5 clever ways to use AI for lead generation

Chances are, your lead gen process is outdated if it's not leveraging AI. This article shows you how.

Fred Melanson

October 19, 2022
·
3
 min read

Too many companies leave money on the table because they can’t generate the right leads. Poorly qualified leads send sales teams down dead ends. Even with the right lead, sales doesn’t always have the right insights they need to close the deals.

How many times has your head hit the desk just trying to understand your leads?

You’ve got some information in the CRM.

Then you have to ask the data team to pull product usage activity.

Then you need to know what marketing emails the lead responded to.

Man banging his head against a desk

Lead generation powered by artificial intelligence does all this for you by seamlessly linking data silos into an easy interface.

By qualifying the right leads and delivering actionable insights, AI lead generation tools empower sales and marketing, shorten time-to-value, maximize conversion rates, and drive growth.

Here’s everything you need to know about how AI lead generation can accelerate your revenue growth.

What is AI lead generation?

AI lead generation lets companies identify and develop high-quality, high-intent leads.

These systems analyze more data from more sources than humanly possible, freeing time for sales and marketing teams to engage with qualified leads meaningfully.

With traditional lead generation strategies, pulling genuine leads from large pools of prospects is too time-consuming.

The problem is that too much data comes in from email marketing campaigns, CRM systems, outbound cold-calling, content marketing, and more.

And that ignores all the internal data available from other data silos like support or product.

There’s just too much data for people to process.

Aggressive filtering is the only way to make traditional lead-generation processes manageable.

Think about it this way. You’ve probably seen entry-level job postings that require:

  • Multiple advanced degrees (or “equivalent” work history). 😮
  • Familiarity with a combination of enterprise systems only used by that employer. 😯
  • Five years of experience with a technology released last year. 😱

HR departments do this to narrow their funnel of high qualified candidates. People don’t bother applying, which makes the pool of applicants easier to handle.

Of course, it also means amazing people never get considered. 😢

How many amazing leads does your lead-generation process filter out? 🤔

Different types of lead funnels

Artificial intelligence doesn’t get bored, doesn’t get tired, and doesn’t skip leads.

Letting AI tools do what they do best automates the drudge work at scale. Every data silo gets included in the analysis. AI algorithms evaluate every prospect constantly.

Freed from their spreadsheets, sales and marketing teams can dedicate more time to high-value engagement with their leads.

And that engagement is enriched by the insights AI lead generation software produces to make campaigns more effective and sales calls more productive.

It’s no wonder you’ll find these AI tools in action at the top product-led companies.

Who’s winning with AI lead generation?

Self-serve B2B sales motions are only one part of the Product-Led Growth model. Companies like Voiceflow, Jasper, Netlify all empower salespeople with AI-generated leads and insights.

Winning companies like these use AI to give sales teams what they need to engage with users immediately.

AI also helps their AEs convert enterprise accounts by making reaching an account’s decision-makers easier.

Adopting AI lead generation is one of the secret sauces that transform Product-Led Growth companies.

AI lead gen + PLG = superpower

In the hands of Product-Led Growth companies, AI lead generation becomes a superpower that accelerates them ahead of the competition.  🦸🏻‍♀️

PLG business models create a goldmine of product usage data: you know who uses your product and understand how they use it.

AI lead generation combines real-time customer behavior with firmographic data and other sources to create Product-Qualified Leads:

🎓 PQL = customers aligned with Ideal Customer Profiles whose behavior shows they are ready for sales engagement.

Unlike traditional lead scoring, AI makes connections between vast product data sets and conversion events that salespeople can’t make. For example:

  • Looking at past customers and they’re actions. 
  • Correlations between multiple specific actions taken in the product.
  • Predicting trends and likeliness to convert. 
  • Find consolidation opportunities otherwise missed. 

Empowered by AI-generated PQLs, sales teams can move the customer to a higher tier, combine users in a team account, and convert teams to enterprise accounts.

Voiceflow is a collaborative platform for developing conversational assistants in call centers, mobile apps, and other applications. Using Calixa’s AI-powered insights, Voiceflow’s sales and marketing teams enhance their own customer conversations.

Previously, Voiceflow’s patchwork of databases and services couldn’t deliver the leads they needed:

“It was a black box. We didn’t have any idea how prospects were using Voiceflow or even a means of easily seeing which trials were active and expiring.”

Calixa lets Voiceflow’s AEs understand where customers are in the sales funnel. Product-qualified leads and behavior-driven insights give AEs the tools they need when engaging with customers.

“We can see user actions and figure out how to advance them in the customer journey. Our conversation focuses on key features to help them.”

AI lead generation increased Voiceflow’s business book and boosted sales productivity. Next, we’ll check out how AI can power your SaaS growth.

5 ways to use AI for lead generation in product-led SaaS

Whether uncovering new customers or refining the customer experience, AI lead generation raises product-led SaaS companies to new performance levels. Here are five ways you can use AI lead generation to improve your business.

1. Use a PLS tool to find revenue opportunities 💰

Without AI, analysis runs into a wall: people have limited attention spans. They can only process so much data before they glaze over.

That leaves money on the table.

With AI-generated insights marketing can optimize messaging and content for every target audience.

AI-driven engagements compress time-to-value for free self-serve users, easing them along the path to paid subscriptions.

AI tools like Calixa let you turn missed opportunities into new sources of revenue growth.

2. Use AI to qualify leads 💡

AI-powered solutions streamline lead qualification so sales teams get more actionable information and close deals faster.

Machine learning models an Ideal Customer Profile (ICP) based on existing customer behavior and your SaaS product’s features.

The AI system uses the ICP to decide which users and accounts are the best fit for sales engagement.

High-quality, high-intent PQLs are primed for that next step. All they need is a little TLC from sales.

Quality PQLs would be enough to make AI lead-gen a no-brainer. But there’s more.

Machine learning looks beyond the customers you know you want. It combines patterns in customer behavior with company information to spot customer profiles you never considered.

These new ICPs actively use the product even though they haven’t gotten a lot of attention.

Calixa and other AI lead-gen tools reveal these untapped customers so, with a little care and tracking, these ICPs will drive revenue growth.

3. Enrich leads with AI-driven insights 🤓

AI-generated leads arrive with rich insights that people can actually use.

Old approaches gave marketing teams buckets of contacts based on rough firmographic and demographic analysis.

With AI technology, marketing teams know how each contact will respond to the right campaign.

Old-school lead generation tools gave salespeople a starting point but not a lot more. But nobody really understood what a score meant. Nobody really knew where the user was on their product adoption journey.

AI-powered leads tell sales teams exactly where accounts are, how they use the product, and what they need to advance in the sales funnel.

Empowered with these insights, sales calls stop being fact-finding missions.

Instead, sales engagements start with precisely the information users need when they need it.

Insights based on product usage make sales engagements helpful conversations that users welcome.

4. Personalize user experiences 🧑‍🦰👨🏿🧑🏽‍🦳

Product-led sales allows personalization at scale. Mass market techniques just don’t cut it.

The more a user’s experience and needs align with, the faster they advance through the sales funnel.

AI-powered insights into user behavior let you understand their needs and motivations.

In effect, marketing campaigns and sales engagements become one-to-one conversations that potential customers value.

5. Improve chatbots in your product to qualify users 🤖

A top priority for AI-driven personalization are the chatbots you deploy to your website and product.

Chatbots use Natural Language Processing to let website visitors and users interact with your company on their terms while freeing reps from low-value engagements.

But a chatbot that gives the same canned responses to everything frustrates people and turns them off your product.

Artificial intelligence improves your chatbot by tailoring the customer experience to each interaction.

Behavior-based insights let you develop more nuanced templates that deliver more personalized responses.

As a result, AI chatbots cover a wider variety of interactions without handing user that are either unqualified or not sales-ready over to reps.

Finally, an in-product chatbot’s cross-selling and upselling pitches, now matched to the user’s product usage, can increase revenue growth.

Conclusion: You’re missing out. Get to work!

Too much data is siloed in too many systems for consistent, high-quality lead generation. As a result, you:

  • Miss opportunities you never knew existed.
  • Leave high-intent leads sitting without sales engagement.
  • Rely on less effective messaging and content.

Leaving money on the table depresses growth and lets competitors take the slack. 😩

If you want to win in today’s PLG SaaS markets, you must win every opportunity from free signups to converting named accounts. 🏆

Calixa’s AI-powered product-led sales platform delivers the real-time insights you need to engage with product-qualified leads and drive revenue growth. 

Calixa AI-powered prospecting

If you want a better understanding of Calixa’s approach to product-led sales, read these articles about:

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Advice for Growth

5 clever ways to use AI for lead generation

Chances are, your lead gen process is outdated if it's not leveraging AI. This article shows you how.

Fred Melanson
|
Director of Content
|
Calixa

Subscribe to High Intent

Your PLG roundup in 5 minutes.

October 19, 2022
ReadTime

Too many companies leave money on the table because they can’t generate the right leads. Poorly qualified leads send sales teams down dead ends. Even with the right lead, sales doesn’t always have the right insights they need to close the deals.

How many times has your head hit the desk just trying to understand your leads?

You’ve got some information in the CRM.

Then you have to ask the data team to pull product usage activity.

Then you need to know what marketing emails the lead responded to.

Man banging his head against a desk

Lead generation powered by artificial intelligence does all this for you by seamlessly linking data silos into an easy interface.

By qualifying the right leads and delivering actionable insights, AI lead generation tools empower sales and marketing, shorten time-to-value, maximize conversion rates, and drive growth.

Here’s everything you need to know about how AI lead generation can accelerate your revenue growth.

What is AI lead generation?

AI lead generation lets companies identify and develop high-quality, high-intent leads.

These systems analyze more data from more sources than humanly possible, freeing time for sales and marketing teams to engage with qualified leads meaningfully.

With traditional lead generation strategies, pulling genuine leads from large pools of prospects is too time-consuming.

The problem is that too much data comes in from email marketing campaigns, CRM systems, outbound cold-calling, content marketing, and more.

And that ignores all the internal data available from other data silos like support or product.

There’s just too much data for people to process.

Aggressive filtering is the only way to make traditional lead-generation processes manageable.

Think about it this way. You’ve probably seen entry-level job postings that require:

  • Multiple advanced degrees (or “equivalent” work history). 😮
  • Familiarity with a combination of enterprise systems only used by that employer. 😯
  • Five years of experience with a technology released last year. 😱

HR departments do this to narrow their funnel of high qualified candidates. People don’t bother applying, which makes the pool of applicants easier to handle.

Of course, it also means amazing people never get considered. 😢

How many amazing leads does your lead-generation process filter out? 🤔

Different types of lead funnels

Artificial intelligence doesn’t get bored, doesn’t get tired, and doesn’t skip leads.

Letting AI tools do what they do best automates the drudge work at scale. Every data silo gets included in the analysis. AI algorithms evaluate every prospect constantly.

Freed from their spreadsheets, sales and marketing teams can dedicate more time to high-value engagement with their leads.

And that engagement is enriched by the insights AI lead generation software produces to make campaigns more effective and sales calls more productive.

It’s no wonder you’ll find these AI tools in action at the top product-led companies.

Who’s winning with AI lead generation?

Self-serve B2B sales motions are only one part of the Product-Led Growth model. Companies like Voiceflow, Jasper, Netlify all empower salespeople with AI-generated leads and insights.

Winning companies like these use AI to give sales teams what they need to engage with users immediately.

AI also helps their AEs convert enterprise accounts by making reaching an account’s decision-makers easier.

Adopting AI lead generation is one of the secret sauces that transform Product-Led Growth companies.

AI lead gen + PLG = superpower

In the hands of Product-Led Growth companies, AI lead generation becomes a superpower that accelerates them ahead of the competition.  🦸🏻‍♀️

PLG business models create a goldmine of product usage data: you know who uses your product and understand how they use it.

AI lead generation combines real-time customer behavior with firmographic data and other sources to create Product-Qualified Leads:

🎓 PQL = customers aligned with Ideal Customer Profiles whose behavior shows they are ready for sales engagement.

Unlike traditional lead scoring, AI makes connections between vast product data sets and conversion events that salespeople can’t make. For example:

  • Looking at past customers and they’re actions. 
  • Correlations between multiple specific actions taken in the product.
  • Predicting trends and likeliness to convert. 
  • Find consolidation opportunities otherwise missed. 

Empowered by AI-generated PQLs, sales teams can move the customer to a higher tier, combine users in a team account, and convert teams to enterprise accounts.

Voiceflow is a collaborative platform for developing conversational assistants in call centers, mobile apps, and other applications. Using Calixa’s AI-powered insights, Voiceflow’s sales and marketing teams enhance their own customer conversations.

Previously, Voiceflow’s patchwork of databases and services couldn’t deliver the leads they needed:

“It was a black box. We didn’t have any idea how prospects were using Voiceflow or even a means of easily seeing which trials were active and expiring.”

Calixa lets Voiceflow’s AEs understand where customers are in the sales funnel. Product-qualified leads and behavior-driven insights give AEs the tools they need when engaging with customers.

“We can see user actions and figure out how to advance them in the customer journey. Our conversation focuses on key features to help them.”

AI lead generation increased Voiceflow’s business book and boosted sales productivity. Next, we’ll check out how AI can power your SaaS growth.

5 ways to use AI for lead generation in product-led SaaS

Whether uncovering new customers or refining the customer experience, AI lead generation raises product-led SaaS companies to new performance levels. Here are five ways you can use AI lead generation to improve your business.

1. Use a PLS tool to find revenue opportunities 💰

Without AI, analysis runs into a wall: people have limited attention spans. They can only process so much data before they glaze over.

That leaves money on the table.

With AI-generated insights marketing can optimize messaging and content for every target audience.

AI-driven engagements compress time-to-value for free self-serve users, easing them along the path to paid subscriptions.

AI tools like Calixa let you turn missed opportunities into new sources of revenue growth.

2. Use AI to qualify leads 💡

AI-powered solutions streamline lead qualification so sales teams get more actionable information and close deals faster.

Machine learning models an Ideal Customer Profile (ICP) based on existing customer behavior and your SaaS product’s features.

The AI system uses the ICP to decide which users and accounts are the best fit for sales engagement.

High-quality, high-intent PQLs are primed for that next step. All they need is a little TLC from sales.

Quality PQLs would be enough to make AI lead-gen a no-brainer. But there’s more.

Machine learning looks beyond the customers you know you want. It combines patterns in customer behavior with company information to spot customer profiles you never considered.

These new ICPs actively use the product even though they haven’t gotten a lot of attention.

Calixa and other AI lead-gen tools reveal these untapped customers so, with a little care and tracking, these ICPs will drive revenue growth.

3. Enrich leads with AI-driven insights 🤓

AI-generated leads arrive with rich insights that people can actually use.

Old approaches gave marketing teams buckets of contacts based on rough firmographic and demographic analysis.

With AI technology, marketing teams know how each contact will respond to the right campaign.

Old-school lead generation tools gave salespeople a starting point but not a lot more. But nobody really understood what a score meant. Nobody really knew where the user was on their product adoption journey.

AI-powered leads tell sales teams exactly where accounts are, how they use the product, and what they need to advance in the sales funnel.

Empowered with these insights, sales calls stop being fact-finding missions.

Instead, sales engagements start with precisely the information users need when they need it.

Insights based on product usage make sales engagements helpful conversations that users welcome.

4. Personalize user experiences 🧑‍🦰👨🏿🧑🏽‍🦳

Product-led sales allows personalization at scale. Mass market techniques just don’t cut it.

The more a user’s experience and needs align with, the faster they advance through the sales funnel.

AI-powered insights into user behavior let you understand their needs and motivations.

In effect, marketing campaigns and sales engagements become one-to-one conversations that potential customers value.

5. Improve chatbots in your product to qualify users 🤖

A top priority for AI-driven personalization are the chatbots you deploy to your website and product.

Chatbots use Natural Language Processing to let website visitors and users interact with your company on their terms while freeing reps from low-value engagements.

But a chatbot that gives the same canned responses to everything frustrates people and turns them off your product.

Artificial intelligence improves your chatbot by tailoring the customer experience to each interaction.

Behavior-based insights let you develop more nuanced templates that deliver more personalized responses.

As a result, AI chatbots cover a wider variety of interactions without handing user that are either unqualified or not sales-ready over to reps.

Finally, an in-product chatbot’s cross-selling and upselling pitches, now matched to the user’s product usage, can increase revenue growth.

Conclusion: You’re missing out. Get to work!

Too much data is siloed in too many systems for consistent, high-quality lead generation. As a result, you:

  • Miss opportunities you never knew existed.
  • Leave high-intent leads sitting without sales engagement.
  • Rely on less effective messaging and content.

Leaving money on the table depresses growth and lets competitors take the slack. 😩

If you want to win in today’s PLG SaaS markets, you must win every opportunity from free signups to converting named accounts. 🏆

Calixa’s AI-powered product-led sales platform delivers the real-time insights you need to engage with product-qualified leads and drive revenue growth. 

Calixa AI-powered prospecting

If you want a better understanding of Calixa’s approach to product-led sales, read these articles about: