Company Executive Insights & Analytics
Network Demand Forecasting
What We’re Showing:
- Predicted traffic volumes in TB per region.
- Color-coded bars indicating high-demand vs. low-demand zones.
- Purpose: Forecast network load by region to guide CAPEX decisions.
- Insight: Reveal seasonal peaks, urban vs. rural usage patterns, and promotional spikes.
- Outcome: Allocate budget efficiently, reduce over-provisioning, achieve 20% CAPEX savings.
- Next Steps: Prioritize tower expansion in high-growth areas; monitor trending regions weekly.
| Region | Predicted Load (TB) | Recommended Action |
|---|---|---|
| East | 500 | Expand Towers |
| West | 300 | Monitor Trends |
Proactive Issue Resolution
What We’re Showing:
- Counts of predicted issues (signal drops vs. call failures).
- Pie slices colored by issue type.
- Purpose: Predict likely network quality issues before they occur.
- Insight: Identify clusters of signal drops and call failures by location.
- Outcome: Reduce support tickets, improve customer QoE by 15%.
- Next Steps: Allocate maintenance crews to high-risk zones; adjust network parameters in real time.
| Circle | Location | Issue Predicted | Action Taken |
|---|---|---|---|
| Circle-1 | Downtown | Signal Drop | Network Boost |
| Circle-2 | Suburb | Call Failure | Support Alert |
Churn Prediction & Retention Strategy
What We’re Showing:
- Customer segments (voice-based vs. data-based) with churn risk percentages.
- Suggested retention offers (discounts, extra data).
- Purpose: Identify segments at highest risk of churning.
- Insight: Provide churn probability alongside recommended retention offer.
- Outcome: Increase retention by targeting top 10% at-risk segments with personalized incentives.
- Next Steps: Launch targeted campaigns, monitor redemption rates, adjust offers dynamically.
| User Segment | Churn Risk (%) | Retention Offer |
|---|---|---|
| Voice-Centric Customers | 85% | 50% Discount on Voice Packs + Personalized Calling Plan |
| Data-Centric Customers | 60% | Free 5GB Data Pack + Loyalty Points |
Customer Lifetime Value Prediction
What We’re Showing:
- Customer IDs with predicted CLV in INR.
- Segments color-coded (High Value vs. Low Value).
- Purpose: Estimate each customer’s long-term revenue contribution.
- Insight: Segment customers into high-, mid-, and low-value groups.
- Outcome: Allocate marketing budget efficiently, focusing on high-value segments.
- Next Steps: Design premium offers for high-value customers; develop reactivation strategies for low-value segments.
| Customer ID | Predicted CLV (₹) | Segment |
|---|---|---|
| C5678 | ₹ 1,20,000 | High Value |
| C9012 | ₹ 40,000 | Low Value |
Revenue Forecast by Region
What We’re Showing:
- Last quarter revenue vs. next quarter forecast in ₹ millions.
- Bar grouping by region, highlighting variance percentages.
[Previous & Next Quarter]
- Purpose: Compare actual revenue from last quarter to forecast next quarter.
- Insight: Identify regions with accelerating or declining revenue trends.
- Outcome: Inform budget reallocation, prioritize growth initiatives.
- Next Steps: Increase marketing spend in underperforming but high-potential regions; optimize pricing promotions.
| Region | Revenue Last Q (₹M) | Forecast Next Q (₹M) | Variance (%) | Recommendation |
|---|---|---|---|---|
| North | ₹ 75 | ₹ 82 | +9% | Maintain current promotions |
| South | ₹ 60 | ₹ 68 | +13% | Increase promotional spend |
Campaign Optimization
What We’re Showing:
- Conversion rates (%) for each active campaign.
- Recommended new campaigns: “Urban Youth Outreach,” “Festive Season Boost,” “Digital Bundle Drive.”
- Purpose: Evaluate performance of current campaigns and suggest new initiatives.
- Insight: Compare conversion rates, identify underperformers.
- Outcome: Reallocate budget to high-ROI campaigns, reduce wasted ad spend.
- Next Steps: Launch new campaigns in pilot markets; A/B test creatives and messaging.
| Campaign Name | Conversion Rate (%) | Optimization |
|---|---|---|
| Summer Boost | 12% | Refine targeting to ages 18–25 |
| Festive Flair | 8% | Adjust creatives for local holidays |
Churn Heatmaps by Region
What We’re Showing:
- Churn percentages by region.
- Color gradient from light (low churn) to dark (high churn).
- Purpose: Visualize regional churn rates to spot high-risk areas.
- Insight: Highlight regions with above-average churn so retention teams can focus efforts.
- Outcome: Reduce overall churn by deploying targeted incentives and network upgrades.
- Next Steps: Roll out loyalty discounts, personalized bundles, and VIP support in high-churn zones.
| Region | Churn Rate (%) | Retention Strategy |
|---|---|---|
| North | 15% | Loyalty Discounts + Personalized Bundles |
| South | 10% | Network Quality Upgrades + VIP Support |
Competitive Benchmarking
What We’re Showing:
- Bar for port-out counts (left axis).
- Bar for sentiment scores normalized on a separate scale (right axis).
- Purpose: Compare our metrics against top competitors to anticipate churn and sentiment shifts.
- Insight: Observe port-out counts and public sentiment scores side by side.
- Outcome: Refine marketing and retention strategy to address competitive weaknesses.
- Next Steps: Enhance customer experience where sentiment lags; launch win-back campaigns in high port-out segments.
| Competitor | Port-Outs | Sentiment Score |
|---|---|---|
| Rival A | 500 | 0.75 |
| Rival B | 300 | 0.60 |