The complexity of the business environment makes investing in outcome-based planning crucial.
The market is in a constant state of flux driven by micro and macro environmental factors. Media and shopper journeys are changing with continuous digital acceleration. Digital media and commerce, while expanding, are fragmenting with new areas requiring a share of the sales and marketing spending. Businesses need to work towards sales & profitability growth through simultaneously optimizing existing and new business operations. Outcome-based planning enables optimum allocation across the entire mix. Creating a repository of learning is also essential.
Econometrics and Data Analytics helps effectively navigate, course correct and maximize ROI.
Questions to ask:
What are the effects of distribution, price, sales promotions, media and other relevant variables on sales? How do the intermediate variables (e.g. awareness, consideration, loyalty, and intent to purchase) impact the purchase journey and the final purchase? What role do the sub-brands and variants play within the overall portfolio? What mainline, digital and activation media impact intermediate variables and final purchase? How does advertising play out in the long and short term? What is the best scheduling strategy for investment deployment and ideal operating weights before diminishing returns set in? What is the composite contribution of all individual components to the business KPI? And what, therefore, is the optimum allocation across all investment areas? How do they vary across different categories/ brands/ sub-brands and variants the business operates in, and how does this vary across markets? What factors indicate the potential for future growth, and how can better forecasting be done to allocate finite budgets to the best areas for maximizing ROI?
Ability to course correct and maximize ROI:
Through Econometrics and Data Analytics, we answered these questions across various categories and brands. For an e-commerce brand in the growth stage, we realized that the potential for accelerated growth lay in Tier 1 cities leading to a course correction in inputs towards them. For a Retail brand embarking on a footprint expansion, we realized that they needed to reduce their footprint and instead move investments into creating a different retail mix and product mix within the retail outlets. For a Mobile brand, we realized the variable impact of different media on products in various sub-segments and the halo impact of sub-brands within the portfolio, leading to optimizing budget allocation across the sub-segments. For a Personal Care brand, we could construct their entire purchase pathway and course correct on theme vs promo allocation, relative-price-index, and identify threats from new formats in the category. For a Healthcare brand, we were able to redirect media investments to new areas and break stagnation for the first time in years, leading to econometric modelling becoming part of their year-on-year marketing spend deployment process.
How to put in practice – Must Haves and Watchouts.
Identify areas where improved efficiency will bring in maximum results and set hypotheses to test. Building cohesive, continuous databases pulling data from different sources is a fundamental requirement. In this era of data deluge, it is also important to decide what to bring in and exclude. One-time exercises do not work. Continuous incremental efforts are needed. Once actions have been taken based on new insights, look at predicted vs actual scenarios to see how to improve forecasting and test new variables. Ultimately outputs have to be looked at in the context of domain expertise – explain the why behind the what. In a diverse country like India, a correct granularity of the exercises is essential, failing which there is the danger of missing out on different factors in different geographies. For multi-category, multi-brand enterprises, cross-category and cross-market insights are necessary with a repository for capturing and refining the learnings over time.