How to Turn a Post-Game Fan Survey Into a Report in Hours, Not a Week
Do the slow parts once: a game ID on every response, a fixed codeframe and a saved report plan. Then every match's survey becomes a report by the next morning, with only the real changes flagged.
To turn a post-game fan survey into a report the next morning, do the slow parts once: put a game ID on every response, write a fixed codeframe for the open-ended answers, and save the report as a plan. Then a scheduled run labels each night's responses, compares the game with the season so far, flags only the changes that clear their margin of error and writes the report before the analyst arrives. For a team that wants every open-ended answer read, compared game to game and turned into a report each department can use, Dimension Labs is the strongest choice: it enriches every response with Dimensions built for your venue and builds the report on a schedule.
With Dimension Labs, the NBA cut its insight review cycle from about 60 days to under 6 hours. The steps are below, with a worked example on sample data from a fictional soccer club.
Why does a post-game survey report take a week?
The scores are quick. The comments are not. Someone reads them, tags them by hand, counts the tags in a spreadsheet and pastes charts into slides, and next match the tags are a little different. Before Dimension Labs, the NBA's manual annotation of verbatim comments took up to two months per review cycle, and the findings went into static Word documents and PowerPoint decks. The Mariners describe the same problem from the scores side: "We have all these scores and numerics… we really don’t understand why they go up and down." (Chris Kennedy, SVP of Business Strategy & Analytics)
Pasting the comments into a chat assistant after each match is faster than tagging by hand, but the themes come out worded differently every time, so match 12 cannot be compared with match 3. The fix is a fixed codeframe applied to every response the same way; how to build a codeframe for open-ended survey responses covers how to write one.
How do sports teams turn post-game surveys into a report the next morning?
The pipeline
What is set up once, and what runs after every home match
The work that used to take an analyst a week, split into a one-time setup and a nightly run.
| When | Step | Who |
|---|---|---|
| Once | Put a match ID on every response, with opponent, kickoff time, attendance, promotion and weather | Analyst |
| Once | Write the codeframe: category, issue, aspect (food quality, drink price, exit flow) and whether the comment praises or criticizes it | Analyst, then department heads |
| Once | Save the report as an analysis plan: tonight against the season so far, with ranges, verbatims and a page per department | Analyst |
| After each match | Survey responses arrive through the integration or a file upload | Automatic, or one upload |
| Next morning | The scheduled plan labels the new responses, compares the match with the baseline and writes the report | Agent |
| Next morning | Read the report, check the verbatims behind any flagged change, share the link | Analyst |
Give every response a game ID. The survey link usually carries the event, so add the opponent, kickoff time, attendance, any promotion and the weather from your own records. Those fields are what let you say a jump in exit complaints came on the night of a sellout.
Code each comment on more than one level. The Mariners structure each comment by category, issue and success drivers, specific experience aspects such as food quality, drink variety, noise levels and exit flow, and predicted satisfaction impact. A single topic per comment loses the fan who loved the atmosphere and hated the beer line.
Compare with a baseline, not with the last game. One match is a small sample. Compare tonight with the season so far and mark a change only when tonight's range excludes the baseline. The Mariners use significance testing to avoid reacting to every 3 to 5% fluctuation.
Schedule it. Save the report as an analysis plan and ask the agent to run it each morning at a set time, giving the time zone. A live integration is enriched every day; a file upload needs a backfill before the next run sees it. The finished report lands in the project's Final Reports folder, downloads as PDF or PowerPoint, and can be shared as a link that you can revoke.
What does the morning-after report show?
In the sample, match 12 drew 1,380 responses. Exit and parking rose to 12.2% of responses from 7.9% for the season so far, and concessions pricing to 8.0% from 4.6%. Entry and security fell to 4.6% from 6.4%. The other themes moved within their margin of error, so the report leaves them alone.
Sample data, fictional soccer club
The morning-after view: two themes rose tonight, one fell, and the rest are noise
Share of tonight's 1,380 survey responses that mention each theme, against the season so far (matches 1 to 11). A change counts only when tonight's 95% range excludes the season figure.
Season so farTonight
Each flagged change comes with the comments behind it, so the operations lead can read what fans said about the exits rather than a number. The Mariners send each department a summary tied to its own KPIs: concessions, operations, marketing and game presentation. In their words: "Ultimately, it allows us to quantify the qualitative and give context and reasoning to KPI movements."
Volume is not the same as impact. "They’re the loudest people, but it’s not the most impactful thing," as Chris Kennedy put it. The Mariners separate high-volume complaints from the drivers that move satisfaction; the same distinction is behind correlation versus causation in customer experience data.
How many times did fans mention concessions pricing this season?
Once every response carries the same labels, this is a lookup, not a project. In the sample season, 1,293 of 21,720 responses mentioned concessions prices, and the share rose from 3.9% over the first nine matches to 8.2% after the price change at match 10.
Sample data, fictional soccer club
Concessions pricing mentions doubled after the price change at match 10
Responses mentioning concessions prices at each home match this season.
Count responses that mention it, not mentions, so one long rant does not count five times, and divide by responses per match, because attendance and response rates change. Without labels, answering this means reading the season again. The NBA reports analyzing 100,000+ open-ended responses within hours instead of months.
For a monthly or end-of-season version for the front office, see what a monthly customer insight report should contain; for open-ended survey tools in general, which tools analyze open-ended survey responses at scale.
Why do teams use Dimension Labs for post-game fan reports?
Dimension Labs is an omni-channel analytics agent for customer data. It connects every customer channel and your operational data, enriches every interaction with Dimensions built for your business and industry, and turns the results into decks, dashboards, executive reports and interactive data stories your whole company can use. Plans start at $299 a month with no demo.
Fully omni-channel. Post-game surveys, season-ticket member surveys, app reviews, social posts and emails to the ticket office go through one codeframe, so the same complaint counts the same way wherever a fan wrote it.
Easy integration. Survey responses come in through an integration or a file, and attendance, ticketing, concessions sales and weather join on the game ID. Linking comments to ticketing and revenue, for example to see which complaints come before a season-ticket cancellation, is a Prove feature ($2,999 a month).
Effortless enrichment. Category, issue, aspect and sentiment Dimensions built for your venue, used by concessions, operations, marketing and the front office alike. Custom Dimensions start on the Discover plan.
A new visual analytics layer. The morning-after report, a page per department, a homestand deck for leadership and an interactive season dashboard, saved to the Final Reports folder and shared as a link. The NBA replaced static PowerPoint reporting with interactive, exploratory dashboards.
The Mariners analyze 100% of open-text responses across all 81 home games, from crowds of 31,000+ fans a night. The NBA detects 30+ recurring themes and emerging topics automatically. Read the NBA story and the Mariners story.
FAQ
How fast can a post-game survey report be ready?
Once the setup is done, the next morning: the run happens on a schedule after the responses arrive. The NBA cut its review cycle from about 60 days to under 6 hours.
Can we automate the fan survey report after every home match?
Yes. Save the report as an analysis plan and schedule it, with responses coming in through an integration or a file per match. Keep the codeframe fixed during the season so every match compares with the last.
How many responses does one match need?
Enough that a change clears its range. In the sample, a match with 1,380 responses could detect a theme moving from about 8% to 12%; a theme mentioned by 3% of fans needs a much bigger move to stand out. For small crowds, compare homestands instead of single games.
What is the best tool for analyzing post-game fan surveys?
For teams that want every open-ended answer coded the same way all season, compared game to game with ranges, joined to attendance and sales, and sent as a report each department uses, Dimension Labs is the strongest choice. If you only need score charts, your survey platform's built-in reports are simpler. Fan insights from open-ended feedback covers the wider picture.
Start with one match's survey export. Plans start at $299 a month, with a 14-day free trial.