What is MQL?

The acronym MQL stands for "Marketing Qualified Lead"

In the shortest definition we could find, courtesy of Hubspot, an MQL is a person who 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 products and services you offer are exactly what they're looking for. But for others, your product or service may not be a good fit. They may never be in the position to buy anything from you at all.

Marketers consider the people in that first group — those who are interested and have the potential to buy your product — as MQLs.

Separating MQLs from unqualified leads typically involves using a lead-scoring program. LeadBoxer assigns a score based on lead interactions and behavior with your business, between 1- 100.

This score can be efficient for ranking a lead's sales readiness in your pipeline.

What is SQL?

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 intent to purchase. They both like what you offer and have a need for what you sell. They also may need to make that purchase soon.

You can use automated software to define an MQL by assigning scores. However, defining an SQL is a bit more complicated. To move leads to sales, this involves a conversation between someone in sales and the potential lead.

An SQL is someone in the marketing funnel:-

• Who may has some specific questions about how your product works or how much it costs.

• Who may not understand how your product fits into their other products.

• Who may not be convinced the solution is right for them.

• Who may be unable to find the answers they need in the marketing materials they've seen.

At the end of that discussion, if the marketeer senses a real opportunity, she pass leads to sales, hence moving MQL to an SQL.

MQL vs SQL: What's The Difference

Distinguishing between MQLs and SQLs is essential. Doing so allows sales team to spend time on qualified leads. This means more efficient sales processes and better conversion rates.

It also helps the marketing team see which channels and strategies bring in more qualified leads for their goals. Hence they become more efficient in nurturing every lead.

Understanding the difference between MQL and SQL helps a business improve its marketing and sales efforts.

1) Decision-Making Stage

As you should know, there are various stages of the funnel that leads goes through before becoming an MQL and later an SQL.

MQLs are typically at an earlier stage of the decision-making process. They are aware of their problem and know there are solutions out there in the market to help them.

MQLs are in a sales funnel's 'awareness' or 'consideration' stage. They are interested in your company's products or services but not ready to buy. They have interacted with your marketing content. This includes downloading an e-book, signing up for a webinar, or subscribing to a newsletter.

However, they have not yet clearly intended to purchase or enter a sales conversation. Most of your MQLs are open to options and might not be interested in a purchase right away. Basically they are in a lead nurturing phase.

By contrast, SQLs are in the bottom stage of the sales funnel, they are in the 'Decision Making' stage. Although they may not have engaged with marketing content other actions may qualify them. Examples are requesting a product demonstration, filling out a contact form with specific inquiries, or engaging directly with sales material.

Their decision-making is more focused on selecting a vendor or product, comparing different offerings, and making a final purchasing decision.

2) Top of Funnel vs Bottom of Funnel

Another great way to differentiate MQL vs SQL is the type of marketing content they interact with.

MQLs focus on finding information and learning. They want to understand their problems better and look for possible solutions. They interact with top of the marketing funnel lead magnets and content like:

• Reading your blog post on 'Best X Tools for lead generation'

• Signing up for your lead magnet, which said 'Generate Leads on Automation'

• Signing up for your newsletter

• Following you on social media

On the other side, SQLs are more focused on consuming content that targets the bottom-of-the-funnel audience. The content can be relevant to selecting a vendor or product, comparing different offerings, and making a final purchasing decision. For example:

• Reading your blog posts on 'Your Tool vs Competitor Tool' or 'X Alternatives For Competitor 1'

• Requesting for a demo call on your website

• Enquiring for your product features on social media (or) through contact form

Engaging and interacting with sales materials, which are more precise and designed for a bottom-of-funnel audience, indicates and differentiates the lead as an SQL.

3) BANT Qualified

BANT is a system (or) framework for Budget, Authority, Need, and Timeline. It's a B2B framework used by sales reps to qualify leads and prospects during their journey. BANT can be applied while comparing MQLs vs SQLs.

It's another great way to distinguish between lead as an MQL (or) SQL

If a lead is BANT qualified, it's an SQL rather than an MQL.

In the following, let's see how the BANT looks different for MQLs and SQLs.

For MQL's:

• Budget:- At the MQL stage, the potential customer may not have a defined budget yet. Maybe they are still exploring solutions and may not know how much they should spend on their answer.

• Authority:- If a mid-size business's junior or senior executive employee interacts with your business, they might not have the authority to make a final purchasing decision for their organization.

• Need:- The need for leads to purchase your product depends on their pain points and how your product (or) service can help them solve them. Also, it is majorly important for your marketing strategy to define their pain points and educate them. For an MQL, some might not be aware of these pain points; hence, there is a long way to go to educate them.

• Timeline:- MQLs typically do not have a set timeline for making a purchase and are not under pressure to make an immediate decision.

For SQL's:

• Budget:- SQLs are expected to have a clearer picture of their budget or at least have a range in mind. Most importantly, they can afford your product or service. Sales teams have to negotiate with them on pricing.

• Authority: SQLs are often the key people in a company. They are responsible for making final purchasing decisions. Hence, they have the authority to buy from you.

• Need:- SQL's know their problems and what are the existing solutions for their issues in the market. Their pain points are clear. Often, it comes down to the specific features and benefits your product offers. These features help them feel the need to choose you over your competitors.

• Timeline:- SQLs have a defined timeline to make the purchase. By offering them discounts and any other benefits with their purchase, they are more likely to buy immediately.

Transitioning a Lead from MQL to SQL

Transitioning an MQL to SQL in your pipeline isn't something that will happen on your own. Your marketing and sales teams must communicate and coordinate to make this happen.

If you're using software like LeadBoxer to track leads, it becomes easier to note down the MQLs with a higher probability of becoming a sales lead through lead scoring.

However, lead scoring is a critical process most businesses use while transitioning a lead from MQL to SQL.

Now, this involves:

• Setting Up a Scoring System: As you identify the lead actions and lead behavior, you assign points/scores to each interaction. For example, downloading an e-book might score lower than requesting a product demo.

• Demographic Information: As we discussed earlier, not every lead has the authority to purchase even though they match your ideal customer profile. Factors like job title, industry, company size, and location can significantly determine the lead's potential to buy.

• Engagement Scoring: Track how leads interact with your emails, social media, and blog posts. Repetitive and frequent interactions tell you that leads in your system are MQLs, and some might be ready to be SQL.

• Lead Score Thresholds: Establishing a threshold score is essential to help sales teams understand when a lead is ready to move to SQL. You should base this threshold on previous data from your business and marketing content.

• Regular Review: Sometimes, SQLs who get on a call with you are not ready to purchase. Hence, do not fill your pipelines with leads with improper attribution. It's essential to review and adjust your scoring criteria continuously. The best way to make it happen is to arrange regular meetings with both sales and marketing teams to help them understand better lead qualifications to help your business grow.

How LeadBoxer can help you transition MQL to SQL

• One-time visitors to your website are most likely not a lead for your product (or) service. Those returning visitors who interact with your content are the ones who can termed as leads. Using LeadBoxer's lead identification feature, you can specify what is a lead for you, and then identify visitors who meet your criteria.

• As these leads interact increasingly with your business, they can later be qualified as an MQL or SQL. Hence, using a leads scoring system and enriching those leads are great ways to qualify and differentiate leads.

• For example, leads that read your blogs are called MQL. Leads that request demos are called SQL.

• Both MQLs and SQLs need to be in a lead management cycle. Using workflow automation, you retarget MQL leads with your marketing (It can be through emails or retargeted ads). By contrast, SQLs are given to the sales team to contact. Integrating your lead management tool with your existing CRM makes it more accessible.

• As you retarget MQLs, potential buyers in your MQL group will engage more with your business. They will read your emails and ask questions to your marketing teams.

• Once these MQLs warm up, lead scoring suggests they are ready to move to SQL. Then, you move those leads and ask your sales teams to contact them.

• Remember, not all SQLs will convert. Move the ones who didn't convert back to MQLs so that the marketing team can nurture them with more marketing material.

Conclusion

We knew from the start that the distinction between Marketing Qualified Leads (MQLs) and Sales Qualified Leads (SQLs) is crucial for the efficiency of your sales funnel and the effectiveness of your marketing strategies.

Differentiation MQL vs SQL doesn't mean you need to neglect one set of leads, both are important for a b2b lead generation. Thus, both marketing and sales teams need to identify these leads and not get stuck up with the thought that 'I am not gonna handle their lead'

Effective communication and coordination are essential between the sales and marketing teams to identify, nurture, and pitch their leads. Here, tools LeadBoxer are going to help them successfully.