Marketing Mix Optimization

Marketing Mix Optimization: since the beginning of Marketing, calculating the ROI of any tactic used to attract customers has been one of the most challenging processes. The fact that not direct link exists among the different expenditures and the revenue got in several different locations and forms, is only part of the problem. The increase in the number of optional tactics across the increasing number of channels is facing a more and more rapidly changing world of consumers.

Today’s companies need to be serviced fast and accurate analytics for they may react almost in real-time to how their marketing campaigns are performing. With the huge amount of data to analyze, new techniques have to be used. Old linear regressions are of no use to create predictive models. OLS regressions with manual modelling techniques are difficult because the bigger and bigger number of variables to be fine-tuned turn this human driven process into an impossible task.

The only true solution is to make use of MACHINE LEARNING and ARTIFICIAL INTELLIGENCE to put the fine-tuning of big OLS into an intelligent loop. i4conAnalytics, has invested time to create new and more accurate modelling techniques that offer the best accuracy in a much shorter timeframe.

Download the attached documents to see some useful insights.

Case Study: leading U.S. Wireless Brand
Situation: with over $800 million in marketing spend, ROI and optimization was sought
Approach: marketing mix optimization
Results: measured savings near $200 million plus CEO and CFO engagement
Beyond savings and ongoing ability to optimize an evolving media mix, the model effort also measured the non-media baseline which showed contributions of service, pricing, mobile devices, plans, long term brand equity, and early social media.
Marketing Mix Optimization


i4conAnalytics MMO Model

i4conAnalytics Ticket Optimization Model