While Insurance Companies are still in the process of putting into place measures that take advantage of IRDA stipulations of 2015, this is as good a time as any to set right some chronic imbalances which have plagued this sector, namely:
- Product / Market mismatch – Marketing Mix Analysis
- Mismatched distribution structure – both markets and skill-related.
- Lacunae in leveraging channel partners optimally / Retail Coverage.
- Pricing disparities which prevent the industry from leveraging value adds.
- Gaping holes in customer service that gives the industry a tardy image and prevents leveraging of customer relationships for future up-sells.
- Identify segments to cross-sell/up-sell, in highly urbanized centers.
All these are tackled by our Neighbourhood-level Marketing Analytics that allow you to zero-in to the right household across every city in the country and automate customized interventions that leverages CLM to the hilt.
Our Analytics Repertoire
- Customer Segmentation (demographics, lifestyle & psychographics)
- Agent Segmentation & Optimization
- Cross-sell / Up-sell opportunities
- Customer Attrition / Retention Prediction
- Customer Lifetime Value
- Agent / Sales Force Optimization
- Sales Analysis
- Channel Profitability
- Personas by Risk appetite
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 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.