Lead Generation MQL vs SQL

A topic that has been debated many times - what is the difference between an MQL and an SQL?  To answer this question, let us first start by decoding these three-letter acronyms. MQL stands for Marketing Qualified Lead, and SQL stands for Sales Qualified Lead. Next, let’s define them and see if we can highlight some differences. 

In order to generate quality leads for your organization’s sales team, you need to have strong marketing. With this, let us start with defining what is considered an MQL.  A marketing qualified lead is a lead that is more likely to become a customer when compared to other leads based on behaviors before the conversion process. It is key for an organization to define a marketing qualified lead strategy that will accelerate your sales team through delivering higher quality leads. A large number of leads that come into an organization through various marketing efforts may not be ready for a sale or may not even be a good fit for your product or service. The goal of most marketing teams is to deliver as many leads as possible for the sales team. With this in mind it helps to have a strong marketing automation tool such as Pardot, Marketing Cloud, Hubspot or Marketo to help automate the process of managing your MQLs.  Once you determine what an MQL looks like, you can start leveraging the defined analytics to determine your total volume.  Once you have determined the volume of MQLs you can begin to deliver those to your sales team. The key is to deliver your highest rated MQLs first so that your sales team is selling to the most qualified leads.

Now that we have an understanding of what an MQL is, we’ll discuss what is considered an SQL.  A sales-qualified lead is a lead that has been researched and vetted by the marketing team and is ready for the next stage in the sales process. A CRM (customer relationship management) tool, such as Salesforce, is an ideal repository for managing these leads. Leads that are nurtured in a marketing automation platform and then fed into a CRM are likely to provide a better list for your sales team to sell against. This is where a lead scoring model can come in handy. SQLs are measured a bit differently than MQLs. Using a method like BANT (Budget, Authority, Need and Timing) is common in the lead scoring process for an SQL. 

In conclusion, the biggest difference between MQL and SQL is the readiness to buy.  Having a clearly defined marketing automation process of determining which leads are considered an MQL or an SQL will significantly improve your organizations lead conversion rate. It not only improves your company’s lead conversion rate, but also helps your sales team become more productive and efficient.  If you would like more information, please contact us today!