During my tenure as a COO at several companies (most recently Marketo, and previously with Business Objects, and Crystal Decisions), marketing and sales teams shared the goals of top of funnel growth.
A recurring theme in those efforts was the ongoing debate (and sometimes more than debate) regarding lead quality and lead quantity.
I have seen (and have personally been guilty as charged) excellent go-to-market executives put hours of work into rationalizing results and writing/rewriting rules and definitions regarding lead quality, lead flow, and other top of funnel metrics.
This entire lead quality quagmire occurred largely due to the fact that human hypothesis and retrospective viewpoints on what constituted a “quality lead” was all leadership could rely on to create the rules/definitions.
Bias, ego, compensation, and other external dimensions would virtually always cloud the efforts to reach clarity.
I personally found the experience to be unproductive, energy sucking, and sometimes divisive (both as a participant and an observer).
All in all, clearly there was and still is opportunity for improvements that would impact execution, resource management and morale when it comes to leads.
Obviously, everyone wants both higher quality and a higher quantity of leads, which are more likely to convert into revenue. Commonly sales teams are measured on close rates (perhaps more impacted by quality) and marketing teams measured on quantity (where quality measures can by default act as a governor).
You can see how this creates problems - as well intended as each group is, each team is motivated by a slightly different but highly dependent target.
I believe through the use of quality data and the elimination of human hypothesis, this problem and the related incongruence can be minimized if not eliminated.
The opportunity to introduce machine learning to this mix is obvious and the possibilities are exciting!
The Problem: Subjective Human Bias
There are many models, methods, and techniques for determining the quality of a lead.
Most recently, marketing and sales teams have relied on software to determine the quality of their leads using scores from 0-100, or stages from cold to hot.
Put simply, once the prospect reaches a certain score or stage threshold, they are passed from marketing over to sales.
Here’s the limitation with most lead qualification and scoring software: they are based on subjective, human-generated assumptions.
For example:
- Lead Scoring: If a visitor goes to the pricing page, give that visitor +20 to their lead score.
- In-market Intent: If a visitor has searched for a relevant keyword to your products/services in Google, give them +10 to their lead score.
- Account-based Fit: If ID reveal shows a visitor is from a company that fits your Ideal Customer Profile, give them +50 to their lead score.
Each of these methods rely on human-generated scores. Those scores might be based on historical data or industry benchmarks, but they are still a best guess using cause and effect thinking.
This thinking is then turned into simple algorithms (which are step-by-step instructions for computer software to follow). “If the user does X, then Y will likely result.”
The reality is that visitors are not so one-dimensional. They are complex. A given visitor could have thousands of possible journeys resulting in an outcome.
Looking at just a handful of data points within the hundreds or thousands of possible permutations can’t be counted up together for an accurate representation of lead quality.
So, who or what can?
The Solution: Machine Learning for Buyer Intent
The only way to process hundreds or thousands of nuanced data points including historical and real-time data, then determine an accurate and repeatable outcome that is not subject to human bias, is through machine learning.
In fact, I highly recommend you read this article which explains why machine learning trumps human-based algorithms for marketing software. You’ll learn something eye-opening, I assure you.
If we harness this breakthrough technology, we can settle the debate over quality by removing human bias.
However, what does that look like?
We need to stop pinning lead quality on only WHO is on your website, and start to include WHAT they are doing in REAL-TIME and WHY those actions are signaling intent to buy or convert when compared to millions of previously processed visitors in the model.
Simplistic measures such as “the visitor was on your pricing page” are not enough In fact, on average, 64% of your most promising web visitors do not go to a pricing page at all.
Which leads us to the exact solution for measuring the what, the why, and the real-time - which is buyer intent.
Stated simply (and obviously): buyer intent is a measure of how likely a prospect is to become a paying customer or converted lead.
However, even buyer intent can be subject to human bias - so it needs an additional layer.
I believe that layer is machine learning - the only way to purify the conversation and cause real sales and marketing process improvement.
Fortunately a handful of technologies are making meaningful breakthroughs in this area.
One of them, Lift AI, has recently caught my attention.
Lift AI is the only buyer intent intelligence solution that uses a proprietary machine-learning model to calculate, yes you guessed it, real-time buyer intent with over 85% accuracy while removing human bias.
Their machine learning model was engineered using billions of historical data points including profiled website visitors and chat interactions leading to sales, layered with real-time on-site behavior displayed by each individual.
Lift AI assigns each visitor a buyer intent score between 0-100, then segments them into high intent, medium intent, and low intent - all in real-time.
Aside from removing the subjective human bias, the real-time machine learning component is a game-changer as you can take action while the visitor is present on your website - while most intelligence tools give you information in what I call latent or asynchronous time, when action is less effective.
Now imagine this: Take existing intelligence from your existing tools - lead scores, in-market intent scores, ICP fit, and so on. Combine that information with Lift AI’s real-time buyer intent score, and suddenly you have an extra laser-focused view of your red-hot, highest-quality, most promising leads right now without fighting over their perceived quality.
And even better - Lift AI’s buyer intent scores also work for completely anonymous visitors that are not identified or known to your other tools.
Enrich The 30% Of Known Web Visitors
On average, ID reveal tools provide intelligence on 30% of your visitors.
Why only 30%? Because you have to match that intelligence against contact information found in 1st, 2nd or 3rd party data sources, and those data sources don’t have every single visitor profiled. Even if they did, much of that information would be outdated or inaccurate - and tools that guess firmographic information such as IP address lookups are becoming less reliable for company names due to privacy issues and the growth of WFH.
So, a band-aid solution is to simply ask visitors for their email address (you’ll see this commonly in web chat with messages like “Before we help, can we get your email address in case we drop?”). Except doing this is sabotaging conversion rates and might only work for a small handful of visitors.
Additionally, these tools are not calculating real-time buyer intent using machine learning, which means they are subject to the human bias discussed previously and are updating the information asynchronously.
That means there is an opportunity within that 30% of known visitors to determine their real-time buyer intent and combine that information with existing marketing tools using Lift AI - and the remaining 70% of your website visitors who are anonymous to you and your tools.
From there, it’s all about taking action to convert those visitors into revenue.
By adding Lift AI’s real-time buyer intent scores to your existing tools and the 30% of visitors they provide intelligence for, you can further qualify, enrich, and act on the intelligence they provide.
Here are some examples:
Engage With Real-time Chat Tools
Lift AI integrates with all modern chat tools such as Drift, Intercom, and LivePerson so that you can deploy playbooks based on each visitor’s intent. For example:
- ID revealed high buyer intent visitors can be directed immediately to live sales agents (who are better at converting visitors than chatbots), and the routing can be prioritized by ICP, intent signals from your ABM providers, and enhancing your lead score based on their real time intent.
- Medium and low buyer intent visitors can be greeted by a mix of escalation chatbots and live agents.
Using this approach alone (across all visitors, including anonymous) results in an average of 9x more conversations converted to pipeline.
It also increases the productivity of your BDR team, as they’ll be spending more time with the right visitors (high intent), and are wasting less time engaging with low intent visitors who just need support, or are merely browsing. Ultimately this means your team can convert more visitors with the same or fewer staff.
Enrich ABM and Qualification Tools
If your ABM tools such as 6Sense and ZoomInfo have identified an in-market visitor or ICP-fit visitor, you can use Lift AI’s buyer intent score to enrich the information you have on those contacts. This helps you to further qualify each visitor, prioritize which account to engage first, and add a layer of confirmation to the intelligence your ABM tools have provided.
Trigger Marketing Automation Tools
With Lift AI buyer intent scores being fed into your MA tools such as Marketo and Hubspot, you can trigger automated actions to help move those contacts through the funnel. Known visitors with an email address can trigger automated email campaigns based on their Lift AI intent score, where high buyer intent visitors are sent an email to book a demo while medium and low intent visitors receive a nurturing email.
Prioritize Sales Follow-up in CRM Tools
Lift AI buyer intent scores can be integrated into your CRM records as a new column of data. Your sales team may look in the CRM and filter the recently traced contacts (as informed by the ABM tool) by Lift AI buyer intent score, then follow-up in outreach first with known contacts who had a high Lift AI buyer intent score.
And Take Action on the 70% of Anonymous Visitors
You’ve seen how Lift AI can enrich and enhance the 30% of known visitors on your website, by working alongside your existing tools.
Now the floodgates really open in terms of lead quantity by looking at the 70% of visitors that you’re currently missing (read more about how you can convert anonymous visitors here).
Unlike existing martech tools, Lift AI does not require any firmographic, demographic, or contact information to assign accurate buyer intent scores - that’s why it can be used across 100% of your visitors to unlock their buyer intent.
The Result? 9x More Conversions
Below is a graphical representation of a website using Lift AI in conjunction with other martech tools.
Starting from the top left, visitors are funneled based on their real-time buyer intent, plus existing technologies such as ABM programs are layered on top. By engaging visitors in real-time using chat, adding color to them using ABM programs, and following up with high intent visitors as scored by Lift AI in your CRM and MA programs, you maximize the revenue potential of your website while also removing as much human bias from the process.
And this is just one example among many of possible outcomes powered by Lift AI’s buyer intent scores.
Lift AI’s recent case study spanning 21 clients found that on average, Lift AI users get 9x more conversations from chat turned into pipeline.
Results like this are genuinely game-changing, and they’re often had in as little as 90 days.
Suddenly, marketing and sales teams both look smarter than ever while celebrating their improved performance. It’s a win, win.
It also finally settles the ongoing fight for lead quality.
Here’s what Formstack had to say about their success with Lift AI
“Leads captured through our Lift AI powered Drift playbooks consistently drive better pipeline and revenue per lead vs. all of our other lead capture tactics." - Bill MacKay, Manager Digital Performance Marketing @ Formstack
If you’re still not convinced, you can try Lift AI for yourself with a free 30 day trial. Simply install the snippet of code and Lift AI will begin scoring the buyer intent of your website visitors right away.
Even better—Lift AI stands by their results, offering a fee structure based on performance to give you peace of mind.
I know this might have felt a little like a Lift AI commercial, however, if there are other alternative solutions that take this approach, let me know! I wish 5-10-15-20 years ago this kind of technology had been available. It would have saved a lot of time and emotion, I’m sure!
