Prediction models that help you act before problems show up
Most businesses already have the data to see problems coming. Customers who are about to leave buy less often. Staff who are about to quit show patterns in overtime and reviews. Good leads look like your past buyers.
How we help
We build models that find those patterns in your data and turn them into a simple score or forecast your team can act on. We also explain what drives each prediction, so it never feels like a black box.
This is for you if
- You find out a customer has left only after they are gone
- Stock or staffing plans are based on guesses
- Your sales team treats every lead the same
- You have years of data but no one has looked at it closely
What we build
Churn and attrition prediction
A risk score for each customer or employee, plus the main reasons behind it.
Sales and demand forecasting
Forecasts by week or month that help you plan stock, staff and cash.
Lead and risk scoring
Rank leads, orders or accounts by how likely they are to convert, pay late or need attention.
How the project runs
Short steps, weekly check-ins and a working result at the end.
Tools we use
Check the data
We look at what you have and tell you honestly whether it is enough to predict what you want.
Build and compare models
We test several approaches and pick the one that is accurate and easy to explain.
Explain the results
You get a short report on accuracy and the factors that matter most, written for non technical readers.
Put it to work
Scores feed into a dashboard, spreadsheet or your CRM, and we retrain the model as new data arrives.
Related work
Power BI dashboard and ML model
HR Attrition Predictor
Flags employees likely to leave in the next 90 days, with the reasons behind each risk score.
See the project
Power BI dashboard
E-commerce Sales Dashboard
Brings store sales, ad spend and website traffic into one report, with a churn risk score for each customer.
See the projectQuestions about prediction models and machine learning
How much data do I need?
It depends on the question. As a rough guide, a few hundred past examples of the thing you want to predict is a good start. We check this before you commit to anything.
How accurate will it be?
We can only say after looking at your data. We report accuracy on data the model has never seen, so the number is honest.
Will my team understand it?
Yes. Every model comes with the main factors behind its predictions, explained in plain language.
Tell us what is slowing your team down
Book a free 30 minute call. We will look at your problem, tell you honestly whether AI or data work can help, and send a short written plan if it can.