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Brand Momentum

Is it possible for a brand to have momentum*? The same Newtonian physics 101 notion that describes how a wave can gather mass, velocity and direction allowing it to travel vast distances or come crashing to shore?

If a brand can have momentum, what will add to it…detract from it? How do we measure it? How do we manage it? What is a BRAND?

A Brand is a Promise Kept.

(Economist – Brands & Branding pg 18 )

That a brand is defined by the promises it keeps is perhaps one of the most powerful constructs an enterprise can adopt. This model strives to recognize and capture the fact that customers will experience broken and strained promises (and customer delight) without necessarily taking overt action– but at some juncture a tipping point will be reached triggering behavioral changes that will have a measurable impact on the brand’s future (momentum).

The challenge has been in measuring the equity shifting customer events in order to calibrate its impact on brand performance. While most agree that an unsatisfied customer has a lower likelihood of spending money with the ‘offending’ enterprise, many have shied from constructing the data net necessary to begin to recognize when that has happened, let alone to understand the extent of the damage that has been caused to the future profit stream (and visa versa****). However technically sophisticated risk management theories and practices are, they simply haven’t been able to make the migration from finance to marketing because of the problem of measuring the customer experience event at a sufficiently granular customer level.

This is an unproven notional model submitted for your consideration, please use all appropriate discretion.   Now that you’ve been warned off…


Within the context of predicting future brand purchase behavior it is important to capture the delivery of pain or pleasure at the key stages of the brand experience chain. The simple fact is that no one will willingly subject themselves to a substandard experience if there is a reasonable alternative at hand

Five Key Stages of a Brand Experience Chain

1. Brand pre-purchase communication experience

2. Brand purchase experience

3. Brand performance

4. Brand billing experience

5. Brand post purchase/support experience

For the sake of simplicity we will assume that each of these stages are equally important and assign a 20% weighting. Also that the brand’s pricing will be within historic norms during the forecast period.

That said, let us begin to look at how Brand Momentum* might help us better predict the consequences of our actions with the customer using Isaac Newton’s framework to help uncover the underlying impacts to the brand-customer linkage.

Momentum = Mass x (Direction x Velocity)


Brand Momentum ~ Mass x (Direction x Velocity)


Definition: NPV/LTV

The cumulative financial value of the brand’s revenue/profit stream reflecting the customer’s financial response to the most recent market offerings adjusted by the risk factor/cost of capital.


Definition: noteworthy brand experiences; positive or negative

The direction factor captures the act of keeping, straining, breaking or surpassing the brand promise. It’s the customer’s attitude toward the brand experience.

However because attitudinal-behavioral correlations are notoriously wide ranging, we will concern ourselves with only those components where the customer is having significant emotional experiences with the brand promise. Therefore we only consider the extreme end points (ie 1-2, 10-11) on the Juster scale, not unlike the approach taken by the Net Promoter Score.

To reflect the natural tendency of remembering/reacting more readily to negative experiences, we can assign negative experiences a more prominent weighting impact, perhaps 1.5x that of positive experiences.

In our example let us assume three of the five links in the brand experience chain merited a red flag:

Positive – Brand pre-purchase communication experience

Negative – Brand purchase experience

Negative – Brand post purchase support experience

They were impressed by the promotion/ad/contest/WoM endorsement, but were severely disappointed by the store/channel experience and attributed that experience to the brand. Having made the purchase, problems/questions have since arisen which the support channel has failed to resolve.

Not a pleasant scenario – but not unlike what happens in real life.

Attribute weighting (assumed
Attribute 11 Point Juster Scale Score (11= 10 in 10 chance in continuing to purchase the brand in future vs 1 = 0 in 10 chance in continuing to purchase the brand in future) Weighted Juster score Weighted
20% Brand Pre Purchase 11 1.0 x 20% = 0.20 0.20
20% Brand Purchase 2 -1.0 x 20% x 1.5 = -0.30 -0.30
20% Brand Performance 3 -0.5 x 20% x 1.5 = -0.15 -0.15
20% Brand Billing 7 0.0 x 20% = Below Threshold Below Threshold
20% Brand Post Purchase 2 -1.0 x 20% x 1.5 = -0.30 -0.30
Total “Red Flag” Scores (0.20 – 0.30 – 0.30) + 1 = 0.60 0.60
Total “Yellow Flag” Scores -0.15 + 1 = 0.85 0.85

++Juster scale scoring system: 11&10= 1.0, 9&8= 0.5, 7&6&5= 0.0, 4&3= -0.5, 2&1= -1.0

The resulting individual ”red flag” score of 0.60 would be summed and averaged across all customers to yield a segment average.

Experiences which result in a yellow flag score (ie 3 or 4) merit careful scrutiny for any shifts in the brand’s velocity. In the interim let us assign a -0.5 weighting yielding a final formula score of 0.85. Note: The yellow zone is purposely skewed to noting negative experiences because of the greater downside risk to the enterprise.

Customers routinely encounter experience disconnects which aren’t enough to precipitate significant change in which case the dominant momentum factors will be convenience, habit and relative value coupled with any continuity enhancement/stickiness programs.


Definition: degree of brand engagement.

The dimension of velocity captures the current level of brand engagement by monitoring the depth and breadth of customer purchases. Depth is simply the frequency of purchases over a fixed time, while breadth is measured by indexing the shopping basket size.

Frequency of purchase comparisons against prior period will yield the directionality needed to determine customer brand engagement. Cross linking the depth of purchase impact from the brand experience scores will enhance the predictive power of the metric. However from the very outset, any delays in the purchase cycle can be the taken as early warning signal from customers. Leading enterprises already use this purchase delay signal to activate a separate cycle of activities to restore the brand’s momentum.

The Customer/Segment index begins to indicate the impact the customer will have on the brand’s future financials.

Time Period Rolling 12 months Depth
Customer data in current period 4.0 Purchases
Segment Norm in current period(or customer’s last measurement) 5.1 Purchases
Customer/Segment Index 0.78

By monitoring the Shopping Basket size from previous periods or alternately indexing to the segment’s average (remembering to normalize for relevant consumption driving factors) the enterprise gains insight to the extent that customers are disengaging themselves from their current brand.

Time Period Rolling 12 months Shopping Basket Size/average purchase occasion Per capita Normalization factor Normalized Per Capita Shopping Basket Normalized Index
Customer $165 1.2 $137.50 0.917
Segment avg $150

By combining these two variables (0.78 x 0.917 =.715) for the ‘red flag’ customers, one derives the second factor weighting yielding a powerful and simple measurement of the velocity at which customers are engaging or disengaging with the brand.

For the sake of expediency let us assign the yellow flag customers the same velocity score of 0.715)


And so if we use:

NPV/LTV = $1.5 Million to represent the mass of the brand,

Red flag/End Point scores to account for 5% of projected occurrences,

Yellow flag/Moderate scores to account for 10% of projected occurrences

The resulting formulation would yield:

Brand Momentum ~ Mass x (Direction x Velocity)

= ($1.5 Million x 5% x 0.60 x 0.715)

+ ($1.5 Million x 10% x 0.85 x 0.715)

+ ($1.5 Million x 85%)

= $32,175 + $91,163 + $1,275,000 = $1,398,338

In other words if everything were to be at normative levels, the brand could expect to see a cost of capital adjusted NPV of $1.5Million.

However because of the customer noted brand experience and brand engagement are both trending considerably below the norm, that portion of the NPV stream is at risk. The drag to its brand momentum is reflected by the revised value of $1,398,338.

The cash flow stream has been reduced from $225,000 [$1.5M x (5%+10%)] to $123,338. Of course the flip side is also possible in which case the brand momentum would be higher than the base line “mass”.

Will the brand actually post a financial result of $1.4M instead of the anticipated $1.5M? Without a real world context, it’s a matter of sophistry. We would anticipate a negative adjustment given the scenario we’ve just outlined, the accuracy of that adjustment is dependent on future calibrations. However the real value to the enterprise lies in having a causal understanding of its actions on the promises kept, broken or strained.


This model endeavours to provide a prescriptive foundation to understanding the consequences of the actions and experiences customers have with their brands using a momentum paradigm.

The metrics for NPV and Velocity are readily available in some reasonable form for most marketers. Anyone with direct-to-customer business models certainly has this information in-house. Brand manufacturers might need to develop some agreed-upon approximation.

The challenge both camps will face is measuring the Direction variable – the same core challenge of the RoC metric. The proffered approach is not perfect, but it seeks to de-construct those parts of the brand promise/brand experience chain that are important to customers and integrating any CEM initiatives you might have underway. For the rest, a sampling of one’s customers (perhaps facilitated via a private online customer panel with services like will yield the requisite data points.

The core value of this model or any model is not the numeric output. Rather it’s in the understanding and subsequent cost/benefit management of the underlying causal impacts when one’s brand promises are broken, strained, kept or exceeded.

I hope you found this article to be of value and look forward to your feedback and perhaps we can co-create a more robust model.


*Brand Momentum was first popularized by John Chambers Pres/CEO of Cisco. The Brand Momentum notion he was concerned about dealt with the future roadmap the brand and its ecosystem will undertake to maintain the ongoing development/evolution of the brand in the fast paced high-tech sector. Not exactly what we are after, but if you are interested please refer to the link for more information ( Cisco, Ron Ricci –

**From this realm – there is a rich history of studies beginning with LaPierre through to Fishbein, Ajzen, Fazio and their contemporaries. All manner of brand and category purchase behavior prediction models have been studied and postulated around the globe using any number of modeling techniques, scales (Likert, Juster) and elapsed time for intentions to be fulfilled, level of familiarity, habit/non habit all in an attempt to find a correlation between attitudes, intentions and ultimately behavior.

***Many studies have pointed out that correlations between intentions and behaviors are not as strong as one would expect – however there is evidence to suggest that the testing effect does influence the behavior – ie those with negative experience were less likely to purchase and those with positive experiences were more likely to purchase.

Source: Do Intentions Really Predict Behavior?
by Pierre Chandon ,INSEAD; Vicki G. Morwitz, New York University; Werner J. Reinartz

****Some may think this is sounding like an earlier elaboration of the Brand Affinity construct which sought to map the brand experience of the value chain on brand affinity. (see ).

Other articles of Interest:

Anatomy of a Brand Purchase

Brand Affinity Dynamics

The Art & Science of Retention

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One Comment leave one →
  1. January 5, 2008 7:27 pm

    Great theory

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