The Indian agri-business industry is characterized by infrastructure shortages, an under-developed process industry, series of recent de-regulations and a renewed focus on research to evolve a more professional approach from ‘farm to fork’. While doing so, some of the key marketing related issues that need to be addressed are:
- Segmentation of markets based on crops grown / pricing / farm size / lease terms
- Identifying & assessment of all the stakeholders on the supply side – farmer, village commission agent, district commission agent, wholesaler, sub-wholesaler, retailer
- Optimizing storage and warehousing locations
- Optimize mechanization – spread of farms vs farm yield
- Classifying markets based on degree of progressiveness, especially infrastructure
- Streamlining the marketing chain – cold storage, distribution – to ensure ‘freshness’ of end-product
- Identify pockets of yield-conscious & wellness-inclined farmers for premium offerings
Our Analytics Repertoire
- Target Identification
(by demographics, rural lifestyle, village infra & psychographics)
- Market Prioritization
- Progressive Index
- Sales Tagging down to Village / Habitation
- Feeder Markets
- Trade Network availability
- Market Expansion spotting, briefing & tracking
- Granular Segmentation by Crops grown or Farm size
- Rural Personas
The BrandIdea Business Analytics Product is distinctly unique. We have been modeling granular data assiduously for the last eight years – painstakingly, from the bottom-up —across 6 lakh villages, 8000 towns and 2 lakh neighborhoods 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.