s product or service, as the key to growing “good profits” and the bottom line. Skeptics dispute this claim, citing a lack of proof; saying that its relative simplicity disguises the more complex issues behind loyalty.

Admittedly, I was one of those skeptics one year ago when we began implementing a similar program for all of the reasons others have cited (plus I’ve never met a form of regression I didn’t like). One year later, I’m a strong advocate (a Promoter if you will) of the concepts behind NPS. And I think that this year’s journey has been an eye-opener for me and has added to an already-strong foundation regarding what works, and what doesn’t, when it comes to measuring customer loyalty.

Here are a few of the keys to success around measuring customer loyalty that are hallmarks of Reichheld’s NPS philosophy:

Listen to Your Customer — What THEY Want to Say

No questionnaire, no matter how long and arduous for the respondent, can cover everything. So let your customers tell you what matters, in their own words, then group them into common themes and read every word they say. And when masses of customer comments are read – really read – there is a far better chance of finding inspiration for a solution than when the data provides only higher “attribute” level detail. We’ve learned firsthand about how important this is recently with one of our clients: verbatims picked up an important pain point (and improvement opportunities) related to a business change that would have been completely missed in a more traditional tracking instrument.

Ask Fewer Questions of More People

Keep it short so you can hear from a big sample and broad cross-section of your customers (and prospects). It’s no secret that industry-wide response rates are problematic for a variety of reasons. One thing we can control is the length of our questionnaires, and we know that as interview length goes down, the percent of people who complete goes up. No sampling methodology is perfect and it is still impossible to talk to everyone. But given how hard it is to get someone to pick up the phone or click on a link, don’t we want to ensure that nearly all of them tell us what we need to know?

Link Attitudes to Behavior — Your Transaction Data

Forget asking a ton of behavioral questions – it’s easier than ever for many companies to link individual customer behavior via unique account numbers (e.g., financial accounts, loyalty program membership, unique customer IDs on every eCommerce site) to data collected through a research study. Linking attitudes with behaviors lets you see if how they feel synchs with how they behave – or if how they feel impacts how they behave! Even better, you can create predictive models to find others who “look like” your best Promoters via the data warehouse, and reach out to them to reinforce their (likely) behavior.

So, those are three pretty solid reasons to like NPS. In my opinion, research about them trumps our inborn, researcher need to analyze everything. Flexibility trumps vigilantly tracking exactly the same thing (often,everything) every month. Real behavior trumps self-reported behavior. And meaningfully better response rates trumps just about everything else.

Is the NPS measure materially better than any other single (or multi) measure at predicting behavior than anything else our industry has tried? I have seen several other researchers try to prove that NPS is not a better predictor of behavior than other traditional outcome measures – but all I’ve really seen is that all of this post-survey behavioral analysis is conclusively inconclusive. Given this, I’ll take my chances with a measure that is simultaneously all about the customer and focused on driving and managing an action that we can all agree is good for long-term business success.

In short, I buy Reichheld’s “good profits” argument. But you need more proof, don’t you?

I’ve also seen firsthand the quality of the verbatim responses the advocacy measure elicits. We’ve tested the traditional NPS measure against “likelihood to buy” in a concurrent study and have been able to read and compare more than 12,000 English language verbatims for each. Subjectively, the verbatims based on advocacy are in general more passionate and give better feedback about what is great and what needs work with my client’s brand. More objectively, nearly twice as many advocacy-based verbatims have been coded as “very insightful” (one variable in our rigorous coding scheme is about the “quality” of the verbatim and we have set the bar quite high) – and this translates into nearly 5,000 additional “very insightful” customer comments for our clients executives to read annually.

Despite this ringing endorsement, I do have two suggestions around how to improve upon the original NPS framework that Reichheld proposes and practices:

1. Buyer Beware! Invest in due diligence on your company’s “ultimate question.” Despite my strong belief in the power of advocacy, (heck, we’ve been involved in programs to help foster it for 15 years), I strongly advise conducting piloting the NPS metric versus one or more “challengers” and analyzing post survey behavior over several months. I have seen one instance where the traditional question didn’t work (it was negatively correlated with post-survey financial volume) for a certain segment for a client of mine. And we’ve had to test several versions of the question to find the right one. My philosophy is this: in the absence of compelling empirical evidence of a better question, focusing on likelihood to recommend is the best single question to use to measure and manage loyalty. But given the investment required in these large scale trackers – you owe it to your company to make sure the question works in your setting.
2. Voluntary Amnesia? Don’t forget everything you’ve already learned! Unlike Reichheld, I recommend that you continue tracking a short (no more than 10) set of previously-identified key drivers in addition to your ultimate question. For most companies, an NPS-like methodology won’t be the first brand or performance tracking research you have ever conducted. You’ve been focusing on some outcome(s) and conducting some form of key driver analysis to determine how to move that/those needle(s). Why stop measuring a short set of attributes that you know matter if you can still keep interview length really short and therefore not materially reduce cooperation rates? While verbatims tell the best and most complete story, by tracking a short set of attribute-level measures you can diagnose some of the reasons for NPS shifts quickly and consistently. 

Brant Cruz leads CMB’s Retail and eCommerce Practice, and has been self-identified as the funniest man in market research. He’s also laid claim to the titles of “Kingmaker,” “Queenmaker,” and “Killer of Sacred Cows.” To learn more about our capabilities and experience in this area, contact us at info@cmbinfo.com

Topics: methodology, NPS, customer experience and loyalty