The Difference Between MQLs and SQLs
This article breaks down the key difference between MQLs and SQLs, and why they are important to measure within advertising platforms.
Marketing Qualified Leads (MQLs) and Sales Qualified Leads (SQLs) are two critical metrics used to measure the effectiveness of a company’s sales and marketing efforts.
For us at Farsiight, these metrics are critical to track and measure as they help us understand the true value our advertising campaigns produce. After analysing these data points, we also make important optimisations, which contribute to improved performance over time.
Although the specific criteria distinguishing MQLs and SQLs may vary slightly between businesses, these metrics generally have typical differences.
What are Marketing Qualified Leads?
MQLs are leads that engaged with a company’s marketing campaigns, such as visiting a website or downloading a whitepaper. These users have shown interest in the company’s products or services and have provided enough information to be considered a marketing qualified lead. However, the sales team has not yet qualified them and therefore are considered a lower value lead when compared with a sales-qualified lead.
What Are Sales Qualified Leads?
An SQL is further down the sales funnel than an MQL. These users have been evaluated by the sales team and deemed a fit with the company’s ideal customer profile.
Companies need to understand the difference between MQLs and SQLs because they require different levels of follow-up and engagement. MQLs may need more nurturing and education before purchasing, while SQLs are more likely to be prepared to purchase soon.
We typically see that most technology, SaaS, or lead-generation-focused companies don’t track and measure MQLs or SQLs within ad platforms. They focus on their website events, such as a free demo, sign-up, or contact form, and this is a big missed opportunity.
Optimising for these website events can be dangerous as they don’t show any level of intent. That’s why we recommend setting up offline conversion tracking, so you can import when a lead becomes an MQL, SQL, or even paying customer. What you’ll likely find is there are keywords, audiences and demographics that generate a high volume of website leads but never end up qualified. With this data, you can optimise your campaigns to filter out these users and improve your customer acquisition cost (CAC).
By understanding the difference between MQLs and SQLs, businesses can better allocate resources, optimise their sales and marketing efforts and drive better efficiency.
If you want help tracking, measuring or calculating your target MQL/SQL, hit us up!
Josh is the co-founder of Farsiight and has spent the past 12 years scaling digital marketing campaigns.
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