Making the best use of data

What is the impact of marketing inputs on sales and market share, in each market?

What is the ROI of each marketing input? Which promotions are more impactful?

How can we optimise budget allocation?

How are competitive activities impacting our performance?

How can we improve the efficiency of our sales force?

How price-sensitive are different markets?

How does pricing impact our brand's sales?

These questions and more have been around since time immemorial. Not just marketers, even CEOs spend time pondering over them. Today, it is possible to get closer than ever before to the right answers, thanks to (a) abundance of data (b) tools to analyse data and (c) evolution of mathematical techniques. New-age marketers are slowly embracing the power of analytics to quantify the impact of marketing inputs on the final outcome.

But, even as (a), (b) and (c) above are invaluable, it takes one more element to draw the right inferences and seek the right direction in the marketing journey.

Thanks to the digital age, consumer response information is widely available across corporations. We have customer metrics, unit metrics (relating to sales), cash flow metrics (including media usage) and we have Web metrics. Too much data also can cause problems — it can lead to the user drowning in data, without any concrete outcome. The primary challenge today is smart integration of all these metrics and establishing a relationship that best explains the desired outcome.

Availability of a plethora of tools, techniques and data alone is not enough. Who will stitch these data forms together? How do we bring in a realistic understanding of markets to get realistic output? This is possible only when the three key disciplines that drive marketing effectiveness integrate — knowledge in marketing, media and analytics.

One can generate a series of equations by linking unrelated factors, but applicability cannot be ascertained with mere statistical techniques. For example, through statistical techniques, one can get a relationship that even says: ‘greater the key competitor's advertising, higher will be the sales of the brand under consideration'!

Any marketer would take a second look at such a statement. It may be correct statistically, but in reality it could well be dismissed as rubbish. Or, it might call for further analysis, involving factors such as propositions and packaging. And such integrated analysis for interpretation and action works if rooted in market understanding and category experience.

Take the case of a brand that we worked for in the consumer products category. Brand A and the competitor brand B had the same proposition, addressed the same audience, in the same market — India. Statistically, it was found that as brand B advertised more, the sales of brand A were getting a positive spike. On deeper analysis, we found that the consumer wasn't able to differentiate between the two brands, and the benefit of advertising by one brand was accruing to both! You can either out-shout the competition or use such insights to adopt a scientific and more effective approach. In this case, we recommended ‘tactical layering' as the media approach (advertising when the competitor brand is not active), besides initiating a rethink of the undifferentiated brand positioning.

The new-age mantra for enhancement of profit through effectiveness not only lies in the data that is collected but also in its smart usage. Like any other business challenge, in marketing analytics too it is imperative that a sound practical knowledge of marketing and media be integrated with analytics.

The writer is Director, RainMan Consulting.

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