What does a Cirqll sales dashboard show that Cirqll itself does not?

Cirqll shows you clearly what is in your pipeline today. For day-to-day work that is exactly what you need. A sales dashboard in Power BI answers a different kind of question: how is it developing, and what can you expect from it?

Think of questions such as:

  • How many quotes are out, and for how long?
  • What share of our quotes ends up as an assignment?
  • What will the pipeline deliver once we account for the chance of success?
  • Are we on track for this quarter's target?

Our article Connecting Cirqll to Power BI explains how the integration works and which five basic numbers belong on a first dashboard. This article goes a step further: how to get the quote stage and the forecast properly into view.

How do you make quotes measurable in Cirqll?

First, a practical point. In the Cirqll API a quote is not a separate object. The public documentation at docs.api.cirqll.nl lists three parts under "Financial": deals, assignments and contracts (as of 8 October 2026). So you track a quote through the deal.

That works fine, as long as you do it consistently. In Cirqll a deal has a name, a value, a percentage, an owner and a customer, among other things. You name your deal stages yourself, for example "Proposal sent", "In negotiation" and "Verbal agreement". A won deal can be linked to an assignment or a contract, and closed deals can be archived.

For a reliable quote overview, agree on three things:

  1. Which stage means "quote sent". One stage, with a clear name, that everyone uses at the same moment: as soon as the quote has gone out.
  2. What the value of a deal is. The quoted amount excluding VAT, not a rough first estimate that never gets updated.
  3. How a deal ends. Won is linked to an assignment or contract, lost gets a fixed marker. That way you can count cleanly what was won and lost later on.

If you also record why a quote was lost, for example in a custom field with fixed options such as "price", "timing" or "competitor", you get a loss analysis for free.

Which pages belong in a Cirqll sales dashboard?

Four pages are enough. Each page answers one question.

1. Open quotes

A list of all deals in the quote stage, with customer, owner, value and the number of days since the deal was created or last updated. Sort by age. A quote that has been waiting three weeks for a response is a reason to call, not a statistic.

2. Quote conversion

What share of the quotes sent is won? Calculate it over closed deals: won divided by won plus lost. Look at it per month, per sales person and per type of service or product group. That is where you see what works and where quotes consistently stall.

3. Weighted pipeline and forecast

This is where the deal percentage comes in. A €10,000 quote with a 40% chance of success counts for €4,000 in the weighted pipeline. Add that up per expected month and you get a more realistic picture than the sum of all open amounts. Set it against your target. Cirqll can store a financial goal per user; you can use that as the target value, or keep targets in a separate table.

4. From sold to delivered

Because a won deal can be linked to an assignment or contract, you can show what happens after the sale: which won deals already have an assignment, which contracts are running and which expire soon. That connects your sales dashboard to what happens next in your business.

Which calculations do you need, and where do things often go wrong?

The calculations themselves are not complicated. Things go wrong with the definitions.

  • Percentages nobody updates. A weighted forecast is only as good as the percentages in it. Agree a fixed percentage per stage, or derive the percentage from the stage in Power BI, instead of having it filled in per deal by gut feeling.
  • Lost, or just forgotten? Deals that sit idle for months distort your pipeline. Agree that a deal is reviewed and closed after a fixed period without activity.
  • Dates. If you want to measure time per stage, you need the moments of change, not just the current status. A snapshot of today says nothing about how long a deal sat in "Proposal sent". So store a daily snapshot, for example in your own database. That is a job for data engineering.
  • Amounts and VAT. Decide once whether you report including or excluding VAT, and stick to it.

Not using Cirqll but HubSpot or Teamleader? The structure is similar. Read Sales dashboard in Power BI: 5 KPIs that matter.

Example: an installation company with lots of quotes

A fictional example. An installation company with three sales people sends dozens of quotes every month, from small repairs to large projects. Everything is in Cirqll, but nobody has a quick answer to the question "how many quotes are out and what will they deliver?"

This is how they approach it:

  1. Clean up the stages. They reduce the deal stages to five, with one clear "Quote sent" stage, and attach a fixed percentage to each stage.
  2. Add a loss reason. A custom field with four fixed options, required when closing a lost deal.
  3. Connect. Deals, customers and assignments flow into Power BI through a connector.
  4. Build four pages. Open quotes, conversion, weighted forecast and sold versus delivered.
  5. Agree a routine. Every Monday they go through the list of quotes older than two weeks together.

After a few months they might see, for example, that small quotes are often won, but large project quotes are mostly lost on timing. That is a conversation you do not have without a dashboard.

Want a sales person to get an automatic alert when a quote has been open for two weeks? You build that with an automation. Examples are in Cirqll and Make.com: 5 automations.

Step by step: getting started with your Cirqll sales dashboard

  1. Pick your three most important questions. For example: which quotes need a follow-up call this week, what percentage do we win, will we hit the quarterly target?
  2. Make stages and agreements unambiguous. One quote stage, fixed percentages per stage and one way of closing deals.
  3. Clean up old deals. Close deals that have been idle for months, otherwise your dashboard starts with a distorted pipeline.
  4. Connect Cirqll to Power BI and check the totals: the number of open deals and the pipeline value must match what you see in Cirqll.
  5. Start with the open quotes page. It leads to action straight away. Conversion and forecast only become reliable once you have a few months of clean data.

Also read Getting more out of your Cirqll reporting with Power BI on when the reporting in Cirqll itself is enough and when it is not.

Help with your Cirqll sales dashboard

You do not have to build the integration yourself. With the Cirqll Power BI Connector your Cirqll data arrives in your own Power BI environment, with a dashboard template with pipeline, analysis and appointment pages and a Deal Explorer. Want to tailor the dashboard to your own quoting process, or combine Cirqll with your accounting? See what we do in dashboarding and which other integrations we build.