What happens when you turn suspects into prospects?
There has been an ongoing debate in B2B marketing circles: Is the Marketing Qualified Lead (MQL) an antiquated, vanity metric?
You can file this argument under similarly counterproductive debates, such as: Inbound vs Outbound and Demand Generation vs Account-based Marketing.
While MQLs don’t translate to immediate revenue or even pipeline contribution, the value isn’t equivalent to open rates, page views, and the like. A MQL is the foundation of processes within a marketing funnel — namely, an inflection point of engagement met that drives expectations for sales intervention.
We can all agree that the process almost always improves results. Plus, let’s not forget, every customer starts out as a lead. No matter where the lead was sourced.
So, yes, MQLs matter. A lot. But how do we distinguish good leads from bad leads? How can we pursue the good ones if we don’t even know what we’re looking for?
With over 60% of revenue coming from our inbound lead generation efforts alone, ZoomInfo has spent considerable time in the entire lead-to-revenue management process across all marketing sourced channels.
How do you define a lead?
In its simplest form, a lead is a person or company that has shown interest in what you are selling. And what does “interest” look like?
(Glad you asked!)
Think about it in terms of dating. Maybe someone will like your Instagram photo. Maybe they’ll ask a friend about you. Or maybe they’ll reach out to you directly to ask you out.
All of these are a form of interest. On its own, if someone were to ask you out interest is immediately confirmed. Whereas, other examples are just hints; mind you, though, when combined, these hints could be enough for you to speed things up and ask the person out.
Leads are no different. Interest can be as subtle as browsing your company website, or as overt as requesting a free demo of a product. Again, specific responses automatically qualify a lead; whereas, other actions may not necessarily require sales intervention.
The tricky part about leads and lead generation is that marketers and salespeople don’t necessarily share the same definition. The common argument is that marketers care more about the number of leads generated, whereas salespeople care more about the quality of those leads.
Let’s use shopping as an example. Say you’re in a market for a new car. Using intent data from auto-sites, a local dealership is able to get retargeting ads to receive special rebate offers available only to newsletter subscribers.
You convert on the newsletter, providing contact information, and even click-thru on the automated rebate offer. At this juncture, you may or may not be a Sales Qualified Lead (SQL); but by virtue of signing up for information related to limited discount offers, you are likely a Marketing Qualified Lead (MQL).
So, what qualifies as a good lead?
Lead Scoring: What is it and why is it important?
For optimal sales and marketing alignment, the two must embrace the following tenant: Opportunity lives at the intersection of fit and timing.
What, exactly, are we getting at?
Certain prospects may demonstrate buying behavior but NEVER be a good fit; whereas, other prospects could be ideal buyers that simply are not engaging with your marketing campaigns. Bad leads are pretty easily identifiable: they consist of any contact with a low probability of converting into a sale. This means they might havet:
- Lack a use case for your product
- Unrealistic expectations/budgets.
- An unspecified timeline.
- Unclear understanding of what they need/want.
This is where lead scoring comes in.
Lead scoring is the process of assigning values to each generated lead based on a combination of behavioral (responses to marketing campaigns), demographic and firmographic data. You can score leads based on a breadth of weighted attributes. Assigning these values helps marketing and sales prioritize leads, respond accordingly, and increase the likelihood of those leads becoming actual customers.
Just how important is a sound lead scoring system? At ZoomInfo, we require sales to follow up on all prospects who hit our MQL threshold within 90 seconds of the conversion. We’re able to enforce that response time because we’re confident in our lead scoring.
How To Calculate a Lead Score
While lead scoring may look different for each company, the common thread will always be data. A good place to start when developing a lead scoring strategy is to look at your list of current customers, and identify what they have in common. Don’t forget to look at those who didn’t become customers, and identify what characteristics they share.
Below are some key steps to building out a lead scoring strategy:
1. Build Multiple Buyer Personas
By now you probably know about buyer personas and how to use them to develop content and sales strategies. And truthfully, that’s the hardest part of lead scoring! Once you have these established, you can begin to use them to identify ideal leads.
The more buyer personas you have, the more well-rounded your lead scoring system will be. When you understand your wider audience, you can begin to identify the multiple attributes that contribute to a lead becoming a customer.
2. Identify Data Points
As always, data is important here. And when it comes to lead scoring criteria, we can break it down into two main categories: demographic and behavioral. Think of demographic data as who the person is, and behavioral data as what that person does.
For example, demographic data consists of things like
- Job function
- Company size
- Job title
Behavioral data, on the other hand, includes
- Email opens
- Web page visits
- Content downloads.
You can then use this data to look back at past and current customers, see what they have in common, and target people with those same attributes.
3. Assign Point Values
There are a host of ways that you can assign value to rank your leads, but the most common way to do it is on a 0-100 point scale. You can then weigh the points in relation to how indicative they are about a lead’s readiness to contact a sales rep.
For example, maybe your ICP (ideal customer profile) is a stakeholder at a large-sized company. Your data also shows that in the past, leads typically download at least two top-of-funnel pieces of content. That is, they’ve done their research.
Through your MQL (marketing qualified lead) analysis, you can then weigh each of these qualifications. Each lead can get points for respective characteristics. You then add up the points, and calculate their lead score.
4. Decide what constitutes a sales qualified lead (SQL)
Again, quantity when it comes to leads does not equal quality. It’s useful at this point to turn to (you guessed it!) data.
Look at some of your best sales, and identify the common characteristics all of those buyers had. This can help you set a benchmark for high scores.
It is also important to keep in mind that lead activity is always changing, and so should their scores. Lead management software can help you keep track of lead activity, and make sure that scoring is updated accordingly.
Why Should You Measure Lead Generation Success?
Lead scoring can seem ambiguous at first. Who gets to decide what attribute should get the most points? And who decides how many points make someone a good lead?
Luckily, it doesn’t have to be as daunting a task as it might seem. With sales and marketing collaboration, lead scoring can bring teams closer together and result in better-targeted campaigns and strategies.
Without lead scoring, you’re walking into the woods with no compass and no sense of direction. Lead scoring takes the guesswork out of refined lead generation.
Trust us, it’s worth your time.