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MASB’s Game Changing Brand Investment and Valuation Project – Part II

August 4th, 2015 Comments off

In Part I of this blog series we discussed ten technical characteristics of brand preference which made it suitable for adoption into market research tools.  But just because something can be done doesn’t mean it should be done.  In fact, one of the issues identified early on by Marketing Accountability Standards Board (MASB) was that the sheer number of metrics in use could lead to a type of analytical paralysis; that is, an inability of insights groups to efficiently advise other functions of the organization.  This has been euphemistically referred to within the group as “swimming in data”.

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Given MASB’s focus this primarily revolved around the plethora of metrics being applied to quantify the overall financial success of marketing activities.  But from our experience addressing this “swimming in data” issue is even more urgent for tactical research applications, especially brand tracking.  It is not uncommon to see between fifty and one hundred different category and brand attributes being monitored.  Each of these attributes captures a dimension of “equity” deemed important for brand success.  But how does an analyst combine these metrics to quantify the total health of the brand?

One popular approach is to apply structural modeling of the attributes versus sales data.  The resulting model provides a means of “rolling up” attributes into one number.  However, there are several challenges with this approach.  One is that such a model often becomes viewed as ‘black box’ by other functional areas.  This lack of transparency and simplicity fuels distrust and slows down adoption of insights.  But even worse is that such a model is only applicable to the environment in which it is derived.  Technological, financial, and even style trends can dramatically change the relative importance of attributes within a category thus uncoupling the model’s link to sales.  For example, being viewed as ‘having fuel efficient models’ is much more important for an auto brand when gas prices are high than when they are low.

Brand preference offers a better approach to the “swimming in data” issue.  As a truly holistic measure it captures the influence of all these attributes.  This was confirmed in the MASB Brand Investment and Valuation project.  Several of the marketers participating in the brand preference tracking trials provided equity data from their internal tracking programs for comparison purposes.  Across the categories investigated there were seven other brand strength ‘concepts’ commonly used.

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A correlation analysis was used to contrast their relationship to changes in brand share of market versus that of brand preference.  What was found is that the strength of their relationships to share varied by category and oftentimes fell below the correlation level deemed moderately strong by Cohen’s Convention (Jacob Cohen, Statistical Power Analysis for the Behavioral Sciences; 1988).  Furthermore, all of these other metrics exhibited correlations to market share substantially below that of brand preference.

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But brand preference didn’t just demonstrate stronger relationships to market share than these other measures, it also captured their individual predictive power.  This is most readily seen by contrasting each measure’s explanatory power of preference to that of market share.  All seven measures exhibit a stronger relationship to preference than to market share.  Given that the preference was gathered on a completely different sample than the other measures, this strongly suggests that the explanatory power of these other measures is acting through preference in explaining market share.

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In addition to these seven common concepts, category specific attributes were also examined.  Of the seventy metrics examined not a single one showed potential to substantially add to the predictive power of preference.

Probably the most extreme example of the advantage of brand preference as a holistic tracking measure comes during a product safety recall.  During these situations it is not unusual to see top-of-mind awareness levels peak near one hundred percent.  At the same time, brand attributes such as safety and trust which typically show milder importance rise to the top.  Under these conditions a structural model’s ability to explain sales may not just drop to zero but actually turn negative.  That is, it will report brand strength rising even as sales precipitously drop!  Since brand preference not only captures the changing level but also the changing importance of these other dimensions, it remains a valuable tool for navigating such times at it will accurately monitor progress in rebuilding the brand in the hearts and minds of consumers.

The Tylenol tampering incident illustrates this.  As the nation watched several people die from the poisoning, brand preference plummeted thirty-two points.  The Tylenol brand could no longer be trusted.  Concurrent with this brand preference drop, Tylenol’s market share fell thirty-three points.  As Johnson & Johnson addressed the situation responsibly, the brand’s previous place in the minds of consumers was slowly rebuilt.  This set the stage for a rebound in brand sales as tamper protected versions of the brand’s products made their way onto store shelves.

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Because of its ability to accurately monitor the total health of a brand, the MSW●ARS Brand Preference measure is quickly becoming viewed as the ‘King of Key Performance Indicators’.  But there are other very pragmatic reasons for incorporating it into your tracking and other research.  In future blog posts we will discuss these and how easy it is to do.

Please contact your MSW●ARS representative to learn more about our brand preference approach.

Categories: Advertising Tracking, MASB Tags:

MASB’s Game Changing Brand Investment and Valuation Project – Part I

July 20th, 2015 Comments off

How much is my brand worth in financial terms?  How much will my marketing grow its value?

Despite their seeming simplicity, these two questions have frustrated brand practitioners for decades.  It is well accepted that there is a link between brand building activities and corporate profits.  After all, the entire field of marketing is based upon this proposition.  Yet it is equally well accepted that there is no standardized approach that companies can rely on to quantify brand value in the dollar-and-cents terms applied to other assets.  This puts marketing at a severe disadvantage within boardroom discussions of resource allocations, as its expenditures are all too often seen as pure costs rather than investments in the business.  And this is despite a growing realization that intangibles account for up to eighty percent of overall corporate value with brands being at the top of the list.

But one industry group is actively working to change this.  The Marketing Accountability Standards Board (MASB) created the Brand Investment and Valuation (BIV) project to establish the quantitative linkages between marketing and financial metrics.   The solution they have proposed is as simple as the questions themselves:  Identify a “brand strength” metric which captures the impact of all branding activities, understand how this metric translates into financial returns (ultimately cash flow), and then use this to calculate a brand value and to project the return from future marketing investments.

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Of course this begs the question, does such a “brand strength” metric exist?  And if so, is it practical enough to be used?  After an exhaustive search of research literature, MASB identified brand preference as the most likely candidate for the brand strength metric.  Brand preference (also known as brand choice) is defined within the common language in marketing dictionary as:

One of the indicators of the strength of a brand in the hearts and minds of customers, brand preference represents which brands are preferred under assumptions of equality in price and availability.

The ability of brand preference to isolate brand strength from other market factors (e.g., price and distribution) separates it from other marketing measures.  Furthermore, previous studies demonstrated that the behavioral brand preference approach pioneered by MSW•ARS met MASB’s predetermined ten criteria of an ideal metric:

  1. Relevant:  It has been proven to capture the impact of all types of marketing and PR activities.  Over the last 45 years it has been used to measure the effectiveness of all forms of media (e.g. television, print, radio, out-of-home, digital), events (e.g. celebrity and event sponsorships), and brand news (e.g. product recalls, green initiatives).  It has also been shown to capture both conscious and unconscious customer motivations and so applies equally to rational, emotional, and mixed branding strategies.
  2. Predictive:  Its ability to accurately forecast financial outcomes has been demonstrated in a number of studies.  This includes studies comparing preference to sales results calculated from store audits, in-store scanners, pharmaceutical prescription fulfillments and new car registrations.  When applied to advertising, changes in brand preference have been proven to predict changes in the above sales sources from control market tests, split media tests, pre-to-post share analysis and market mix modeling.  In fact, Quirk’s Magazine noted over a decade ago that “this measurement has been validated to actual business results more than any other advertising measurement in the business”.
  3. Objective:  It is purely an empirical measure by nature.  No subjective interpretation is needed.
  4. Calibrated:  It has been applied to the broad spectrum of brands and categories and its correlation to sales has proven consistent across geographies.  Furthermore, it self-adjusts to the marketplace where it is collected so it has the same interpretation without any need for historic benchmarks.

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  1. Reliable:  It has been shown to be as reliable as the laws of random sampling allow.  This is true both for brand preference gathered at a point in time and for changes over time caused by marketing activities.  The table below summarizes this consistency in measuring changes.  Changes in brand preference caused by 49 campaigns were each measured twice among independent groups of costumers.  Observed variation between the pairs was compared to what would be expected from random sampling.  The ‘not significant’ conclusion confirms that the measure is as reliable as the laws of random sampling allow.

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  1. Sensitive:  It is able to detect the impact of media even from one brand building exposure (e.g., a single television ad shown once).
  2. Simple:  It is easily applied and understood.  It can be incorporated within any type of customer research including tracking, pre-testing, post-testing, segmentation, strategy, product concept.
  3. Causal:  While it captures the effect of product experience, it is not driven by just product experience.  In fact, it has been proven predictive of trial for new products for which consumers have no experience.
  4. Transparent:  It doesn’t rely on ‘block box’ models or norms.
  5. Quality Assured:  Its reliability and predictability are subject to continuous review.

To verify its suitability as the brand strength metric, MASB included an aggressive trial of brand preference as part of its BIV project.  A cornerstone of this endeavor was a longitudinal tracking study sponsored by six blue chip corporations and conducted by MSW•ARS Research.  The two year study covers one hundred twenty brands across twelve categories with a variety of market conditions.  In part II of this article we will review several of the key findings from this project, which are already changing industry perceptions on measuring brand value and making brand building investments.

The MSW•ARS Brand Preference measure can be incorporated into a wide variety of research and can even become a standard key performance indicator in your reporting, particularly in your tracking data.  In future blog posts we will discuss this and how you can easily apply it.

If you don’t want to wait then please contact your MSW•ARS representative to learn more about our brand preference approach.

Is Brand Preference Marketing’s Higgs Boson?

November 20th, 2014 Comments off

Higgs Boson-02Chances are you have heard of the Higgs Boson, an elusive elementary particle that physicists have spent the last fifty years and billions of dollars to find.  Reports of its potential discovery have captured headlines around the globe.  If verified, not only will it help cement our mathematical understanding of how the universe works, but will set the trajectory for future technological advances.

What has this got to do with the marketing discipline?  For the last fifty years we have been dealing with our own elusive particle, an accurate metric that quantifies the financial value a brand provides.  Without this the mathematics is incomplete for financial forecasting, planning, justifying marketing investment or improving marketing return.

But 2015 may be the year that this changes due to the work of the Marketing Accountability Standards Board (MASB).  This group of marketing and financial practitioners and academics has been pursuing aggressive “game changing” projects to not only create general principles and methodological standards for brand valuation, but to prove them out in brand “trials” that serve as practical examples of their application.  Based on prior research, MASB chose the MSW•ARS brand preference measurement approach as the cornerstone of its two-year long brand investment and valuation trials.  The first installment of this research was presented at the group’s summer summit in August and the initial results have been making waves in industry news.

Mathematics of Brand Preference

Just like physics equations hinted at the existence of the Higgs Boson, so did the equations of marketing hint at brand preference.  For years marketers have dissected sales data and realized that maintaining market share and price point were critical to maintaining revenue streams.

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But this just pushes the question a level deeper to: What drives a brand’s unit market share?  Economic theory provides two of the key elements, price relative to competing products and distribution.  Simply put, on average the less costly in terms of time and money a product is to obtain, the higher the demand for it will be.  But people are not economic robots.  They will oftentimes choose a more costly option if they feel that it will provide them a decisive benefit, even if it is a purely emotional one.  Thus it is the breadth and strength of consumers’ preference which set the base level for a brand’s unit market share with distribution and relative price acting as modifiers to it.

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So how effective is brand preference in explaining a brand’s unit market share?  In the initial MASB trial analysis, six months of brand preference, unit share, price premiums, and distribution were analyzed across twelve participant categories containing one hundred nineteen brands.  The categories examined included a diverse mix of product types; prices from thirty cents to thirty thousand dollars, impulse buys to deliberate purchases, consumables to durables.  Across these categories brand preference accounted for seventy-one percent of the differences between brands while effective distribution and price premium added another fourteen percent.

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With this milestone achieved the next step is already underway, incorporating brand preference in financial and marketing forecast and planning applications.  More details on these endeavors will be forthcoming in future installments.

Please contact your MSW●ARS representative to learn more about how brand preference is embedded throughout all of our research solutions.