Prediction Market First Trade Tracking
Prediction market first trade tracking means recording the moment a new user places their first trade and tying it back to the creator, link or campaign that brought them in.
Quick answer: Log five events in order: link click, account created, funding or wallet step completed, first trade placed and second trade placed. Credit each first trade to the creator link or code that started the journey, and report cost per first trade instead of cost per click, because a click tells you very little about trading intent.
This page covers which events to log, how to keep creator attribution clean and what to report to your growth team. LuvKaizen has run creator campaigns for prediction market platforms, including Polymarket, which reached 185M impressions in 3 months.
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What counts as a first trade, and why does it beat a signup?
A first trade is the first filled order a new user places on a market, whether they buy a yes or a no position. It is the point where a visitor stops browsing and puts real money behind a view.
Signups are a weak signal on prediction markets. Many people register to watch an event, never fund the account and never come back. A first trade shows intent, and it is the event your product team already treats as activation.
- Signups are cheap and noisy. Creator audiences often register out of curiosity, so a signup count can look strong while almost nobody trades.
- First trade is closer to revenue. It confirms the user finished verification and funding, and it is the best early predictor of repeat activity.
- It lets you compare creators fairly. Two creators with the same click volume can deliver very different numbers of first trades.
- It keeps teams aligned. Marketing, growth and product all read the same event instead of arguing over signup definitions.
For the wider picture on creator work in this category, see our prediction markets marketing page.
Which events should you track from click to first trade?
Five events cover the full journey. Log each one with a timestamp and the same user or session identifier so the chain can be rebuilt later.
| Event | What it shows | Where to log it | Common mistake |
|---|---|---|---|
| Link click | A creator audience member reached your site | Tracking link with campaign and creator parameters | Dropping the parameters on a redirect |
| Account created | Interest turned into a registration | Signup form or wallet connect | Not storing the original source with the account |
| Funding or wallet step | The user can actually trade | Deposit or wallet connection event | Treating verification as funding |
| First trade placed | Activation, the main event to report | Order filled event from your backend | Counting placed orders that never filled |
| Second trade placed | Early repeat behavior | Order filled event, second occurrence | Ignoring it and judging creators on one trade only |
Server side events are more reliable than browser pixels for the last three rows, because wallet flows and in-app browsers often block client side scripts.
How do you credit a first trade to the right creator?
Attribution is where most prediction market campaigns lose clean data. These practices keep it readable:
- One tracking link per creator. Add the creator name, platform and campaign to the link, so a click on Kick can be told apart from a click on X.
- Creator codes as a backup. Many viewers open the app later and skip the link. A short code entered at signup catches them.
- Creator landing pages. A page per creator or per wave lets you pass the source through the whole signup flow.
- A written attribution rule. Decide first touch or last touch before the campaign starts, and use the same rule in every report.
- A fixed attribution window. Pick the number of days between click and first trade you will count, and apply it to every creator equally.
- Deduplication. One user, one first trade. Remove test accounts, team wallets and repeat signups from the same device.
If you are also running clip distribution, give clippers their own link parameters so reposted clips do not blur the creator numbers. Our Polymarket marketing agency and Kalshi marketing agency pages show how we run creator work for each platform.
How does first trade tracking work with LuvKaizen?
We build tracking into the campaign from day one, so the first trade numbers are usable when the first posts go live.
- Brief. You share your platform, target markets, the signup flow and the events your team can already log.
- Sourcing and checking creators. We shortlist creators whose audience fits your category, and check their audience and past results before anything is agreed.
- Matching to your markets. Creators are matched to the countries, languages and market topics you want to reach.
- Agreeing the deals. You see the proposed creators and terms and decide which ones go ahead.
- Briefing and going live. Each creator gets a short brief, a tracking link and a code, and we confirm the events fire before posts go out.
- Tracking and reporting. You get reporting by creator on clicks, signups, first trades and second trades.
- Scaling what works. Creators and formats that produce first trades get more of the plan, the rest are dropped.
Creators follow platform rules and local law, and campaigns are briefed accordingly.
Which first trade KPIs should you report?
Keep the report short and use the same definitions every week.
| KPI | Formula | What it tells you |
|---|---|---|
| Click to signup rate | Signups divided by clicks | Whether the creator audience matches the product |
| Signup to first trade rate | First trades divided by signups | Quality of the audience and the onboarding flow |
| Cost per first trade | Campaign spend divided by first trades | The number to compare creators and waves on |
| Second trade rate | Users with a second trade divided by first trades | Early retention, not just a one time try |
| First trades by market category | First trades grouped by sports, politics or crypto markets | Which topics to brief creators on next |
Mistakes to avoid: judging a creator on clicks alone, mixing attribution rules between reports, counting test accounts, and cutting a creator before the attribution window has closed. For ranking-focused work on the same category, see prediction market SEO agency.
Get a first trade tracking plan for your next campaign
Tell us your platform, your markets and where users sign up. We will map the events to log, set up creator links and codes, and show you what the reporting will look like. Send us a brief.
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Frequently Asked Questions
What is prediction market first trade tracking?
It is the practice of logging a new user's first filled trade on a prediction market and linking it to the creator, link or campaign that brought them in. It lets you report cost per first trade instead of cost per click or signup.
Why track the first trade instead of signups?
Signups include many people who never fund an account. A first trade shows that the user verified, funded and acted, so it is a much closer match to real activation.
Can you track first trades without a pixel?
Yes. Server side events from your own backend are usually more reliable than pixels, especially with wallet flows and in-app browsers. Pair them with creator links and codes so the source stays attached to the user.
How long should the attribution window be?
Choose one window before the campaign starts and apply it to every creator. Prediction market users often trade around an event, so a window that is too short can undercount creators who post early.
How do you stop first trade numbers being gamed?
Deduplicate by user and device, exclude team and test wallets, and review the second trade rate next to the first trade rate. Creators whose first trades never lead to a second trade deserve a closer look.



