Don’t you just love it when someone anticipates your needs? The waiter asks if you’d like another drink. A new hire takes initiative. The Uber driver plays anything by Akon. 

Well, guess what? Your leads like it too. 

Intent-based targeting delivers timely, personalized experiences at scale and helps you close more deals.   

What Is Intent-Based Targeting?

Intent-based targeting is when businesses create tailored experiences for leads based on their online behavior. 

Say a lead searches for “affordable B2B database tools” on Google or another search engine. A sales rep then emails them an infographic breaking down the pricing structures of three low-cost B2B databases. 

Is this spying? Perhaps. But it helps your leads get the information they need. 

That lead who received your helpful infographic will be thankful. You just cut their research time in half. You improved the user experience. Do this enough and they’ll start to trust you as an advisor (or a mind reader)—which only increases the chances they’ll buy from you later.   

Marketers and salespeople track various lead activities to estimate user intent and inform their outreach.

Below are some common sales signals you might use to power intent-based targeting:

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  Downloading a white paper, pricing guide, or case study 

  
  
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  Clicking on a free demo link in a cold email 

  
  
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  Spending several minutes on a product page on your site

  
  
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  Visiting product comparison or competitor sites

  
  
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  Liking a feature release (or similar) post on social media 

  
  

By using such signals to identify high-intent buyers, you help your sales and marketing teams focus their efforts on accounts that show real interest. You also gain insight into each lead’s specific needs, which helps you deliver highly personalized outreach at opportune times. 

In addition, don’t forget the importance of sales software. SaaS tools play a crucial role in intent-based B2B marketing and sales.

Sales and marketing automation tools automatically track lead activity and intent data. They then analyze this information to predict buying intent. Some even trigger automated outreach based on these estimates. 

How SaaS Teams Use Intent-Based Targeting

SaaS teams use intent-based targeting to improve conversions for in-market buyers and leads in the consideration phase of purchase. 

Here are some examples of how SaaS teams use intent-based targeting: 

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  A CRM provider sees a spike in visits to their pricing page and immediately triggers a personalized outbound sequence using sales automation tools.

  
  
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  A product-led growth (PLG) startup uses third-party data from B2B data providers to identify which companies are researching their competitors.

  
  
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  A sales engagement platform spots increased traffic to its “comparison” blog posts and prioritizes outreach to those companies.

  
  
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  A real estate tech brand uses Google Analytics data to identify common pain points among a segment of its audience before sending outreach to them. 

  
  

Why Is Intent-Based Targeting Important?

When done correctly, intent-based targeting can dramatically improve your sales team’s precision, speed, and conversion rates. 

Precision: Focus on the Right Accounts

Car salespeople develop a sixth sense for the dollar signs above any person who walks into their shop. 

While you may not be able to conclude a lead’s likelihood of converting from their facial expressions, you can use intent data to form your own digital sixth sense. 

Did a lead spend two minutes on a product page? Replied to an email? Asked for a demo? Time to follow up. 

By removing the guesswork from audience selection, intent-based targeting helps sales and marketing teams zero in on the right accounts and avoid sinking time into unqualified leads. 

Automate your outbound with AI employees

Equip your team with the best-in-class outbound tools and our AI BDR Ava, who automates your entire outbound workflow.

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Speed: Act on Buying Signals in Real Time

Sales teams use sales automation software to act on buying signals in real time. Automated outreach campaigns activate when a lead reaches a certain threshold of buying intent or takes a relevant action. 

This fast “speed-to-lead approach” ensures your potential buyers receive the information they need exactly when they need it, leading to higher conversions and less drop-off to competitors. 

Conversion: Trigger Outreach at the Moment of Interest

Customers want you to take their situation into account when you send them sales messages. In fact, 71% of customers expect personalized interactions from businesses. 

Intent-based targeting is like having a team oracle who offers accurate predictions about what your leads need most from your brand at any given moment. 

As a result, a lead researching your tool’s integrations receives relevant content about integrations, not some unrelated feature. This alignment between your messaging and the lead’s current phase in the buyer journey boosts outreach relevancy. And that generates more positive replies. 

Some tools go a step further than predicting the lead’s intent. AI sales platforms use those predictions to conduct the outreach. For example, Artisan’s automated follow-up feature sends personalized emails to leads it determines to be qualified.

How to Build an Intent-Based Strategy

Let’s look at the six key steps for building an intent-based sales strategy that consistently generates, nurtures, and converts your leads. 

Define Your ICP and Intent Criteria

Clearly defining your ideal customer profile (ICP) is the first stage of any successful intent-based campaign. 

A lead’s buyer intent is based on two major factors:

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  Fit: How well the lead fits your ICP based on a detailed description of your ideal customer in terms of demographics, firmographics, technographics, and other details.

  
  
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  Behavior: The activities that clue you into customer intent, such as visiting a specific product page or spending enough time on a blog post.  

  
  

To create your ICP, review the makeup of your best customers (the ones who get the most value from your solution). 

Use this data to build a comprehensive document outlining their industry, company headcount, revenue numbers, technology use, and other details that will help you pick good-fit accounts out of a crowd. 

As for intent criteria, consider the common buying patterns and triggers of your ideal customers. What are the steps towards a purchase? You can discover these by reviewing the online journeys of past customers, either in your CRM or via surveys and interviews with your clients. 

In your hunt for common buying triggers, answer the following questions:

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  What content did they read right before reaching out to a rep? 

  
  
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  What websites did they visit to learn how to solve their problem?

  
  
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  What web searches did they make?

  
  
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  Which pages on your website led them to book a demo? 

  
  

Actions that commonly precede a sale are the raw material of your buying intent predictions, and they will act as the triggers of targeted outreach. 

Gather Intent Data (Signals)

Now that you’ve determined your intent criteria, it’s time to start collecting B2B intent data, also known as buying signals. 

Your sales automation platform will use these signals to score leads, predict a lead’s intent, and trigger automated outreach. 

There are two types of intent-based B2B data:

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  First-party data: Data you collect from your site using cookie tracking, web forms, sales and marketing platforms, and tools like Google Analytics. Examples include repeat website visits, content downloads, scroll depth, navigation paths, and more. 

  
  
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  Third-party data: First-party data usually isn’t enough to get a comprehensive profile of your leads, so companies also use reputable lead data providers like Bombora, G2, and other platforms that specialize in B2B data. 

  
  

Remember that you might already be capturing a lot of first-party intent data in your various sales, marketing, and customer support platforms without being aware of it. For example, a lead clicking on a link in a marketing campaign email is likely a buying signal. 

Make sure to connect these data silos and collect all intent data in a central hub. For most B2B companies, that hub is their CRM or marketing automation platform.

Identify Engaged Accounts

Once you have signal data coming in, it’s important to track that activity over time and use it to make predictions about each lead’s level of purchase intent. This is how you start to spot the engaged accounts. 

Here’s how to make sense of all that intent data coming your way:

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  Build lead intent scoring models: These automated models score leads based on intent data. Typically, they weigh different signals based on their predictive value. 

  
  
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  Create a score threshold: Choose a threshold that qualifies an account as engaged. Now, when a lead hits this predetermined score (say, 70/100), lead scoring systems automatically trigger automations, such as notifying a sales rep. 

  
  
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  Integrate signals with AI sales tools: This is by far the most hands-off approach. First,  connect your outreach automation tool with your signal data. An outreach tool like Artisan can then analyze this data, uncover a lead’s engagement level (shown below), and send them personalized outreach. 

  
  

Prioritize Your Hottest Prospects

Not all signals are created equal. For example, a free trial sign-up is usually far more predictive of a future purchase than a download of your latest ebook. That’s why businesses assign different weights to each signal. 

For example, a scoring model might include the following buying signals and weights:

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  Download an ebook: +2

  
  
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  Download a pricing guide: +3

  
  
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  Sign up for a free trial: +10 

  
  
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  Open 10 nurturing emails: +5

  
  

Within your platform, create score thresholds that determine what type of content is sent to a lead. 

For example, a lead with a score of nine or below might remain in an email nurturing sequence. Meanwhile, a lead with a score of ten or above will auto-trigger a notification to a sales rep, who will reach out to book a meeting. 

Finally, don’t forget to align these scoring models with your overall demand generation strategy. It’s important to account for the hottest touchpoints at all stages of your funnel, such as repeatedly commenting on a LinkedIn post.

Personalize Outreach and Content

It’s one thing to estimate a lead’s buying intent. It’s another to send them personalized content that shows you recognize their interests, struggles, and goals. 

Here are some examples of using signals to tailor outreach: 

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  If a cold lead downloads a white paper about a specific function of your product, send them an automated email that talks about related features. 

  
  
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  If a prospect comments on a feature announcement, follow up on LinkedIn to ask about pain points related to that feature. 

  
  
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  If a free trial customer watched a webinar breaking down your premium package, call them asking if they’d be interested in a live demo.  

  
  

Increasingly, companies are turning to AI sales automation platforms to scale personalized outreach. For example, Artisan’s AI BDR named Ava tracks leads’ web and social media activity and sends personalized LinkedIn and email messages. All without any human intervention. 

Measure and Refine

Ongoing measurement of the effectiveness of your intent model is key. Identify which predictions prove correct, and then make iterative tweaks to your models to improve forecasting efficacy. 

Here are the main methods for optimizing your intent-based targeting model: 

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  Track signal-to-conversion rates: Monitor which intent signals (and combinations of signals) correlate most strongly with your closed-won deals. Also, track conversion rates for different combinations of intent signals. 

  
  
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  Schedule regular model reviews: Every quarter, review model performance. Analyze won deals and lost deals against the account’s past intent signals. Look for patterns in deals that closed successfully without giving off any intent signals, and vice versa. 

  
  
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  Make adjustments to signal weights: Decrease the weight of signals that aren’t correlating with closed deals or eliminate them entirely. And increase the role of signals with a strong predictive value.

  
  
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  Integrate sales rep feedback: Set up communication lines between sales and whoever is responsible for the intent model. Reps can flag false positives, and this field intel will help your team improve the model. 

  
  

Sometimes your automated outreach might be misaligned with the lead's actual interests. This occurs because you’ve misunderstood their intent and misread the signals.

If any of your outbound campaigns have comparatively low engagement, re-evaluate your conclusions about the desires of the leads who take a specific action. Then try alternative outreach messages. If you see an uptick in conversions, your content now better matches intent. 

Automate Outreach That Works With AI

Companies running intent-based marketing and sales strategies often give leads the odd feeling that you’re in their head. “How did they know I wanted to learn more about exactly that?” 

Artisan helps you implement intent-based targeting without having to learn a bunch of intent-based marketing tools and workflows. 

After an easy initial set-up, the platform’s AI BDR, named Ava, automatically tracks leads’ behavior, qualifies them, and sends personalized outreach via LinkedIn and email. The result is a consistent stream of high-intent marketing-qualified leads. 

Automate your outbound with AI employees

Equip your team with the best-in-class outbound tools and our AI BDR Ava, who automates your entire outbound workflow.

Yes! I want to book a demo.