Peter (Host): How do we avoid the pitfalls of classic Marketing Mix Modeling?
Sinan (Sales Head, NA, Research & Analytics): Typically, when we focus on deciphering RoI of marketing spends and incremental revenue, the classic modeling techniques do not incorporate the principles of the ‘Path to Purchase’. At the end of the day, the day the sales vs. marketing congruence continues to be elusive. Before getting into measurement of RoI, we take a step back and map out the ‘Path to Purchase’ and understand intermediary drivers that lead to sales. These intermediaries could be consumer awareness, share of mind, distribution, or the 3As – Affinity, Accessibility, Affordability. It’s important to understand how to influence each of these intermediate levers independently and their inter-relationship that drive sales. For example, if your objective in the short term is to drive awareness, then you should know which tactic delivers the highest RoI to drive awareness. Or if your goal is to increase distribution alone – which tactic should I use. In one case, we were able to point out that driving distribution was a function of relative price difference between the client’s own two brands. This allowed them to also focus on their own pack size and price mix rather than pumping more into trade discounts. By keeping only sales in focus, we may end up thinking very linearly about the variables that lead to sales.
Peter: What are the fundamental steps for a retailer to start monetizing their media and data assets?
Seema (Solution Expert, Research & Analytics, WNS): In terms of paving the road: First, there is navigating the complex ad tech world and getting the right partner on board. From ad tech, to data, ad ops to ad sales, each service line needs to complement the other and often the fragmented players (albeit specialized) mean more hands offs, margin cuts, less net revenue and compromised efficiency for the retailer. So, having a partner who can service end-to-end makes a lot of sense. Second, getting your consumer profiles & preferences all in one place so that you can power through creating segments and personas in interesting shapes and sizes so that you do the right targeting and allow for attribution. Third, is getting your programmatic proposition in place while keeping consumer experience at the heart of it. So, this directly dictates which of your media assets are reserved buys, private or open auctions. You’ll see the CPM and yield you can command in these different channels is so intricately tied to your data and targeting capabilities. It becomes crucial to have a tech agnostic partner that can unlock the immense possibilities with your data as well as they can network with agencies & exchanges out there.
Peter: How can companies keep track of emerging trends and brands and future-proof themselves?
Sinan: We have a very relevant success story with one of the largest global beverage CPG clients of ours. We co-created an “Emerging Brands and Trends Tracking'' platform with them. There is no shortage of data resources in the fingertips of large CPG’s today. POS, Primary Market Research, Product and Ingredient DB’s are just to name a few. Social Media Listening and generating insights around emotional sentiment, food and beverage pairings, consumption occasions have emerged in the not so distant past but they become a commodity very quickly, everyone does Social Media Listening today. The differentiation and real value comes from integrating Social Media data and insights into other relevant data sources and driving actionable insights for various user groups. Not only we are continuously listening to consumers on social media and identifying emerging brands and food and beverage ingredient trends, but we also integrate this data to various other value-added data resources such as POS, M&A DB’s, other Market Research data such as Mintel and specialty food and beverage blogs etc.
There are 3 key user groups who are heavy users of this platform in our client organization. Brand and Marketing teams are obviously the heaviest and most frequent users. New Product Development R&D groups use it for inspiration in using new ingredients and packaging types. And finally, when those emerging brands that we identified are starting to hit POS in significant scales, Strategy and M&A group is very interested to know about them. We are listening across the world real time and from an AI/ML perspective, the Taxonomy we co-created with our client is very differentiating. It is an ever evolving human in the loop A/MLI process, in which potential emerging brands or ingredients are identified by the algorithms and then they get finalized by a human expert in the loop before tracking starts.