What our partners achieve — real results from IB partnerships.
Three examples of what the work looks like in practice. Each one maps to a different partner type. Each shows what changes when the structure is right.
Scenario 1: Community Trader, Telegram FX signals introducing broker
A community trader ran a Telegram FX signals group. They had built a strong following. But they were tied to one broker. So their commission income was unstable. And there was real risk if that one broker deal changed.
We mapped how their traders behaved. We grouped them by how long they stayed and how much they traded. Then we matched each group to a broker that suited them. Not the one that paid the highest rate.
The result was steadier income. Trader drop-off fell. And the community trusted the broker picks because they were a good fit — not a push.
Active trader numbers rose by 25 to 30 percent over the next quarter. Drop-off in newer trader groups fell by 15 to 20 percent.
This is the retention work we describe in detail on our How It Works page.
Scenario 2: Financial introducer — expanding to new trader groups
An experienced financial introducer wanted to bring in traders across more than one market. But they were struggling to build a steady income model as they grew.
We looked at how their commission was set up. We mapped how their traders behaved in each market. Then we built an income model that matched those patterns.
We changed the broker setup so income did not rely on one market. This made it easier to plan around. And more steady when any one market went quiet.
Account life rose by 20 to 25 percent after the change. Trader activity in gold rose by 18 percent. Gold is one of the most active markets among retail traders in licensed European markets.
Scenario 3: Forex educator — YouTube FX content creator moving to an IB model
A forex educator with a large YouTube following wanted to build a proper IB setup. But they did not want to lose the trust of their community. And they did not want to push broker links in a way that felt forced.
We looked at how their viewers actually traded. We found problems in how their broker setup was built. Then we matched the referral system to viewer type — not to which broker paid more.
The result was a setup that felt right to the community. Traders stayed longer. And income grew because the fit was genuine — not forced.
Trader retention rose by 28 percent over the following months. Active funded traders referred rose by 22 percent.
These results came from fixing the setup — not from pushing harder.
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