Sales dashboards and data science for better decisions.
All your numbers on one screen, up to date and without building reports. And on top of that, data science: who your best customers are, which ones are about to leave, how much you'll sell and which product will run out.
Book an assessmentFrom seeing what happened to knowing what to do
Analytics has four levels. Descriptive: what happened (sales, margin, collections). Diagnostic: why it happened (which route, product or customer explains the drop). Predictive: what will happen (how much you'll sell, who will stop buying). And prescriptive: what to do (who to call today, what to restock this week). Most companies stay at the first one, built by hand in Excel.
To reach the others we use data science techniques that don't need millions of records. RFM segmentation classifies each customer by how recently they bought, how often and how much they spend: that separates your best customers, the growing ones and the ones cooling off. Customer lifetime value tells you what each one is worth over time and how much is worth investing to keep them. Pareto analysis shows which few customers and products explain most of the margin.
From your history we train models that forecast sales and demand and estimate, customer by customer, the probability that they stop buying. Each forecast is later compared with what actually happened, so you know how much to trust it.
What's included
How we build it
- The business questionWhich decision you want to make better. The indicators come from that, not the other way round.
- The dataYour sources are connected and cleaned: duplicates, gaps and names spelled three ways.
- The modelSegmentation, forecast or churn risk, tested against your own history.
- The dashboard and the actionOne screen that says what happened, what's coming and what to do, and updates itself.
When it's worth it
When someone builds the same Excel report every week, you decide with numbers from a month ago, or you don't know which customers bring the margin.
When it isn't
If your sales aren't recorded anywhere, no dashboard will help: the data has to be captured first.
Frequently asked questions
Is it the same as a sales dashboard in Excel or Power BI?
The idea is the same: seeing your numbers. The difference is that nobody builds it by hand: it updates on its own and flags anything out of the ordinary. If you already use Excel or Power BI, we start from there.
What is predictive analytics?
Using your history to estimate what's coming: how much you'll sell, which product will run out and which customers are buying less often.
How do I know who my best customers are?
With a recency, frequency and monetary (RFM) segmentation: it ranks your customers by how recently they bought, how often and how much they spend. It usually shows that a few explain most of the margin.
Which indicators should a business owner watch?
It depends on the business, but almost always: sales and margin against the previous period, active and lost customers, days to collect and inventory that doesn't move. Few, and always the same ones.
Do I need a lot of data?
We check in the assessment. With little history the dashboard still puts the present in order, and the forecast improves as data builds up.
How much does a dashboard cost?
It's quoted after the free assessment, based on where the data comes from. The price arrives next to what it should return.