What is a conversion rate? A sales / marketing conversion rate is the percent of leads or opportunities that are converted from one stage to another. Simply stated, if we have 10 opportunities in one stage and 8 of them move to the next stage then the conversion rate is 8 out of 10 or 80%. Note that conversion rates are based on the quantity of transactions and not on the value of the transactions. Conversion rates can be calculated for every stage of the demand waterfall but there are a couple of standard conversion rates used by most organizations; the Marketing Qualified Lead (MQL) to Sales Qualified Opportunity (SQO), and the SQO to Closed Won. The criteria used to define MQLs and SQOs can significantly vary from one organization to the next but even with that variation the generally accepted rates I see published as benchmarks are 40% to 60% for MQLs to SQOs and 20% to 25% for SQOs to Closed Won. That said, it’s most relevant to track your own internal conversion rates over time and look for improvements that reflect changes to the health of your pipeline.
Conversion rates are also expressed in terms of a time period. At minimum, the period over which you measure a conversion rate should be at least as long as the average sales cycle. The period can be moving such as “last 90 days” so you can get real time conversion rates but note that the hockey stick effect may skew the results if you’re measuring opportunities that are converted to Closed Won.
All of this sounds pretty simple but here’s where it typically gets confusing based on corrupted data in your CRM system:
- The conversion date is the date an opportunity moves and not the opportunity close date. Be careful to not pull your data set based solely on close date.
- Many CRM systems like Salesforce.com don’t prevent users from skipping stages.
- Many CRM systems like Salesforce.com don’t prevent users from moving opportunity stages backwards.
CRM systems like Salesforce are not configured “out of the box” to collect the necessary conversion data. There are several ways to address this but my preferred method is to create a field for each sales stage that records the date of every stage advancement. Note that I said “advancement” not movement. A common issue related to poor conversion rate data quality is that most systems allow users to move sales stages backwards. Another challenge is that most systems allow sales stages to be skipped. Both skipping sales stages and moving them backwards can be addressed by the creation of custom validation rules in your CRM system.
You may get push-back from a few users complaining the requirement to move opportunities through every stage is a waste of time but that’s like saying the sales process and sales playbook is a waste of time. It makes no sense. You may also have them question why they can’t move sales stages backward. Sales stages represent actions, preferably customer actions, that have either occurred or not. Once an action occurs that bell can’t be un-rung so there is really no reason to move back a stage.
With those validation rules comes good data quality for accurate conversion rates as well as sales cycle times attributable to your organization, a single region or an individual sales rep.
Putting Conversion Rates to Use – The Demand Waterfall
The design of a demand waterfall can be used to help determine the quantity of inputs to the various channels required to create the target amount of closed business. A waterfall can be a single channel design or a more complicated matrix of multiple and intertwined relationships. Here is a visualization of a simple demand waterfall. Demand waterfalls can be significantly more complex as illustrated here by SiriusDecisions.
Once you have accurate conversion rates you can answer the question: how many inbound inquiries do we need to make the target revenue? The math behind the series of calculations is simple but the number of steps can be many, depending on the complexity of your waterfall design. Here are the steps for the simple waterfall illustrated.
- Divide the company revenue or bookings target by the ASP (Average Selling Price) to find the number of closed won transactions required to attain the target.
- Divide the quantity of closed won transactions by the SQO conversion rate % to get the quantity of SALs required.
- Divide the quantity of SALs required by the MQL conversion rate % to get the quantity of MQLs required.
If you perform these calculations and your result is ridiculously unattainable then something has to change. Given your conversion rates are accurately calculated the math doesn’t lie. There is the temptation to rationalize the result as inaccurate and forge ahead without challenging the assumptions that were used. Is the company revenue or bookings target reasonable? Are market factors at work that will materially change the ASP? Are the historic conversion rates appropriate to use in the future? Ignore these questions and you could be setting up the company for failure.