As a key stage in the formal sales process, lead qualification helps your business identify marketing-ready leads (MQL) and sales-ready leads (SQL) through the evaluation of open leads generated through various marketing campaigns and channels. The SQLs have already entered the sales funnel. Hence, your sales team can close sales deals by connecting and communicating with them.
However, the MQLs have only shown interest in the product or service offered by your business. As they have not entered into the sales funnel, your marketing team needs to nurture and influence MQL to convert them into SQL. As a commonly used key performance indicator (KPI), MQL to SQL conversion rate or lead to opportunity conversion rate helps you understand the percentage of marketing-ready leads being converted into sales-ready leads.
According to Gartner.com,
“Marketing qualified lead (MQL) to sales qualified lead (SQL): the rate at which sales development representatives turn raw or scored leads into qualified leads based on the organization’s qualification criteria.”
You can use MQL to SQL conversion rate as an important metric to assess the quality of leads generated by various marketing campaigns. Also, you can close more sales deals only by increasing the MQL to SQL conversion ratio consistently. That is why; your lead generation and qualification strategies must focus on calculating, evaluating, and increasing the MQL to SQL conversion rate.
Entrepreneurs, marketers, and decision-makers calculate the conversion rate in a variety of ways. Most decision-makers prefer calculating the metric using a simple and straightforward formula –
If the total number of MQL generated in a month is 1000 and the total number of leads ready to make a purchase is 330, the MQL to SQL conversion rate for the month will be 33% (i.e., 330/1000).
You can make informed decisions only by calculating and evaluating the conversion rate accurately. You can easily evaluate the metric by visualizing it by making a line graph or summary chart. The visualization will help you compare MQL to SQL conversion ratios for various months.
But you must remember that the MQL to SQL conversion ratio varies across industries and lead generation channels. For instance, the rate is 31.3% for leads generated through websites and 24.7% for leads generated through customer referrals or employee referrals.
The rate decreases to 4.2% for leads generated through events and 0.9% for leads generated through email campaigns. Likewise, the MQL to SQL conversion rate is higher for certain industries than others. Most decision-makers accept 13% as the MQL to SQL conversion rate benchmark.
You must keep in mind your industry and the lead generation channel to evaluate the metric accurately. Also, you can identify trends and gain actionable insights only by comparing the conversion rate for the current month with the conversion ratios of previous months.
No business can increase the close rate without monitoring and increasing the MQL to SQL conversion rate consistently. In addition to calculating, evaluating, and monitoring the key metric, you must implement a strategy to increase the conversion rate. The strategy will help you increase the MQL to SQL conversion rate by adopting a slew of best practices and guidelines.
MQL to SQL transition and conversion are collaborative processes. The lead will interact with the sales team while making a transition from the marketing team. But the marketers nurture leads by sending broad and generic messages, while the sales team specifically drives lead conversion by sending focused and specific messaging. Your sales team can convert MQL into customers efficiently only when the messaging remains consistent throughout the process.
A significant percentage of leads engage with marketing messages personalized according to their interests. Your marketing team can nurture MQL only by answering their immediate questions and personalizing every follow-up message. They can further accelerate the transition by connecting MQL to the right sales development representative. The sales representative will accelerate the conversion process by making personalized connections and answering immediate questions proactively.
In addition to sending personalized follow-up messages, your strategy must nurture MQL with a sense of urgency. Your strategy must set timeframes to ensure that a relevant message is delivered to each marketing-ready lead in a personalized and timely way. Many organizations these days invest in marketing automation software to send personalized follow-up messages to the lead on time. Also, they track why the messages are not sent on time by setting up automated notifications.
You can make your brand stand out during the MQL to SQL conversion process by focusing on market validation. Your team can help leads conduct market validation by providing them with success stories, case studies, and similar resources. You must include success stories in the marketing campaigns as well as make sales development representatives use the success stories as a powerful market validation tool.
You can easily increase and boost the MQL to SQL conversion rate by using the right metric or framework for scoring leads. There are always chances that you have to change the lead scoring metrics or extend the sales qualification frameworks to improve the quality of MQL. Also, the additional metrics will help you collect relevant information that will help your team convert MQL into SQL.
Marketers and sales development representatives overcome several barriers while converting MQL into SQL. Your strategy must focus on eliminating these barriers by receiving feedback and suggestions from both teams regularly. At the same time, you must use the barriers as criteria to refine your offerings and messaging according to changing customer needs and emerging industry trends.
You can use MQL to SQL conversion rate as a key metric to evaluate the lead quality and boost lead nurturing activities. But your business can close more sales deals only by calculating and evaluating the lead-to-opportunity conversion ratio accurately and increasing the rate consistently.
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