Predictive
Analytics
Churn happens before you see it. Value concentrates in segments you have not yet identified. The signals that explain both are already in your data. We build the models and pipelines that surface them, automatically.
You know what customers
did, not what they do next
Your segments are
static snapshots
You discover churn
only after it happens
Customer data is not the problem. Most businesses have more of it than they know what to do with. The gap is between what the data records and what it predicts, and that gap is where poor decisions get made.
173tech closes the gap. We build predictive models that give your teams a forward-looking view of customer value, risk, and behaviour at an individual level, all automated.
What Predictive Analytics Looks Like
LTV Prediction
Aggregate LTV tells you how a cohort performed. It does not tell you which customers to invest in. We predict value at the individual level, at the moment it can still influence a decision.
- Predicted value scores aligned to your real decision window
- Outputs connected to ad platforms to optimise toward revenue quality
- Financial forecasts built on per-customer predicted LTV, not averages
Scores new users on day zero, giving the growth team a reliable signal to optimise spend.
Churn Prediction
Most churn models tell you what already happened. We build systems that identify risk at the individual level, early enough to change the outcome.
- Customer-level risk scores updated continuously
- Clear explanations of drivers so your team can act with confidence
- Retention effort concentrated on customers worth saving
Dynamic Segmentation
Static segments built on last month's data are already wrong. We automate the logic so your customer groupings reflect how people actually behave right now.
- Unified customer profile across behaviour, value, and feedback
- Segments that update automatically as behaviour shifts
- Personalisation at scale without manual intervention
How We Build Predictive Analytics
A typical engagement starts from 8 weeks at £48,000, taking you from discovery to production-ready predictions.
Align on the target metric, and confirm which decisions the model needs to power.
Audit available signals across sources, identify gaps, and confirm data readiness.
Understand distributions, correlations, and which signals predict outcomes.
We build candidate models, test them against real outcomes, and validate that the predictions hold.
Deploy automated pipelines with retraining schedules, drift monitoring and notifications.
We review model performance with your team and make sure the predictions are driving real decisions.
Your Collaboration With Us
We deploy an experienced data team tailored to your business and technical needs, scaling resources up or down across each project phase to ensure efficiency and high-quality delivery.
- Project Lead: Hands-on management of delivery
- Engineering Lead: Design optimal data architecture
- Data Engineer: Pipeline creation & optimisation
- Data Analysts: Data modelling, reporting & activation
- Data Strategist: Business impact & data adoption
A Few Case Studies
Sharing Our Knowledge
Get In Touch
Our friendly team are always on hand to answer questions, troubleshoot problems and point you in the right direction.
