Sales
Profitability by portfolio, customer clustering and sales rep performance. High revenue and low margin usually live in the same client.
Talk to a specialistSelling a lot is not the same as making money.
Ranking reps by revenue is the most common sales indicator and one of the most misleading. It rewards volume, and volume with aggressive discount, expensive freight and stretched payment terms can lose money but only once the cost shows up, in a report nobody crosses with the sale.
The work here is moving from revenue to margin by segment: by customer, by product, by region and by rep. It is common to discover that a significant part of the portfolio loses money, and that it was being celebrated.
The questions we answer
- Which customer is genuinely profitable after discount, freight and cost to serve?
- Which rep delivers margin, not just volume?
- Which product pulls the sale and which only takes up space in the mix?
- Where is the discount policy being applied outside the rules?
- How much time does the sales team spend building reports instead of selling?
The indicators of this industry
The ones that show up in most projects in this industry. The final set is always agreed with you an indicator nobody uses is dead weight on a dashboard.
- Profitability. Gross and net margin by customer, product and region, margin per rep, cost to serve, average ticket, average discount granted and out-of-policy discount.
- Portfolio. Revenue concentration, ABC curve of customers, active and inactive customers, repurchase rate, portfolio churn, share of customer wallet.
- Team performance. Target attainment, conversion rate by funnel stage, average sales cycle, portfolio coverage, mix sold per rep.
- Predictability. Forecast versus actual, weighted pipeline, seasonality by territory, propensity to buy per customer.
The solutions we use most here
- Business Intelligence. Crossing CRM, ERP and commercial policy so margin appears by segment.
- Data Analytics. Portfolio clustering, propensity to buy and churn risk.
- Integration & AI Automation. The end of the closing spreadsheet that ties the team up every month.
How we run it
We start with the crossing of sales and cost which is where the information is usually broken, with one side in the CRM and the other in the ERP. We define with the sales leadership what goes into cost to serve, because that is the decision that changes the whole analysis. Only then come the dashboards by role: leadership sees the portfolio, management sees the team, the rep sees their own margin.
How we measure results
The most frequent indicators are gross margin gained by portfolio segment, hours given back to the sales team and a reduction in out-of-policy discounting.
We now have a far more robust, fast and visual view of each management area’s results.
Sales director national fuel distributor
About this industry
Our CRM is out of date. Does that rule it out?
No, but it sets the order of the work. Incomplete CRM data is common, and part of the project is precisely creating the routine that keeps the records alive. We start with what the ERP already records reliably invoiced sales is always the cleanest data in the house.
Can we show margin to the rep?
You can, and it is usually the change that moves the result most. It is a policy question, not a technology one: access governance lets each rep see their own portfolio without seeing their colleagues’.
How do we define cost to serve?
It is a business decision, not a technical one, and we run the conversation. The criterion has to be agreed up front: how much freight, commission and overhead goes into the calculation. An imperfect criterion, but a single one applied to everyone, already removes most of the distortion.
How long until the first result?
The first dashboard usually goes live within three to six weeks. In one project in this area, automating the KPIs gave 190 hours a month back to the sales team.
Which part of your portfolio loses money?
Thirty minutes of conversation is usually enough to point at where to look.
We understand processes before recommending technology. Automation, data, artificial intelligence, and custom software for companies seeking efficiency, control, and scale.