Predictive analytics solutions are worth buying when a prediction changes a decision. We establish that in scoping, then build the model that beats your simplest existing rule.
Everything runs inside EU regions, with the training data staying where your source systems already sit.
What These Predictive Analytics Solutions Cover
Forecasting. Demand, revenue, stock, staffing levels. Seasonal in nearly every case, usually with a trend underneath, and usually handled better by a carefully specified statistical model than by something newer.
Churn and retention. Scoring accounts by likelihood of lapsing, ordered so somebody can work down the list. The ranking matters far more than the raw probability.
Segmentation. RFM, clustering, or a straightforward behavioural split. A segmentation earns its keep when the segments get treated differently.
Pricing analysis. Elasticity where the transactional history genuinely supports the estimate, and a plain statement of what more would be needed where it does not.
The Baseline Comes First
Before anything is modelled we build the obvious version: last year plus growth, everyone who has not ordered in ninety days, or a three month moving average.
Where that version is close enough, we say so in week one at our cost rather than month four at yours.
When a model does beat the baseline, the size of the margin is the business case, and it is a number you can hold any future supplier to.
Measured Against Data It Has Not Seen
Every model is scored against a held-out period, or a random sample where timing is not a factor.
Results get reported against your decision rather than a textbook metric. For churn that is precision at the top of the list. For a forecast it is error at the horizon you actually plan to.
Our predictive analytics consulting includes that evaluation in the handover, so your team can re-run it and get the same number.
Data Residency and the AI Act
Training data, model artefacts and scoring logs each get a named EU region, agreed at scoping and written into the architecture note.
Where a model informs decisions about people, that record is the evidence base the EU AI Act rewards. Keeping it from the start costs an afternoon, and a data science expert on your side can read it without translation.
How Engagements Start
A paid scoping exercise comes first, covering whether the data supports the question and what a model would need to beat.
Then fixed price against a defined deliverable. Code, features, evaluation and documentation are handed over, so whoever maintains it next does not need us.
Our data science consulting services are bought in pieces, so one scored list can prove the approach before predictive analytics solutions are extended across the business. Tell us what decision a prediction would change.
Related Services
Unreliable underlying figures are a data quality problem, and modelling them produces confident nonsense.
Where the history is not being captured at all, that is data engineering. Where the output needs to reach people weekly, that is dashboards, and where models are run as engineering rather than analysis, that sits with AI and LLM applications.