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Long timelines, efficiency losses, inconsistent quality and reduction in margins – these are the issues that beset the traditional retail supply chain in India and it is exactly these lacunae that eB2B Cos are rapidly addressing. Especially in Tier 2 and Tier 3 towns.

But to do this, eB2B Cos need to understand the spread and profile of the huge spread of intermediaries that make up the distribution network. Doing this at a macro level is not enough – the more micro the data is, the more tailored and cost-effective the solution would be. Since eB2B Cos are also addressing issues like credit, logistics and customer foot-falls, hyper-local data & insights are absolutely indispensable. And this is BrandIdea’s forte!

Our Analytics Repertoire

  • Retailer, Distributor and Wholesaler Universe with their size, profile and location
  • Uncovered Outlets with their size, profile and location
  • Profile of outlets around Retail outlets; demographics, occupation, life-stage, lifestyle, income, HNWIs, etc.
  • Profile and spread of SMEs, etc.
  • Feeder Villages listing and profile, and profile of catchment areas around the Feeder Villages

The BrandIdea Business Analytics Product is distinctly unique. We have been modeling granular data assiduously for the last ten years – painstakingly, from the bottom-up — across 6 lakh villages, 8000 towns and 2 lakh neighbourhoods of India. We use an array of data-science techniques to generate powerful and compelling granular analytics, which make actionable insights literally pop out of the screen, with the help of versatile data visualizations.

Since the resulting interventions are customized and intense at the micro-level, there is minimal wastage of marketing and sales effort, as against a top-down, trickle-down approach. Also, these efforts drive higher growth by aggregating the effect of customized actions as against the diffused effect of top-down implementation.

At the micro-level, the multiplicity of these data points result in insightful predictive and prescriptive analytics, leading to surprising revelations that answer queries which traditional research would have struggled on. Such insights would not have emerged but for the granularity of data and analytics.


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