What information about the sales organization, products/services, and customer pain points do you need before you design an effective lead scoring system?
This is by no means exhaustive, but here are some of the angles I'd consider when building a lead scoring system:
What does your web/content ecosystem look like? - what's your new content publishing cadence? What's the mix of content across one pagers, ebooks, webinars, IRL events? What high-value pages do you have on your site? What does a typical user's journey look like (are they binging a bunch of content in one session? Or visiting your home page and signing up for a trial?)
Do you have access to any third party intent signals? - do you have access to intent signals from a third party like 6Sense or G2 and can you bring that into your scoring model? I don't always recommend this, but if you have a limited sales team, adding intent might help to focus your AEs/SDRs.
Buying group - who are your core personas, and who is a buyer vs. influencer on the sale? Can you score buyers more aggressively, and influencers a little less?
How big is your sales organization? Do you have 1 SDR or a team of 10? This is one of the most important indicators you should consider: Your organization might be strapped in SDR resources, meaning you should be filtering for quality. Or, you might have a bigger team, meaning you can send a higher volume of MQLs through to the team.
Do you have multiple SKUs or solutions that you are selling to different buyers? If so, you might want to consider a product-based scoring system that adds points if folks are interested in different elements of your product or service.
What's your typical sales cycle and deal size? For SMB business with smaller deal sizes, you should err on speed to lead and reaching out when folks are engaged, as these buyers will often go with whoever gets back to them first. For enterprise businesses with longer deal cycles, you might want to consider more stringent criteria for lead scoring.
What's your plan to allow folks to 're-MQL'? Make sure that you build a system that is flexible enough to allow people to come back through on the right cadence. If you are solely reliant on new leads or prospects you will quickly need to increase budgets and campaign activities to be able to hit your demand targets.
What high intent signals can you mine across all of the above questions to get at an "ideal" MQL?
Finally: INTERVIEW sales leaders, all the way up to the CRO to get alignment on the definition of a "warm" prospect. If you work day in and day out with BDRs, you may get a different perspective than what someone in leadership would say. Build a slide deck with a few examples: Ex. a product leader from this industry visited our site via an organic search result, clicked around on 3 pages, and then came back a week later to download this white paper. Do you think we should have a sales person reach out?
Below is a summary of the information I recommend. However, please take this and evolve it to meet the needs of your business, target audience and goals.
- Sales organization. What is your sales process? How long is the sales cycle? Are you a product-led sales org, enterprise or somewhere in between? Based on your process, what type of sales team structure is in place to support the process? How has the team been performing and what are the forecasted outcomes?
- Product/services. What is your go-to-market motion? Are you developing a lead scoring system for PQAs and PQLs or SQLs and MQLs? This scoring approach is very different. Based on the GTM motion, you can then define the actions that support your lead scoring system.
- Customer pain points. What is the competitive landscape? Depending on your framework (e.g., personas, jobs to be done, etc.) outline what problems you are solving for your customers. What value are you driving based on your unique selling proposition?
I also recommend that you take an iterative approach. Don’t feel like you have to establish the scoring system at 100% accuracy on day one. Get started with an educated hypothesis and continue to improve based on its performance and the feedback you receive from the sales team. There should be a constant feedback loop to continue to refine your lead scoring system.