Sales and pipeline
The CRM knows what is being negotiated; the ERP knows what was ordered and invoiced. Muvia joins them: pipeline and conversion with one definition, the customers who are ordering less, and Athena answering the sales team's questions.
Illustrative scenario: it describes a typical case, not a customer project.
Pipeline lives in the CRM, revenue in the ERP, and the sales meeting somewhere in between.
Opportunities are in Salesforce, orders and invoices in the ERP. Every sales meeting starts from two different extracts, and the question that really matters, which customers are buying less, gets answered late: once the drop is already in revenue.
Putting both worlds in one place lets you measure conversion against what was actually invoiced, and see a customer slowing down while it happens.
- Who it's for
- Sales leadership, sales operations, area managers and reps; management accounting for the comparison with targets.
What you get
- Conversion on what was invoiced
- The CRM pipeline sits next to real orders and invoices, not next to an estimate.
- A customer's slowdown shows early
- The gap from a customer's own history surfaces while orders slow down, not at year end in the revenue line.
- One definition for the meeting
- Pipeline, conversion and targets come from the same dataset for everyone: the discussion is about customers, not extracts.
- Answers without waiting for an extract
- Sales reps ask Athena and see the query it ran, so the answer can be checked.
For the technical team
How it is built in Muvia
- 1
Connect the CRM and the ERP
Salesforce and HubSpot come in through their connectors, orders and invoices through an incremental copy of the ERP database. Every source becomes a table refreshed on a schedule.
- 2
Join deals and revenue
A query links opportunities and invoices on customer code or VAT number and becomes a dataset with stable fields: the CRM's customer and the ERP's customer are finally the same.
- 3
Measure pipeline and conversion
A dashboard shows pipeline by stage, conversion by rep and by quarter, and revenue against targets. The sales meeting report goes out as a PDF every Monday.
- 4
Find the customers slowing down
With the period-over-period and deviation-from-baseline (z-score) presets, compare each customer's recent orders with their own history. An alarm opens when a customer drops below the threshold.
- 5
Let Athena answer
A sales rep asks in plain words, say which customers in the North-East ordered less than last year, and Athena answers with the table and the query it ran. It is a module each company chooses whether to switch on.
SQL query
WITH addMonths(toStartOfMonth(today()), -3) AS cutoff,
monthly AS (
SELECT customer_code, toStartOfMonth(order_date) AS month,
sum(net_amount) AS ordered
FROM orders
WHERE order_date >= addMonths(toStartOfMonth(today()), -12)
AND order_date < toStartOfMonth(today())
GROUP BY customer_code, month
)
SELECT customer_code,
sumIf(ordered, month >= cutoff) / 3 AS last_3_months,
sumIf(ordered, month < cutoff) / 9 AS baseline,
sqrt(greatest(sumIf(ordered * ordered, month < cutoff) / 9 - baseline * baseline, 0)) AS std_dev,
(last_3_months - baseline) / nullIf(std_dev, 0) AS z_score
FROM monthly
GROUP BY customer_code
HAVING baseline > 0 AND (last_3_months = 0 OR z_score < -2)
ORDER BY last_3_months = 0 DESC, z_score- The data it needs
- Opportunities, stages and activities from Salesforce (or Microsoft Dynamics 365)
- Leads and campaigns from HubSpot
- Orders, order lines and invoices by customer from the ERP on SQL Server
- Quarterly targets by sales rep and region, from an Excel file
More cases in this line
All use cases- Margins and management accountingInvoices and costs sit in the ERP, customers and sales reps in the CRM, the budget in a spreadsheet. In Muvia they become one margin by customer and by product, with the Monday report and an alarm when the numbers drift from budget.
- Demand and stock forecastingSales history and stock levels are already in the ERP. Your data scientist builds a forecasting model with scikit-learn; Muvia runs it every night next to the data and puts forecast, actual sales and understock in front of the people who reorder.
- Data science on company dataYour data scientist trains wherever they like, in their own Jupyter with their own tools. Muvia gives them governed data to start from, runs the model on a schedule next to the data, and puts the scores into dashboards, alarms and reports.
Bring us a question you can't answer today.
We start from a real question your business has and walk the path from source to dashboard with your systems, not a demo dataset.