Harmonizing POS data and determining secondary baselines based
on POS data

Business Problem

Multiple POS data providers, different granularity (levels) and different data formats have caused delays in getting actionable and meaningful insights from POS data. Many times planned promotions are not executed by retailers in the same week and with same offer hence, harmonizing the data from various sources to make sure the alignment is perfect between planning and POS data becomes very critical in order to get correct insights. Baseline volume is very important factor in measuring promotion effectiveness. Incorrect baselines leads to incorrect promotion analysis.

Issues

  • Challenges in harmonizing data from multiple sources, different levels and data formats.
  • Lack of meaningful insights from POS data to plan promotion
  • Delays in executing the right promotion at the right time.
  • Challenges in predicting accurate baseline volume.
  • Overspending and Underspending on promotions.

The SpendO Way

  1. Built in connectors for all major POS data providers like Nielsen, IRI.
  2. Supports all major data formats.
  3. SpendO architecture supports easy roll up/ drill down of POS data to align with promotion data.
  4. Built in algorithm to determine secondary baselines based on POS data.

“POS data is very critical to accurately measure effectiveness of trade promotions”

Built in POS connectors in SpendO helps to harmonize all types of POS data easily and timely manner. Also baseline calculation using POS data helps to understand the differences between primary and secondary baselines.

It is very important know the actual results of the promotions before investing in the same promotions in future. For Example, XYZ promotion planned for 100K units for certain product and customer executed for only 50K units. This information will help to plan promotions in future.

Secondary baselines help to determine the differences between forecasted primary baselines and secondary baselines. This helps to accurately measure incremental effectiveness of promotions.

Promotional Forecast Accuracy

 ActualForecast
Volume111.81M125.16M
iTO139.71M170.90M
ROI15.2%21.4%
ActualForecastVarVar %
15,55418,000-2,446-13.6%
15,28218,000-2,718-15.1%
33,39835,000-1,602-4.6%
40,36035,0005,36015.3%
28,04018,00010,04055.8%

Measuring Impact

  • SpendO Helped a global CPG company to improve their variance between actual and planned from 15% to 7% accurate.
  • The Planners learnt from past results and used these learning to improve planning accuracy.
  • Baseline analysis helped the planners understand the depth of reach with retailers and plan the promotions more effectively.
  • It also helped them to avoid overspending and underspending on some of the high stake promotions.