Forecasting and Analytics
We use sales, payment, and customer activity history for forecasts, scoring, and anomaly detection. Before rollout, the result is compared with the current process on a held-out historical period.
When you need this
- →Data has been piling up for years, but decisions are made by gut
- →Churn is noticed when it is too late to retain the customer
- →Procurement and capacity are planned manually in spreadsheets
- →You suspect losses or fraud that are hard to trace
What's included
- Forecasting: demand, customer churn, capacity, revenue
- Scoring: applications, leads, and risks
- Recommendation systems for stores and services
- Anomaly detection: fraud, failures, process deviations
- Data audit and regular data preparation pipelines
- Post-launch work: quality monitoring and recalibration
Process
How we work
- 01
Initial conversation
We clarify the context, arrange a call, and sign an NDA before materials are shared if needed.
- 02
Preliminary assessment
We review the process, data, and existing systems, then prepare an approach and sequence of work.
- 03
Plan and contract
We describe the first milestone: the work, the acceptance result, and the required time and budget.
- 04
Pilot and development
The first milestone may validate the riskiest part. The remaining work and acceptance process are stated in the plan.
- 05
Launch and support
We run acceptance and transfer milestone deliverables after payment. Documentation and training are included when the client needs them.
Post-launch support
We fix warranty defects for three months after delivery. Ongoing support, monitoring, and development are covered by a separate agreement.
Questions and answers
Is our data enough?
We check volume, completeness, and update frequency before estimating development. If the history is too short, we describe what needs to be collected and when the work can be revisited.
Why is the forecast better than spreadsheet rules?
That depends on the process. A new calculation is useful only if it improves on the current rules over a historical period. We run that comparison before rollout.
How do you check calculation quality?
Before rollout, we reserve a period that was not used during setup and calculate the result on it. After rollout, figures are compared with a control group or baseline period.
What will you need from our team?
We need data access and an employee who understands how the figures are produced and where exceptions occur. The client IT team will also need to help with access and integrations.
Related services
Get a preliminary assessment
Describe the task. After reviewing it, we will propose a call and a list of materials for an initial assessment.
contact@amplifylab.it.com