Mumbai-based iPredictt Data Labs, a big data analytics provider of machine learning software to B2C, B2B companies recently launched a marketing RoI tool, iPredictt MMM+. Built using Big Data tools, MMM+ allows data transformation to best fit non-linear relationships between advertising variables, product sales, brand strength in competitive scenarios, awareness and market share.
In an interaction with Express Computer, Rohit Verma, CEO , iPredictt Data Labs sheds light on marketing mix models and how companies can leaverage big data analytics to predict the performance of marketing channels
Edited Excerpts
What are the big data trends you are seeing in the market? What CIOs are looking for?
Data is the new tool for all companies to compete on. And the volume of data is growing by the day given digital penetration into lives of consumers. Most of the touch points are today digital where you are capturing consumer journey from product discovery to sales. Unless companies understand various elements of customer choices, it would be very difficult to survive a market like India. As we know India is not a protected market like China. Here world’s biggest companies operate, they bring in almost of a decade of high quality digital experience coupled with data sciences. Indian companies have to quickly catch up or they will perish. CIOs are still trying to organize their departments to deal with the data deluge and its early days in India
Please share your insights on traditional marketing mix models and its challenges
Traditional marketing mix does not cover many aspects of changing business dynamics. Such as social media nuggets. For any marketing one of the most visible consumer choices are today seen on social platforms. Unless it’s given right weightages, Traditional MMM will not provide a true picture. Traditional Marketing Mix Modelling or MMM is laced with biases as they do not incorporate impactful dimensions such as large volume of social data, channel lag, channel fatigue etc.
Can you please tell us about the use of Big Data Analytics to predict the performance of marketing channels? Can you share use cases of it?
Using various Big Data Tools, channel’s performance and its link to sales, brand awareness, market share can be deduced. This helps in understanding which channel is most effective or which combination of channels in most effective. This is important for any brand manager to understand real impact. Till now, its only been extending the spends trend of the past. With digital dynamics have changed.
Example. If a brand has 100 cr to spend. There are five channels like TV, Print, Radio, Outdoor and Digital.The first question solved is which channel fits best and will give best sales output. iPredictt’s MMM+ which is an advanced prescriptive marketing mix model using big data tools delivers that using historical and social data and other tools of data transformations
How with the advent of Big Data Analytics, Marketers are using it to bring in real time data, social perception and accurate mapping of diminishing returns. Can you please explain with examples?
This is an evolving science, not sure if marketers have started using this. We work with some of the FMCG companies and the tools used are still old ones which provide opaque results.
The big data tools map channels based on lag and fatigue parameters. The tool is able to tag each channel accordingly and output data is synchronized accordingly.
Please share your insights on the iPredictt MMM+ and its relevance in the current market scenario
iPredictt MMM+ is very relevant for any marketer who wants to get best results from every dollar spent. It removes the need to use intuition or hunch or past performances. As digital marketing spends move up the graph, the need to hit the right audiences and right channel is very much required. Hopefully, big data will play its appropriate role in helping brands make faster decisions.
