Sales pipeline performance: AMA
CRM data is much richer than what meets the eye. Here's how to unleash it.
“Am I happy or sad today, Chris?” This is how my CRO would start our 1:1 every week.
At first, it caught me off guard. Surely, with countless deal reviews, an army of analysts crunching numbers, and 100+ CRM dashboards at their fingertips, the Sales team knew exactly how the quarter was shaping up.
But they weren’t even close to knowing. And it wasn’t their fault.
Reporting on your CRM metrics (i.e., pipeline) is so challenging because it’s one-dimensional. You can see a perfect snapshot of where things stand today but have no context on how you got there or what the future might look like.
But I have good news. Your sales pipeline reporting doesn't have to live down to the limitations of what's available in your CRM. The key to unlocking its power is transitioning from static pipeline snapshots to a deal-based lifecycle view of the data.
Here’s why and how we transitioned at Equals and are now helping our customers do the same.
The power of deal-based lifecycle reporting
What do we mean by deal-based lifecycle reporting, and why does it matter?
What is it?
Deal-based lifecycle reporting shows the entire journey from when a deal is created to when it is closed. It’s more than just tracking the various stages of the sales funnel; it also includes changes in other attributes like deal value or expected close date.
A typical example looks something like this:
The opportunity was created on Oct 3rd, 2023 for $5K with a Nov 30th close date
Since the prospect moved slowly, real negotiations didn’t initiate until Feb 2024
The deal finally moved to Closed Won on Mar 31st
Why it matters
Traditional CRM reporting would lose all of the historical context. However, with deal-based lifecycle reporting, we can reconstruct the complete journey of how every deal evolved to draw insights about the future.
Four analyses unlocked by pipeline history
I eventually realized deal-based lifecycle reporting was the missing piece to answer my CRO’s question.
“Am I happy?”
Do we have the coverage needed to hit our number? Are there some promising deals that are undervalued right now?
“Am I sad?”
Are we hanging on to stale deals that will never close? Are we creating enough pipeline today to help position us for success next quarter?
With a complete historical view of your pipeline, you can answer all these questions, making entirely new categories of analysis possible.
1. Change tracking
Question
How does this week’s pipeline compare to last week, and what happened to the deals we talked about last week?
Answer
With deal-based lifecycle reporting, it’s easy to turn the clock back in time and compare your pipeline from the prior week to this week at the individual deal level. From there, you can easily categorize the variance between the two time periods based on distinct sources of change. This gives you a clear sense of what changed and where to focus the attention of your follow-up investigations or actions.
Here’s an example of what that might look like comparing the open pipeline set to close this month from 1 week ago vs. the current week. Yes, we love a good bridge at Equals.
For companies with longer sales cycles, it’s helpful to supplement the current month snapshot above with the table view below that shows the open pipeline changes in the next six months.
2. Bookings forecast
Question
How does our pacing compare to this same time last month or the month before that?
Answer
Instead of relying on straight-line pacing as a comparison, it’s helpful to create what the actual bookings build looks like in a given month or quarter. This can give you a more realistic picture of pacing because we all know the last week or even day of the period brings a flurry of closed-won deals.
The chart below looks at the historical average of bookings progression, based on the last 12 months, using the company’s actual performance data and plots that against the period-to-date actuals.
Question
How much of the pipeline we started this period with should I expect to convert?
Answer
Instead of relying on a generic coverage ratio (e.g., 3.0x), deal-based lifecycle reporting allows you to run a more accurate analysis using your own data. The chart below compares how much pipeline you had on the first day of the month that was set to close that same month vs. what actually converted to closed-won.
Understanding this ahead of time gives you the confidence to know where you stand and enables you to shift into action mode sooner when you’re behind.
3. Conversion rates
Question
Has there been a performance shift in recent months?
Answer
The easiest way to spot longer-tail changes is cohorting conversion rates by when the deal was created. Doing so makes it easier to identify the source of the change and whether you expect that trend to continue, a critical component of any planning process.
In the table below, we show conversion rates of deals across each stage of the sales funnel. Note that it’s important to clearly show the number of Open deals to avoid drawing false conclusions from cohorts that haven’t fully aged yet.
In general, we look at stage-to-stage level conversion rates to quickly identify drop-offs in the funnel (e.g., S1-S2 CVR is the only point where CVR is <50%), as well as overall conversion rates to track overall funnel efficiency and benchmark performance vs. peers.
Side note
Identifying the source of the change can sometimes be more art than science, but I recommend grouping these into internal or external factors.
Internal changes include things like tweaks to your sales motion, product offerings, or pricing models, while external factors relate to the competitive landscape (e.g., win rates in head-to-head deals) or macro-environment (e.g., prospects citing budget constraints on lost deals).
4. Deal velocity
Questions
How long is it taking us to close deals? Are we hanging on to stale deals longer than we should?
Answer
The length of your sales cycle is one of the biggest determinants of your team’s maximum sales capacity, but looking at deal length from start to finish only tells part of the story.
In the charts below, we show stage-to-stage level conversion (charts on the left) plotted against the ACV and median Days-in-Stage of deals at the stage (charts on the right). Showing these side-by-side helps you see if a change in deal velocity may be coming from a spike in volume (signaling capacity constraints) or a jump in ACVs (higher deal value = more complexity/approval chains).
By tracking the movements between each stage, it’s easy to identify bottlenecks in the sales funnel and take action.
Side note
Many times, the best resolution is moving deals to closed-lost faster. At Equals, we love it when buyers say “yes”, but a close second is a quick “no”. Many teams spend too much time trying to convert the wrong prospect to a yes that 1) will be a churn risk down the line and 2) takes time away from the strong yes you could’ve converted or upsold instead.
How to unlock your pipeline history
The good news is that all this data already exists in your CRM – it's just waiting to be unlocked.
Salesforce offers out-of-the-box reporting through Opportunity history data, which tracks changes in fields like Amount, Close Date, Stage, and Probability. You can enhance this by manually enabling change tracking on additional fields and custom objects through the Field history object.
HubSpot also supports change tracking automatically through their deal Property history objects.
Having historical data available is a helpful starting point. However, there’s still a good amount of effort required to transform that raw data into a usable format. You'll need to use SQL to complete the following steps, which mirror the process outlined in our post on How to build Annual Recurring Revenue:
Pull the raw history data from your CRM
Transform it into a daily record for each opportunity
Join it with other opportunity attributes
Clean up any inconsistencies in the data
Getting through the set-up phase is time-consuming, and the work is never done. You’ll constantly iterate on the data as the business’ go-to-market motion evolves, product offerings expand, and org structure changes.
But the payoff is worth it. Once you have this foundation, you can answer virtually any question about pipeline performance and evolution.
We can help
We've helped dozens of companies unlock these insights from their CRM data implementations, ranging from early-stage startups to those with $100M+ ARR.
Everything outlined above, including all the charts and tables, can be built with Equals. Here’s how:
We connect directly to Salesforce or HubSpot
We write the queries to clean and transform the data you need
We build all the analyses (that update automatically as fresh deal data rolls in)
We build a live, shareable dashboard that auto-sends to Slack and email (daily, weekly, or monthly)
If you're intrigued by the potential of this reporting but unsure where to start, our team of Equals Experts (including me) are ready and waiting to help.