Our client, world’s first performance branding company collapses the silos between performance and brand to unify marketing objectives, targets, & strategy


Transorg Analytics adeveloped a market mix model and a KPI forecaster (both embedded in one end to end framework) on top of it by using advanced analytics and machine learning techniques covering at least 8 brands across US, UK and Canada regions to provide granular level insights at the ‘Country X Brand X Sub-brand X level and at the ‘Channel (platform plus audience) X’ level.

Models are refreshed weekly to remain calibrated with updated spend budgets and most recent actuals.

For each brand the input data used for building the models included:

  • Channel wise spend on a weekly basis.
  • Weekly total business revenue
  • Promotional Periods
  • Monthly spend budgets.
  • Monthly revenue goals (just for comparison)

Modelling (MMM)

  1. Analyse historical spend distributions and their contribution towards total business revenue.
  2. Manual weights can be assigned towards specific channels and months based on previous year data.
  3. Output the spend recommendations based on MMM model on a monthly/daily level.

Modelling (Forecasting)

  1. Take the spend recommendations of MMM model as an input.
  2. Generate weekly revenue forecasts with in-built cross validation.
  3. Interpolate forecasts into monthly and daily level.


  • Daily/Monthly Spend Recommendations
  • KPI (like revenue) forecasts daily/monthly on spend recommendations
Learn more about TransOrg’s value proposition, solution methodology and implementation approach