How much historical data do we need?

It depends on the question. Simple revenue or demand forecasts often need 12–24 months of consistent records. Churn models need enough cancelled and retained customers to learn patterns, sometimes hundreds of accounts, not millions. We assess your data before promising a model.

Is this full data science or basic reporting?

We focus on practical SMB use cases: forecasts, segment trends, churn or payment-risk flags, and dashboards, not research-grade ML for its own sake. If your data only supports descriptive analytics today, we say so and help you get there first.

What tools and stacks do you use?

Python, SQL, and your warehouse or exports: Looker, Metabase, Power BI, or custom Django dashboards. Models are documented so your team knows assumptions and limits.

Can predictions connect to our product or CRM?

Yes. Scores and forecasts can feed CRM fields, admin alerts, or internal tools via API when you want ops to act on them, not just view a chart.

How do we get started?

Share the decision you want to improve (forecast inventory, flag churn, prioritize collections) and sample data. We propose scope, accuracy expectations, and timeline.

Predictive Analytics

Forecasts and risk signals
your SMB data can actually support

Demand forecasts, churn flags, and ops dashboards, built on your sales, subscription, or inventory records, with clear limits on what the data can predict.

Discuss your data

Predictive

Data

Forecast

Risk

Churn

Dashboard

Refresh

Who this is for

Founders and ops leads who have data in spreadsheets, CRM, or an app, but decisions still run on gut because nobody has time to model it.

Subscription & SaaS

Churn risk lists, renewal focus, and MRR forecasts when you have enough account history.

Retail & inventory

Demand forecasts and stock alerts from sales and seasonality: not perfect, but better than guesswork.

Services & B2B

Pipeline weighting, payment-risk flags, and capacity planning from CRM and billing exports.

What we deliver

Actionable outputs, not a slide deck of correlations

Demand & revenue forecasts

Short-horizon forecasts from historical sales or subscriptions, with documented assumptions.

Churn & retention signals

Accounts or cohorts flagged for outreach when usage or payment patterns look risky.

Risk & collections flags

Late-payment or order-risk scores for finance and ops, scoped to your ledger data.

Executive dashboards

KPI views with forecast bands and drill-downs your team will actually open weekly.

Data readiness assessment

We tell you if you need cleaner exports or more history before modeling is worth it.

CRM & tool hooks

Push scores to CRM fields or alerts when ops should act, not just static reports.

What we won't pretend

SMB analytics with honest scope

Data limits upfront

Thin or messy data gets a cleanup path, not a fake precision model.

Documented assumptions

You know what the model uses and when to distrust it.

Right-sized methods

Simple baselines first; heavier ML only when data justifies it.

Refresh & drift

Models need updates as business changes. We plan for that.

Related services

Predictions sit on data pipelines and systems you already run.

Analytics & reporting

Custom software

Frequently asked questions

Often 12–24 months for forecasts; churn needs enough cancelled and retained accounts to learn patterns. We assess before scoping a model.

Practical SMB use cases: forecasts, churn flags, dashboards. If data only supports descriptive analytics today, we say so and help you get there first.

Python, SQL, your warehouse or exports, and Looker, Metabase, Power BI, or custom Django dashboards, with documented assumptions.

Yes: scores and forecasts via API or scheduled exports so ops can act, not just view charts.

Tell us the decision you want to improve and share sample data. We propose scope, accuracy expectations, and timeline.

Want forecasts you can explain to the board?

Share the decision and the data you have. We will tell you what is realistic to predict and what to fix first.

Talk to us

Forecasts and risk signals your SMB data can actually support