Support Tickets per Order: Ecommerce Contact Rate Benchmarks and How to Lower Yours (2026)

Short answer: Ecommerce brands receive between 19 and 46 support tickets for every 100 orders, depending on what they sell. Gorgias Ecom Lab data for merchants at the $10M GMV band (March 2026) puts Toys & Games at the low end and Electronics and Vehicles & Parts at the top, with a median of 25 across 14 verticals. The number that matters more is how many of those tickets still reach a human. With an AI agent resolving 80% of conversations, a brand at 25 tickets per 100 orders sends only 5 per 100 orders to its team.

Tickets per order, also called contact rate, is the cleanest way to forecast support workload and cost from the one number every ecommerce team already plans around: orders. This guide covers the 2026 benchmarks by vertical, how to calculate your own rate without inflating it, why stores drift above their vertical, and the levers that bring the human-handled rate down.

Support tickets per order: 2026 benchmarks by vertical

Gorgias publishes contact rate as tickets per 100 orders for merchants at the same size ($10M annual GMV), so verticals can be compared like for like. The third column is what that rate means for a store shipping 10,000 orders a month.

Source: Gorgias, ticket volume guide, citing Gorgias Ecom Lab, March 2026, $10M GMV band. Monthly ticket column is our arithmetic (orders x rate / 100).

Three things stand out:

• The spread is 2.4x. An Electronics brand gets roughly one ticket for every two orders. A Toys & Games brand gets one for every five. Copying a support headcount or budget from a brand in another vertical will be wrong by a wide margin.
• Use the median, not the average. The median across the 14 verticals is 25; the simple average is 29 because Electronics, Vehicles & Parts and Hardware pull it up. Gorgias makes the same point in its research titled "Stop benchmarking against the average."
• Higher volume does not mean worse service. In the same data, first response time varies 5.5x across verticals, but CSAT varies by only 0.2 points. High-contact verticals carry more work to deliver the same experience.

Keep the scope in mind: these are Gorgias merchants with at least 30 tickets, smoothed by GMV band and vertical. It is the best public breakdown by vertical, not a census of ecommerce, and it only counts what landed in the help desk.

How to calculate your own contact rate

The formula is simple:

Tickets per 100 orders = tickets created in the period / orders placed in the period x 100

The inputs are where most brands go wrong. Before you compare yourself to the table, clean them up:

• Count conversations, not messages. One customer thread is one ticket, however many replies it takes.
• Remove noise. Spam, auto-replies, carrier notifications, marketplace alerts and out-of-office emails are not customer contacts.
• Include every channel. Many brands only count what reaches the help desk by email. WhatsApp, Instagram DMs and website chat that never become a ticket are still customer contacts, and for brands selling on WhatsApp they can be a large share of the real number.
• Decide on pre-purchase questions. The Gorgias table includes all tickets, so keep them in to compare. Track post-purchase contacts per order separately if you want a pure service metric.
• Use at least a full month. Tickets lag orders by days. A single week swings with your shipping calendar.

Worked example

An apparel brand places 12,000 orders in September. Its help desk shows 3,050 tickets, of which 260 are spam and system mail, leaving 2,790 real tickets.

• Help desk only: 2,790 / 12,000 x 100 = 23.3 per 100 orders, close to the Apparel & Accessories benchmark of 22.
• Now add the 900 WhatsApp and Instagram conversations the team answered from a phone and never logged: (2,790 + 900) / 12,000 x 100 = 30.8 per 100 orders.

Same store, same month, and the real workload is a third higher than the help desk suggests. If you are planning staffing or AI coverage, the second number is the one to plan for.

Why your tickets per order sit above (or below) your vertical

Product complexity. Gorgias attributes the Electronics rate to customers having more pre- and post-purchase questions about technical products. Compatibility, setup and "will this fit my model" questions do not come up for a bag of coffee.

First-time buyers. Gorgias notes that first-time customers generate more tickets than repeat buyers and that BFCM brings a disproportionate share of them, so contact rate tends to rise during peak periods, not just order volume. Plan November on a higher rate than September.

Delivery experience. "Where is my order" (WISMO) tops Gorgias's list of the highest-volume ticket categories. A slow carrier week or a missing shipping notification lifts tickets per order almost immediately.

Policies customers cannot find. A returns policy buried in the footer turns into "how do I return this?" tickets on orders that were perfectly fine.

The channels you open. Adding WhatsApp or website chat surfaces questions that would never have become an email. Your contact rate goes up, but so do conversions from pre-purchase questions that now get answered. That is a good trade if the answers are instant.

How to lower human tickets per order: six levers

There are two different goals here. Deflection stops the question from being asked. Resolution answers it without a human. Most brands need both, and the metric to manage is human-handled tickets per 100 orders.

1. Send order updates before customers ask. Proactive shipping, delay and out-for-delivery messages on WhatsApp and email remove a large share of WISMO contacts. A delay message sent the day a parcel stalls costs far less than ten "where is it?" tickets.
2. Let an AI agent look up the order. Order status is a lookup, not a judgment call. An agent connected to your store and tracking app can answer it on any channel, at any hour, with the actual carrier status.
3. Automate returns, exchanges and cancellations end to end. Check the order date against the return window, start the return, offer an exchange first. Keep humans for exceptions and partial refunds.
4. Answer pre-purchase questions where shoppers ask them. Sizing, compatibility and "which one should I buy" questions are revenue, not cost. An agent that answers from your catalogue and sizing guide on site and on WhatsApp shortens the path to checkout.
5. Tag every escalation and fix the root cause. If the same question keeps escalating, it is usually a missing policy, a product page gap or an agent instruction that needs a rule. Review escalations weekly and close the gaps.
6. Make handoffs clean. When a conversation does need a person, pass the reason and a summary into the help desk so the agent does not start from zero. That cuts handle time on the tickets that remain.

What a good target looks like

Your total contact rate will mostly track your vertical and your channels. The human-handled rate is what you control. Here is what different automation levels mean at your vertical's benchmark:

At 80% automation, an Electronics brand handles fewer human tickets per order than an apparel brand with no automation at all. That is the real benchmark gap worth closing.

From contact rate to AI support cost

Because contact rate turns orders into conversations, it also turns orders into an AI budget. Manifest AI bills only per AI reply: $500 per 10,000 AI replies, scaling linearly, with a $500 monthly minimum. A conversation averages about 3 AI replies. Assuming every ticket in the benchmark becomes one AI conversation:

Two notes on reading this. First, it is an estimate: your average replies per conversation and your WhatsApp and Instagram volume will move it. Second, on an annual contract the price is agreed once from current volume and is not raised during the year, even if volume grows. Brands that use Manifest AI with BIK also get the BIK helpdesk free, with unlimited seats and tickets, for the conversations that still need a person.

How Manifest AI handles per-order tickets

Manifest AI is an omnichannel AI agent platform for ecommerce brands, running across your website, WhatsApp, Instagram and email. It works with Gorgias, Zendesk and Freshdesk, and with any ecommerce platform through its API.

• Order status, returns and cancellations: agents use tool calling into your store and ecommerce plugins to look up orders and handle returns and cancellations end to end, depending on how they are built for your policies.
• Pre-purchase questions: product discovery and sizing answers on site and on WhatsApp, so pre-purchase contacts turn into orders.
• Shopper memory: context carries across conversations and channels, so a customer who asked on WhatsApp is not asked again on email.
• Clean handoff: tickets arrive in your help desk with the handoff reason and a summary of the conversation. Live chat transfer works in Gorgias and Zendesk.
• Self-improving agent: it suggests fixes from escalations, and every change goes through approval and versioning before it goes live.
• Built for you: our team builds your agents during onboarding and on request afterwards, with support 7 days a week. Typical launch is about 2 weeks.

The guarantee: 80%+ automation within 30 days, measured on eligible automations, or your money back. Brabar, for example, resolves 87% of support queries with Manifest AI.

Not sure where your contact rate is coming from? We offer a free audit of your CX setup (help desk, team and ticket mix) with a suggested automation plan. Book a call or start with a 30-day free trial.

Frequently asked questions

What is a normal number of support tickets per order for ecommerce?

Between 19 and 46 tickets per 100 orders for Gorgias merchants at the $10M GMV band in March 2026, with a median of 25 across 14 verticals. Toys & Games is lowest at 19; Electronics and Vehicles & Parts are highest at 46.

How do I calculate contact rate?

Divide the tickets created in a period by the orders placed in the same period and multiply by 100. Remove spam and system mail, count every channel including WhatsApp and Instagram, and use at least a month of data.

Does contact rate go up during Black Friday?

Yes. First-time buyers generate more tickets than repeat customers, and BFCM brings a disproportionate share of them, so tickets per order rises along with order volume. Compare your November rate with September to size the lift for your store.

What is the most common ecommerce support ticket?

Order status ("where is my order") is consistently the top category, followed by returns and exchanges, sizing and product questions, account and subscription issues, and payment and billing. Tag a month of your own tickets to get your exact mix.

How do I reduce support tickets per order?

Send proactive order updates, let an AI agent answer order status and run returns end to end, answer pre-purchase questions instantly on site and WhatsApp, and fix the root cause of repeat escalations. Track human-handled tickets per 100 orders as the metric that matters.

Sources and method

• Tickets per 100 orders by vertical, top ticket categories and first-time buyer statements: Gorgias ticket volume guide, citing Gorgias Ecom Lab, March 2026, $10M GMV band, accounts with at least 30 tickets.
• 2.4x volume spread, 5.5x first response time spread and 0.2-point CSAT spread: Gorgias, "Stop benchmarking against the average" (April 2026).
• Arithmetic: monthly tickets = orders x rate / 100. Median of the 14 rates is 25 (7th and 8th values); simple average is 406 / 14 = 29. Human tickets = rate x (1 - automation rate). AI replies = conversations x 3; cost = AI replies / 10,000 x $500, with a $500 minimum.
• The worked example and the automation scenarios are illustrative, not measurements of any merchant.