Marketing Mix Modeling for a US-based Consumer Durables Firm

  • 20%

    net sales opportunities

  • 12.7%

    improvement in incremental sales

  • $28m

    annualized cost savings

  • 16%

    ROI improvement

  • The client, a US CPG firm, wanted to quantify ROI of media vehicles such as DM and DRTV
  • The ROI was to be quantified over a two-year period, for which time series data on marketing spending on these vehicles and total sales through different channels was available
  • A multiplicative model was developed to forecast sales and arrive at the ROI from each vehicle
  • Identified data elements, e.g. sales, media spending, macro variables
  • Performed sanity checks for variables, e.g. missing values, extreme values, etc.
  • Calculated ad-stock functions to arrive at the most appropriate function for decay
  • Tested for stationarity and autocorrelation in the sales time series and determined the appropriate differencing, autoregressive, and moving average terms
  • Developed models incorporating alternate sales response functions
  • Compared alternate models based on forecast accuracy and model stability
  • Derived ROI the change in sales per unit change in spend based on the model prediction
  • Enabled the client to estimate and comparatively evaluate the ROI from its various marketing channels
  • Both DRTV and DM spending contributed significantly to sales growth (DRTV was a larger contributor than DM and also had superior ROI)
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