A lot of things can go wrong on the journey from prospect to qualified lead.
Here’s just a few of them that marketers and sales pros run into.
The lead isn’t:
- ready to buy on a timeline that makes sense for your enterprise.
- the actual decision-maker with “dotted line” buying authority.
- interested in your product or service in any way whatsoever.
- fully qualified according to your own internal sales criteria.
- fully qualified based on opinion of the sales representative.
Argh! With all of that, it’s almost a wonder businesses find qualified leads at all.
We’ve discussed how you can use BANT lead qualification to accelerate the process of turning a marketing-qualified lead into a sales-qualified lead. Using the right qualification framework can save a lot of time, money, and aggravation in the long run.
To fully qualify your leads, however, you need to go one step further.
You need to get into leads’ heads and predict the likely sales outcomes.
In short, you need lead scoring.
What is Lead Scoring?
Lead scoring uses your data – the whole history of all your past sales – to evaluate how likely it is that a lead will ultimately become a customer. Based on criteria derived from the activities of previous customers, your lead scoring system assigns a quantified value to each lead.
This value increases as the lead takes actions consistent with a future purchase.
It also provides you with a framework to understand lead behavior and take proactive action. For example, it’s easier to determine what stage of the buyer journey a lead has reached and when you should follow up when you have structured historical data to rely on.
The question: How the heck do you get started with lead scoring?
What data goes into it?
As with so many things in scientific marketing, scoring your leads relies on choosing the right data. You don’t want to get bogged down with vanity metrics, but it’s also not a matter of “the more, the merrier.” There are specific data points that create clearer scoring.
They break down into two categories:
- Explicit data mainly centers on enterprise buying factors; some is available publicly.
- Implicit data consists of the signals a lead sends when accessing your web content.
Let’s take a closer look at how these work out.
Explicit Factors in Lead Scoring
1. Job Title
Even in today’s world of complex B2B consensus sales, you can usually determine whether a lead is viable based on the good old company org chart. Usually, job titles will make it clear that the lead is both in the right department and at a suitable level for strategic procurement decisions.
Let’s face it: You’re not going to get very far trying to sell a product or service into the wrong industry. When you serve multiple different verticals, however, those that are more desirable (in terms of cycle time or deal size) may result in a higher lead score than the ones that are secondary.
3. Company Size
Most sophisticated business solutions only really reach peak value when an enterprise is at a certain scale. Some are targeted at SMBs (small- and medium-sized businesses) and may be less useful to larger companies. Whatever the case, this is definitely something you want to keep track of.
4. Annual Revenue
Annual revenue is a huge factor in setting the “ceiling” for what a reasonable strategic buy looks like from the lead’s perspective. Just like you don’t want B2C customers taking out a second mortgage to afford you, find the comfortable middle ground for your B2B leads.
5. Number of Employees
Most solutions fit in smoothly with a certain headcount. For example, if you’re trying to sell marketing automation software, it makes sense to pitch it to a “team of one.” If you’re in an area like compliance or data security, your value increases with headcount.
Implicit Factors in Lead Scoring
Pageviews are a vital early metric in judging interest. When someone is intrigued by what you have to offer, they’ll usually view more pages and have longer, deeper sessions. Of course, your site should also be set up to drive conversions with lead capture and AI chat bots.
Return traffic that delivers multiple visits from a single user is a huge sign you are on the right track with someone. It means they are looking forward to your updates or they’re getting more information – for example, from a colleague – then returning to evaluate your claims.
8. Type of Content
The content types that someone views is one of the best indicators of what buyer journey stage they’re in and what their next move might be. As visitors progress toward bottom of the funnel content like whitepapers and case studies, their lead score should obviously go up.
The sooner you get leads to take action, the better. Recency helps you understand just how motivated someone might be. Ideally, they’ll move smoothly from one step to the next and jump on that purchase! If they fall idle, then their lead score should go down.
Scoring Your Leads Can Double Your Qualification Conversion Rate
Just a few years back, the majority of enterprises were building up their own mechanisms for lead scoring by chaining together different data points from various analytics systems.
While you can still do it this way – and it may be a great learning experience for some marketers – it’s no longer necessary to do everything by hand. You can save time and be accurate.
A great Customer Relationship Management (CRM) system will synthesize your lead scores for you using the data about your prospects it correlates from other systems and collects itself.
At Bluleadz, we swear by the HubSpot CRM for those who want to get started with lead scoring.
It’s fast, effective, intuitive, and – best of all – it’s free.
Lead scoring makes life easier for sales and marketing alike. Implement it today and zoom in on those hungry leads!