Algorithm builds the data infrastructure, attribution models, and intelligence layer that connects marketing activity to revenue growth - so you stop debating dashboards and start making decisions.
The gap between data and decisions
Every platform generates data. Google Ads, Meta, GA4, CRM, finance systems - the volume is not the problem. The problem is that none of it is connected. Marketing reports say one thing. Finance says another. The board asks a question and three teams give three different answers.
This is not a lack of data. It is a lack of connection. Attribution is fragmented. Reporting is manual. Nobody can say with confidence which activities are generating revenue and which are generating noise. The result is not bad data - it is bad decisions made with incomplete information.
Algorithm builds the data infrastructure, attribution models, and intelligence layer that turns disconnected sources into a single, reliable view of commercial performance - so every decision, from budget allocation to channel strategy, is grounded in evidence.
What most businesses have
Each source tells a different story
What Algorithm builds
One truth. One set of numbers. Revenue.
What good data infrastructure looks like commercially
The point of data infrastructure is not better dashboards. It is better decisions - made faster, with higher confidence, and connected to commercial outcomes.
When every channel is measured against the same commercial framework, you know where to invest and where to pull back - without guesswork or politics.
One connected data layer means marketing, finance, and the board are all looking at the same numbers. No more conflicting reports. No more debate about what is working.
Marketing Mix Modelling (MMM) lets you simulate scenarios before committing budget. Model the impact of shifting spend, entering a new channel, or changing creative strategy - before the money moves.
The difference between data as a cost and data as a competitive advantage
The Data & BI model
Each layer builds on the one below it. Data infrastructure feeds attribution. Attribution feeds intelligence. Intelligence feeds modelling. The result is a system that improves every decision across the business.
The foundation layer
Connect every data source into one reliable system.
Before analytics can deliver value, the data layer has to work. Algorithm builds and maintains the infrastructure that connects GA4, Google Ads, Meta, CRM, and finance systems into a unified data environment. Clean pipelines, consistent naming, reliable ingestion - so every downstream report and model is built on data you can trust.
Know what is actually working
Connect marketing activity to commercial outcomes.
Platform-reported conversions are not the same as revenue. Algorithm builds multi-touch attribution models that connect every touchpoint to downstream commercial outcomes - including paid media - pipeline, revenue, and customer lifetime value. When you know which activities genuinely drive results, every budget decision improves.
Reporting that triggers decisions
Replace static dashboards with actionable intelligence.
Most reporting tells you what happened. Algorithm's intelligence layer tells you what to do about it. Automated reporting surfaces the signals that matter - budget pacing, channel efficiency shifts, conversion rate changes, and revenue attribution - with clear recommendations attached to every data point.
See the future before committing budget
Model the impact of decisions before you make them.
Marketing Mix Modelling (MMM) uses historical data to quantify the contribution of each channel to revenue. Algorithm's MMM capability lets you simulate scenarios - what happens if you shift 20% of search budget to social? What is the revenue impact of entering a new market? - so budget decisions are based on modelled outcomes, not assumptions.
The measurement layer across all of RACE
Every RACE stage generates data and every RACE stage depends on it. The Data & BI layer is the connective tissue that makes the entire system measurable, attributable, and improvable.
Intelligence built into the system
Data & BI is not a separate service bolt-on. It is embedded into every engagement - shaping the strategy, measuring the impact, and improving the system continuously. You do not pay for analytics separately because it is how Algorithm works.
Every report, model, and dashboard is built to answer a commercial question. We do not build data products for the sake of it. If a metric does not connect to a decision, it does not make the cut.
Algorithm's data team includes strategists who understand business context, not just analysts who build charts. The person interpreting your data understands your commercial objectives - because they helped set them.
Most reporting tells you what already happened. Algorithm's MMM and scenario planning capability lets you model what will happen - so you make decisions based on projected outcomes, not historical patterns alone.
Right now, it might be your biggest source of doubt.
Build the Data Layer