Electronics Demand Landscape: Which Cities Are Driving Orders
Demand for electronics is heavily concentrated at the top of each city tier, with a steep drop-off as the index falls. In tier-1, Delhi commands the maximum index score of 100, with Bangalore close behind at 89. Mumbai and Hyderabad sit at 53 and 52 respectively, while Pune (38) and Noida (34) trail significantly — indicating that even within metro India, electronics demand is not evenly distributed.
In tier-2, Jaipur leads at 100, followed by Lucknow at 83. The remaining cities — Nagpur, Coimbatore, Indore, and Vadodara — cluster tightly between 50 and 53, suggesting a more balanced mid-market demand profile. This relative parity in tier-2 means sellers can justify simultaneous multi-city activation without over-indexing on a single hub.
Tier-3 is where the demand story becomes most interesting. Jhajjar tops the tier at 100, with Raigarh-MH close at 93 and Khorda at 82. These are not traditional electronics retail strongholds, yet their index scores rival those of established tier-2 cities. Mohali, Aurangabad-MH, and Karnal round out the tier between 55 and 59. This pattern strongly suggests that unmet demand in smaller markets is now finding expression through e-commerce channels, making tier-3 a genuine growth frontier for the category.
Average Order Value by City Tier: The Surprising Premium in Small Markets
The AOV data cuts against the conventional assumption that bigger cities mean bigger baskets. Tier-1 cities average ₹2,682 per electronics order. Tier-2 cities come in lower at ₹2,072. Yet tier-3 cities deliver an AOV of ₹5,028 — nearly 88% higher than tier-1 and more than 2.4 times the tier-2 figure.
Several structural factors likely drive this. Tier-3 buyers typically have fewer local retail alternatives for high-value electronics, so when they do purchase online, they are buying items — such as laptops, larger audio systems, or specialised gadgets — that they cannot source locally. This 'destination purchase' behaviour inflates basket sizes. Additionally, tier-3 buyers may consolidate multiple accessory purchases into a single online order to justify delivery costs.
For sellers, this creates a meaningful revenue-per-shipment opportunity: a single fulfilled tier-3 order generates almost twice the gross revenue of a tier-1 order. However, this advantage is immediately complicated by the RTO risk profile, which must be factored into any contribution margin calculation. Pricing strategy, product assortment, and packaging standards all need to be calibrated differently for tier-3 fulfilment to capture the AOV opportunity without absorbing disproportionate return costs.
RTO Risk in Electronics: How Return-to-Origin Rates Erode Margins by Tier
Return-to-origin is the defining operational challenge for electronics e-commerce in India, and the tier-wise data makes the risk gradient unmistakable. Tier-1 cities hold RTO at 7% — a manageable rate for a category where products are high-value and verifiable. Tier-2 cities see RTO jump to 17%, more than doubling the metro rate. Tier-3 cities hit 29%, meaning nearly one in three electronics shipments fails to deliver successfully.
What makes the tier-3 RTO figure particularly difficult to manage is the simultaneous prepaid share of 82% — the highest across all tiers. Conventionally, high prepaid rates are treated as a proxy for buyer intent and a natural RTO suppressant. The electronics data breaks that assumption: buyers in smaller cities are willing to pay upfront, yet returns remain nearly three times the metro rate. This points to causes beyond payment hesitancy — address quality issues, logistical accessibility, product expectation mismatches, or courier serviceability gaps are more likely culprits.
For operations and growth teams, this means RTO mitigation in tier-3 requires interventions at the product description, imagery, and logistics layers — not just payment nudges. NDR (non-delivery report) management workflows, proactive buyer communication post-dispatch, and carrier selection based on pin-code-level delivery success rates are all levers that become critical at scale in these markets.
Prepaid Share and Payment Behaviour Across Tiers
Across all three tiers, prepaid adoption in electronics is notably high, reflecting the category's established digital-purchase familiarity among Indian consumers. Tier-1 cities record a 77% prepaid share, consistent with the metro buyer profile where UPI, card payments, and wallet transactions are deeply habituated. Tier-2 sits close at 74%, suggesting that payment infrastructure in mid-sized cities is broadly comparable to metros for this category.
The standout figure is tier-3 at 82% prepaid — the highest of the three. This is significant because it demonstrates that buyers in emerging markets are not the cash-on-delivery-dependent cohort they were historically assumed to be, at least within electronics. Digital payment adoption has clearly penetrated deeper into India's geography than fulfilment infrastructure has.
For sellers, the high prepaid share across all tiers means that working capital tied up in COD reconciliation is relatively limited in electronics compared to fashion or FMCG categories. However, the mismatch between tier-3's 82% prepaid and 29% RTO rate is a critical operational signal: prepaid orders that are returned still generate reverse logistics costs, and the refund-processing burden is higher on prepaid transactions than COD. Sellers must therefore build robust reverse logistics SLAs specifically for tier-3 electronics returns.
Monthly Order Volume Trends: Reading the Demand Curve for 2026
The six-month order volume data from January to June 2026 reveals a clear growth trajectory punctuated by one notable trough. January recorded approximately 1.31 million orders, which dipped to 1.14 million in February — likely reflecting post-festive demand normalisation. March bounced back to 1.34 million, and volumes have broadly climbed since, reaching 1.48 million orders in June 2026, the highest single month in the tracked period.
The February dip is a recurring pattern in Indian e-commerce and should not be interpreted as structural weakness. More instructive is the direction from March onwards: three successive months of growth, culminating in a June figure that is approximately 13% above the January baseline. This indicates that electronics e-commerce demand in India is on a sustained upward curve rather than being purely event-driven by sale seasons.
For inventory and supply chain planning, this trend has direct implications. Sellers who plan stock replenishment purely around festive quarter surges risk under-serving a market that is now generating consistent mid-year volumes. Demand forecasting models should incorporate this baseline growth rather than treating non-festive months as low-priority periods. The June peak in particular warrants investigation — whether driven by pre-monsoon purchasing, academic-year device purchases, or platform promotions — to inform forward planning for 2026's second half.
Emerging Cities and the Next Wave of Electronics E-Commerce Growth
Beyond the ranked city tiers, a set of emerging cities shows early but meaningful electronics demand signals: Jhajjar, Upper Subansiri, Uttarkashi, Bina, Nelamangala, Anupgarh, Umarkhed, and Bijainagar. These locations span geographically diverse states — from Haryana and Uttarakhand to Maharashtra and Karnataka — indicating that electronics e-commerce penetration is not concentrated in any single region.
Jhajjar's position as the tier-3 demand index leader (100) makes it the most immediately actionable of these markets. Its proximity to Delhi's logistics infrastructure likely facilitates faster fulfilment, potentially explaining its strong demand despite being a small city. Nelamangala, situated near Bangalore, and Mohali, adjacent to Chandigarh, follow a similar satellite-city pattern — benefiting from metro-adjacency without metro-level competition for consumer attention.
For electronics sellers evaluating geographic expansion, these cities represent an early-mover window. Competition from established players is typically lower in such markets, customer acquisition costs are comparatively modest, and the AOV data suggests that when purchases do occur, they are high-value. The risk, as with all tier-3 expansion, is RTO — making serviceability assessment and carrier reliability at the pin-code level a prerequisite before committing marketing spend to these emerging demand pockets.