All companies interested in selling more should have a conversion funnel and qualification criteria by which potential customers can be assessed.
How do you separate visitors reading your blog from email subscribers, marketing qualified leads (MQLs), and sales qualified leads (SQLs)? At what point should your sales reps step in to assist the MQL to SQL process?
Timing the conversion funnel progress between stages correctly is critical to getting as much of your audience from the top of the funnel (TOFU) to become actual customers. Approach them too early, and you’ll push them away. React too late, and they might leave for another company.
Let’s see how an effective transition in the MQL to SQL process works, starting with what happens before a visitor becomes an MQL.
What Are Marketing Qualified Leads?
Marketing qualified leads (MQLs) are generally defined as leads who have expressed significant interest in your offering but aren’t ready to buy yet. They have a problem and are aware that your brand could solve it, but either need more time or more information to commit.
The exact criteria for MQLs differ between companies, but some frequent MQL indicators are:
- Watching product demos on your website
- Downloading free in-depth content (e.g. white paper)
- Leaving items in the shopping cart to calculate shipping costs
- Messaging your chatbot
- Participating in free coupon giveaways (e.g. by signing up for a newsletter)
- Answering quiz questions to get a product recommendation
In general, MQLs take more actions and are more engaged with your marketing than occasional visitors or passive content consumers (e.g. blog readers or newsletter subscribers). But how exactly do they differ from SQLs?
What’s the Difference Between MQLs and SQLs?
While MQLs are interested in your offering and consume product-related content, they aren’t ready to buy yet. SQLs, on the other hand, are ready to buy and want to see information related to their specific use cases.
For example, MQLs might realize they need a solution for qualifying B2B leads. At the same time, SQLs are comparing a shortlist of buyer intent platforms.
In lifecycle marketing, MQLs are somewhere between awareness and consideration stages, whereas SQLs are already between consideration and making a decision.
So who decides that an MQL should become a SQL?
How MQLs Turn Into SQLs for Most Businesses and Products
There are goals and objectives for most sales and marketing teams that determine which actions would transform MQLs to SQLs. Requesting live demos or sales calls definitely fall into that category, for example.
Other qualifying actions might depend on multiple factors. If there are not enough SQLs for your sales team to work with at the moment, they might decide to contact more MQLs earlier in the funnel. If sales reps are too busy, they might delay contacting recently converted SQLs to tackle the backlog first.
Various lead scoring systems could also automate the MQL to SQL process by assigning quantifiable values and presenting SQLs to the sales team once they pass a certain threshold. Such lead scoring solutions might work off either first-party or third-party data.
For manual lead scoring, customer segmentation becomes imperative and involve any of the following:
- Demographic. Job title, income, industry, country.
- Firmographic. Company revenue, number of employees, growth trajectory.
- Behavioral. Downloading reports, spending large amounts of time reading website content, engaging with customer support.
- Technographic. Using technologies that either integrate or replace your current solution.
Even though experienced sales reps can identify qualified leads to work with, high-quality lead scoring software can do so much more efficiently.
A 5-Step MQL Process From Visitors to Buyers
Your website visitors don’t just become MQLs and then SQLs in a matter of minutes. For some potential customers the process might take weeks.
Most companies identify five steps that visitors go through to turn into buyers.
1. Visitors Become Contacts
The amount of visitors on your website doesn’t tell you anything about their engagement. A million bot hits might spike your analytics but have no effect on your sales. Visitors might also end up on your website by accident or quickly become disinterested.
However, when visitors volunteer some information about themselves they become contacts. Now you have their permission to contact them and develop the relationship further.
The most frequent information visitors give businesses is their email address, phone number, or social media usernames (by becoming followers).
2. Contacts Become MQLs
In terms of engagement, contacts stay at the top of the funnel. Most might consume the marketing content provided to them but never take any actions that would lead to a sale.
It’s important to try to assess contacts based on your ideal customer profile (ICP) criteria. That way, they can become marketing qualified or even sales qualified much faster.
You can also assess whether contacts are moving closer to the middle of the funnel (MOFU). For example, they might be trying to find out whether your product fits their specific use cases.
3. MQLs Are Nurtured With High-Quality Content
Contacts turn into MQLs when they realize that their problem can be solved by your product or service. There might be significant barriers — such as cost, training, or technological compatibility — but the process is moving along the conversion funnel.
Marketing qualified leads are interested in studying your offering more closely. They want comparison tables, testimonials, FAQs for specific questions, pricing structures, webinars, etc. In other words, anything that helps them overcome friction.
4. MQLs Turn Into SQLs When They Are Ready to Buy
Different sales teams might define sales qualified leads differently. Overall, an SQL is a lead who is ready to buy but is not yet certain of all the details. They move from the middle to the bottom of the funnel (BOFU).
Once an MQL turns into an SQL, they should be handled by your sales team for sales conversion.
5. SQLs Are Handed Off to Sales Teams
When your sales team contacts new SQLs, they should resolve any doubts and answer any questions that potential customers might have regarding how your product would help them achieve their goals. It’s also a great time to discuss price quotes and terms of sale.
Contacting SQLs at the right time is key to the success of your sales strategy. In the era of artificial intelligence, trying to guess the state of your SQLs manually seems very inefficient. Is there a better solution on the market today?
How to Convert MQLs to SQLs Automatically
As mentioned above, automatic lead-scoring tools might rely on first- or third-party data to classify certain MQLs and SQLs. But most of them stop short of integrating different types of data together and leveraging machine learning to better predict the ideal time to contact new SQLs.
Lift AI is different. This buyer intent solution is powered by a machine-learning model trained on billions of data points and over 14 million live sales conversations. The model then integrates your website’s first-party data to make accurate real-time predictions about which visitors are most likely to turn into buyers (around 9% of the overall traffic).
The solution even works for visitors who are completely anonymous (can be up to 98% of average website traffic) and not recorded in your CRM. When a high-value visitor lands on your website, Lift AI connects them directly to your sales reps via online chat (works with any chat platform you already use). Lower-scoring visitors can be greeted with a nurturing bot or a self-help guide to avoid overwhelming your BDRs.
You can start seeing the results of Lift AI working almost immediately. In 90 days, Lift AI customers have reported increasing their conversions through chat by two to 10 times. PointClickCare improved conversions by 400%. Formstack grew its pipeline by 88%.
Leave worrying about the exact MQL to SQL process to other companies and enjoy a steady flow of highly qualified leads without any manual filtering. As a result, you can direct more resources to the bottom of the funnel, where they really matter.