Marketing's magic metric
Elasticity is a misunderstood and neglected metric that can help marketers choose the best prices, the best promotions, the best media and so achieve optimum brand value, a leading academic has argued.
Writing in the current issue of Market Leader, Robert Shaw, honorary professor of marketing analytics at Cass Business School, described popular metrics such as awareness, engagement, loyalty and satisfaction as being helpful for brand beauty contests.
"But to pragmatic decision-makers they're as useful as sunroofs on submarines," he said.
Take price – "the litmus test of successful marketing" – where a premium signifies brand strength, differentiation and customer preference.
Cutting the price should theoretically increase revenues and market share, but Shaw pointed to the cautionary tale of General Motors which chased market share and ended up bankrupt.
"Smart decision-makers scrutinise revenue-growth and also take account of cost-growth," he averred, and they can pinpoint the precise price to optimise brand value.
That could mean raising prices and conceding market share while growing brand value. Or the opposite. "There are no cast-iron generalisations and the right decision depends on the details of the value calculations," Shaw advised.
A similarly pragmatic approach needs to be taken to decisions on promotions, which consumers have come to expect, but which can often damage brand value.
Shaw highlighted cannibalisation and rebates as big destroyers of brand value but added that, "judiciously planned, promotions are a major source of value for brand owners".
Turning to media elasticity, Shaw said this was typically much lower than price or promotional elasticity, with the law of diminishing returns setting in rapidly.
But knowledge of diminishing returns curves could enable planners to set an overall media budget that would help them both to find the total budget that optimised value-added and to select a mix of media that optimised value for a given total budget.
"Elasticity is not an esoteric concept," he declared. "This neglected metric deserves to be better known and more widely used."
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15 09 market leader article
1. 34 Market Leader Quarter 4, 2015
answers depend on the type of decision
being taken – pricing decisions, promotional
decisions or media decisions.
Pricing decisions
Price is the litmus test of successful
marketing. It communicates positioning
to the customer and reinforces the
competitive stance the marketer wishes to
adopt. A premium signifies brand strength,
differentiation and customer preference. It
is arguably the easiest factor to change and
probably the most mismanaged.
The link between price and brand value
is intricate and easily misunderstood. For
most brands, price elasticity is higher than 1,
Marketing’s
magic metric
ROBERT SHAW
MARKETING METRICS
so cutting the price will increase revenues
and market share. Boardroom strategists and
investment analysts often argue in favour of
maximising market share. When General
Motors tried to increase its domestic market
share in 2004 from 28% to 29% by cutting
prices, its profits went into freefall, it crashed
and needed a government bailout.
Smart decision-makers scrutinise revenue-
growth and also take account of cost-growth.
Starting from a low base as prices increase,
margins and profits initially increase, then
they peak and finally they decrease. Smart
decision-makers pinpoint the precise price
to optimise brand value. Because the price
elasticity describes the consumer response to
price changes, it can tell you which direction
price should be moved in to maximise profit.
But this directional insight also depends
on the price level at which you are currently
trading. It might (depending on current
pricing and the elasticity) be better to
raise prices, concede market share and
grow brand value. But, equally, it might
be better to do the opposite. There are
no cast-iron generalisations and the right
decision depends on the details of the
value calculations.
Imagine a company with a brand that sells
on the high street and online. A price war
has eroded the premium and decimated the
profits. Figure 1 shows the present financial
performance. The CEO needs a new pricing
strategy to save the business. As CMO,
should you recommend deeper price cuts or
restoring the price premium?
A wise CMO understands elasticity and
has established that on the high street, the
elasticity is 1.5, and online, where customers
can easily comparison-shop, elasticity is 2.0.
This information enables a what-if analysis
to be calculated (Figure 2).
Raising the price on the high street
is the best strategy in this illustrative
example. High street customers are loyal by
comparison with online, and a strong brand
should exploit its strength on the high street.
Online, where the market is dominated by
comparison shoppers, the current price is
right and should (if possible) be maintained
in this case. Even if the online price has
to move in tandem with the high street
price, the best overall strategy is still a price
increase as the high street gains more than
outweigh the online losses.
What are we trying to achieve with
pricing? The customer should be able to buy
at a price that maximises the brand owner’s
profit over time and is consistent with the
brand. Rapid changes of price unsettle the
customer; but the customer expects regular
promotional deals and offers and will be
unsettled if they cease.
Which metric is most critical when making decisions? Awareness?
Engagement? Loyalty? Satisfaction? Many metrics are used, each of
which has its proponents and utility. But there is one metric that trumps
the others as a measure of value created, and that is elasticity. In this
article, Robert Shaw describes how elasticity can be measured and
why it is so significant
E
lasticity is a neglected yet
hard-working metric that helps
decision-makers choose which
activities to expand and which to
contract. Its job is to quantify the propensity
of customers to switch. For decision-makers,
it provides the vital link from marketing
activity to customer switching, and then to
revenue, profit and brand value.
No other metrics do this. Popular metrics
such as awareness, engagement, loyalty
and satisfaction are handy for brand beauty
contests. But to pragmatic decision-makers
they’re as useful as sunroofs on submarines.
So, what help do elasticity figures provide,
and where can they be obtained? The
Figure1: Current financial performance
Figure 2: Net value after price changes
Illustrative
Revenue
Variable cost
Fixed cost
Net value
High street
2000
1000
1000
0
Online
800
400
400
0
Illustrative
+ 20% price rise
- 20% price cut
High street
(elasticity1.5)
65
- (161)
Online
(elasticity 2.0)
- (11)
- (25)
2. 100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Market Leader Quarter 4, 2015 35
ROBERT SHAW
MArKeTing MeTrics
ProMoTions decisions
Promotions are temporary incentives and
attention-getters. They are easy to run and
brands often greatly outspend advertising
with promotions. Marketers frequently
disparage them and say they damage the
brand; yet customers expect them and, if
they are used judiciously, promotions can
be the foundation of brand profitability
and market share.
Elasticity for promotions is often two
to three times higher than the pure base
price elasticity. While customers rationally
assess the saving for both, for promotions
the larger elasticity arises from the wording,
the visual impact and the placement of the
display. With promotional elasticity levels
of 3 and above, at first sight the additional
sales volume and market share that can be
obtained looks tempting.
Research by Lodish, Sharp and others
indicates that promotions often damage
brand value. So what goes wrong?
Cannibalisation is a big destroyer of value.
The promotional uplift draws volume – not
only from competitors, but also from the
existing brand. Often half or more of the
uplift is cannibalisation. Rebate – payment
for placement of display – is the other big
destroyer of value.
For example, if a half-price promotion on
the high street (Figure 1) boosts volumes
eightfold, this 700% volume increase
equates to 300% revenue increase (due to
the lower price) and the cost of goods grows
by 700%. So the promotion would virtually
eliminate all value, even before taking
account of cannibalisation and rebates.
Cannibalisation causes a massive loss,
because half of the 700% volume increase
comes from switching away from other
own-brand products. Rebates add insult to
injury, by making payments of hundreds
of thousands of pounds for loss-making,
volume-boosting promotional displays.
Smart decision-makers are pragmatic
about promotions, choosing configurations
that are profitable. Judiciously planned
promotions are a major source of value
for brand owners. Badly planned, they are
loss-making and damage brand equity.
But promotion and pricing alone are only
part of the mix, and marketing media also
need to be optimised, again using elasticity.
MediA decisions
Elasticity is a vitally important, yet often
neglected factor in media decisions. Media
elasticity is much lower than price or
promotional elasticity, often in the range
0.05 to 0.15. As a consequence of elasticity
being so low, consumer response to
media spend obeys the law of diminishing
The optimum total budget is £2 million and yields an incremental brand value of £680,000
with a mix of 46% TV, 42% internet display and12% internet search. Cutting the total to
£1 million slightly reduces the incremental brand value to £560,000 and the optimum mix is
40% internet display, 35% TV and 25% internet search. Increasing the budget to £4 million
halves incremental brand value of £340,000 with an optimised mix of 44% TV, 37% internet
display, 6% internet search and13% press.
£1m £2m £3m £4m
£800,000
£700,000
£600,000
£500,000
£400,000
£300,000
£200,000
£100,000
£0
Total budget
Distributionofspend
Valueadded
Press Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value addedPress Search TV Display Value added
Figure 3: How total budget impacts brand value added and
optimum spend allocation
3. 36 Market Leader Quarter 4, 2015
returns. This law was articulated in 1769
by Jacques Turgot as a general law of
economic input and output. In the case of
media, the first exposure produces a strong
response but the responses produced by
additional exposures rapidly tail away. This
phenomenon was first described by Edward
Chamberlain in 1933.
Knowledge of these diminishing returns
curves enables planners to set an overall
media budget to do two things:
∆ To find the total budget that optimises
value added
∆ To select a mix of media that optimises
value for a given total budget, as shown in
Figure 3.
WHere To oBTAin THe MeTrics
Elasticity metrics are a great starting place.
In many situations a one-dimensional
elasticity coefficient can depict consumer
behaviour. However, in some situations,
elasticity has to be generalised to two or
more ‘consumer response coefficients’ to
depict the multidimensional behaviours
which consumers display as they switch and
respond to marketing activity.
For example, if demand falls sharply above
a price point, then a set of more general
consumer response metrics is needed. At
high levels of media spend, saturation effects
come into play and, again, these curves
are best described by two or more metrics.
Promotions are multidimensional and need
more information than a single elasticity
figure. These consumer response metrics
can be obtained from several sources: finite
difference analysis, econometric analysis,
reach and frequency models and market
structure models.
∆ Finite difference methods were
discovered by Newton in 1687. Their
application to marketing is new and
has been led by pioneering work by the
British mathematician Dr David Merrick.
This approach enables enormously
detailed promotional response metrics
to be measured, pinpointing differences
in duration (one, two or three weeks),
frequency (monthly, quarterly), depth (cuts
of 10%, 25%, 33%, 50%), details of the deal
(eg half price versus BOGOF), differences
between channels, between product lines,
between the wording, the visual display and
the placement. Such details are not available
from other methods.
∆ econometrics was defined by Nobel
Prize winner Ragnar Frisch in 1926 and
has had a long and distinguished history.
It has been applied to marketing for over
50 years and its usage has been boosted
by the availability of powerful computer
software and hardware. It has become
the tool of choice for media agencies and
marketing mix consultancies.
∆ reach and frequency methods can be
used to estimate media response metrics
in the absence of econometric data. They
exploit the statistical laws for combining a
number of Opportunities To See.
∆ Market structure models infer the
consumer response from a limited
description of all the competing brands in
the category (including price, market share
and media spend). In the best approach
of this type, each brand is regarded as a
member of a set of brands with which it
competes, to a greater or lesser extent.
The degree of competition within this
‘partially-competing set’ determines the
ROBERT SHAW
MArKeTing MeTrics
Figure 4: Market structure diagram showing strength of
inter-brand competitiveness
optimal price point and media spend
for each brand. In Figure 4, solid lines
represent stronger competition, dotted lines
weaker competition.
concLusion
Elasticity and the related consumer response
metrics are neglected yet hard-working
numbers. They provide decision-makers
with powerful tools for choosing the best
prices, promotions and media and achieving
the optimum brand value.
Price elasticity shows whether the brand
should take a more premium position
or whether it should go downmarket.
Promotional elasticity shows where to spend
rebates to maximise brand value and how to
avoid tactics that drive volume up and value
down. Media elasticity shows the optimum
mix that maximises brand value.
Elasticity is not an esoteric concept.
Whether you are data-rich or -poor, there
is always an answer. For the data-poor, you
can use market structure models and reach
and frequency. For the data-rich there are
finite difference methods and econometrics.
This neglected metric deserves to be better
known and more widely used.
Robert Shaw is honorary professor of
marketing analytics at Cass Business School
rs@robert-shaw.com
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Finite difference
methods were
discovered by Newton
in 1687. They enable
enormously detailed
promotional response
metrics to be measured