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Digital Analytics & TrackingData Platform BuildWarehouse MigrationData Team ModernisationAI EnablementData Strategy SprintEmbedded AnalyticsTechnical ConsultingAI & Analytics Agents

Industries

Ecommerce & DTCB2B SaaSFintech & lendingInsuranceHealthcare & telehealthConsumer brandsTravel & attractionsAgencies

Company

Cases About Talk to us
Fintech & lending

Put budget behind the ads that bring funded loans

Ad platforms see an application start, while the money is made days later when a loan is approved and funded in a system they cannot see. We connect spend to underwriting and funding outcomes in your warehouse, send those outcomes back to the ad platforms, and add AI so growth, risk and finance spend their time on insight and decisions. We did this for a US lease-to-own lender, matching offline applications to ad spend, and built reporting across every business line for a Colorado credit union.

Book a free discovery call See the work

Free 30 minute call with the engineer who would do the work. You keep the first fix whether or not you hire us.

What we get called in for

The problems teams bring to us

Consumer lenders, BNPL and lease-to-own providers, credit unions, card issuers, and wealth and investing apps.

01

Google Ads leads never tie to funded loans

Campaigns are judged on cost per application while approval rates vary widely by source. A channel with cheap applications can bring mostly declines, and nobody sees it until the funding report lands weeks later.

What we do

We capture click IDs and consented identifiers at application, match them to decisions and fundings from your loan origination system in the warehouse, and upload approved and funded outcomes to Google Ads and Meta as offline conversions. We did this for a US lease-to-own lender, and the same method works for cards and deposit accounts.

02

Meta's financial ad rules broke our targeting

Since January 2025, US ads for financial products must run in Meta's Financial Products and Services special ad category, which removes lookalike audiences, narrow age and gender targeting and ZIP code targeting. Meta can also restrict the data it accepts from financial services websites. Campaigns that relied on audiences now depend on the quality of the conversion signal.

What we do

We rebuild the conversion signal so it can carry the campaign: server-side events, deduplicated, with approved or funded outcomes as the optimisation target and neutral event names that stay within Meta data rules. Reporting separates what changed because of the policy from what changed in performance.

03

iOS app signups we can't attribute

Most iOS users decline App Tracking Transparency, so user-level attribution for installs, KYC completions and first deposits largely disappears. Paid social looks weak in reports, and the channels that drive app growth are hard to defend.

What we do

We set up SKAdNetwork and AdAttributionKit conversion values around the events that matter, such as completed onboarding or a first deposit, and combine them with your MMP and first-party data in the warehouse. We traced and fixed a broken iOS signup attribution flow for Ginmon, a German robo-advisor.

04

Approval, funding and loss data locked away from marketing

Credit decisions, fundings, repayments and charge-offs live in the LOS, the core and the servicing platform. Marketing optimises for volume with no view of which sources bring loans that perform, so cheap growth can turn into losses later.

What we do

We model applications, decisions, fundings and repayment outcomes into one customer-level view, and keep sensitive fields out of marketing tools. Growth teams see approval rate, funded volume and early performance by channel and campaign without touching raw credit data.

05

Credit union marketing that reports loans and new members

Credit union campaigns often run through an agency while applications land in a separate LOS and the core. The board asks what marketing delivered in loans and new members, and the answer is a count of clicks.

What we do

We connect ad platforms and GA4 to loan and membership outcomes with privacy-safe matching, and build a monthly view of cost per funded loan and per new member by product. For a Colorado credit union we built the tracking and reporting across every business line that this sits on.

06

Finance, risk and growth each report different numbers

Growth counts applications, risk counts approvals and finance counts funded balances, each from its own extract with its own dates. Weekly reviews open with a debate about whose number is right.

What we do

We define the funnel once in dbt, from first visit to funded and performing, with each stage tied to its system of record. An AI assistant answers questions from that model and shows its working, so leaders spend the meeting on insight and decisions.

Results

Work we have done in this space

US lease-to-own lender FinTech · Consumer lending

Ad spend matched to real applications, including the offline ones.

We rebuilt tracking on a server-side GA4 setup, brought every source into one warehouse and built attribution that ties spend to completed finance applications.

OfflineApplications matched
Server-sideData collection
OneMarketing warehouse
 Forex backtesting platform FinTech · Trading SaaS

Spend tied to signups and revenue during a fast growth push.

We built the acquisition dashboard and product analytics for a fast-growing trading replay tool, so the team could see cost per acquisition by channel and how traders use the product.

ClearCost per acquisition
TrackedTrader behaviour
Data-ledRoadmap
 Colorado credit union Financial services · Banking

One analytics setup and one view across every business line.

We built an enterprise GA4 architecture for one of the largest credit unions in the US, tracked every product application funnel and gave each team reporting it trusts.

EnterpriseGA4 architecture
EveryProduct funnel tracked
Self-serveInternal team
 Ginmon FinTech · Digital wealth management

Signup attribution restored so marketing spend ties to real customers again

A signup flow that broke attribution, worst on iOS. We traced where the source was lost, helped simplify the flow and rebuilt tracking so every signup is credited correctly.

RestoredSignup attribution
VisibleiOS conversions
SimplerSignup path
Questions

What people ask us first

How do lenders track which ads lead to funded loans?

Store the ad click ID and consented contact details with each application, then match applications to funding records from your origination system. Upload funded outcomes to Google Ads and Meta as offline conversions so bidding optimises toward them. Google only attributes imported conversions to clicks from the previous 90 days, so slow funding cycles also need an earlier approved stage as a signal.

What is Meta's Financial Products and Services category?

It is a special ad category that Meta made mandatory in January 2025 for US ads about credit, banking, investing and similar products. It replaced the older credit category. It limits targeting by age, gender and ZIP code and removes lookalike audiences, and ads that should use it but do not can be rejected.

Can we use GA4 and Meta pixels on a loan application?

You can, with care. Personal and financial details must never reach analytics or ad platforms, which means checking URLs, form fields and event parameters as well as the tags themselves. We audit what each tag sends, move key events server side where we control the payload, and send only what measurement needs.

What data should a fintech warehouse hold first?

Start with ad spend, web and app events, applications, decisions and fundings, joined on a customer ID. That alone gives cost per funded account by channel, the number most growth teams are missing. Repayment and loss data can follow once the funnel is trusted.

Tools we work with here
Google Analytics 4Google Tag Manager (server-side)Google Ads offline conversionsMeta Conversions APIAppsFlyerSegmentSalesforceSnowflakeBigQuerydbt
Services

Where teams usually start

Digital Analytics & Tracking

Tracking that ties every sale and lead to the spend that produced it.

Data Platform Build

A tested data model of your business that people and AI tools can query.

Technical Consulting

A senior engineer works on one stuck problem until it is fixed.

AI & Analytics Agents

Ask your data a question in plain English and get an answer you can check.
How we work

How an engagement starts

The work runs in three steps. You see working output within weeks and can stop after any stage.

01

Discovery call

A 30 minute call with the engineer who would do the work. We look at your setup, tell you what we would fix first, and whether you need us for it.

Day 1
02

Blueprint sprint

We map your sources, stakeholders and goals, then give you an architecture and a prioritised roadmap. You keep it whether or not we do the build.

2 to 4 weeks
03

Build in sprints

We ship working tracking, models, dashboards and agents every two weeks. You can stop after any sprint, and everything built stays yours.

Every 2 weeks

What happens on the call

Book your call
  • 30 minutes with the engineer who would do the work
  • No slides or sales pitch
  • A clear answer on whether we can help, and a referral if we can’t
  • The first fix we would make, which you can use either way
Next step

Get your first fix in 30 minutes

Bring the question your team can’t answer fast enough. The engineer who would do the work looks at your setup with you and tells you the first thing we would fix, plus a straight answer on whether you need us at all. It costs you half an hour, and you keep the fix either way.

Book a free discovery call