The client is a large FMCG marketer in FMCG category.
In recent times their FMCG brand in the matured urban market has faced stagnation in sales. The client is try to get marketing insights on their media plans which can help increase media throughput and thereby increase sales and market share.
TV is the largest & most prominent media vehicle for this brand and so any improvement in TV output is bound to have the biggest impact.
Standard market mix models are only able to capture the effectiveness of different media vehicles in driving sales and their overall RoI. It offers a generic attribution of sales to AV but several questions remain unanswered:
Which type of channels (e*g* National/Regional; Cable Satellite/Non-CableSatellite; Primetime/Non-Primetime) work better?
Which genres (Action Ahriller' Soap Opera' Comedy' etc.), work better than others?
How are we to allocate the given budget across channel types' genres andday parts to increase sales' without any increase in budget.
To answer the above questions one has to go beyond generic market mix models and perform deep dive analysis into media*
Break the contribution of overall AV into different channels(e*g* National/Regional; Cable Satellite/Non-Cable Satellite; Primetime/Non- Primetimet
Break the contribution of overall AV into genre level contribution
Simulate various business situation of reallocating AV budget withinchannels at different combinations to get sales uplift
This market mix model provided the contribution of ,TV at an overall level ,he contribution of ,TV obtained from marketin mix is
then used for the deepdive analysis Followin analysis are performed to deliver answers to the models.
To derive respective weights of different combinations of channels &genres.
To derive the contribution of channels and determine each one's effectiveness
Optimize the budget allocation of TV for different components ofchannels to simulate sales uplift
The deep dive analysis provided the following actionable insights:
Identified the channels which have higher contribution to sales as compared to others
Prioritized the list of genres which are most contributing to sales, whichwarrant an increase in TV GRPs
Optimized the media budget by cutting spends on unproductivechannels, genres and day parts and reallocated the savings toproductive channels, genres and day parts
4% to 10% sales uplift obtained using different scenarios
Vintage : Jan 2009 to June 2012
Granularity : Monthly
Impact Variables
Sales Volume
Input Variables
Distribution
Out of Stock
Share Amon Handlers
TV GRPs (converted to Ad stock)
5 Key Competitors' Marketing inputs
price
The following analysis was conducted on the data for the market mix model:
Exploratory Analysis
Counts, sums, averages, distributions
Trends, Seasonal, Peaks and Troughs
Bayesian Networks
Multivariate Relationships
Path to Purchase
Share Amon Handlers
Vector Auto Regression (VAR)
Variant level sales anal sis
Parameter Estimates
Carry Over Effects
There are a great many additional business insights that can be derived from media deep dive analysis that was not possible with conventional market mix modelling.
The analytic procedures adopted indicated that Regional Channels viaCable Satellite Network during Primetime was the most effective channelsto invest in. Next in line are the National Channels through Non-CableSatellite in the Non-Primetime day parts. Within genres it was able toisolate soap opera and comedy as the winners compared to feature films,cricket and action thrillers.