Commerce is spreading. Value is concentrating.
Across twelve months of EasyEcom data, the clearest pattern is a growing divergence between where orders come from and where value sits. Order volume is widely distributed. Value is considerably more concentrated. The same pattern extends well beyond geography: different commerce models carry radically different economics.
| Segment | Share of orders | Share of value | AOV | Divergence index |
|---|---|---|---|---|
| Outside the 96 largest cities | 57.2% | 39.3% | $8.66 | 0.69 |
| The 96 largest cities | 42.8% | 60.7% | $17.89 | 1.42 |
| Top 3 states by value | 26.0% | 44.1% | — | 1.70 |
| B2C | 89.4% | 64.1% | $10.11 | 0.72 |
| Fulfillment | 10.37% | 6.9% | $9.44 | 0.67 |
| Quick commerce | 0.04% | 1.7% | $667.49 | 47.2 |
| B2B | 0.29% | 27.3% | $1,344.65 | 95.3 |
Volume follows people. It fills Uttar Pradesh and Bihar, and it arrives from beyond the ninety-six largest cities more often than from within them. Value follows structure. It gathers in Maharashtra, in Karnataka, and in a handful of commercial districts where a single order is worth six times the national average.
The line kept climbing
EasyEcom-processed order volume continued to build through the year, with the second half materially ahead of the first.
| Period | Orders | Change |
|---|---|---|
| August to January | 94.1M | — |
| February to July | 112.3M | +19.3% |
The rate of expansion has moderated sharply, though. Festive volume grew 99% between 2024 and 2025. On the current run rate it grows under 20% into 2026, a fall of roughly 80 percentage points in a single year. That is still growth, and 2026 would still be the largest season the platform has handled. But the years that forgave a rough operating model are ending.
The big festive spike is giving way to a longer season
The festive season looks different when viewed across the quarter rather than through a single peak. October did not produce a dramatic jump, but demand remained elevated across the surrounding months.
| Month | Orders | Month on month |
|---|---|---|
| August 2025 (estimated) | 16.64M | — |
| September 2025 | 16.60M | — |
| October 2025 | 16.67M | +0.4% |
| November 2025 | 14.93M | -10.4% |
| December 2025 | 16.45M | +10.2% |
The monthly data suggests elevated demand is being spread across a wider period, making the season look more like a plateau than a single spike. August is estimated and therefore excluded from this inference; the plateau is measured from September onward.
The signature sits in value rather than volume. October carried the year's highest consumer share of value at 75.80%, against 69.24% in August and 64.27% by July 2026. The festive season is there in the mix, even when it is invisible in the count.
The next festive season starts from a much higher base
Diwali moves 19 days later in 2026, shifting the centre of the festive calendar deeper into November. If elevated demand continues to behave like a quarter-long season, brands will need to shift their preparation window with it.
Some states deliver far more value than their volume suggests
Thirteen of India's fifteen largest commerce states change position when the ranking switches from order volume to order value. Only Maharashtra and Delhi hold their place. The most quoted map of Indian commerce is a volume map. It is not the map that describes where money is made.
| State | Rank by orders | Rank by value | Movement | Orders | Value ($M) | AOV |
|---|---|---|---|---|---|---|
| Maharashtra | 1 | 1 | 0 | 25,749,014 | 477.8 | $18.56 |
| Uttar Pradesh | 2 | 4 | -2 | 23,629,311 | 222.1 | $9.40 |
| Karnataka | 3 | 2 | +1 | 19,404,757 | 336.8 | $17.36 |
| Tamil Nadu | 4 | 5 | -1 | 13,095,191 | 159.8 | $12.20 |
| Gujarat | 5 | 9 | -4 | 10,954,209 | 108.5 | $9.90 |
| West Bengal | 6 | 8 | -2 | 10,912,287 | 109.3 | $10.02 |
| Delhi | 7 | 7 | 0 | 10,293,379 | 128.6 | $12.49 |
| Telangana | 8 | 6 | +2 | 10,084,890 | 135.2 | $13.41 |
| Rajasthan | 9 | 10 | -1 | 8,448,692 | 78.6 | $9.30 |
| Bihar | 10 | 15 | -5 | 8,323,601 | 52.9 | $6.36 |
| Haryana | 11 | 3 | +8 | 8,302,746 | 329.7 | $39.71 |
| Kerala | 12 | 11 | +1 | 8,234,767 | 78.2 | $9.50 |
| Madhya Pradesh | 13 | 14 | -1 | 7,390,485 | 55.0 | $7.44 |
| Andhra Pradesh | 14 | 13 | +1 | 7,351,077 | 57.7 | $7.85 |
| Punjab | 15 | 12 | +3 | 6,480,693 | 63.4 | $9.78 |
Haryana is the clearest outlier, moving eight places from 11th by orders to 3rd by value, with an AOV of $39.71. Its value is concentrated in Gurugram and Sonipat, pointing more toward corporate and distribution activity than consumer demand. Bihar moves five places in the opposite direction, from 10th by orders to 15th by value, with the lowest AOV in the set at $6.36.
Where you sell changes what an order is worth
The gap between the highest and lowest state average order value is 7.1 times. Set Haryana aside as structurally distinct, and Maharashtra at $18.56 is still 2.9 times Bihar at $6.36. That range exists inside one country, on one platform, under one set of definitions.
Highest: Haryana $39.71 · Maharashtra $18.56 · Karnataka $17.36 · Telangana $13.40 · Delhi $12.50
Lowest: Tripura $5.60 · Bihar $6.36 · Odisha $6.36 · Jharkhand $6.47 · Chhattisgarh $6.72
More than half the orders come from outside the biggest cities
The biggest cities still carry a disproportionate share of value, but they do not account for most of the order volume. More than half of all orders come from everywhere else.
| Segment | Orders | Share of orders | Value ($M) | Share of value | AOV |
|---|---|---|---|---|---|
| 96 largest cities | 88.1M | 42.8% | 1,575.2 | 60.7% | $17.89 |
| Everywhere else | 117.7M | 57.2% | 1,018.7 | 39.3% | $8.66 |
The concentration is even sharper at the very top: the five largest cities contribute just 15.7% of orders, while the top ten account for 22.0%.
Bengaluru brings the volume. Gurugram brings the value.
Bengaluru handles 11.0 million orders, 84% more than Mumbai, and one in every eight orders among the resolved cities. Gurugram is seventh by volume and second by value. It generates more order value than Delhi, Hyderabad or Chennai individually, on roughly half of Delhi's order count.
| Rank | City | Orders | Value ($M) | AOV |
|---|---|---|---|---|
| 1 | Bengaluru | 11.0M | 244.8 | $22.19 |
| 2 | Mumbai | 6.0M | 158.3 | $26.36 |
| 3 | Delhi | 5.8M | 90.8 | $15.65 |
| 4 | Hyderabad | 5.2M | 94.7 | $18.24 |
| 5 | Pune | 4.3M | 66.4 | $15.35 |
| 6 | Chennai | 3.2M | 58.3 | $18.13 |
| 7 | Gurugram | 2.8M | 192.9 | $69.86 |
| 8 | Kolkata | 2.5M | 35.2 | $14.05 |
| 9 | Ahmedabad | 2.5M | 34.8 | $14.20 |
| 10 | Thane | 2.0M | 51.8 | $26.22 |
Gurugram's average order is $69.86, more than four times Delhi's $15.65. Below the metros the range widens rather than narrows. Noida records $32.75 and Greater Noida $40.70, both far above Delhi, despite sitting in the same urban region. Rajkot, on nearly a million orders, records $6.51.
Quick commerce looks like retail but runs like distribution
The transaction profile is unlike conventional consumer commerce. Quick commerce order value remains remarkably high and stable even as order volumes rise sharply through the year.
| Period | Orders | Value per order |
|---|---|---|
| August 2025 to January 2026 | 16,740 | $688.19 |
| February to July 2026 | 29,648 | $674.36 |
| Change | +77.1% | -2.0% |
Orders more than tripled while value per order remained within a relatively stable band, never falling below $590 in any month. That profile is difficult to reconcile with a conventional consumer basket and appears more consistent with supply into quick-commerce networks.
| Order type | Value per order | Against B2C |
|---|---|---|
| B2C | $10.11 | 1.0x |
| Quick commerce | $667.49 | 66x |
| B2B | $1,344.65 | 133x |
The economics place quick commerce much closer to a distribution relationship than a conventional retail order. For brands, that means different considerations around replenishment, stock positioning and dispatch cadence.
The real shift is happening inside the order mix
Order volumes tell you how much moved. They do not tell you how much came from demand and how much from a changing brand base. Composition is the sturdier signal, because what the platform processes is more robust than who is on it.
| Series | Range | Mean | Coefficient of variation |
|---|---|---|---|
| B2C share of value | 11.22 pts | 64.31% | 5.2% |
| B2B share of value | 10.08 pts | 27.11% | 10.8% |
Two movements are visible. Quick commerce share of orders more than doubled, from 0.024% to 0.052%, but the base stays tiny throughout, around five orders in every ten thousand. A marginal channel became less marginal. It did not arrive at scale.
B2B value share has no direction at all. It runs from 22.91% in October to 32.99% in July, a spread of 10.08 points. Similar movement in points to B2C, but against its own size, B2B swings twice as hard, lurching more than four points in a single month four times over.
Why the second one matters more
Consumer demand is millions of small decisions. It aggregates smoothly. Consignment demand is a few hundred thousand large ones. One order can move a month. So the value crossing the same warehouse floor can shift by a third, with no change in consumer behaviour at all. Capacity planned against consumer seasonality will be wrong every time a consignment lands.
Six ways the playbook needs to change
Every rule below is attached to a number from the preceding pages. None of them is advice in general. Each is what follows if the finding is true.
Plan for efficiency, not just capacity
The festive cycle is still growing, but its rate of expansion has moderated sharply from the previous year. That changes the question from how much more capacity to add to how efficiently the existing network can absorb additional demand.
Build for the season, not just the peak
The monthly data points to demand distributed across a broader festive window rather than concentrated in one month. That puts sustained pressure on inventory, replenishment and working capital, not just peak-day staffing.
Plan around the calendar you actually have
Diwali falls on 8 November in 2026, later than it did in 2025. Seasonal planning built entirely around last year's dates risks putting inventory, people and capacity in place before the demand window actually arrives.
Stop treating every market the same
More than half of orders come from outside the 96 largest cities, where average order value is substantially lower. The scale of these markets makes them impossible to ignore, but their economics may require different approaches to fulfillment and service.
Give different commerce models different operating logic
B2B represents a tiny share of orders but a substantial share of value. Quick commerce has a similarly distinct transaction profile, making both difficult to manage effectively using the same assumptions as conventional B2C.
Plan quick commerce as distribution
The transaction profile observed in the dataset is far closer to a high-value supply movement than a conventional consumer basket. As the channel grows, brands need to think beyond storefront visibility toward replenishment, stock positioning and service levels.
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