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How do I identify stage conversion rates?

To access this feature, you'll need the CaliberMind funnels product.

What's a Conversion Rate?

A conversion rate has the starting population (accounts or people - depending on your funnel type - that started in a certain stage during a given period) as the denominator and the "success" population (accounts or people - depending on your funnel type - that are in your starting population and moved to the next stage). In other words:

Conversion Rate = (Subset of Start Stage that Progressed to the End Stage) / (All Start Stage in that Period)

When we look at conversion rate trends over several quarters or months, we can begin to see whether we're moving accounts or people through the funnel more or less effectively.

Why are Conversion Rates Powerful?

Knowing how much volume passes through a stage every quarter is fine, but in my opinion, understanding conversion rates and the number of days in a stage are powerful tidbits that can help you improve funnel efficiency, which ultimately means we're no longer about filling a pipeline with copious volume - we're focused on generating more pipeline and bookings from the volume we already have.

For example, if I know that my sales team is converting less qualified accounts into pipeline, I have a red flag I need to research. This downward trend in conversion rates could mean that an integration broke, someone changed the sales views in their CRM (making it hard to find their leads), marketing changed their channel mix for the worse, or lead follow-up became less of a priority for sales management.

When I know there's a new trend, I have a shot at avoiding it in the future if it's bad and repeating it in the future if it's good. We highly recommend reading this article on the compound effect of incremental change in funnels.

How does CaliberMind define a Cohort?

Cohorts make the difference between calculating a true conversion rate and looking at a weird ratio.

For example, if we don't cohort our data, later stages that happened this month might be larger than earlier stages. When we tell the executive team that, surprise!, our conversion rate is higher than 100%, they'll tell you you're wrong before you can blink. In their mind, the funnel should be biggest at the top and gradually get smaller under closed won.

If we decide to cohort by the MQL date, that means that the starting and biggest population will be the pool of MQLs, and then we'll take that same MQL population and watch how they subsequently move through the funnel.

Let's put that another way.

Let's say we have 50 people take a survey in May and 100 people take the survey in June. If we're cohorting, we watch that original group of 50 people and flag which of those 50 became a customer (let's say 5 people) for a conversion rate of 10%.

If we don't cohort, 2 people may have converted into a customer in May and 12 people in June. If we look at the ratios, May will be 4% (2 divided by 50) and June will be 12% (12 divided by 100) even though 3 of those 12 took the survey in May.

Cohorting allows us to snap the line and keep the population we're analyzing by week/month/quarter consistent over time. It's also a truer representation of our buyer's likelihood to buy because we're keeping watch of any buyer's behavior and analyzing it 1:1.

The scenario for our Use Case -

With a board meeting just on the horizon, I know my CMO will ask several questions about the funnel. How did we do compared to prior quarters? If things changed, were they for the worse or the better? Why did they change?

Before I can answer that last question, I need to understand my conversion rates compared to prior periods so I can form a hypothesis to test what changed.

There are three different ways we can analyze funnel conversion rates in CaliberMind:

  1. Funnels: Data Explore
  2. Funnels: Trend Analysis
  3. Funnels: Cohort Analysis


When I use the Data Explore dashboard, it's like using a super powerful pivot table. I need to make several decisions about how I want to view my data. First, I'm going to look at conversion rates by month and stage. That will allow me to see how my conversion rates are changing over time.

  1. First, I'll open the dashboard:
open data explore dashboard
  1. Next, select how much time you want to analyze. In this example, I'll select This and Last Year:
data explore time selection
  1. Then pick how you want to cohort the data. I recommend cohorting by the stage start date when calculating conversion rates and then clicking Apply:
date cohort for data explore
  1. Choose date aggregation = Months, and click Apply:
Date aggregation data explore
  1. I want to view the table so the Row is Stage Name (1), the Column is Stage Start Date (2), and the Metric is Conversion Rate (3). Remember to click the green Apply button after each selection:
pivot table selections for data explore
  1. Finally, I can review the results. I've highlighted a few areas of interest to dive into further in my research:
conversion rates by stage

Why Is My Final Stage Conversion Rate 0%?

Each stage's conversion rate is the percentage of how many started in the stage you're viewing that subsequently moved to the next stage. For example, if I'm looking at 06: Late Stage Opportunity - Best Case / Commit, my numerator is the number of late stage that moved to 07: Customer. Because in our case "Customer" is the final stage and there is not a subsequent stage, there can't be a conversion rate over 0%.


Trend Analysis Conversion Report

The Trend Analysis Dashboard is a great way to quickly get conversion rate trends in an easy-to-read visual format. I'm going to do this by opening the dashboard and:

A. Select the timeframe I want to view. We recommend at least 5 quarters to understand whether or not there is seasonality in your sales cycle.

B. Click the conversion rate tab to make sure that's the chart I'm viewing.

C. Select the funnel stage I want to analyze. Note that your conversion rate is always the percentage of accounts or people that started in the stage you select and then subsequently moved to the next stage in your funnel.

D. Select your date aggregation. I recommend months because it helps me spot quarterly trends, like does pipeline conversion go down in month three with my full cycle sellers?

F. The chart will automatically compare this year to the prior period, which is a great way to understand whether you're on trend or seeing an exception.


The cohort view lets you look at the overall conversion rate for the selected period and allows you to break down the data into smaller increments to see how the conversion rate trends over time. From the cohort view, I've called out the recommended selections for this analysis in the screenshot below:

Cohort dashboard for conversion analysis
  1. Select the date range. We recommend at least 5 quarters worth of data to determine whether or not you're experiencing some seasonality in your selling cycle.
  2. Select the metric to display in the middle table (above "5" with the green bars) and select Apply.
  3. Select the stage to cohort by and then click Apply.
This selection does impact how conversion rates are calculated and will differ from your Cohort Analysis and Trend Analysis because the Cohort Analysis chart cohort is always the number of people or accounts that started in your first stage in the given time period in the central chart (above "5" with the green bars). In Trend Analysis it's the stage start date, and in the Data explore you can choose whether you want to cohort by the stage or journey start.
  1. Select the date aggregation to display conversion rates in the central chart.
  2. Once the data selections have run (remember to click Apply where applicable) chart #5 shows the total conversion rate for the period.

The central table of the Cohort Analysis dashboard is where I can begin to spot some interesting trends and begin my research:

cohort report conversion analysis

Can I skip stages and calculate conversion rates between early and late stages?

At this time, conversion rates strictly are defined as the percent of accounts or people that were in the listed stage in the given period that subsequently moved to the next stage (at any point in time).

We do not have an out-of-the box way to skip stages, but please contact customer success in your dedicated Slack channel or to get a set of options for how to tackle this request.

How did we do?

How do I know the last event that happened before a journey stage change?

Funnel Person Status Exits