MQL to SQL Conversion Rate is a measure of how successful your efforts are in converting leads into paying customers. It is a ratio of the number of customers who purchased your product or service to the number of leads you generated.
MQL and SQL are important metrics in understanding the impact of how you market your products and services. You can optimize your marketing campaigns to improve conversions by tracking these values.
What is MQL?
MQL stands for marketing qualified lead. The term is often used to indicate a sales prospect that has demonstrated an interest in the product or service being offered by the business.
Typically, MQLs will have already raised their hand and expressed interest by filling out a form on a website and providing more detailed contact information.
What is SQL?
Sales Qualified Leads (SQLs) are MQLs that have been handed off to sales to pursue further. SQLs tend to be more likely to convert because they’re already qualified leads — meaning they’ve met the criteria for you to believe they may be interested in buying your product or service.
When to use MQL to SQL Conversion Rate?
Marketing is a process of continuous experiment and testing. You can use MQL to SQL conversion rate after each marketing campaign as a measure of your campaign’s success.
Let us take an example. Say you have run a marketing campaign intending to generate leads for your product or service X. If out of 100 leads generated, 30 opted in and five people purchased the product giving you an MQL to SQL Conversion Rate ratio of 1:6.
What does this ratio mean?
This means 70% of leads generated were not interested in your product or service X. It also means that out of 100 leads, five people were interested and converted into customers. Now, if you vary the number of leads generated to 500, you can potentially get 25 paying customers, i.e., MQL to SQL Conversion Rate of 1:40.
You can now use this information to plan your next marketing campaign.
The median value for MQL to SQL Conversion Rate is between 1:5 and 1:10. You can use these numbers as benchmarks for yourself, but they might vary depending on the nature of your business or product.
You can also use MQL to SQL conversion rate to measure your team’s performance. You can compare it across teams or individuals to see which member is more successful in generating SQLs – making them more efficient and productive.
Why should you use MQL to SQL Conversion Rate?
MQL to SQL Conversion Rate helps you to understand how many leads are converted into customers. It provides you with an idea to work upon in improving your conversions.
The MQL to SQL number enables you to figure out the percentage of people interested in buying your product or service but could not purchase because there was no simple way for them to make a payment or there were no means of delivery.
This information is handy in identifying the loopholes in your sales process and improving conversions.
How to calculate MQL to SQL conversion rate?
MQL to SQL conversion rate is calculated by dividing the number of sales-qualified leads (SQL) by the number of MQLs.
The number of SQLs / Number of MQLs = MQL to SQL
For example, you generate 100 leads, and out of those, 5 bought your product X. Your MQL to SQL conversion rate would be:
5 / 100 = 0.05 or 5%
You can perform this calculation after each marketing campaign.
Industry average MQL to SQL conversion rates
The average MQL to SQL conversion rates vary by industry. You can compare your numbers with the industry norms and benchmarks. This comparison helps you in identifying areas that need improvement.
The following table shows the MQL to SQL conversion rates for different industries:
Industry Average MQL to SQL Conversion Rates
|Industry||Average MQL to SQL Conversion Rate|
|Oil and gas||32%|
|Higher education and colleges||45%|
|Manufacturing and PCB Design||42%|
What is the ideal value for MQL to SQL Conversion Rate?
The ideal value of MQL to SQL conversion rate depends on many factors. Factors such as the nature of your business, your industry, average customer lifetime value, etc., have a significant impact in deciding an optimal conversion rate for you.
At one end, if MQLs cost more to acquire than the revenue they generate, it does not make sense to generate more MQLs.
On the other end, if your conversion rate is less than 1%, you might be missing out on a large number of potential customers. Your sales process might need revamping, or your product or service might not be impressive enough. In such cases, increasing MQL to SQL Conversion rates by even 1% can significantly increase the number of paying customers.
What could be the reasons for the low MQL to SQL Conversion rate?
There could be many reasons for the low MQL to SQL conversion rate. Here are a few of them:
- Your sales process might need revamping as something is lacking in it. Your team might not know how to close a sale, or you might be missing one crucial step in your sales process that needs immediate attention and improvement.
- You might be targeting wrong leads or generating irrelevant traffic.
- Your product or service might not be up to the mark and needs improvement.
There could also be other reasons for low conversions. Whatever may be the reason, you need to identify it first to implement the necessary changes that would result in a significant increase in conversion rate. The earlier you identify and fix these issues, the better it would be for your business.
What are some common mistakes in MQL to SQL calculation?
Many companies make mistakes while calculating MQL to SQL conversion rate:
- They count multiple responses for one lead. For example, if one lead generates 3 phone calls and each of those leads results in 2 sales, it is counted as 6 sales instead of 3. This not only gives incorrect information but also hides the actual number of sales.
- They count MQLs rather than SQLs. The number of MQLs generated should always be counted instead of counting just MQLs without adding any value to it.
- They assume that all leads are equal in nature and find no reason to record or track specific details about each lead. For example, some leads might require more effort to convert into sales while some others might not. If you do not track and record these details, it would be very difficult for you to analyze the data and improve your conversion rate.
Data collected over a long period of time can be analyzed to reveal trends that could give you valuable insights into your product, business, and marketing. Analyzing the data periodically would allow you to find ways to improve your conversion rate for both SQLs and MQLs.
The more MQLs are converted into SQLs, the higher would be your conversion rate. If you find that there is something lacking in your business or sales process, it is necessary for you to improve it so as to increase MQL to SQL conversion rates. Implementing changes might take some time but will definitely bear results in the long run.
It is also important for you to analyze and collect data over a long period of time in order to find trends and patterns that would give you valuable insights into your product, business, and marketing. Implementing changes on the basis of these insights would result in a significant increase in conversion rates.