Both marketing and sales should always have the same end goal. However, MQL vs. SQL is a typical point of contention between them.
While marketing departments strive to create as many leads as possible, they also want to assist the company make as much money as feasible. Increasing the number of sales-qualified leads will aid in this endeavor. To maximize income, marketing and sales teams must collaborate closely to define what constitutes an MQL and a SQL and agree on a hand-off strategy that will push as many leads through the sales funnel as possible.
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Is there a distinction between MQL and SQL?
Yes, and no. The specific definitions of MQL and SQL differ depending on a company’s unique customer lifecycle and the marketing-sales agreement. There are, however, general definitions for both to assist you to comprehend the differences, the similarities, and where they count the most when it comes to your sales and marketing lead generation campaigns.
What is an MQL (marketing qualified lead)?
An MQL is a lead that has demonstrated some level of interest that your marketing team believes is more likely to become a sale than other leads but isn’t yet ready to buy. This is usually discovered via lead intelligence and intent data, which is frequently aided by analytics such as their search intent data, the pages the visitor, a click-through on the newsletter that was emailed to them, etc.
Before being approached by sales, these leads require extra marketing support.
What is an SQL (sales qualified lead)?
An SQL is a prospective client who has passed through the sales pipeline, has been thoroughly analyzed by both marketing and sales, and has been considered ready for the next step in the sales process: converting the lead to a customer.
These leads have shown an interest in your services or products and have fit your companies ICP (Ideal Customer Profile), indicating that they are a good fit for the product or service.
Despite the fact that the primary distinction between MQL and SQL is where they are in the sales pipeline, the lines between the two can still become confused, and there are often differing viewpoints on where leads belong.
MQL vs. SQL / Marketing vs. Sales
An SQL is a decision maker engaged with your company and may become a customer if nurtured properly. In contrast, an MQL is a lead who has engaged with your company and could later potentially become a customer if nurtured appropriately. Only when an MQL is ready to speak with the sales team, they become an SQL.
Notably, a great example in aiding this transition from MQL to SQL could be utilizing a CTA or call to action. If the MQL has been nurtured well enough to garner interest in responding to that CTA, they become an SQL by displaying their willingness to invest their time and effort in actively finding out more. There is now a legitimate need, and they could be ready to buy or be sold to.
However, because marketing and sales teams approach the topic differently, it’s vital that they collaborate to determine where each lead is in the buyer’s journey. According to LinkedIn 90% of MQLs are never changed to SQLs because they were wrongly identified as MQLs too early in the buyer’s journey.
Gathering Lead Intelligence
How visitors interact with your organization online or behave on your website is a big indicator of whether they should be classified as an MQL or SQL. The following are some general behavioral characteristics to keep an eye on and consider:
Inbound leads / form fills
One of the easiest ways to tell if a lead is sales-qualified is if they ask to be contacted. MQLs may seek further information, but they rarely ask to be reached in any other way. Many SQLs will request to be contacted and indicate that they are interested in learning more about your product or service.
Similarly, decision-makers do not have time to waste seeking a meeting or taking advantage of a free demo trial. You can use this as an indication that the prospect is now a SQL, and it’s time to let the sales team work their magic.
The majority of a company’s leads are likely to originate from a select few marketing sources as opposed to every possible channel.
If sales intelligence suggests that the majority of your customers come from Linkedin and email marketing campaigns, for example, then the prospects you get from those referring sources are more inclined to be sales-qualified than those you get from Facebook and cold-calling.
This isn’t a suggestion that you should abandon alternative lead generation methods in favor of your most successful. Still, it’s certainly worth understanding the demographic of the customer from within those channels, alongside the nature of the marketing and/or sales approach on each platform.
Unique vs. repeat user
They should be deemed an MQL if this is their first visit to your website. Visitor InSites can identify your anonymous unique website visitors. They may be ready to be categorized as a SQL if they’ve visited your website three or four times to look at relevant product or service pages.
Is there a pattern to the length of time they spend actively browsing? Are they looking at the same pages? These are all important considerations for determining if these visitors have a legitimate interest.
It’s also crucial to recognize the content on the pages they’re looking at. Perhaps they’re actively looking for any deals or promotions, in which case they’re likely to be classified as a SQL unless the marketing department has other contact information with which to send tailored and personalized offers, for example.
Understand your sales cycle and its stages
In addition to the number of times a prospect has converted, the conversion itself influences whether a lead is classified as MQL or SQL. What kind of post-click landing page deal did they take advantage of?
In e-commerce, for example, consumers are browsing the site when a pop-up asks if they want to sign up for a discount code. If they do, it’s fantastic; however, they’ve just engaged for their own advantage at this point, and it’s possible that it’s just in case. They are still an MQL at this point, from which targeted emails and offers can be delivered.
However, the lead continues to browse and comes across an item they like, but the page informs them that quotations are available upon request or that samples can be obtained by calling. Should they reach out, then given their legitimate interaction with the firm, they’re ready to be approached as a SQL if you’ve had that call or they’ve filled the form for a quote, which includes prospective quantity requirements, their job role, the purpose for browsing, and so on.
Of course, not all landing pages fill outs will be converted into SQLs. Before organizing a demo, sales teams should conduct their own research about the person’s job title, decision-making authority, and company. The examples throughout this article clearly demonstrate how different offers necessitate more or less lead input. The fact that the lead cannot engage at a level that fits them will further entice them to the company because they are not hard-sold.
SQLs must be determined using demographics and ideal client profiles (ICP). Demographic data like industry, job title, and company size indicate how eager and invested they are in buying your product or service. When determining if a lead is an MQL or SQL, other details, search intent behaviour, company pain points, and funding rounds may be helpful.
Lead scoring takes both lead behavior and demographics into account, assigning a value or score to each lead based on their information and interactions with your company. This is critical because it prevents your sales team from reaching out to customers before they’re ready to buy, which could jeopardize any credibility you’ve built up to that point.
Many businesses evaluate leads based on the following factors such as demographic and company information. You should also include their online behaviors and an indication of receptiveness.
Are they subscribed to your email list, and if so, how long have they been signed up for? Do they click on any links within those emails, or is there evidence of forwarding to anyone else? Have they searched the keywords related to your company
Have they been referred by a friend, and what did the ‘friend’ purchase?
Do they engage in communication or page activities on social media?
The core of the lead hand-off process is defining MQL vs. SQL. After scoring leads, you’ll be able to tell whether they’re MQLs or SQLs, which ones to nurture further, and which to pass on to the sales team.
Transitioning MQL to SQL
You know which leads fit where now that you’ve built MQL and SQL definitions, but you still need to figure out when and how to transfer qualifying sales leads to the sales team.
First and foremost, both marketing and sales teams must take into account the full client lifecycle.
- You nurture an email marketing list sending out helpful content with calls to action to generate click through’s.
- The prospect opens and click-through many emails and then goes to your website to discover more about your products, services, and prices. Visitor InSites identifies the web visitor by name, company, title, and contact information. The lead is now designated an MQL, and the marketing team will need to nurture it further.
- The marketing team markets to the prospect and retargets them to schedule a demo. The lead is then most likely a SQL at this stage after having scheduled a demo, which asks for more qualifying information (job title, ad spend, software used, etc.).
- The sales team uses the qualifying information to determine if they are a qualified meeting. Creating an SQL
How well sales and marketing teams collaborate and share insights is crucial to a smooth transition from MQL to SQL. Having clear sales and marketing alignment on the information you’ll need to pass along and how you’ll follow up based on the prospect behavior and intelligence gathered.
LinkedIn: An example of MQL vs. SQL
An example of poor MQL vs. SQL judgment is assuming that an accepted invitation to connect means the prospect can be contacted directly with a service offer. In most cases, this will result in no response or, even worse, the connection disconnecting you from their network, thereby burning the bridge.
Connecting or inviting them to a group is a wonderful example of rating prospects. Before going in with ‘the pitch,’ the target as an MQL would require a relationship to be formed (i.e., nurturing). Invite them to a group, check if they accept, and then ask if they would like any further information or have any questions. In this way, an MQL is far more likely to become a SQL.
There is typically an interest in the field in which you specialize, and even if there isn’t, you’re not burning any bridges by simply offering further support if they ever require it. Meanwhile, they can be targeted further while still sitting as an MQL by having your updates visible or receiving notifications that something new has been posted within the group they joined.
Align sales and marketing
Businesses should adopt both an MQL and SQL strategy rather than an MQL versus SQL mindset. Both marketing and sales have equally vital roles to play, and the two sorts of leads should not be contrasted.
Qualification standards must be established and followed, and leads must be transferred from marketing to sales in a timely manner. The stronger the SQLs are, and the more deals you can close, the greater the teamwork between the two teams is.
Create distinct, fast-loading post-click pages for each offer to convert ad clicks into conversions.
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