CRM reports you build yourself

It is the first Monday of the month. The sales manager wants to know, before the ten o'clock meeting, how much was won last month per account manager and how much is still open in the Proposal stage. So at half past eight someone exports the deals from the CRM. They go into a spreadsheet, a pivot table goes on top, and at five to ten there is a chart in the slide deck.

In the meeting someone asks which deals make up the 40,000 in Proposal. Nobody knows, because the spreadsheet is a snapshot and the link to the deals is gone. A week later the number is already wrong. Two deals were lost and one slipped to next quarter. The meeting then turns into a debate about whether the number is right, rather than what the team should do about it.

That is the real cost of reporting outside the CRM. It takes time, it goes stale at once, and it cuts the number loose from the records. In Lumo you build the report on the data itself. You pick the data, such as deals, leads or activities. You pick what to measure: a count, a sum of deal value, an average or a ratio. And you pick the breakdown, such as owner, stage, pipeline or lost reason. The preview recalculates with every choice.

Put the report on a dashboard and everyone looks at the same number at the same moment. Click the Proposal bar in the meeting and you see the deals inside it. The conversation is about the deals again. If you want to know which numbers are worth tracking each week, read our guide on sales KPIs that drive decisions. For turning a pipeline into a prediction, see the guide on sales forecasting.

Say a distributor of technical parts has 12 account managers and two pipelines, one for new customers and one for growth at existing accounts. The sales director wants to know every Monday, in twenty minutes, where the team stands. This is an example of how that dashboard could look.

At the top sits a key figure with won deal value this quarter and a goal line at the quarterly target. Next to it a bar chart with won value per owner. Below that a funnel with the number of deals per stage in the new customer pipeline, so you see where deals get stuck. A table of lost deals by lost reason shows whether price, lead time or a competitor costs the most deals. And a line with completed activities per week shows whether the team has enough customer contact.

The dashboard gets a pipeline filter. In the meeting the director sets it to new customers first and then to growth. If one account manager has a lot of deals in Proposal, the director clicks that bar and opens the underlying records. It becomes a conversation about three specific deals and their next step.

For the weighted outlook the team builds a separate report: the sum of deal value times the win probability per stage, broken down by month of expected close date. You set the win probability per stage in your pipeline. There is no separate forecast screen. This report does that job.

A report is only as good as the data underneath. Stages and win probabilities come from pipeline management. Activities come from activities and calendar, including meetings that arrive from Google Calendar. Leads and their status come from lead management.

If fields are missing or deals are incomplete, the data quality rules in CRM adoption and guidance help. You can require, for example, that every deal has an expected close date. Duplicate organizations make totals per customer unreliable, and you merge those in duplicate management.

Sales managers have their own page on pipeline and team visibility. The page for RevOps and leadership goes deeper into a fixed set of numbers.