June 19, 2024

Signal-Based Selling: Why Anonymous Website Visitor Behavior is the Most Important Signal (With Numbers to Prove it)

Don Simpson

To stay ahead of the competition, companies must continually refine their approach to identifying and engaging with potential buyers. One concept that’s gaining traction is signal-based selling (which may sound familiar if you've read any of our articles on buyer intent). This is the idea of using various signals—data points that indicate buyer interest or intent—to drive your sales decisions and strategies.

But the challenge is in finding the right signals in the noise. 

With so many data points to choose from—social media interactions, ICP fit, email engagement, search keywords, website analytics, and much more—it’s like looking for a needle in a haystack. 

Most of the  tools we’re familiar with promise to show you “in-market” buyer intent signals, but they often fall short, limited by incomplete data and outdated databases. 

Finding the most reliable and actionable signals in this crowded market is key to success.

But there’s one signal that everyone is missing, even though it’s right under our noses, yet it’s delivering outsized results compared to every other signal. 

That’s where website visitor behavior emerges as the game-changing signal that can cut through the noise and deliver significant results.

Recap: What is Signal-Based Selling?

People are bombarded with hundreds, even thousands of ads and marketing messages each day. This is even more true now that everyone is using generative AI like ChatGPT to create content. That means companies can no longer rely on traditional "spray-and-pray" tactics that cast a wide net in the hopes of catching a fraction of sales.

Therefore, sales and marketing efforts need to be smarter and more finely targeted. And that means rethinking traditional inbound and outbound strategies.

Signal-based selling solves these challenges with an approach that focuses on reaching out to prospects at times when they are most likely to be receptive to your message based on their “signals” of intent. It goes back to the marketing foundation of reaching the right people at the right time with the right message.

Companies have begun to take an inbound-led outbound approach to maximize sales efficiency. Instead of traditional cold calling with generic pitches, this method relies on identifying signals that indicate a visitor's buying intent. By analyzing these signals, sales teams can better prioritize leads, personalize outreach, and increase pipeline and sales.

5 Commonly Used Signals and Their Limitations

While signal-based selling is powerful, its effectiveness depends on the quality and relevance of the signals used. Here are 5 common signals in the industry and their limitations:

  • Demographic signals: Give a broad picture of ICP (Ideal Customer Profile) but lacks the specificity to measure actual buying intent. Relies on having an ID reveal or Account information on hand in order to work. some text
    • For example “XYZ Company is in California”
  • Firmographic signals: Similar to Demographic signals, Firmographic signals give more detailed information about the Account’s company. Relies on having an ID reveal or Account information on hand in order to work. some text
    • For example “XYZ Company has 311 Employees and is currently hiring a new Director of Marketing” 
  • Behavioral signals: Indicative of intent but fragmented and hard to put together. Relies on having an ID reveal or Account information on hand in order to work (except for one Lift AI, more on this lateR). some text
    • For example “ABC Contact from XYZ Company opened your marketing email and spent 30+ seconds reading a blog post”.
  • Psychographic signals: Hard to collect and analyze accurately, less reliable in predicting actual purchase behavior. some text
    • For example “XYZ Company is going through a restructure, so are less likely to spend on new products”.
  • In-market signals: Broad market-wide actions that can be tracked into databases of 3rd party data which can be sparse, delayed, or inaccurate. Relies on having an ID reveal or Account information on hand in order to work. some text
    • For example “XYZ Company just used a search term on a competing website that matches your products and services”.

Despite the promise of these signals, many fall short of giving a complete and accurate picture of buyer intent. Attempting to orchestrate them altogether results in a patchwork mess of fragmented signals that are not necessarily related, and ends up burning sales resources in the process.

But one of the biggest challenges is the complete lack of insights for anonymous buyers. As you can see, the majority of signals rely on having an ID reveal or Account information on hand in order to work. That means the signals provide no usable data on completely anonymous buyers.

Additionally, studies show that buyers are 60-70% of the way through their buying journey before they engage with a sales rep. This anonymity means traditional signals miss out on a large chunk of potential leads early in the sales process where companies can get the competitive first-mover advantage (in fact, 50% of sales go to the first company who responds to customers, let alone get in front of them first by predicting their intent). 

Given these limitations it’s clear traditional buyer intent signals fall short. This is why we need a more reliable and broader signal – website buyer intent.

Why Website Buyer Behavior is the Most Important Signal Right Now

In the world of signal-based selling, the debate rages on about which signals truly drive pipeline and sales. At Lift AI, we believe website buyer intent is the gold standard. Here’s why this signal outshines all others.

Full Visibility, Full Control, Maximum Insights

Think about this: If the majority of signals rely on 3rd party data and Account-matched information, then you’re inherently missing out on signals from anonymous buyers. Plus, those signals are likely to be sparse in nature, inaccurate, outdated, or easily available to all of your competitors.

But on your website, you have full visibility of every possible signal as it’s all contained within your website as 1st party data and within your control. 

No ID Reveal Needed. Or Anything Else For That Matter

And those signals are all behavioral in nature. You don’t need to have an ID match, nor do you need to know any demographic, firmographic, or in-market signals (although you’re welcome to add those on if you have them). 

Behavior alone can dictate whether a visitor is likely to buy or not, just like an experienced salesperson at a retail store can pick up on the micro-behaviors that a likely buyer shows in person. And after all, as Winston Churchill said, “behavior never lies”.

Real-Time Data & Action is Critical

Real-time data on your website gives you real-time insights and action. This is key to engaging with prospects at the right moment in their buying journey—something traditional signals miss out on due to data delay. 

1st Party Data is the Gold Standard for Marketing & Sales

Plus, first-party data from your website is far more accurate and reliable than third-party data. You own and control data collection and analysis, so it’s relevant to your business and not dependent on outdated or incomplete external sources. This is particularly important as the future of website marketing is moving to be cookieless, which will render many of the traditional signals useless.

Only AI Can Predict Behavior

At Lift AI, we use advanced algorithms and our pre-trained proprietary machine-learning model to analyze, predict, and score all website visitor behavior, whether those visitors are known or anonymous. 

The process starts with data collection, tracking every interaction a visitor has on your website. This data is then analyzed to identify patterns and micro-behaviors that indicate buying intent. Based on this analysis, we assign a buyer intent score to each visitor.

One of the key benefits of Lift AI is its real-time processing. When visitors interact with your website, their intent score is updated so your sales tools and teams can engage them based on the most up-to-date data. 

With an accuracy rate of over 85%, Lift AI’s intent scores provide a solid foundation for lead prioritization and outreach, making sales efforts efficient and effective. 

And it’s the only tool on the market that can do this.

The behavioral signals that Lift AI analyzes are not to be confused with the handful of high level conversion events that some other tools track such as pricing page visits (hint: 88% of buyers don’t even visit your pricing page), content downloads, webinar registrations, email opens, and so on.

By focusing on complex website buyer intent signals you can cut through the noise and get to what really matters—turning visitors into customers with precision and confidence.

Results From Real-time Website Behavioral Signals

Using just this one signal alone, Lift AI clients uncover hidden pipeline and revenue on your website while increasing sales efficiency. For example:

  • PointClickCare: 168% more qualified leads in 30 days
  • Chronus: 85% new pipeline from anonymous visitors 
  • Drift Customers: 9x more conversations to pipeline
  • Truckstop: 3.8x ROI in 1st Month, 27x ROI in 5th Month
  • Fluke Biomedical: 345% more revenue per visitor 
  • Loopio: 733% more meetings booked 
  • Intelex: 4x sales efficiency 

Enhance Existing Tools with Lift AI’s Buyer Intent Signals

If website buyer intent signals are powerful enough on their own to work with anonymous visitors, think about how integrating Lift AI into your existing tools will make them even more effective Here’s how Lift AI can add to your sales and marketing tech:

ID-Reveal Tools

ID-reveal tools only identify a fraction of your website traffic (up to 30% on average, and often with match rate accuracy as low as 9%), but when you combine them with Lift AI’s intent scores, you hone in on the buying intent of those contacts and accounts. This allows your sales team to prioritize and focus on the leads with the highest buyer intent more precisely and efficiently, which we call the “bullseye” 

Take a look at this example from Lift AI client, Chronus. 

Chronus, a mentoring software leader, combined Lift AI’s buyer intent scores with 6sense’s ABM platform. This integration allowed Chronus to find known accounts with high intent and supercharge their sales strategy. By adding Lift AI’s real-time intent scores to the 6sense buying stages, Chronus increased their lead to opportunity conversion by 11.6x, from 3.4% to 39.3%. Focusing on high intent visitors allowed Chronus to engage with potential buyers more effectively and efficiently.

Lift AI alone generated 85% of Chronus’ total pipeline from completely anonymous visitors—traffic that traditional ID reveal tools couldn’t capture. The combination of Lift AI and 6sense created a “bullseye” of visitors, allowing Chronus to engage with high intent prospects in real time through live chat before they went to competitors. This integration not only grew Chronus’s pipeline and revenue but also maximized their ROI on 6sense and increased their sales team's efficiency.

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