Lead Scoring: Where Can AI Help?
Key Takeaways:
“Lead Scoring” in sales is the process of assigning a “score” to each lead to indicate likelihood of ultimately converting that lead.
People have historically defaulted to a totally unstructured process for scores as opposed to any sort of centralized system. The rise of AI assistance can help create customization at scale.
AI companies like Ask-Dwight have tailored their large language models (LLMs) around helping salespeople customize scoring for themselves, allowing them to self-standardize with what they value most.
“Here goes Kyle again on his ‘AI helps everything in sales’ spiel,” I know, I know. But the truth is, AI (and, specifically, LLMs) can help take a sales team from a ragtag team of underachievers to award winning efficiency FACTORIES.
If you know where to use it, AI can avoid the de-humanization of your sales process and still unlock efficiencies you never thought possible.
Here at Ask-Dwight, we believe lead scoring is on that frontier.
What is Lead Scoring?
Lead scoring is a process by which you assign a “score” to your leads, which helps you focus on the best performers.
In short, it makes you more efficient with your time.
For instance, you might spend half your day on a lead that just got the discovery call on the books and is led by your best friend from college.
Alternatively, the lead who’s ghosted you for four months and needs the quarter to “get liquid” might take the backseat of your mental load in favor of other prospects.
It doesn’t guarantee you won’t waste your time, but it does try to analytically design your day based on what will earn you the most ROI with your time.
If you’ve not heard of or tried lead scoring before, close this article immediately and go give it a shot! It’ll change your life.
How Do People Traditionally Score Leads?
If you’re a little more seasoned in the sales world, you might know lead scoring as a more personal or company-wide process, which may help you early on with your daily task management but can get tricky as you evolve across different teams and leaders.
But what if that process was more customized?
What if you said to yourself, “maybe my company is scoring leads with the BANT model, but I know I’m converting sales every time a person engages more than once a month?
Do I leave those sales on the table, just because my company can’t meet those needs?
Or what if you’re the sales lead and your teammates are sharing a MILLION of these examples. How do you create a centralized system of lead scoring that also allows for some customization depending on your team individuals’ strengths and weaknesses?
These are issues that come up every single day, even with sales teams actively using AI.
It’s not enough to score leads like a lumbering dinosaur of the 20th century. You have to marshal your resources and personalize each person’s lead scoring process.
Do that, and you may find yourself shattering quotas this year.
How to Score Leads At Scale With AI
Now what’s a fun lead scoring exercise without a little AI right???
Here’s what you do:
Log into any LLM (we prefer Ask-Dwight, but you can use any).
Ask it to provide you with a baseline lead scoring framework. You can base it off of your company’s model, or you can ask it to provide you an outline to fill out.
Adjust that framework to include any specific needs you may have. For example, “factor in companies that received our Christmas card this year, companies with fewer than 500 employees, and women-owned businesses.”
Reassign weights to each allocated factor to better align to your unique goals and sales strengths.
Lastly, ask the model to export as an uploadable document to support your Sales Playbook. Download and use that to support a new custom GPT- or, with Ask-Dwight, just upload to your “My Playbook” section and prioritize your pipeline in any chat!
The reality is that your competitors are already using AI to streamline their lead scoring. You can either beat them at it or lose to them at it.
You can bet your bottom dollar they’ll have their teams spending time on what matters most, both as a team but also as individuals.
In the end, you’re not really using AI here to automate.
You’re using AI to beat your competitors at an efficiency chess match, with AI as the cheat code.
Game on, suckas.