Unlike the mobile phones market, the mobile services market in India is undergoing intense competition that’s giving the Management sleepless nights. Yet, along with challenges, multiple opportunities exist, when viewed with a granular lens.
- Market Development – Penetration into small towns and rural needs to be driven by understanding of consumer behaviour which can vary dramatically within geographies; segmentation is crucial, and so is rural distribution
- Higher Value Realization through robust marketing mix analysis – especially from smartphone users, the key task being to understand their spread across markets and tailor services to cater to them.
- Shared Resource Efficiencies – severe pressures on ARPU demand that shared resources remain an integral part of operations, not just on tower optimization, but retail expansion as well. Predictive Analytics can play an important part in evolving a more realistic sharing of resources
Our Analytics Repertoire
- Market Penetration Potential & Reach Estimation
- Retail Coverge Gaps
- Market Segmentation
- Consumer Segmentation (demographics, lifestyle & psychographics)
- Customer Lifetime Value / ARPU Optimization
- Reach / Resource Management
- Sales Force Allocation / Optimization
- Content Usage
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.