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When spend on advertising
is so high, why is its ROI not calculated?
£17 billion a year is spent
on advertising by UK companies1, but only a very small proportion of
this is assessed to give a ROI (return on investment). For too many the immortal
phrase “I know half my dollars are wasted, but I don’t know which half”2
is a fair summary of spend analysis.
…especially as there
are measurement techniques available
Over the last 10 years a
change in attitude in the marketing industry has moved towards accountability3.
In the US, 70% of marketers now say they use ROI calculations to guide long-term
decision on how they do business. Also, increases in desktop computing power and
availability of accurate data have led to new tools to quantify the advertising
ROI for businesses.
Significant financial benefits
result from using software systems that calculate payback from advertising. Sales
can increase by around 10% simply by re-phasing media spend (see following case
study). On a wider scale, advertising effectiveness can be improved by 25% to
50% by assessing ad spend and using the results to re-engineer budget allocations.
In some cases this is enough to turn an unprofitable brand into a profitable one.
Measurement techniques can also be used to generate forecasts and run “what if”
scenarios.
Case Study
The chart below shows the
actual (historical) advertising activity and resulting sales in blue. The relationship
between the two has been derived using sales modelling. Advertising at a lower
rate each week allows more weeks to be bought. This scenario is shown in red.
Comparing this with the original plan reveals that although peak sales are slightly
lower there is a 10% increase in sales for the same budget.
Using sales modelling
to break down the impact of specific sales drivers at different times and identify
the ROI on ad spend.
The value of sales arising
from different influences can be quantified period-by-period by statistical processes.
A variety of factors will act on sales in any one period, from advertising to
price and distribution; disentangling the impact of two or more factors that are
changing at the same time is critical to strategic decision making.
Sales modelling gives the
historical quantification of how many sales in each period were due to each driver,
including advertising. Graphically this can be represented as a contributions
chart as below:
In this example advertising
accounted for around 15% of the year’s sales. Crudely this means that sales would
have been 15% lower over the year if no advertising had taken place. By inputting
the actual cost of the advertising alongside price and margin data we can calculate
the ROI on past advertising spend.
Setting budgets according
to the shape of diminishing returns….
Increasing advertising spend
does not lead to a proportionate increase in sales. Practitioners and researchers
have found that a diminishing returns graph most accurately reflects the payback
from advertising. This applies too for other areas of marketing, such as awareness
generation or call centre handling.
To calculate the point where
advertising for one brand is generating maximum sales and profit see the chart
below. Here the sales response is the red line and the profit from advertising
net of its cost is the dotted black line.
…and allocating the money
at corporate level
The calculations are more
complicated when allocating budgets across a number of brands, variants, market
sectors and media channels. Here a ‘matrix’ of non-linear relationships is required.
The response curves for two brands in two markets are shown in the next chart.
With only a small budget it seems best to spend on brand B in market X as this
is the steepest response. As the total budget increases, the marginal return from
brand B in market X diminishes and more can be gained by allocating some of the
money to other brands and markets. Given the shape of the curves, there exists
for each budget an optimum profit maximising allocation.
There are, however, many
factors other than response levels to consider when allocating advertising budgets.
Brand B could be less profitable than brand A, or media costs in market X could
be higher than in market Y; minimum spend levels and the strategic importance
of certain markets also need to be taken into account. All these factors and more
will alter budget allocation. Tailored software will be needed to do the calculations
(typically such software is spreadsheet based).
Some markets are easier
to model than others…
Sales modelling is limited
by the quality and availability of the necessary data and by the complexity of
the purchase process. Fast moving consumer goods suit sales modelling analysis,
because they have short consumer purchase cycles. Also sales are tracked accurately
and in detail using data from scanners.
The automotive sector is
much harder to model. Disparities between purchase and registration timings, multifarious
promotional deals and long purchase cycles all make it much more difficult to
isolate the time when a consumer is prompted into action by an advertising message.
The importance of incorporating
client experience into the mix
IT processes should not
be seen as the “Holy Grail” of ROI evaluation; it is important to have buy-in
from all key parties at all stages to ensure that assessment results give best
value to the business. Typically this is achieved through a series of meetings
and workshops where the assumptions driving the model are refined until a realistic
‘optimum’ is reached. As ROI analysis is historical, assumptions based on experience
about the impact of marketing plans will be required to enhance future ROI.
In summary
There are a variety of benefits
from undertaking an advertising payback analysis. The main ones are:
-
Increased profits through more effective allocation, phasing and allocation of
budget levels
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Time saved in deciding corporate level budget allocations. The process is designed
to ‘level the playing field’ by being objective, consistent and transparent. This
allows management to focus on what matters and not be diverted by spurious opinions
and ‘pet theories’.
-
Risk assessment. The tools developed will run “what if” forecasting. Through an
evaluation of alternative strategic responses you can improve your business reaction
to events like price changes, fluctuations in the economy, or a competitor launch.
[1] According to Advertising
Association UK data
2 Comment by Lord Leverhulme
3 USA Advertising Age Survey
(2003)
About the Author
Karl Weaver is Director
at Data2Decisions. To learn more about calculating the pay-back from advertising
and how it could help your business, visit the Data2Decisions website at http://www.d2dlimited.com/
or contact Karl Weaver on 020 8502 9160.
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