Brand Momentum
Is it possible for a brand to have momentum*? The same notion of momentum we are all familiar with in the physical world much as a wave that gathers mass, velocity and direction allowing it to travel vast differences before dissipating or crashing on 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?
At the centre of this maelstrom is the very heart of the brand-customer linkage. There are many aspects to that linkage – but the best, most succinct definition I have come across is that
A Brand is a Promise Kept.
(Economist – Brands & Branding pg 1 
Simple, direct and to the point.
A “promise kept” plus “promise broken” plus “promise strained” plus “promise surpassed” is the sum total of the brand experience up to the present point in time.
But what of the future momentum of a brand-customer linkage? The notion that present day activities may trigger delayed consequences – that if/when noticed - may require considerable resources to realign to the norm or suffer the consequences of the new equilibrium state.
Stepping back for a moment, isn’t this ‘simply’ a problem of identifying and forecasting the impact of attitudes and intentions** as a result of the experience customers have with the brand promise?
What holds true in understanding any behavioral forecast is that when there are meaningful consequences to a decision – consumers are apt to be more reflective in their decision making and follow through on those convictions***.
But for many brands, the consequences of the decision is not life or death, rather it is relatively risk-free decision involving a few dollars being pushed and pulled by degrees of a promise strained/surpassed/broken, emotions and the ease of switching to an alternate.
And so the forecasting challenge is considerable. The behavior we are trying to understand is the degree to which customers are prepared to accept the current status or if they have reached a tipping point that will precipitate a new equilibrium – sometimes to the immediate exclusion of the original brand – other times with a more gradual series of disengagement behaviors.****
Before you go any further realize that this model/formula has not been validated and as such stands in its current state as a thought starter. It is a naïve attempt and does not purport at being anything more than a notional construct and subject to brand/segment specific verification and calibration.
Now that you’ve been warned off ….
BRAND MOMENTUM
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 for the simple fact 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 to each and also that the brand’s historic price proposition will be within historic norms during the forecast period.
That said, let us begin to look at how Brand Momentum* may help us better predict the consequences of our actions with the customer. And like the traditional understanding of Momentum in the physical world, we hope to use the framework of Newton’s formulation to help us uncover the underlying impacts to the brand-customer linkage.
Momentum ~ Brand Momentum
THEREFORE
Momentum = Mass x (Direction x Velocity)
Brand Momentum ~ Mass x (Direction x Velocity)
Mass = 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.
Direction = noteworthy brand experiences; positive or negative
Velocity = degree of brand engagement. The extent to which customers are committing themselves to the brand by virtue of the depth and breadth of their brand purchases.
DIRECTION:
The direction factor captures the act of keeping, straining, breaking or surpassing the brand promise – in short the customer’s attitudes 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 – something they are likely to want to tell their colleagues or friends about, something that truly matters to them . Therefore let us concern ourselves at the moment with the extreme end points (ie 1-2, 10-11) on the Juster scale.
Furthermore if one purposely assigns negative experiences a higher weighting than positive experiences (perhaps 1.5x weighting) one begins to reflect the natural tendency to remember/react more readily to negative experiences.
For example, let us assume of the 5 links in the brand experience chain (see above) three of which had end box (red) flags:
Positive - Brand pre-purchase communication experience
(they loved the promotion/the ad/the contest/the endorsement from a colleague, etc….)
Negative - Brand purchase experience
(but were severely disappointed by the store/channel experience and attribute that experience to the brand)
Negative - Brand post purchase support experience
(having purchased the brand, there have been problems/questions which have arisen and the support channel failed to resolve)
Not a pleasant scenario – but not unlike what can happen with new product introductions.
| Attribute weighting (assumed equal) |
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 score |
| 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.
Those 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 subject to more refined weightings particular to your brand – which in this example yield a final formula score of 0.85.
Note: The yellow zone is purposely skewed to monitoring only negative experiences because of the greater downside risk to the enterprise.
But most customer brand experiences will not be particularly notable.
Customers typically experience disconnects in the brand promise which aren’t enough to precipitate significant change. Hence in a status quo scenario, the dominant factors in the brand’s momentum in most instances will be convenience, habit and relative value, coupled with any continuity enhancement/stickiness programs all of which will be represented in the velocity factor.
VELOCITY
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 period, while breadth is measured by indexing shopping basket size.
Frequency of purchase comparisons against year ago and/or previous period and/ or current period segment averages will yield the directionality needed to determine the extent to which the customer is engaged to the brand. 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 the first early warning signal your customers are sending you. Leading enterprises already use this purchase delay as a trigger to begin a separate cycle of activities to restore the brand’s momentum.
So working with the index of current level of engagement we have a starting point that begins to refine the impact the customer will have on the brand’s financial’s.
| Time PeriodRolling 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 again gains insight to the extent that customers are beginning to disengage themselves from their current brand relationship.
| 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 | $150 |
#customer has 20% more (Hhld size, income, etc..) than the segment average
^^ or previous period customer average
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 also 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 the normative level, the brand could have expected to continue 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 experiencing drags to its brand momentum as reflected by the revised value of $1,398,338.
The cash flow stream that is experiencing drag 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 – but we should be seeing a negative adjustment to the base line given the scenario we’ve just outlined. How accurate that adjustment is – will depend on future brand formula response specific calibrations. The real value to the enterprise however lies in having a causal understanding of its actions on the promises kept, broken or strained.
Conclusion
This model endeavors to provide a prescriptive foundation to understanding the consequences of the actions/experiences customers have with their brands from the standpoint of a momentum paradigm.
It hopefully serves to engage a more detailed assessment and calibration in order to help enterprises better understand the impact various brand investment decisions have on the customer’s brand experience chain and subsequently on their RETURN ON CUSTOMER calculations.
Data requirements for this model are modest as the brand engagement factor inputs are usually available from internal records or typical customer research. The more demanding requirement of tracking customer feedback across the brand experience chain would be readily available from any call center or satisfaction tracking methodology.
In part what this model strives to illustrate is that customers will experience broken and strained promises without necessarily taking overt action – but at some juncture a tipping point will be reached triggering behavioral changes that will impact the brand’s future (momentum).
Notations:
*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 – http://newsroom.cisco.com/dlls/tln/newsletter/2002/july/part1.html/)
**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
INSEAD http://www.acrwebsite.org/topic.asp?artid=275
****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 http://miroslodki.wordpress.com/brand-affinity-dynamics-part-1-of-3/ ).
Other articles of Interest:
Great theory