RoAS - the single most powerful metric known to advertisers. It can enrich or ruin your ad campaign. It can make or break your brand. It is an essential ingredient to optimise your Ad spend. According to some, it is the holy grail of marketing.
RoAS expands to “Return on Advertising Spend” It measures the amount of revenue generated as a result of the money spent on advertising.
The formula for ROAS is:
ROAS = 100 x (Revenue generate due to ad) / (Dollar Spend on the Ad)
As simple as this formula appears, you are never going to the get the answer by simply plugging in the numbers. That is because
· If you are a digital marketer, who tracks customers from click to cart, and put forth Cost per Sale as ROAS, you are not even remotely correct. Cost per Sale a highly biased version of the truth. This is because of last mile attribution. Last mile attribution means that the channel that hands over the product and collects the cash, gets all the credit, ignoring contributions from brand equity, seasonality, synergies from other media and even promotions working in tandem. It is like the goal scorer in soccer, getting all the credit for shooting the goal and not giving credit to those who set up the play and passed the ball. Cost per Sale may give you ahigh, but it can also give you a hangover.
· If you are an FMCG or CPG player you are truly stuffed. “Revenue from ad” is simply not available to you, not from any of your internal sources or from any of your retail panels or external vendors.
· Finally advertising possesses the property of persistence. It means that advertising has both immediate short term sales and sales in the long term. Customers, who buy due to the ad, may continue to buy even after the ad has stopped playing. This is the long term effect of advertising. Ignoring long term effects reduces your ROAS by half.
So what is the right way to estimate ROAS? We at RainMan believe that the only way to estimate a near correct ROAS is using mathematics or statistics, aligned with a sound knowledge of marketing.
This combination allows us to construct equations that mimic the market place and capture all the dynamics at play. Brand equity, distribution, seasonality, price, promotions, media, event sponsorship, PR, halo from sister brands, competition activity and other economic factors all have to be used in conjunction.
Then these equations are adjusted so as to capture the nuances of persistence, saturation, synergies, thresholds, non-linearity and non-symmetry in marketing. Solving these equations is the only way to arrive at the truth.
Isn’t it time to kick some RoAS?
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The COVID-19 pandemic has dramatically changed how markets operate and how consumers behave, shaking up the world in ways we’ve never seen before. As we move forward, the way we do marketing needs to change too. One key tool for this is the Marketing Mix Model (MMM), which traditionally helps businesses figure out the best ways to spend their marketing dollars and understand what works.
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How does one evaluate the return on investment from a sponsorship – let’s say the big bucks spent by Dream 11 on sponsoring the shirt of the Indian cricket team. Spend by Dream 11 was reported to be Rs 358 Cr for150 matches across all India teams – Men's, Women and Under 19. The interesting thing is that this rate is not even half spent by Byju’s and before them Oppo, who spent a whopping Rs 5.09 Cr per match. The increase and decrease in rate seems to be based on how buoyant some companies felt, a few years ago as opposed to how they are feeling today.
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RainMan has worked for over 15 years in the area of Marketing Analytics, and one consistent and recurring theme has been that otherwise great marketing companies, leave a lot of opportunity go a begging when it comes to use of their assiduously collected data.