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For some years now, Attribution analysis has been king, and digital is being measured using Attribution models, which evolved over a period of time from simple attribution to the website of the transaction, to giving some credit to the others in the funnel (judgemental); and finally, to some statistical methods used to weight the impact of each website along the purchase path. Despite all of these advances, Attribution always suffered from a fatal flaw of not taking mass media, in store activity and promotion or indeed brand equity into account. This meant that all credit was given to advertising online, and the credit duly inflated. Not the ideal situation for your brand.
Moreover, the entire method depended on serving cookies to individual devices and then tracking the path to sales. This has now been upended by privacy laws, and slowly but surely, the ability to track individual paths needed for attribution is reduced.
Does this mean that marketers, especially those that spend a bulk of their budget on online, operate without even the limited knowledge that one got from attribution analysis?
Facebook, Google and other players have recognised the need for another measurement system that does not depend on individual data, but can operate with aggregate data not only from online but every other influencer of sales.
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Marketing Mix Modelling (MMM) has been a trusty old work-horse of FMCG companies, who rarely have individual data of consumers (online sales being a small fraction).The data available at weekly levels for both sales and inputs that include other important factors such as promotions, competitive activity apart from offline and online advertising. This method when used by online marketers will give a better picture, as this technique can figure out the diminishing effectiveness of each media in the context of the overall environment.
This can lead to better allocation of budget between media, understanding synergistic effects of media played together, improved return on marketing through optimization, and a comparison at individual website, type of input (video vs static) for every dollar spent.
Is MMM easy to deploy?
The answer is that it takes more discipline on the marketer’s part to collect data across the board, refresh the data at regular intervals, and also have the capability to run statistical models. It requires more effort but as the old adage goes” nothing worthwhile is achieved without hard-work”. The good news is the pain goes away as the systems set in and more processes such as structured data collection, validation of models and so on are automated. The tools exist, the adoption is the next step.
The ROI attribution that was done for digital advertising was never anywhere near perfect. The main issue was that it attributed “credit” based on various algorithms, each of which had its own share of problems. More importantly it had the issue of last mile attribution. Since people may have checked out a brand and then bought it online, all credit was given to digital advertising.
There seem to be many large brands that are spending too little on advertising, eventually leading to a weakening of the brand and its ability sell and command a premium. Take for instance Tanishq, a leader in the fine jewellery space with over 20 k cr in turnover, it is all but invisible on mass media. Sure, it is a fast growing brand, but is it actually taking full advantage of its strengths and the headroom in the industry? Probably not.