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The Difference Between MQL and SQL and Why it Matters
The Difference Between MQL And SQL And Why It Matters

The Difference Between MQL and SQL and Why Does it Matter?

As a marketer, there are plenty of terms you will hear bandied about, some of which are really important to the marketing process, others not, so much. However, there are two terms that you will hear constantly from the lead generation point of view, and these are MQL and SQL.

MQL = Marketing Qualified Leads
SQL = Sales Qualified Leads

You will come across these terms while using marketing automation software and elsewhere and they have a huge impact on your marketing strategy. In fact, the success or failure of your marketing strategy can be defined by the number of MQLs you are able to attract, but if the company really wants to drill down on the leads, it might judge the performance of your marketing strategy based on the number of SQLs you could muster.

So, let’s take a closer look at both.

The War Between Marketing Sales – MQL vs SQL

Imagine a scenario wherein your marketing team has put in loads of effort and resources in attracting leads to your website, and it then passes all those leads to the sales team.

You pat yourself on the back for a job well done. Right! Wrong. Because the sales teams come right back at you and say that a majority of your leads were useless. What you shared were unqualified leads, and not ones that had any real sales potential.

You are angry. You tell the sales team, “Hey! You probably did not make the effort to convert all the excellent leads we sent your way. Your fault. Don’t blame us.”

This is a scenario that happens across more organizations than you think.

So, who is at fault here? No one? Everyone?

Without resorting to the blame game, Let’s try and find an answer as to why this happens. The reason is an inability to understand lead qualification. So, don’t approach your marketing strategy in a half-baked manner.

It is imperative you understand the difference between MQL and SQL to ensure you are able to effectively qualify leads.

What is MQL?

Yes, we have already said that MQL is Marketing Qualified Lead. But, it’s important to get a drill down understanding of what this qualification is all about.

So, what is MQL? In detail?

MQLs are people who are more than likely to become your customers and this can be gauged from their repeat interest in your business’s content assets such as your website.

From an audience that consists of potential customers, MQLs show more potential to become your customers. These leads aren’t ready to buy, but are ripe for nurturing. As a marketer, you need to keep engaging with them via personalized messaging to move them through the sales funnel.

You can identify MQLs with lead scoring based on pre-identified behavioral pattern, such as repeated visits your website, content asset downloads such as case studies, whitepapers and eBooks. You know you have an MQL on your hands when they start to actively consider your product. 

From this point onwards, your nurturing should convert the MQL into an SQL.

What is an SQL?

SQLs or a Sales Qualified Leads are personas that are much further into the sales funnel and are ready to buy the product/service.

This essentially means they are ready to hear a sales pitch. After doing a ton of research and through the course of your lead nurturing process, SQLs realize that your product is the answer to their problems.

The lead at this stage is no longer owned by the marketing team or is their responsibility. The lead is now the sales team’s responsibility. Sink or swim.

There is an in-between stage here, where the lead is handed over. This is called the Sales Accepted Lead (SAL). This is when the marketing team evaluates the lead on various parameters they have worked out with the sales team, and passes on the MQLs to the sales team.

SAL is like the bridge between MQLs and SQLs and it is imperative that both marketing and sales teams sit together and hammer out the SQL definition, so that there is no MQL SQL debate. 

The Buyer Journey and Qualified Leads

Don’t see MQL vs SQL as an us versus them kind of battle. If you take a look at the buyer journey, as represented by the figure below, you will get a fair idea of both types of leads:

MQLs are at the consideration stage of the buyer journey wherein, they are downloading your business’ eBooks, product/service cases studies, guides and more to get a better understanding of the solution they are looking for. They are in the research stage and a primary source of their research are your content assets.

SQLs have moved to the decision stage of the buyer journey wherein they are filling up the product demo form, downloaded the product comparison sheet and have extensively been through product testimonials. They want to make a decision. This when the sales team should come in and strike when the iron is hot.

 

The Importance of Understanding the Difference

Think of your marketing strategy as the means for MQL marketing. But, the real and tangible determinant of the success of your marketing strategy is the number of SQLs that come out of your MQLs. So, it’s important that you work with the sales team to come up with a list of qualifying ‘sales lead’ parameters and try to mold your marketing strategy keeping those parameters in mind.

Also, it is imperative to understand that both are important in the scheme of things and you need to keep refining the lead parameters till you are absolutely bang on. It is also important that you have a seamless and comprehensive lead scoring tool in place that will help you qualify these leads better.

Lead generation should result in better MQLs, which should result in better SQLs, which ultimately should result in increased sales. This is the end goal.

Conclusion

Whether it’s MQLs or SQLs, both are important for the success of your marketing campaign. Knowing what both are, will help you configure and deploy a strategy that delivers high ROI. This ROI can be measured in the MQLs, SQLs and the final sales figures.

 

Anjali Gupta
Anjali Gupta

Marketing Manager

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