Calculating Conversion Rate in Sales

Math is relentless. Whether you are the President of the USA or the Pope, no one has the power to change the reality of the numbers. It doesn't matter whether you agree with the result of an equation or not; it won't change because you want it to be different. The narratives can be changed, but the end result will always remain the same.

In sales, this statement also holds true. However, the data culture in sales departments is relatively recent, which has led most companies today to monitor these metrics incorrectly.

To avoid misreading the data, in this article we show you ways to generate the correct Insights from your team's results (remembering that it is vital to have well-mapped business KPIs to do this work).

How to calculate the sales conversion rate simply and quickly

• MQL - Marketing Qualified Lead
• SQL - Sales Qualified Lead
• Opportunity
• New clients

You can extract multiple insights from analyzing conversion rates between these steps.

We get to know whether the team is wasting leads, which salesperson is producing more, and which stages are bottlenecks in the funnel, among many other pieces of information.

MQL → SQL Conversion

This is the first relevant conversion to analyze within the business process. We know that MQLs can be either meetings scheduled by the Outbound pre-sales team, or hand-raisers from the end of the funnel coming from Marketing (Inbound).

A healthy benchmark for this KPI would be to stay above 40%. In the scenario where it is below this range, we work with some assumptions:

1. MQLs generated by marketing are not very qualified. It is necessary to increase the conversion bar.

2. Outbound's pre-sales team is "pushing" meetings without a good profile;

3. The sales professional is struggling to properly qualify the MQLs.

* Preferably, it is better to pay attention to the first two assumptions as they are at the beginning of the funnel.

1. Solution: On the marketing side, it is interesting to increase conversion attrition by asking more relevant questions on end-of-funnel conversion forms, for example.

At the same time, providing richer content can also help improve lead qualification.

2. Solution: In Outbound pre-sales, an SLA (Service Level Agreement) must be created, where, before scheduling the meeting, it is necessary to confirm several relevant pieces of information about the lead to show that the moment is really for purchase.

3. Solution: For the last premise, the answer is not so simple. There are some interesting actions that can be taken, such as;

• Recording of meetings;
• Monitoring of the meetings.

The first option turns out to be the most practical. The manager has limited time during business hours to track all calls and meetings, and, with the recording option, he can review them anytime and better understand the situation, thinking calmly about the paths to take.

Tools like Zoom and Google Meet have this functionality in their paid plans. For those without a budget at the moment, an interesting and free option is Loom.

SQL Conversion → Opportunity

SQL is one of the most important KPIs for the sales department. It can be generated at two different times depending on the company's business model.

You can:

• Consider it a lead being worked on by sales
• Consider it a lead with a proposal already sent

The first scenario happens in companies that work only with Inbound sales. The second occurs in hybrid models or only in Outbound scenario.

Once an MQL becomes an SQL, the sales team's goal is to convert it into an Opportunity.

This Opportunity lead can be either a forecast lead (in Outbound or hybrid model) or a submitted proposal (in Inbound). If this rate is below 50%, we proceed to analyze some assumptions:

• The definition of "forecast" is very subjective, causing confusion within the team.
• Many proposals are being sent to leads that are not at the time of purchase.
• SQLs generated in Inbound do not fit well.

Once an MQL becomes an SQL, the sales team's goal is to convert it into an Opportunity.

The solution to these problems is easy to understand, but difficult to implement:

First, defining what a forecast is for your company is essential, and it must be based on the criteria your customers use to close the deal. The ideal, then, is to have a formal SLA outlining what an SQL needs to evolve into to become an opportunity/forecast.

If many proposals are being sent to leads outside the purchase window, it is necessary to align the submission criteria with the team.

The same is true for SQLs generated within the Inbound process (when your pre-sales team works on a lead to make the initial qualification). If the pre-sales team is more focused on the volume of meetings scheduled for the salespeople than on their quality, the possibility for salespeople to return the SQL to the pre-sales stage should be open if it does not meet the minimum qualification criteria.

Opportunity → New Customers

This is the last conversion rate within the sales funnel. It represents the forecasts or submitted proposals that became new customers. It can range from 20% to 70%, depending on the quality of the opportunities. Below this range, there is a serious qualification issue.

If multiple leads are forecasted and fewer than 20% are closed, we know the sales team is incorrectly moving leads through the funnel.

To solve this problem, it is necessary to formalize what a forecast is and prevent the team from forwarding proposals to all leads who ask for one (only to those who are more certain of closing).

MQL → New Clients

This conversion rate is very interesting in showing the sales team's work.

A salesperson who works several MQLs and closes very few is doing something wrong. Therefore, an interesting way to evaluate this work is to follow this KPI.

This rate is also excellent for comparing the work of different salespeople. If two have closed the same number of clients, it is interesting to know who has worked more MQLs.

The one with higher conversion is probably making better use of the leads at hand, wasting fewer MQLs.

The interesting conversion rate of this step will be around 4% to 10%. It is very difficult for this KPI to pass this range.

If it is higher, there are 3 scenarios to analyze:

• Your company has an amazing conversion rate and will be a unicorn in no time.
• MQL definition in your business is wrong.
• Data is being tracked incorrectly.

SQL → New Customers

The conversion rate between SQL for New Customers reflects some of the salesperson's productivity relative to the leads they are working on or have submitted a proposal for.

It is normally between 10% and 30%. (Values above this range are unsustainable and difficult to maintain over the long term.)

Below are some possible scenarios for when the conversion rate is below 10%:

• The seller is having difficulty generating urgency and value.
• The product does not have a good market fit.
• The seller is forwarding proposals to leads without a profile or at the wrong time.

It is only possible to know if the salesperson is struggling to generate urgency and value by recording or tracking the meetings. In this way, it becomes easier to train the salesperson to enrich the speech and facilitate the conversion.

The same goes for the salesperson scenario that forwards proposals to poor-quality leads. It is a good practice to determine in advance what profiled leads are, thus preventing proposals from being forwarded outside that target market.

Regarding timing, the salesperson needs to build a strong commitment with the lead. It is normal for the buyer to delay his decision. Because of this, the salesperson must be clear and objective to determine whether the lead is considering buying the solution or is asking for the proposal just to end the meeting.

Knowing how to calculate the sales conversion rate correctly can save your business!

There is no point in evaluating several KPIs within your process and calculating them wrongly.

Structuring a sales funnel with clear KPIs is the ideal scenario to generate constant insights for the management and evolution of the sales process as a whole.

Due to the complexity of collecting this information accurately and consistently, having a tool to do the work is essential.

If you want to know about a business reporting software that does all this work for you, and that can be integrated into your CRM in less than 1 minute (without the help of developers), talk to one of our experts, and we will be happy to assist you!