Executive Summary
The numbers the business is judged on, where the growth is coming from, and the three moves that matter this week.
AI Insights
Written weekly against a fixed 30 day window, grouped by the team that has to act.
Net sales trend
Daily, This month vs last year (dashed), in Cr
Channel mix
Share of net sales, MTD
Top performing stores
By SSSG, MTD
| Store | Sales | SSSG | Type |
|---|---|---|---|
| Bandra Linking Rd, Mumbai | 24.2 L | +14.2% | COCO |
| Koramangala, Bangalore | 22.6 L | +12.8% | COCO |
| CP Connaught Place, Delhi | 21.1 L | +11.1% | FOFO |
| JM Road, Pune | 19.8 L | +9.6% | COCO |
Needs attention
By SSSG, MTD
| Store | Sales | SSSG | Type |
|---|---|---|---|
| Viman Nagar, Pune | 4.8 L | -9.4% | FOFO |
| Salt Lake, Kolkata | 5.2 L | -7.1% | FOFO |
| Gachibowli, Hyderabad | 5.6 L | -5.8% | FOFO |
| Dharampeth, Nagpur | 6.1 L | -3.2% | FOFO |
Net sales trend
Daily, This month vs last year (dashed), in Cr
AOV price bands
Share of bills
COCO vs FOFO
Net sales and SSSG
Sales by region
MTD
| Region | Sales | Share | SSSG |
|---|---|---|---|
| West | 19.4 Cr | 37% | +8.1% |
| South | 15.2 Cr | 29% | +6.9% |
| North | 11.6 Cr | 22% | +2.7% |
| East | 6.2 Cr | 12% | -1.4% |
Store sales trend
iBandra Linking Rd, monthly net sales last 12 months vs prior year (dashed), in lakh
What this store sells
Net sales by category, in lakh
Store P&L league
Top of the table by EBITDA margin, MTD
| Store | Type | Sales | NOB | AOV | Target ach. | EBITDA % |
|---|---|---|---|---|---|---|
| Bandra Linking Rd, Mumbai | COCO | 24.2 L | 6,505 | 372 | 108% | 26.1% |
| Koramangala, Bangalore | COCO | 22.6 L | 6,125 | 369 | 104% | 24.3% |
| CP Connaught Place, Delhi | FOFO | 21.1 L | 5,765 | 366 | 101% | 22.8% |
| JM Road, Pune | COCO | 19.8 L | 5,410 | 366 | 96% | 19.4% |
| Hauz Khas, Delhi | FOFO | 18.4 L | 5,015 | 367 | 94% | 18.1% |
| Viman Nagar, Pune | FOFO | 4.8 L | 1,350 | 356 | 72% | 10.4% |
Note: full store P&L needs per-store cost data (rent, manpower, COGS, aggregator commission). For FOFO stores we show what the franchise shares. Depth of P&L is a data input we will confirm.
Category mix
Share of net sales
Hourly sales movement
iAverage day, share of sales by hour
Top SKUs
MTD
| SKU | Units | Share | Attach |
|---|---|---|---|
| Naked Nutella | 2,66,000 | 9.0% | Bestseller |
| Belgian Chocolate | 2,36,000 | 8.0% | Med |
| Chocolate Overload | 1,77,000 | 6.0% | High |
| Lotus Biscoff | 1,45,000 | 4.9% | Med |
| Ferrero Rocher | 1,30,000 | 4.4% | High |
| Red Velvet | 1,18,000 | 4.0% | Med |
| Ferrero Rocher Shake | 1,21,000 | 4.1% | Med |
Pilots & new launches
Tracking since launch
| Launch | Outlets | Daily sales | Cat. share |
|---|---|---|---|
| Dubai Chocolate Waffle | 180 | 9.2 L | 7.0% |
| Mini Waffle Party Box | 140 | 4.6 L | 3.5% |
| Kinder Bueno Swirl | 90 | 3.1 L | 2.4% |
Daily sales since launch
iBy launch, week 1 to week 8 since launch, in lakh
Outlets live by launch
Current footprint
Category share per launch
Share of its parent category
Launch tracker
Tracking since launch
| Launch | Outlets | Daily sales | Cat. share | Signal |
|---|---|---|---|---|
| Dubai Chocolate Waffle | 180 | 9.2 L | 7.0% | Scale |
| Mini Waffle Party Box | 140 | 4.6 L | 3.5% | Hold |
| Kinder Bueno Swirl | 90 | 3.1 L | 2.4% | Watch |
New vs repeat revenue
Last 12 months, identifiable base
Cohort retention
Share of a cohort still buying, by month since first order
Coupon and offer analysis
MTD
| Offer | Redemptions | Revenue | Avg discount | Incremental? |
|---|---|---|---|---|
| Flat 20% weekday | 2,40,000 | 5.2 Cr | 19.6% | Low |
| Buy 1 Get 1 shakes | 1,45,000 | 3.2 Cr | 24.1% | High |
| Loyalty birthday treat | 72,000 | 1.3 Cr | 12.3% | High |
Honest caveat: new vs repeat and cohorts are computed on the identifiable base, loyalty, app and direct. Swiggy and Zomato anonymise the customer, so aggregator walk-ins sit outside cohort maths. We size and label this clearly rather than overstate it.
Complaints by category
MTD
Aggregator funnel
Impression to order, blended Swiggy and Zomato
Store watch, ops
Highest complaints per 1,000 bills, MTD
| Store | Complaints | per 1k bills | Top issue | Audit |
|---|---|---|---|---|
| Salt Lake, Kolkata | 142 | 14.1 | Delivery delay | 79% |
| Gachibowli, Hyderabad | 118 | 11.8 | Quality | 81% |
| Viman Nagar, Pune | 96 | 9.2 | Missing item | 83% |
| Dharampeth, Nagpur | 71 | 7.6 | Packaging | 88% |
- 8 of 12 are a footfall gap, walk-ins down 9 to 14% vs last year.
- 4 are a billing gap, footfall fine but conversion of walk-ins is low.
- 5 of the 12 sit in West metro, a cluster, not random.
| Store | Conv. | Target | Gap |
|---|---|---|---|
| Viman Nagar, Pune | 38% | 52% | -14 |
| Salt Lake, Kolkata | 41% | 52% | -11 |
| Gachibowli, Hyderabad | 44% | 52% | -8 |
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How it works
Quick for a number, Standard for a short deep dive, Deep for the full why. It writes the queries, pulls the data, and comes back with the action, every figure tied to a real query. On the live version it runs on your own data and never leaves your environment.
Reviews and rating
iNet promoter score
iChannel ratings
iAverage star rating by channel and mode
Volume is real and large: one Mumbai outlet alone carries 5,797 delivery reviews, and one Delhi outlet 8,217 dining reviews. Ratings are weighted by that volume.
Ratings trend
iBlended rating, last 12 months
A gentle slide from 4.3 to 4.1. Small on paper, but it is the number aggregators rank you on. This is recoverable.
Sentiment by theme
iShare of classified reviews, positive and negative themes
What customers are actually saying
Verbatim public reviews pulled this month, tagged by sentiment and channel.
What is real here: the channel star ratings and the verbatim quote cards are scraped from live public reviews on Zomato, Google and Swiggy. The 88,000 review count, the sentiment split and the NPS are our read of those reviews, illustrative. The live version streams these daily from every channel and ties each theme to store and SKU.