MQL vs SQL: Defining the Difference
Every company needs leads. A lead is someone who has expressed an interest in your company’s product or service to some degree.
Before you send these leads to your sales department, you need to identify if they are MQLs or SQLs. That means you are stopping to consider where each potential customer is in his or her journey. If you chase someone that is not yet ready to be approached, you could lose his or her business. Knowing the difference between an MQL and SQL is crucial if you want to grow your business.
What is an MQL?
MQL is an abbreviation of “Marketing-Qualified Lead”. The term refers to somebody more likely to become a customer of your business than other leads.
That person is, therefore, ready to receive marketing. Website visitors will make up the majority of your leads. Visitors’ behaviors and engagement levels are tracked to find out at what stage they are. A visitor may have demonstrated an interest in your website’s content, downloaded content, signed up for a newsletter, or filled out a web form.
Each of these activities is assigned a lead score.
High lead scores can trigger those leads to become MQLs. In short, that means an MQL is more likely to purchase your product or service. However, it is important to know an MQL is a visitor who is not ready to buy your product or service yet.
Although the above types of visitor activity can lead to MQLs, some are weaker than others. For instance, if someone visits your website only once and downloads a free newsletter, the visitor has not necessarily expressed interest in buying.
He or she will probably have only given his or her email address. Stronger leads come from people who submit active interest in a product or service. For example, a visitor could have requested a demo request or a sales form.
What is the best way to define MQL vs SQL?
You must look at specific behaviors to determine what makes an excellent MQL before you pass the lead on to your sales department. If your marketing team passes on lots of leads who have not expressed interest in your product or service, your sales team will struggle with the low-quality of those leads. You must identify the criteria you use to measure MQLs before they are passed on to the sales stage.
What is an SQL?
While an MQL refers to someone who is not yet ready to purchase your product or service, an SQL is a lead that is qualified as a potential customer.
SQL stands for “Sales-Qualified Lead”. Therefore, the SQL is within your company’s buying circle, unlike an MQL, which is not yet at the buying stage. Your business will use a lead scoring process to identify serious buyers. That helps your sales team to determine which actions and qualities qualify a lead to become an SQL.
You can identify SQLs mostly through demographics. Techniques like customer profiling are used to determine whether the lead is ready to be passed on to the sales department. You can decide how serious a lead is about your company and its services by analyzing information like the lead’s industry, company size, and job role. Information like budget and pain points are also relevant to qualify a lead as an SQL.
Defining the Difference Between MQLs and SQLs
In short, an SQL usually indicates a person is immediately interested in your business’s products or services. Sales representatives should contact an SQL within the first 24 hours of being declared as an SQL.
By contrast, MQLs are leads that have expressed general interest in your company’s products or services. That means they may need more information before they can become sales opportunities. It is best to place MQLs in an email nurture program, which uses marketing automation software.
The MQLs are scored based upon elements like clicks, website visits, and email opens. You can then determine if those MQLs can become SQLs.
So, the main difference between MQLs and SQLs has to do with the lead’s readiness to purchase. If you pass MQLs on to your sales representatives before they are ready to become SQLs, you could lose those leads’ business.
It is much better to wait until a lead is hot before your company’s sales team pursues it.
By understanding the difference between MQLs and SQLs, and using the leads’ data in the right way, you can increase your customer base.