Category
Predictive analytics and AI
The short answer
Which customers will churn, buy again or convert, before they do?
On this page 5 sections
Predictive analytics uses your historical data to score what is likely to happen next: which customers are about to cancel, which leads will close, how much stock you will need. It used to need a data science team. No-code platforms now build and validate the model from a connected data warehouse, and push the scores into the tools your team already uses.
Do you have enough data?
A model needs examples of the outcome you want to predict. If you want to predict churn, you need a few hundred customers who churned and the history of what they did beforehand. If your customer data lives in five disconnected spreadsheets, fix that first.
Teams that do train their own models will need compute. GPU clouds such as RunPod rent capacity by the hour, which suits occasional training runs better than buying hardware.
Read what predictive analytics means for a small business and build or buy a predictive model.
At a glance
| Feature | Pecan AI | RunPod | Database Mart |
|---|---|---|---|
| What it is | No-code predictive platform | Hourly GPU cloud | Monthly servers incl. GPU |
| Needs engineers | No | Yes | Yes |
| Connects to warehouses | Snowflake, BigQuery, Redshift, Databricks | n/s (not stated on the vendor’s site) | n/s (not stated on the vendor’s site) |
| Billing | Talk to sales | Pay as you go | Monthly rental |
Guides
What is predictive analytics for a small business?
Build or buy a predictive model?
SaaS metrics: LTV, CAC, payback and churn explained
Tool profiles and comparisons
Other tools in this space
Plain links, no commission. Listed so you can compare fairly.
- BigQuery ML: Train models with SQL inside BigQuery.
- Akkio: No-code predictive analytics aimed at agencies.
- DataRobot: Enterprise automated machine learning.
From our network: Artificial Intelligences compares AI tools and models on cost and capability.