Stop leaving money on the table. AI-driven demand capture will transform your business

Executive Summary:

• Companies spend over $1T to bring customers to the door, but $19 of every $20 they spend does not convert to revenue. 
• The crux of the issue is this - we can’t see visitors on our website properly, therefore we can’t optimize our conversion for them.
• Traditional conversion approaches run into the same problem again and again - website visitors want to remain anonymous, so we can’t see or identify them.
• The shift is this - instead of viewing our marketing and sales funnel from an “account-in” approach, we should flip it upside down and look at it from a “buyer-out” approach.
• In other words, you shouldn’t spend another cent on advertising spend until you have exhausted the conversion capabilities of your #1 sales channel: your website.
• So we need to stop focusing just on who is on our website, but why they’re on the website.
• Account Identification tools provide account-level data for up to 30% of website traffic, but not always individual buyer intent data.
• The real metric we need to measure is real-time behavioral signals that lead to conversion.
• There is only one tool on the market that can currently do this: Lift AI.
• It surfaces hidden buyers on your website based solely on their real-time behavior
• By looking just at behavior (the why) instead of the visitor ID (the who), Lift AI can give you a complete and accurate view of buyer intent for every individual visitor - including the 70% or more of visitors on your website who are typically completely anonymous, and the 30% who are account revealed  
• With that newfound visibility, you can flip your funnel on its head, and approach your marketing and sales from a “buyer out” perspective rather than “account-in”. 
• Formstack used Lift AI to generate 422% more monthly recurring revenue by focusing their engagement strategy on high intent visitors (and also achieved 18x ROI in doing so).
• Okta increased the sales velocity of conversations to pipeline by 5x by ensuring their sales team only spent time engaging high intent visitors
  
  

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Companies spend over $1T to bring customers to the door, but $19 of every $20 they spend does not convert to revenue.

Clearly, too much emphasis is placed on creating demand, rather than capturing demand.

Creating demand gets most of the budget, and therefore most of the attention.

That means big money is being pumped into advertising, promotion, and top of funnel activities.

What we end up with is a leaking funnel, with prospects being shoved into the top and then lost further down.

Don’t get us wrong - creating demand is essential to the lifeline of a business.

But capturing demand is a much more cost effective way to drive significant revenue growth and profitability

The path to capturing demand effectively isn’t so simple. If it was, we would have mastered it by now.

To make significant improvements, we need to think differently. And with new AI capabilities you can think and act differently to create transformational results.

The best place to start with this is on your website. That’s where your the majority of your best prospects are right now, and it should be your #1 revenue channel. 

Your Problem is This - You Can’t Really See Website Visitors

In the last decade we’ve seen numerous attempts to improve demand capture on websites.

From slick landing pages to pop-up offers, multi-step forms, online chat, ID reveal tools, and more.

Some of these tactics work well to plug the holes in our leaking funnels, but they still leave the vast majority of traffic not converting.

The crux of the issue is this - we can’t see visitors on our website properly, therefore we can’t optimize our conversion for them.

Instead, we rely on a one-size-fits-all approach for identifying visitors that gets the results you’d expect.

For example, we use “deanonymization” tools that can reveal customer account or contact details, but that only works for about 30% of our traffic, leaving 70% of our website visitors still completely anonymous and overlooked.

We also use tools like online chat, but then ask customers for their email address in an attempt to ID reveal them, sabotaging conversion rates up to 80% in doing so.

These approaches run into the same problem again and again - website visitors want to remain anonymous and are only willing to give up their personal information right near the very end of a buying journey, which is often too late to be useful in conversion optimization. 

So how can we see our entire website funnel of traffic, capture all of that demand (including anonymous visitors), and convert it?

The Paradigm Shift: Buyer-Out vs Account-In 

First, we need to shift our paradigm of thinking. This is hard, because we’ve been thinking the same way for years.

The shift is this - instead of viewing our marketing and sales funnel from a “account-in” approach, we should flip it upside down and look at it from a “buyer-out” approach.

In other words, instead of focusing on driving more traffic into the top of the funnel, we should prioritize converting the potential buyers at the bottom of our funnel that we’re currently missing, first.

Once that is sorted, we can start layering in the traditional funnel elements on top as needed - such as account-based marketing and scaling advertising to bring in visitors to the website at the start of the funnel.

In other words, you shouldn’t spend another cent on advertising spend until you have exhausted the conversion capabilities of your #1 sales channel: your website.

The only way to accomplish this is by having full visibility into your funnel from top to bottom, otherwise you can’t spot the likely buyers, and therefore you can’t flip your thinking.

It will take some mental acrobatics to get there, alongside breakthrough technology to execute. 

Let us explain from the ground-up.

Knowing Who A Visitor Is Doesn’t Mean They Are A Buyer

In order to get full visibility into our website funnel, we can’t rely solely on trying to deanonymize visitors to find out who is on your website. 

As mentioned, this strategy can only identify 30% of visitors on average - and even then it doesn’t tell us who is likely to buy, only what company they are from.

So we need to stop focusing just on who is on our website, but why they’re on the website.

We’ll get to how you can measure the why later, but for now let’s unpack the who so we can understand how we got here.

The reason we’re focused on the who, is because that’s all we could accomplish with technology at the time, so it became the status quo.

It’s also very helpful in certain situations, especially if you’re a B2B company relying on a target account strategy. 

In these situations, knowing that one of your target accounts have been on your website can be a great sales insight.

Here’s how Account Based Marketing (ABM) tools and sales intelligence tools have traditionally determined who is on your website in a process called “deanonymization”:

• ID Reveal via IP Address Lookup - This uses each visitor’s unique IP address (think of it like a home address, but on the internet) and compares it with a database of other IP address records that contain people’s contact details or company details. If the IP address of the visitor matches an IP address found in the database, the tool will pass through their details. 
• ID Reveal via Form Fill  - Similar to IP addresses, if a visitor fills out a form on your website (such as name, phone, and email address), these tools will once again try to match them with the database of existing records. If a match is found, any other relevant information is passed through (this could include company size.
• Database Matching  - In both of the above examples, the strategy involves matching visitor information to information stored in a database. This is the beating heart of an ABM or sales intelligence tool. Not only do they store all of the information their customers receive in a shared database, they also buy data from other providers to have as much data as possible. 

This kind of data can be incredibly useful to sales teams. If you’re a B2B company, you’d be crazy not to have an ABM programme to help identify which companies are on your website.

However, these tools can only get you so far because they’re still concerned with who is on your website.

In-Market Intent is Not True Intent

To counter this, many tools have introduced a concept they call “buyer intent”, which is an attempt to discover if the ID revealed visitor is showing signals that could mean they’re close to converting. 

However, these tools more accurately use a subset of buyer intent called “in-market buyer intent” or “pre-intent” which is mostly off-site, third party signals that could be construed as intent, alongside some cursory on-site data. 

Typically, in-market buyer intent or pre-intent looks at technographic data, psychographic data, market updates, and market activity:

• Technographic Data - This falls under the premise that companies using certain technologies (or combinations of technologies) may be in the market to buy a product or service similar to yours (especially if the tool can pickup that a contract renewal is up)
• Psychographic Data - This is data which helps to build a profile of your target accounts, for example what their pain points might be as pulled from social media or annual reports (this is hard to come by, and is often outdated or inaccurate)
• General Market Updates - This is data relating to the companies movement in the marketplace - recent hires, leadership changes, funding, and acquisition,

When it comes to in-market activity, the tools use a combination of actions taken by target accounts in broader online sense, including:

• Similar Content Consumed - If you’re selling meeting scheduling software, it might be of interest to know that a visitor on your website has looked at content related to meetings on other websites, which has been stored and captured in the database.
• Search Terms Used - If the tool knows that a visitor has searched for something in a third party website, the tool can see and store the search terms that visitor used. The tool can then surface that information to you if the search term is relevant to what you’re selling. 
• Basic Website Metrics - Some tools supply you with a small portion of first-party data on your website in the form of basic website metrics. For example, it may look at how long the visitor has been on your site, if they visited a pricing page, and if they watched a video. It will then assign a score for each action and tally them up in an attempt to represent the visitor’s intent.
• Marketing Engagement Metrics - If a user clicks on one of your marketing emails, it may indicate a signal of intent. If they then click on a link inside of your email, an additional intent signal is logged. The same logic is used for form fills (e.g. contact forms) or downloads (e.g. ebook downloads). These engagements are often considered as strong intent signals by traditional tools.

The 6 Major Challenges of Traditional ABM and In-Market Intent Tools

So, all in all the modern ABM tool is fairly sophisticated using a combination of ID reveal technology and in-market signals. 

However, there are six major challenges with this traditional technology:

1. Their databases use third-party data. Meaning, the data has been purchased or acquired from another source. That means the data could be out-dated, inaccurate, or irrelevant. It also means your competitors can access the exact same data set as you, eliminating any competitive advantage you would have if the data was first-party.
   
   
2. The ID reveal methods are not working as well anymore. That’s because of increasingly strict privacy laws impacting what information can be shared with providers, and because visitors are reluctant to give up their personal information via form fill. The work from home boom has also confused IP address look-ups. Instead of getting company information, they’re getting home computer information.
   
   
3. Their data is not always provided in real-time, when it matters. These tools typically rely on a notification system to let you know when a visitor has been on your website in the past X amount of time (which can vary). However, it’s far less useful to know that Tim from CocaCola was on your site 3 days or 30 minutes ago than if they are on your website right now.
   
   
4. Their data only works for an average of 30% of your website visitors, meaning 70% or more remain completely anonymous and fall through the cracks of your funnel.

5. ABM tools provide account-level data, and not always individual intent data. So, your team might know that a target account is showing some in-market intent at a broad level, but what if there is an individual visitor on your website right now that is showing intent to purchase?
   
   
6. Their in-market data isn’t always useful because it’s too simple. Imagine that your ABM tool is telling you that someone from CocaCola was on your website and they looked at similar content to yours and used a relevant search term to get there, then went to the pricing page - so they have an intent score of 75 and must be “in-market”. Well, this visitor could just be looking for support for your type of software. Or they’re a competitor using a VPN to confuse the IP address, and are visiting your pricing page because they’re looking at how you’re currently positioning your product. The point is, that data alone is too simplistic and doesn’t model true buyer intent (more on this soon).

To read more about traditional in-market intent signals (and how they compare to the newest AI-powered methods) read this take on the old way vs the new way by Greg Wolfe, the former COO of Marketo.

What You Need is  The “Why” - Buyer Intent Behavior

So, we’ve determined that the old way of thinking is all about the who, which isn’t getting game-changing results. 

And it was brought about as the status quo because that’s all we could do with technology.

That’s now changed.

Instead of focusing on the who, which tells us basic information about our visitors, we can look at the why, which tells us what the true intent of each visitor is.

More specifically, a more sophisticated version of “buyer intent” which is a measure of how likely any given visitor is to convert.

However, we need to get even more specific, because as we’ve learned, “in-market buyer intent” is helpful but more importantly the real metric we need to measure is real-time behavior.

Think of it like this. A seasoned salesperson working in a retail store develops a knack for knowing who is likely to buy and who isn’t, based purely on their nuanced behavior as they navigate through the store.

Knowing the name of the customer doesn’t help in determining this behavior. Nor does knowing what industry they’re in, what company they work for, or any other simplistic data point. 

Instead, the salesperson calculates a complex, unconscious series of heuristics including body language, facial expressions, eye tracking, timing, and more to know who is kicking the tires versus who is genuinely interested.

They do this in real-time - they don’t do it once the customer has left the store.

The problem is that you can’t do this on a website. There’s no human that can actively watch a website visitor and gather the same level of insights. Additionally, even if it were possible, it’s not scalable for the thousands of website visitors who could be there at any given time.

So, you need a way to measure behavior online, in real-time, that is both complex and nuanced, and can scale into the thousands. 

The Only Real-Time Website Buyer Intent Solution is Lift AI

That solution is “real-time behavioral website buyer intent”

The premise of behavioral website buyer intent AI is to predict the likelihood of a given visitor to convert based on their behavior in real-time, as processed by artificial intelligence using billions of data points for repeatable accuracy.

There is only one tool on the market that can currently do this: Lift AI.

Lift AI is the only website-exclusive website buyer intent technology that uses artificial intelligence to predict the likelihood of any visitor to convert, all in real-time. 

In other words, it surfaces hidden buyers on your website based solely on their real-time behavior, offering a complete and accurate view of buyer intent for every individual visitor.

It works by analyzing each visitor’s behavior as they navigate your website, assigning them a buyer intent score between 0-100 (where 100 is extremely likely to buy). The artificial intelligence model is pre-trained on billions of data points to ensure that each buyer intent score is accurate more than 85% of the time.

For example, traditional in-market intent tools often cite “pricing page views” as a strong indication of intent. However, Lift AI knows that more than 64-88% of your high intent visitors don’t go to the pricing page at all - so how can you find them?

Lift AI’s behavioral buyer intent is on a completely different level to “in-market intent” in six critical ways:

1. By looking just at behavior (the why) instead of the visitor ID (the who), Lift AI can give you meaningful insights on every individual visitor - including the 70% or more of visitors on your website who are typically completely anonymous. 
2. Lift AI can also be combined with ABM data to isolate the individual intent of visitors within the 30% of known accounts on your website, giving you more precise and actionable signals that you can take action on quickly.
3. Lift AI uses machine learning models to calculate buyer intent behavior rather than simplistic calculations. That means it can handle the complexity and nuanced nature of website visitors and their unique journeys. For example, data signals can’t be added up in a linear fashion. Instead, each signal needs to be cross-referenced against each other, then aggregated to determine a level of intent.
4. It all happens in real-time. Would you rather send your sales team chasing a target account who was on your website 2 days ago, or have them engage the customer on your website right now who’s showing strong buyer intent right now, before they leave your website? This is particularly important when data shows that 50% of deals go to the sales team who responds to customers first - if you can see high intent visitors in real-time you can reach out to them before competitors get a chance.
5. Lift AI uses far more data signals in its calculation. As we know, behavior is nuanced and subtle, so to analyze it digitally means looking at more than just what page the visitor is on and for how long. We need to look at hundreds, if not thousands of real-time behavioral signals, all together.
6. Lift AI delivers results quickly. Because Lift AI doesn’t require months of configuration, integrations and testing, Lift AI will deliver value in the first 30 days - shorter time to market, value, and ROI. Its buyer intent scores flow easily into the tech stack you are already using.

How Lift AI’s Buyer Intent Scores Are Used

The most typical use-case of Lift AI is to integrate the buyer intent scores with a real-time engagement tool, such as online chat via Drift. Users can set up a “playbook” which directs any high buyer intent visitor to a live sales agent via the chat window, where the live sales agent  has the best chance of converting that visitor. Here’s a great example of how Fluke Biomedical did just this to increase their revenue per visitor by 345% using Intercom.

However, Lift AI’s buyer intent scores are not only for finding hidden buyers and surfacing them for conversion. You can also set up rules and playbooks for dealing with lower intent visitors. For example, a low intent visitor could be directed to a particular landing page or article which is designed to nurture early-stage prospects. This saves your BDR team from engaging with lower value visitors, allowing them to focus all of their time and resources on converting high intent visitors while using automated systems to nurture lower intent visitors.

Lift AI’s data can also be integrated into almost any of your existing tools, meaning its buyer intent data can be passed through to enrich their data or perform new functions - including your ABM tools which are using ID reveal. Now you can find out who is on your website, and why they’re on it. This overlap creates a “bullseye” of isolated buyers within target accounts that your team can prioritize and focus on.

Another use-case is to integrate Lift AI with your remarketing and advertising tools. Instead of targeting visitors who have been on your website in the last 30 days, you can create a retargeting list of high intent visitors who have been on your site, increasing your chances of conversion.

The critical thing is this - Lift AI allows you to see the behavioral intent of every visitor in your funnel, including the hidden buyers. 

With that newfound visibility, you can flip your funnel on its head, and approach your marketing and sales from a “buyer out” perspective rather than “account-in”. 

Get Paradigm-Shifting Results, Almost Overnight 

So, Lift AI is at the forefront of this paradigm shift in thinking and technology, but what does that mean in terms of results?

As you’d expect of any leap, the results are game-changing - and they come about quickly. Lift AI will deliver value in the first 30 days, resulting in a shorter time to market, value, and ROI. The buyer intent scores flow easily into the tech stack you’re already using - and it doesn’t require months of configuration, integrations and testing. Here are just some of results that Lift AI users have achieved:

• Chronus used Lift AI to uncover 85% of net-new pipeline from completely anonymous visitors that were being missed before.
• Formstack used Lift AI to generate 422% more monthly recurring revenue by focusing their engagement strategy on high intent visitors (and also achieved 18x ROI in doing so).
• Fluke Biomedical used Lift AI to increase their revenue per website visitor by 345%
• On average, Lift AI users who have integrated buyer intent scores with online chat such as Drift convert 9x more conversations into pipeline.
• Okta increased the sales velocity of conversations to pipeline by 5x by ensuring their sales team only spent time engaging high intent visitors

“Our goal for ARR from chat for the first year was to generate $50-$100K. In the first year, we were able to attribute over $1M in incremental recurring revenue to Lift AI."

• John Walker, Director of Demand Marketing, PointClickCare

Here’s the important part - if you are skeptical of the paradigm shift in thinking, technology, and results, you can test it yourself.

Get in touch with us and the team will set you up with a free high intent playbook (if you have more than 20,000 visitors per month). The majority of Lift AI free trials start seeing a lift in revenue before they’ve spent a single cent.