What problem does it solve?
A club's service team faces peaks that follow the fixture list. Ticket phases open, a kit is released, a match day brings parking, gate and drink price questions, and the volume arrives in hours while most questions repeat. The same inbox also holds the conversations that make money: season ticket inquiries, renewals and membership sign ups.
Clubs also answer in more than one language and outside office hours, because fans follow them from other countries and write on match days and weekends. The Winnipeg Blue Bombers describe reps tied up on parking and drink price questions with less time for the fans asking about season tickets, and Instagram and Facebook messages that were not answered at all.
How does it work?
- Ground the agent in club content. It reads the website, the membership and ticketing rules, the stadium guide and the shop catalog, so answers match what the club publishes.
- Answer on the fan's channel. The agent runs in the website widget and the club app, in the club's tone of voice. 1. FC Köln hands complex matters to human service or its WhatsApp channel.
- Guide to the next step. It links to the ticket shop, the right membership page or the shop, and runs scripted journeys for renewals and sign ups.
- Hand over. Ticket disputes, refunds, accessibility needs and anything the agent cannot answer go to the service team with the conversation attached.
- Learn from the questions. Unanswered and repeated questions show gaps on the website and in the ticketing flow, and the club fixes those pages too. FC Schalke 04 found and closed self service gaps this way.
- Audience
- Customer facing
- Autonomy
- Supervised agent
- Adoption
- Early adopters
- Channels
- Web chat, Mobile app
What is it worth?
Benchmarks are computed from the public deployments below: one data point per organization per KPI, with who made each claim.
| KPI | Median | Reported range | Data points | Claimed by |
|---|---|---|---|---|
| Containment rate | 70% vendor reported | 20% to 90% | 3 | 3 vendor |
| Contact deflection | Too few to pool | 70% | 1 | 1 vendor |
| Customer satisfaction | Too few to pool | 90.4% | 1 | 1 vendor |
Value drivers: Lower cost to serve, Customer experience, Revenue growth, Speed and cycle time.
Indicative value
A football club with 200,000 members and a busy ticketing and shop service
EUR 37,500 to EUR 480,000
Service team time released per year
How this is calculated
Formula: contacts * automatedShare * minutesPerContact / 60 * staffCostPerHour. The low scenario uses every low input, the high scenario every high input.
| Input | Low | High | Basis |
|---|---|---|---|
| Fan contacts per year across email, chat and phone contacts, contacts per year | 150,000 | 300,000 | Editorial assumption, replace with your own contact volume. |
| Share of contacts resolved without staff automatedShare, fraction of contacts | 0.2 | 0.4 | Low is the 20% of Ask Spurs interactions resolved by the agent alone. High is the 40% drop in service center calls that LoyJoy reports for 1. FC Köln, the lower of its two channel figures. Chatbot containment shares (70% at the Winnipeg Blue Bombers, more than 90% at FC Schalke 04) count chatbot conversations only, not all contacts. Replace with your own pilot data. |
| Staff minutes per contact minutesPerContact, minutes per contact | 3 | 6 | Editorial assumption, replace with a time study of your service team. |
| Fully loaded cost of a service staff hour staffCostPerHour, EUR per hour | 25 | 40 | Editorial assumption, replace with your own cost. |
What it leaves out: Staff time only. It treats every resolved chat as a contact staff would otherwise have handled, although off season chats may partly be new demand. It leaves out the revenue from fans who buy a ticket or membership after a conversation, the cost of the platform and of keeping content current, and the match day peak, where the saving is capacity at the moment it is scarce rather than an average.
Who already uses it?
4 public deployments, strongest evidence first. Grades: A regulator or audit, B the organization itself, C vendor case study, D anonymous or estimate.
1. FC Köln
Germany · Media and entertainment · 2026
1. FC Köln, a Bundesliga club, runs the LoyJoy AI agent Hennes as its digital fan service on its website and in its native iPhone and Android app. Hennes covers the fan shop, tickets, events, membership, squad and stadium topics, leads fans to shop and ticket pages, and routes complex matters to human service or WhatsApp. LoyJoy reports a 70% drop in service email volume and a 40% drop in call volume at the service center, without a baseline period or a date range.
- Contact deflection: 70%, email volume in customer service, no baseline period stated
"70% less email volume in service thanks to case-closing resolution by the AI agent"
Claimed by: vendor - Contact deflection: 40%, call volume in the service center, no baseline period stated
"40% less call volume in the service center"
Claimed by: vendor
FC Schalke 04
Germany · Media and entertainment · 2026
FC Schalke 04, a German football club with more than 200,000 members, runs the botBrains chatbot ERWIN across its websites, from the VELTINS-Arena pages to the membership area and contact pages. ERWIN answers questions on memberships and events and forwards what it cannot answer to the service team. It is integrated into Salesforce Service Cloud, where it also suggests solutions to staff and fills topic and case fields. botBrains reports that more than 90% of inquiries were resolved directly and a satisfaction score of 90.4%.
- Containment rate: at least 90%, all inquiries to the chatbot, period not stated
"More than 90% of all inquiries were resolved directly through the chatbot."
Claimed by: vendor - Customer satisfaction: 90.4%, chatbot CSAT, period not stated
"A CSAT score of 90.4% confirms high fan satisfaction."
Claimed by: vendor
Tottenham Hotspur
United Kingdom · Media and entertainment · 2026
Tottenham Hotspur runs Ask Spurs, a multilingual agent built on Salesforce Agentforce for its website and club app, announced by Salesforce on 15 October 2026. It answers questions on ticketing, memberships, retail and stadium events in eleven languages, for logged in members and guest visitors, and hands unresolved conversations to the club's support team. Salesforce reports an 86% engagement rate with 20% of interactions resolved by the agent alone.
- Containment rate: 20%, share of interactions resolved by the agent alone, period not stated, as of 15 October 2026
"Ask Spurs has an 86% engagement rate, with 20% of interactions resolved by Agentforce alone, all grounded in trusted Spurs fan data."
Claimed by: vendor
Winnipeg Blue Bombers
Canada · Media and entertainment · 2026
The Winnipeg Blue Bombers, a Canadian Football League club, use Tidio's Lyro AI agent on their website to answer repetitive game day questions such as parking, drink prices and gate entry. Scripted flows guide fans through season ticket inquiries, renewals and membership sign ups. Instagram and Facebook direct messages were connected to Tidio for the first time and go to the club's social media team. Tidio reports that Lyro and the scripted Flows together handle 70% of chatbot inquiries without a human, with the rest routed to the Ticketing and Fan Services team.
- Containment rate: 70%, all chatbot inquiries, Lyro AI and scripted Flows together, period not stated
"Tidio now handles 70% of all chatbot inquiries without any human intervention."
Claimed by: vendor
How do you implement it?
A model agnostic playbook: what to prepare, the order to build in, and what goes wrong.
Data you need
- Website, membership, ticketing, stadium and shop content in a form the agent can search
- A written split of what the agent answers and what goes to staff
- Past service tickets and chats to find the most frequent questions
Systems to integrate
- Website and club app
- Service desk or CRM for handover and case creation
- Ticketing and shop systems for logged in answers, optional
- WhatsApp or social messaging as a handover route to the service team, optional
Complexity: Medium
A question and answer agent over the club's public content needs the website, the shop and ticket pages and a handover route. Logged in answers such as order or membership status need the ticketing and CRM systems. 1. FC Köln, FC Schalke 04 and the Winnipeg Blue Bombers answer mainly from public content, while Tottenham Hotspur built Ask Spurs on 4.6 million unified fan accounts so it can answer logged in members.
- 1
Start with the public questions
Take the top 50 questions from past tickets, answer them from published content and measure how many conversations end without staff. Leave account specific answers for a later phase.
- 2
Add fan journeys for renewals and sign ups
Scripted flows for season ticket inquiries, renewals and membership sign ups, as the Winnipeg Blue Bombers built, are easier to control than free text. Send fans who are ready to buy to a person quickly.
- 3
Plan for match days and releases
Test the agent with the volume of a ticket phase opening or a kit release, with fresh content for the fixture, and decide who watches the conversations live on the day.
- 4
Close content gaps weekly
Review unanswered questions each week and fix the website page or the knowledge base, so the number of repeat questions falls.
Guardrails
- Answer only from club content and say when it does not cover a question
- Hand ticket disputes, refunds, safeguarding and accessibility needs to staff
- Tell fans they are talking to an AI assistant from the first message
- Never give prices, dates or ticket availability the agent cannot read from a live source
KPIs to instrument
- Share of conversations resolved without staff and share handed over, by topic
- Customer satisfaction on resolved conversations
- Service email and call volume against the fixture calendar
- Questions with no answer found, as a content backlog
Human in the loop
Service staff take every handover with the conversation attached, review a weekly sample of answers and own the content the agent relies on.
Common failure modes
- Wrong match day information
- Gate times, parking and kickoff times change. An agent reading stale pages sends fans to the wrong place at the moment it matters. Tie these answers to a maintained source.
- Resolution counted without a definition
- Vendors report resolved, automated or engaged shares that mean different things. Define resolution as no return on the same topic within seven days before comparing figures.
What are the risks and rules?
EU AI Act
Limited risk (transparency)
A customer facing chatbot is subject to the transparency duty in Article 50: people must be told they are interacting with an AI system. It makes no decision on access to essential services.
Guidance
- Article 50, transparency obligations for providers and deployers of certain AI systems (European Union, Europe). Requires that people are informed when they interact with an AI system, which applies to a fan chatbot.
Controls to put in place
- Disclose the AI assistant and offer a route to a person
- Keep fan personal data out of prompts and logs unless the fan is logged in and the purpose is service
- Set retention for chat transcripts and honor deletion requests
Frequently asked questions
- How many fan questions can an AI agent resolve?
Vendor reports in the evidence range from 20% of interactions resolved by the agent alone at Tottenham Hotspur to more than 90% at FC Schalke 04. The shares are defined differently and none is independently audited, so measure your own on a pilot.
- Does a fan agent replace the ticketing team?
No club in the evidence reports that. The Winnipeg Blue Bombers route the remaining 30% of chats to reps, and Tidio describes those as fans ready to buy tickets or with complex questions.
- Which languages does it need?
Clubs with an international fan base need several. Tottenham Hotspur offers Ask Spurs in eleven languages, and botBrains says 8% of messages to the FC Schalke 04 chatbot came from outside Germany.
How to cite this page
Blits.ai AI Use Case Library, "AI agent for fan and ticketing service at sports clubs", last verified 11 November 2026, https://www.blits.ai/ai-use-cases/fan-and-ticketing-service-agent-for-sports-clubs. Licensed under CC BY 4.0. Method: how we verify use cases.
Changelog
- 11 November 2026: First published