Start a project ↗
AI development

Predictive analytics services built on your own data

Our predictive analytics services turn the history already in your CRM, booking system and sales records into forecasts your team can plan around: next month’s demand, the customers likely to leave and the leads most likely to buy. Each forecast is tested against what actually happened before you rely on it, then delivered where your team already works.

1,000+projects
delivered for businesses in the US and the UK since 2016
Weekly
progress updates once work starts, plus a monthly report
5.0
star rating on Google from our clients
What it is

What predictive analytics services include

Predictive analytics uses patterns in your past data to estimate what is likely to happen next. A demand forecast says how many orders, calls or bookings to expect each week. A churn model flags customers who are drifting away. A lead score ranks new inquiries by how likely they are to become paying clients. Each one gives a number and a reason, so people can plan staff, stock and follow-up instead of guessing.

We start with the decision and the data, not the algorithm. Often a well-built forecast in a dashboard is all a business needs; sometimes a machine learning model earns its place. If your history is too short or too patchy to predict from, we say so and help you start collecting the right data first.

Signs predictive analytics fits

  • You plan staff or stock from gut feel or last year’s numbers
  • Customers leave before anyone notices they were slipping
  • Your team chases every lead with the same effort
  • You hold a year or more of orders, bookings or CRM data
  • Reports show what happened, never what is coming
Get a free AI consultation ↗
What’s included

What’s included in our predictive analytics services

From a data review to forecasts your team checks every week, plus the monitoring that keeps them honest.

01

Data audit

We map what you hold in your CRM, booking, sales and web analytics tools, how clean it is and how far back it goes.

02

Data pipeline

Sources joined into one tidy dataset that refreshes on a schedule, so forecasts never depend on a manual export.

03

Forecasting models

Demand, churn and lead quality models, starting from simple baselines and adding complexity only when it helps.

04

Backtesting

Each model tested on past periods it never saw, so you know how far off it tends to be before you plan around it.

05

Dashboards and CRM fields

Forecasts and scores delivered in a dashboard, a CRM field, a spreadsheet or a weekly email, where people will see them.

06

Monitoring and retraining

Accuracy tracked against what really happens, with models retrained when your business or market shifts.

In depth

Predictive analytics in depth

What makes a forecast one that people trust and act on.

Start with a baseline

Every forecast is compared with a simple rule, such as last year’s figure for the same week or a rolling average. If a more complex model cannot beat that baseline on your own past data, it does not go live. This keeps the work honest and often shows that a well-kept simple forecast does most of the job. Where a model does earn its place, you see how much better it is, in plain terms, before you decide.

Forecasts given as a range

No model knows the future. We show each forecast with a likely range and explain what drives it, such as season, price changes, marketing spend or local events. Planning to the range rather than a single number helps you staff and stock sensibly, and makes it obvious when reality starts drifting from the plan.

Scores your team will act on

A churn or lead score is only useful if someone acts on it. We agree what happens at each score, for example a call from the account manager or a faster reply to a promising lead, and put the score where that person already works, inside your CRM or booking system. Then we track whether those actions change the outcome.

How it works

How our predictive analytics services work

A first forecast on your own history, then a live trial, with a progress update every week and a monthly report.

  1. Step 01

    Discovery

    The decisions to support, the data you hold and how success will be measured, with a scope and a price.

  2. Step 02

    Data and baseline

    Your data cleaned and joined, and a simple baseline forecast set as the bar to beat.

  3. Step 03

    Model and backtest

    Models built and tested on past periods, with the results shared before anything goes live.

  4. Step 04

    Launch and monitor

    Forecasts delivered to your team, checked against reality and retrained as your data changes.

Why Griffon

Why Griffon for predictive analytics

One team connects your data, builds the forecasts, puts them in your CRM or dashboard and runs the marketing that acts on them. We judge each model against a simple baseline and real outcomes, and we tell you when a plain spreadsheet forecast will do.

Once the work is paid in full, the code, the models, the pipelines and the accounts they run in are yours. Your data stays yours throughout, and any capable analyst can pick up the work.

Part of our AI development ↗

2 hours

our usual reply to a new inquiry, one business day at most

Weekly

progress updates, plus a monthly report with the data and the work done

One team

strategy, design, development and marketing under one roof

You own it

the design, code and accounts are yours once the work is paid in full

FAQ

Questions about predictive analytics, answered

What do predictive analytics services include?

A review of your data, a pipeline that keeps it fresh, forecasting or scoring models tested on your own history, and dashboards or CRM fields that put the results in front of your team, with ongoing monitoring.

How much data do we need?

It depends on the question. Weekly demand forecasts usually need at least a year of history to capture the seasons. Churn and lead scores need enough past customers or leads with known outcomes. We check this in discovery.

How accurate will the forecasts be?

We do not promise a figure before seeing your data. We test each model on past periods it never saw, compare it with a simple baseline and show you the typical error before you rely on it.

Where will we see the forecasts?

Where your team already works: a dashboard, a field in your CRM, a shared spreadsheet or a weekly email. We avoid adding another tool people have to remember to open.

Who owns the models and the data?

You do. Your data stays yours, and the code, models and accounts are yours once the work is paid in full.

Contact

Get a free AI consultation

A 30-minute call. No deck, no pressure. Bring the site, the numbers and the goal, and leave with a plan and a price.

Start a project