Executive Reports
December 12, 2021

There's a New ABM in Town: Anonymous Buyer Marketing

Don Simpson


For many years, digital marketers have been pursuing demand generation and customer growth with a strategy called Account Based Marketing - ABM. For a good summary of what ABM is all about, we turn to how it is described by Marketo (now Adobe), one of the leading marketing technology vendors:

“Account-based marketing is a focused approach to B2B marketing in which marketing and sales teams work together to target best-fit accounts and turn them into customers. In the age of information abundance, marketers are always fighting for the attention of potential customers. Because of this, companies that want to focus on the highest possible ROI need to place their attention on high-value accounts, keeping account penetration, marketing penetration, and brands in consideration. To reach their goals, marketing teams must employ strategies that meld the expertise of sales and marketing to locate, engage with, and close deals with high-value accounts that matter the most.”

One of the key aspects of ABM to note from this description is marketing and sales teams working together on targeted accounts and turning them into customers. ABM is successful when the marketing and sales teams can agree upon the ideal accounts, and then execute a plan that targets those accounts with marketing campaigns and sales outreach. By focusing on those high value accounts, marketing spend and sales efforts can be more efficiently utilized to win new deals. 

Yet this all assumes we KNOW who these accounts are… This is effective in defining your target market for outreach and proactive marketing, but what do you do when you are trying to maximize the revenue you generate from your website and up to 98% of your visitors are anonymous? How can Account Based Marketing possibly work when we DON’T know who the accounts are on our website - or we know the account but not who the person is on our website (when they may have as much or more value than our known accounts)? How can ABM possibly work when it is the new ABM, ANONYMOUS BUYER MARKETING, not Account Based Marketing?

We’ll explore that later, but first, let’s consider how B2B companies manage an ABM strategy today and the tools being used to market & sell to their known accounts.


There are three primary categories of technology and tools that businesses are utilizing today to engage customers online: Systems of Intelligence, Systems of Action, and System of Record. Let’s briefly understand each, and then figure out how we can possibly target those anonymous buyers and accounts.

Systems of Intelligence 

These tools determine who a website visitor is with large databases of information to help your systems of action prioritize them. Typically these tools can identify up to 30% of your website traffic, but cannot effectively address the challenge of the other 70% remaining anonymous. Additionally, their definition of “known” is  just a company name or email address, and typically leaves you not knowing who the actual visitor is. Some examples of vendors in this category include:

  • 6Sense
  • Zoominfo
  • Demandbase
  • Clearbit

Systems of Action

These tools (which are often online chat tools) enable humans or automated bots to engage with website visitors in real-time based on playbooks of best-practice engagement tactics. They prioritize those visitors who are known by the aforementioned systems of intelligence, but still miss out on delivering curated customer experiences for those 70% of anonymous visitors on your website. Some well known examples of vendors and tools in this category include:

  • Drift
  • Qualified
  • LivePerson
  • Intercom
  • Livechat
  • ChatFunnels

Systems of Record

These tools enable marketing and sales teams to store all captured information about known website visitors and follow up with them  with sales tactics after their session has concluded. Once again, these tools cannot be effective with anonymous visitors as their core capability is based upon knowledge of the website visitor (contact information) which is stored in the system. There are numerous vendors in this category, of which the best known ones include:

  • HubSpot
  • Salesforce
  • Zoho
  • Marketo


A team of marketers and sales professionals will utilize all three categories of these tools to deliver the right experiences to buyers as they make their way through the customer journey from awareness, to consideration, to decision, and ultimately on to purchase. This “tech stack” of tools is very effective, in delivering experiences as part of a typical ABM strategy. But going back to our earlier question -- how can these systems be more effective at  ABM when the ABM is the Anonymous Buyer Marketing on your website? How can these tools be effective at all for those 70% of website visitors who remain anonymous but still  demonstrate a high intent to purchase? 

The reality is that these tools must be amplified with other data and technology that might not know the name or email address of those visitors, but can predict the 'buyer intent' of them in real-time, so you can engage and convert them before they leave your site.


The concept of uncovering the buyer intent of anonymous visitors is so powerful, we had to derive a new name for it - Anonymous Buyer Marketing.

So, how do you turn anonymous buyer marketing into revenue? It’s no simple feat to determine the buyer intent of your website visitors. In fact, it’s not something that any human can do accurately, at scale. For this, we must turn to AI and machine-learning models. They possess the unique ability to codify millions of data points, then learn based on failure and success modes. By profiling millions of visitors, and looking at thousands of historical buyer journeys that lead to purchase or leads online, they can be modelled to accurately predict the buyer intent of any given visitor. The trick is to combine this pre-trained data with real-time behavioural data for each visitor in order to predict their buyer intent “in the moment”.

Lift AI does every day for its customers like Formstack, Nitro, PointClickChare, and more, helping these companies increase chat revenue and pipeline by 2-10x. How does this happen?

First, we must determine the buyer intent of all the anonymous visitors. Your marketing efforts might recognize up to 30% of your website visitors using an intelligence or account-based marketing tool such as our Partners at 6Sense. Yet, what about the remaining 70% of anonymous visitors? 


Lift AI reveals the buyer intent of all of your visitors - for both the 30% known and the 70% anonymous. By knowing each visitor’s buyer intent, the proper marketing tactics can then be employed to engage those visitors. 

Second, by knowing the level of intent of these anonymous visitors, we can take sales action in real-time. This is critical as high-intent buyers are in the “moment of truth” -- they are ready to buy and will do so if engaged at the right time with the right tactic.

Lift AI uses a pre-trained machine-learning model to automatically assign each and every visitor a 'buyer intent score' in real-time. High intent visitors can be routed to your live chat agents immediately for the best chance of converting, while medium and low visitors can be routed to chatbots for support and nurturing.

By integrating with the systems of intelligence, action, and record, Lift AI amplifies the data of your existing tech stack. Here’s how:

Systems of Intelligence: Your ABM tools can reveal the identity of 30% of your website visitors, including any key accounts you’re targeting. Lift AI supports this by revealing the buyer intent score for each of those accounts - helping you prioritize their treatment. It’s one thing to know that Coca Cola is on your website. It’s another thing entirely to know that there’s someone from Coca Cola AND they have a high buyer intent, right now, in real-time. 

Systems of Action: Your chat tools have automated playbooks, but they are typically “one size fits all”. By that, we mean that most chat tools are set up to engage visitors on particular pages, with cookie-cutter opening lines that are the same no matter the buyer’s intent. Lift AI helps you customize those playbooks based on the visitor’s unique buyer intent. For example, a high buyer intent visitor will be directed to a live agent using  playbook A, where medium intent visitors are sent to a concierge bot and can quickly escalate to a live agent using playbook B, and low intent visitors are sent to a chatbot and self serve experience using playbook C. 

Systems of Record: Your CRM tools contain all the information about your contacts. This information is primarily used for analytics, future sales follow-up, or marketing automation. Lift AI helps you store the buyer intent information for each known contact so you can prioritize follow-up and marketing automation with those particular contacts. This is especially powerful when there was a key account on your website that also had a high buyer intent, but you didn’t have the workforce available to engage them with the right playbook while they were on the site. You missed them. But, now you can follow-up with those visitors sooner than you would have otherwise, as you know they’re recorded in your CRM as having been on the site AND had a strong buyer intent. 

When ABM  is really Anonymous Buyer Marketing, you need to reveal the unique buying intent of every visitor on your website (especially those anonymous ones), so you can create the right experience and playbook for each visitor based on their likelihood to convert.

You can try Lift AI free for 30 days as well. Just sign up and copy-paste a small JavaScript snippet to your website, and Lift AI would automatically integrate with your chat platform. 

Accurate  scoring with anonymous buyer intent will make predicting sales and planning your overall ABM strategy much easier. Learn more how AI and machine-learning tools such as Lift AI are able to boost conversions without any extra human resource expenditures involved and give you more control over your ABM success. 

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