ibs Analytics
THE ADVANCED DATA DECOMPOSITION MODEL (ADDM)
![]() A sale is the result of the consumer perception of several Features such as:
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- Some external factors are to be taken into consideration like unemployment, growth rate, inflation rate, which have an impact on the consumer purchase's budget. Moreover, household happiness can increase sales, as people are willing to buy.
“SALES ARE MAINLY RELATED TO CUSTOMER PERCEPTION OF VARIOUS COMPONENTS, SO IS THEN FORECAST”
Although some of theses factors are hardly measurable, some others can be detected and even decided by the retailer. Moreover, a sale can be defined by some item's specifics:
- General trend,
- Seasonal cycle,
- Seasonal peaks,
- Price changes,
- etc.
SALES FORECAST MODELING
![]() From the sales history, ibs Analytics builds a forecasting engine of regular sales. By applying information mining & other methods, ibs Analytics extracts for each item several of its specifics components:
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- Weekly Variations- It models short-term variations of sales, represented by the variability of customers and changes in level of sales from a day to another
- Seasonal Peaks - It reveals repeating peaks in sales, mainly related to calendar and non-calendar events
- Baseline Forecast - It combines the above mentioned services, to provide a baseline forecast to end-user
MARKETING POLICY MANAGEMENT
![]() In addition, to the above forecast results, providing expected sales under same hypothesis, the below models allow to reflect change of these hypothesis on the forecast sales level and provide required simulation for the various connected businesses (offer management, pricing, promotions, markdown, allocation…)
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- Promotional Elasticity - Increase in volumes depending on the promotional policy (Single, BOGO, BAGB / Bundles)
- Elasticity Built Curve - Price change / promotion effect over time and its diffusion
- Flyer and Advertising Elasticity - Impact on communication over sales
- Halo and Cannibalization - Cross effects between items and sales correlations