Our work: digital marketing, AI, and development case studies

The problem

Spend was climbing every quarter while the sales team complained that almost none of the leads were worth calling. Conversion tracking counted anyone who reached a form, so the bidding algorithm was optimising hard toward people who would never buy.

What we did

• Rebuilt conversion tracking so only qualified enquiries counted as conversions.
• Split campaigns by intent, separating high-intent product searches from research traffic.
• Cut a long tail of broad-match search terms that had been billing for months.
• Wrote comparison and alternative pages targeting the searches buyers actually run.

The problem

Sales worked leads in the order they arrived. Genuinely hot prospects sat in the queue behind tyre-kickers, and by the time anyone called, the good ones had already spoken to a competitor.

What we did

• Trained a scoring model on their historical closed-won and closed-lost data.
• Scored every inbound lead on likelihood to close, not just on form fields.
• Wired scores into the CRM so the highest-value leads surfaced at the top of the queue.
• Fed the same scores back into ad platforms so bidding optimised toward real revenue.

The problem

A funded startup needed a consumer fintech app in front of users quickly, without the security and compliance shortcuts that make a first version impossible to build on later.

What we did

• Ran a short discovery to cut the scope to what genuinely mattered for launch.
• Designed the onboarding flow first, since that is where fintech apps lose most users.
• Built cross-platform for iOS and Android on one codebase to keep the timeline realistic.
• Handled secure authentication and data storage properly from the first commit.

The problem

A small support team was drowning in the same handful of questions. Off-the-shelf chatbots had been tried and abandoned, because they invented answers that were confidently wrong.

What we did

• Built a retrieval system grounded in their real documentation and help centre.
• Made the assistant cite its source on every answer so users could verify it.
• Set explicit guardrails: when it does not know, it says so and escalates.
• Added a clean handoff to a human that carries the conversation across.

The problem

Their existing dashboard had been fine at a few thousand events a day and fell over as customers grew. Queries timed out, and every new enterprise client made it worse.

What we did

• Redesigned the data model around how the queries were actually run.
• Moved heavy aggregation off the request path so dashboards load instantly.
• Built proper multi-tenant isolation so one noisy customer cannot affect another.
• Load-tested well past the projected ceiling before going anywhere near production.

The problem

A D2C brand was buying traffic profitably on paper but losing money in reality. Platform-reported returns looked healthy, the bank account disagreed, and nobody could explain the gap.

What we did

• Implemented the Conversions API so tracking survived iOS privacy changes.
• Reconciled platform-reported numbers against actual orders to find the real return.
• Ran a continuous creative testing cycle instead of leaving two ads running for months.
• Fixed the checkout flow and added abandoned cart recovery before scaling spend.