Sales Performance Forecasting

Identifying market potentials set against competitor pressure

IKEA is a Swedish multinational conglomerate that designs and sells ready-to-assemble furniture, kitchen appliances and home accessories, among other useful goods and occasionally home services. As of March 2021, there are 378 IKEA stores operating in 30 countries, and in the fiscal year, 2018, €38.8 billion (US$44.6 billion) worth of IKEA goods were sold. All IKEA stores are operated under a franchise from Inter IKEA Systems B.V., most of which are operated by IKEA Group, and some of them are operated by other independent owners.

The Challenge

IKEA India was looking to understand precise spending on home appliances and furniture category on residential building precision in order to assess their outlet locations’ catchment area sales potential. The company understands that PIN code or city locality– level data does not suffice to achieve here the precision of the sales prediction model output as desired.

The KENTRIX Solution

The KENTRIX household/residential building precise mapped information about income, expenditure, and consumer lifestyle affinity segmentation was modeled into a geospatial sales value map applying ML-driven calculations fed by consumer profile data in combination with purchase data in the category home appliances and furniture.

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  • On residential building precision, expected annual furniture and home accessories spending was calculated using the KENTRIX consumer profile data set. Thematic maps were created for the expected turnover visualization. With this, IKEA India sales outlets were analysed in a complex geospatial data equation using customer potential income, shopping affinities, consumer lifestyle affinity, competitor pressure, site accessibility, traffic times, etc.
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  • Competition sales locations were mapped, and competitor pressure thematic maps were created, overlaying over the potential maps and unfolding the next best location(s) to finalize. Other furniture brands and their outlet locations were rated and translated into a competitor influence map identifying competitor pressure on precise subsets of consumers.

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