DataTokkDataTokk

Data analytics for FX & CFD brokers

Know which clients, channels and IB partners are actually profitable.

Connect marketing, CRM, trading and payment data to see the real economics behind acquisition, deposits and trading activity.

Discuss your data challengeSee how it works

One connected chain

  1. Acquisition
  2. Deposit
  3. Trading
  4. Broker revenue
  5. Contribution

What we cover

One connected view across acquisition, trading and payments.

  1. 01

    Acquisition & clients

    See what happens after the FTD.

    Connect channels and IB partners with KYC, deposits, trading activity and downstream client value.

  2. 02

    Trading & finance

    Turn trading activity into broker economics.

    Calculate revenue and direct costs according to your execution model — because deposits are not revenue.

  3. 03

    Payments & operations

    Connect payments to the client lifecycle.

    See payment success, withdrawals and provider performance in the context of clients, markets and acquisition sources.

Consistent metrics across systems, brands and regions.

Implementation example

One client view from acquisition to broker revenue.

From experience working with a forex broker

What changed

  • One client identity across website, app, CRM and trading systems.
  • Acquisition sources connected to deposits, trading activity and broker revenue.
  • Client metrics available directly in CRM for day-to-day decisions.

Sources

  • Marketing
  • CRM
  • Trading
  • Payments

Unified client metrics

One client identity, agreed metric definitions

Dashboards · CRM · Alerts

Reports for management and metrics inside operational tools

Illustrative dashboards · Demo data

Performance funnel — visit → FTD → GR

Follows visits through registrations and first-time deposits to gross revenue by source. It shows volume and revenue, not profitability: acquisition and direct costs are not included, so true contribution cannot be read from this view.

Synthetic demonstration concepts built on invented data. Not client screenshots or measured results.

Delivery, reliability and technology

Built for sensitive brokerage data and daily operations.

Data quality
Consistent client identity and metric definitions across marketing, CRM, trading and payment systems.
Operations
Automated data updates, monitoring, documentation and ongoing support for production analytics.
Deployment
Cloud or on-premises, depending on your security, infrastructure and data residency requirements.

Technologies we have worked with

Pipelines

  • Dagster
  • dbt
  • Kafka
  • Airflow

Data platforms

  • Snowflake
  • BigQuery
  • ClickHouse

Analytics

  • GA4
  • AppsFlyer
  • Amplitude

Reporting

  • Tableau
  • Power BI
  • Looker Studio

How we work

  1. 01

    Start with one business question

    Define what you need to answer and identify the required data sources and access.

  2. 02

    Connect and validate

    Integrate the relevant systems, align metric definitions and validate the numbers against source data.

  3. 03

    Put it into daily use

    Deliver dashboards, CRM metrics and alerts, then maintain and support the analytics in production.

Get in touch

Start with one question your reports cannot answer.

Tell us what you want to understand. We’ll review the question, your current data setup and suggest a practical first step.