Most leads arrive at your website somewhat interested in your company. But they’re still in research mode. Only after a period of nurturing are they ready for a meeting with a sales rep.

The problem? Lead nurturing is a lot of work. 

You have to track each lead’s ever-changing interests, send them relevant information (usually across multiple channels), and monitor the results.

That’s why sales teams are automating lead nurturing with AI sales tools. And they’re seeing incredible results. 

Understanding AI Lead Nurturing

Let’s look at what AI lead nurturing is, how it works, and why it’s one of the most talked-about topics in sales at the moment. 

What Is AI Lead Nurturing?

AI lead nurturing involves using artificial intelligence to automate the ongoing process of engaging leads. Sales teams configure AI lead nurturing tools like AI BDR platforms to send the right messages to the right leads at the right times. The ultimate goal is to consistently turn unqualified leads into sales prospects without human intervention.  

AI lead nurturing platforms take over the following tasks:  

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  Qualifying, scoring, and segmenting leads

  
  
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  Researching leads across social media and the web

  
  
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  Creating and running personalized omnichannel sequences

  
  
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  Following up with leads that take specific actions 

  
  
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  Optimizing outreach based on lead behavior, engagement metrics, and buying intent  

  
  

AI lead nurturing builds on traditional lead generation and lead nurturing techniques, such as email marketing workflows, by adding more intelligent automation. 

Whereas an email marketing tool might send a pre-written series of emails to a new lead, an AI lead nurturing tool researches that lead and creates a tailored omnichannel sequence specifically for them. This is just one example of how AI kicks up the level of relevancy.

Why AI Lead Nurturing Matters for Modern Sales

Sales reps are overworked. Managing outbound lead gen, as well as nurturing tasks, is downright overwhelming. There’s too much outreach to write, send, and track on any given day. 

This limits their ability to execute all lead nurturing tasks at scale. And a level of scale is almost always needed to bear fruit. 

Routine tasks that sales reps struggle to scale include:

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  Sending timely follow-ups

  
  
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  Personalizing nurturing emails for each lead

  
  
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  Tweaking their outreach sequences based on engagement levels 

  
  
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  Executing complicated multi-step sales workflows

  
  

AI takes over these repetitive tasks, automating personalized lead nurturing at scale. This speeds up the rate at which qualified leads fly through the sales funnel. 

It also enables sales professionals to spend more time building relationships with interested prospects and less time persuading potential customers to finally take that sales meeting. 

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Benefits of AI-Powered Lead Nurturing

AI lead nurturing helps modern sales teams scale their efforts without losing the human touch. 

It covers all of the following areas: 

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  Behavior-based personalization: AI uses real-time engagement signals to tailor messages and timing for leads. For example, if a lead downloads a white paper and provides information about their pain points in the web form, the AI tool can tailor outreach messages accordingly. 

  
  
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  Improved conversion rates: Consistent, timely follow-ups and relevant messaging help move leads through the funnel faster. 

  
  
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  Time-saving automation: Repetitive (not to mention boring) tasks like email follow-ups, lead research, message writing, and CRM updates are handled automatically.

  
  
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  Smarter prioritization through predictive analytics: By comparing each lead to your ideal customer profile, and analyzing their online behavior, AI tools help you identify and target the highest quality leads.

  
  

Key Strategies for Effective AI Lead Nurturing

From behavior-based personalization to omnichannel engagement, here are some of the best strategies for creating an effective AI lead nurturing system. 

Leverage Behavior-Based Personalization

If a customer entered a clothing store and started trying on shoes, the store’s sales rep wouldn’t start blabbing about t-shirts. Instead, they’d measure their feet, teach them about the different shoe styles, and seek to understand their fashion preferences. 

Behavior-based personalization allows you to provide this same level of care to your potential buyers at scale and across various forms of online communication. That way, your leads always receive the educational content they need to arrive at a buying decision. 

Here are the best tactics for creating behavior-based personalization: 

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   Use AI to tailor messages based on user actions (e.g., link clicks, page visits). For example, if a lead clicks on a link in your email, that signals to the AI tool that they’re interested in that email’s content. The AI platform will then send more related messages. 

   
   
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   Segment leads by purchasing stage or persona for more relevant outreach. In practice, this could mean the tool sends first-time web visitors (awareness stage) top-of-funnel content, but sends those who downloaded a white paper (consideration stage) case studies and webinar suggestions. 

   
   
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   Personalize content dynamically to boost engagement. For instance, the AI agent could discover that email open rates are highest for a specific lead in the morning. On that basis, it adjusts the automated cadence to send emails to this person at 9 am sharp. 

   
   

96% of marketers agree that personalization positively impacts a company’s sales. By boosting the relevancy of your outreach, behavior-based personalization improves the customer experience and does wonders for converting MQLs to SQLs. 

Integrate AI with Your CRM for Data-Driven Nurturing

Connect your AI lead nurturing platform with your CRM to give it full context on each lead. This helps it prepare more personalized outreach and make smarter sequencing decisions based on lead history and status.

You’ll also avoid duplicated outreach, since the AI will be able to “see” the lead’s communication and transaction history. 

Below are some data points that will help the AI craft highly targeted messages: 

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  Company details: The company size, annual revenue, industry, and other business intel. 

  
  
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  Lead demographics: The lead’s location, gender, age, and other personal details. 

  
  
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  Purchase history: The lead's past purchases from your company, current plan, etc.

  
  
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  Past customer interactions: Past meeting/call notes logged in the CRM, content downloads tracked in your marketing automation tool, tickets in the customer support platform, etc.

  
  
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  Technographics: The technology solutions the lead’s company is using. 

  
  

How deeply your AI tool can personalize its outreach is highly dependent on how much intel you have on each lead. So it’s worth investing in data enrichment tools that use their database or web scraping abilities to flesh out your CRM company and contact records with accurate data. Some AI lead nurturing tools, like Artisan, already come with this as a feature.  

Adopt an Omnichannel Engagement Approach

If you’re only using email for nurturing, you’re leaving revenue on the table. 

Why? 

First, some of your leads will prefer other channels, like LinkedIn or SMS. 

Second, you can’t hit leads as frequently if you just use one channel. Seven cold emails across seven days is borderline stalking. But seven messages, spread across LinkedIn, email, text, and chat? That’s just called persistent, high-quality nurturing. 

AI lead nurturing platforms act as a control center from which you can run omnichannel engagement. They also ensure that all outreach messages, regardless of channel, are consistent with your brand and highly personalized.

For example, Artisan has a suite of multichannel outreach features for sending personalized messages across email and LinkedIn. All on autopilot. If a lead replies to an email, AI BDR Ava will take that into account when crafting the next LinkedIn message. 

Implement Dynamic Workflows and Timely Follow-Ups

Leads go cold quickly. 

It’s best to reach out immediately after they’ve shown interest. In fact, according to a lead response study by LeadResponseManagement.org, the success rate of contacting a lead drops significantly within the first hour after they show interest, decreasing more than tenfold.

AI lead nurturing platforms contact your leads at the right time—typically, that means immediately after a successful lead generation. They then continue to reach out to the lead over the long term, keeping your business top of mind. 

Here are the main pointers to keep in mind when setting up an automated follow-up and nurturing workflow:

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  Set triggers for follow-up emails based on engagement or inactivity. 

  
  
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  Create multi-channel sequences that adapt to lead actions. 

  
  
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  Test outreach delivery times to find when leads are most responsive. 

  
  
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  Configure real-time alerts for reps when leads signal high intent.

  
  

Make full use of all the features available in your platform. A tool like Artisan, for example, can identify your anonymous web visitors with its Website Visitor Tracking feature, qualify them, and, if they pass the test, send them targeted messages related to their web behavior. 

Compared to the standard approach of having a human rep reach out whenever a lead downloads an ebook or visits your site, this AI-driven approach is far more reliable. 

An AI tool is never on vacation when a lead needs guidance most. As a result, you lose fewer sales due to slow reaction time. 

Utilize Predictive Analytics for Lead Scoring

Most AI lead nurturing tools use machine learning to power predictive analytics, which allows them to automatically score leads in terms of how likely they are to buy from you. 

These tools analyze a lead’s online behavior and demographics, as well as your company’s historical sales data to assign a score. This helps the tool—and your sales reps—prioritize outreach to the leads most likely to convert. No more preparing for a meeting for a lead who didn’t care in the first place. 

AI lead nurturing tools also optimize their predictive models over time. They automatically compare their predictions with actual results and fine-tune accordingly. For example, the AI might add weight to scoring criteria like job title, or demote the importance of the lead’s industry, then see if that tweak creates more accurate predictions.  

Implementing AI Lead Nurturing in Your Outbound Strategy

Let’s look at a plan for setting up an AI lead nurturing system that supports your current outbound sales strategy. 

Prepare Your Data and Integrate Your CRM

To start taking advantage of AI lead nurturing, you first need to prepare your data and integrate it into your CRM. This is because your chosen AI nurturing tool will use CRM data to make decisions about how to interact with your leads. 

Here’s how to prepare your CRM data: 

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   Clean lead data in your CRM. Consider using a B2B data enrichment tool to continuously verify and update your contact and company records with fresh data. 

   
   
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   Segment your leads effectively. Organize your leads into groups by factors like industry, company size, and job title to allow for more targeted lead nurturing efforts.  

   
   
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   Connect AI tools to access full lead context. Most AI lead nurturing tools integrate with popular CRMs. Set up the integration so data flows smoothly between platforms. 

   
   
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   Set up event tracking (clicks, visits) for smarter triggers. Implement event tracking for key lead behaviors like email opens and content downloads to trigger personalized, automated email follow-ups. 

   
   
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   Establish hands-off rules. Decide which indicators suggest a lead is ready to speak to a human rep, and determine how that hand-off will be done. You can usually set up automatic notifications that loop in reps when a lead is assigned a certain score. 

   
   

Depending on your platform, you may also want to define lead scoring criteria, implement compliance safeguards, and build content libraries of your case studies, blogs, and other relevant content that the AI can use to learn about your solutions and target audience. 

Design AI-Driven Nurture Playbooks and Workflows

Follow the steps below to set up AI-driven sales playbooks and workflows: 

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  Build sequences for different lead types and stages. For example, create persona-based email campaigns tailored to specific industries, company types, and job titles. 

  
  
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  Define triggers and branching logic for each step. Set up behavioral triggers that auto-send messages when a lead visits a certain web page, clicks a link, or downloads a resource. Create content tracks that shift based on the lead’s response to this outreach.   

  
  
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  Integrate cross-channel touchpoints. Run omnichannel outreach sequences that engage buyers across social, email, SMS, and other mediums. Consider adding a “call lead” step to the sequence, which will notify a sales rep to place a call. 

  
  

A tool like Artisan allows you to instruct your AI BDR to use a specific sales style when creating sequences with its Playbooks feature. Examples include the Uno Reverse, which engages leads with thought-provoking questions, and the Ultrahuman, which talks to leads like you would a friend at the bar. 

Train and Monitor Your AI Assistant

AI sales tools aren’t born geniuses. 

Sure, AI BDRs and SDRs can be proficient out of the gate. But most of the time, as with any sales rep, you have to train them. That means monitoring output and identifying ways to tweak workflows, inputs, and configurations for better performance.  

Here’s how to train your AI tool:

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  Feed the AI your tone, messaging examples, and escalation rules. Teach your AI what works and how to engage with prospects by feeding it case studies, product white papers, content guidelines, and your most successful sales emails and messages.  

  
  
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  Monitor early messages and adjust as needed. When you first launch your AI lead nurturing platform, read its messages. Based on what you like and dislike, adjust the tool’s settings and your knowledge base (source material) until the AI gives you the outputs you want. Soon, it’ll be able to operate with less oversight.  

  
  
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  Set up feedback loops and regular reviews. Establish an AI review cycle, weekly at first, then quarterly once the tool is functioning as you’d like. During these reviews, analyze performance metrics and find areas for improvement. 

  
  

Track Performance and Continuously Optimize

Despite being highly automated, you still shouldn’t think of your AI lead nurturing approach as a set-and-forget system. To get the most out of your AI-driven campaigns, you should track performance and find ways to optimize the system.

Here’s how to optimize continuously: 

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  Measure open, reply, and conversion rates. Low reply rates? Perhaps you need to refine your AI email strategy. That might mean giving the AI a better email template or feeding it successful sales emails that have worked for you in the past. 

  
  
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  Run A/B tests on subject lines, timing, and cadence. This helps you identify ideal outreach strategies. Some AI tools run A/B tests in the background. 

  
  
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  Regularly refine workflows based on performance data. If your more laid-back emails are performing better than formal-toned ones, instruct the AI to use an informal tone across all channels. 

  
  

If you do this consistently, over enough time, your AI lead nurturing strategy will march steadily towards perfection. 

How Artisan Simplifies AI-Powered Nurturing

Artisan is an AI-powered sales platform that automates B2B lead generation and nurturing with an AI BDR named Ava.

Ava can autonomously execute all of the following tasks: 

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  Automate multichannel outreach sequences (email and LinkedIn)

  
  
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  Personalize outreach using multiple data sources and behavior tracking

  
  
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  Optimize outreach based on consistent self-testing

  
  
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  Score leads and qualify them based on their behavior and ICP-fit

  
  

Artisan also comes with built-in tools for email deliverability optimization and engagement analytics, making it easy to track and improve performance. 

Artisan’s AI BDR technology represents the next step in sales automation. Users can hand off the beginning and middle stages of their sales process to an AI BDR without any loss in quality. This enables sales reps to focus on essential human tasks like meetings. 

Embracing AI Lead Nurturing for Outbound Success

Time spent manually nurturing leads is time wasted. Sales reps don’t need to track lead activity, monitor scores, and write and send follow-ups.

AI lead generation and nurturing tools do this for you. 

Platforms like Artisan track lead behavior, send targeted messaging, and react to lead responses, slowly nurturing them to a purchase with relevant emails and LinkedIn messages. 

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.