Consider MQL and SQL. You may know that the “L” in these terms stands for “Leads.” If you’re in sales or marketing, you may even be tasked with increasing MQLs or SQLs.
However, that is a basic understanding. Digging in a little deeper about the similarities, differences, and uses of these two terms can help you to be even more effective. Let’s learn more about both.
Defining Marketing Qualified Leads (MQLs)
The acronym MQL stands for “Marketing Qualified Lead.”
In the shortest definition we could find, courtesy of Hubspot, an MQL is a person that is more likely to become a customer when compared to a typical person.
Think of it this way: Many people may connect with your company. They may visit your website, attend your webinars, or chat with you at a trade show.
For some of these people, the goods and services you offer are exactly what they’re looking for. But for others, your product or service is not a good fit. They may never be in the position to buy anything from you at all.
The people in that first group — those who are interested and have the potential to buy your product — are your MQLs.
Separating MQLs from unqualified leads typically involves using a lead-scoring program. You’ll assign a certain set of points to actions people might take, such as:
- Reading an email message you sent.
- Chatting with you on social media.
- Downloading an ebook.
- Filling out an online form.
Once people have amassed enough points, due to all of the actions they’ve taken over time, they can be considered MQLs.
They’ve shown enough interest that it seems likely they are ready to deepen the conversation with someone — typically in sales — within your company.
Defining Sales Qualified Leads (SQLs)
The acronym SQL stands for “Sales Qualified Lead.”
This person has not only shown a deep interest in your products and services, but they have also shown some sort of intent to purchase. They not only like what you offer, but they actually need to buy what you sell. They also may need to make that purchase in the near future.
While defining an MQL can be done through automated software that assigns scores, defining an SQL is a little trickier. Typically, this is something that involves a conversation between someone in sales and the potential lead.
- May have specific questions about how your product works or how much it costs.
- May not understand how your product fits into the other products they’re using.
- May not be entirely sure the solution is right for them.
- May not be able to find the answers they need in the marketing materials they’ve seen so far.
People like this need to have a discussion with sales.
At the end of that discussion, if the salesperson senses a real opportunity, this person moves into the SQL category.
Why Does Knowing the Difference Between MQLs and SQLs Matter?
You may be wondering why it’s so crucial to understand whether someone is an MQL or an SQL. After all, a lead is a lead, right?
Understanding where your leads fall into these two categories can help you understand who should be in charge of that next conversation. This could mean the difference between making or losing a sale.
For example, we’ve long been told that people move through a traditional sales funnel in which they become aware of a product, consider options, make a decision, and then become an evangelist for the brand.
While this simplified form of a sale might still make sense in some industries, others consider their sales moving through more of a “tornado”.
They may use social media posts in the awareness phase, for example, and then leap back to social media to evaluate solutions and understand usage. They may swing far away from the product before purchase, rolling out to e-commerce before finally deciding to look at a product catalog.
Consumers are doing a lot of the heavy lifting here, and they’re relying on marketing resources to guide the conversation.
Pushing a savvy consumer to sales at the wrong time could cause a sense of pressure, and that could derail the sale. These people are doing their own homework. They’re not ready to talk yet.
Similarly, connecting a consumer with sales too early means sales must inform the consumer about the product’s ins and outs — and that’s a task best left to marketing.
On the flip side, sending a lead to sales too late might lead to missed opportunities. By the time these people get to the sales team, they may have made a decision and chosen a competitor.
When you have a firm understanding of the typical steps a consumer takes in order to become marketing qualified, and when you know what sorts of behaviors seem to suggest that a purchase is right around the corner, you’ll be well positioned to guide and shape these crucial conversations.
The Transition from MQL to SQL
By now, it’s probably clear to you that an SQL begins life in the company as an MQL. But this move from one state to the other isn’t spontaneous and organic. It requires an ongoing nurturing and communication process. It’s here that many opportunities are lost.
A handoff meeting between marketing and sales can be vital.
The marketing team can offer up a list of all of the resources the person has consumed over a period of time, typically pulled from
For example, if the prospect has been almost exclusively researching one specific type of product, the salesperson knows the product that should open up a conversation.
Similarly, the salesperson can walk in the customer’s footsteps and read back through all of those resources, looking for knowledge gaps that the consumer might have. Those are ideal conversation starters that can pull the sale forward.
What happens if the sales call didn’t go as planned? This could be a sign that the MQL isn’t so “qualified” after all, but all hope isn’t lost.
When marketing teams are aware of this issue, they can add the person back into the content marketing program.
Maybe a series of follow up email messages about key features, or an invitation to a webinar, could help encourage a deeper level of comfort with the product. In a few weeks or months, that person really could be marketing qualified, and the next sales call could be a touch smoother.
Putting Theory into Action
While defining an MQL and an SQL is vital — it’s also personal. That means there’s no handy template you can download in order to sort your leads. Instead, you’ll need to have some in-depth conversations
- Customer personas.
- Typical time to close projects.
- Marketing resources.
- Customer/prospect lists.
- Lead scoring method.
You’ll need to think about how each persona interacts with your company during each buying phase. You’ll define what steps are meaningful and signal a deeper commitment.
You’ll also identify the assets you’re missing that could compel action. Those are the decisions that will help set up your lead scoring method. You’ll use them to understand how an MQL is passed to sales — and what comes next.
When you have a theory in place, sales and marketing will need to keep that conversation going. It’s vital for marketing to know more about the leads that sales finds easiest to convert.
How long have these leads been in the pipeline? What assets did they touch? What sorts of companies are they from? What are their titles?
Sales teams may encourage their marketing colleagues to lock MQL rules down tight. That way, the leads they’re given almost always convert into
Unfortunately, a system that’s calibrated too carefully can lead to very empty, loose sales pipelines. And that can leave sales teams with little — or nothing — to do all day.
Meeting regularly to discuss opportunities won, opportunities lost and lessons learned can help the entire group to come up with a plan for the future.
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Identifying MQLS and SQLs starts with capturing the right data. We can help you grab that data.
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