Create an effective AI lead generation strategy

A business can’t survive without a healthy pipeline of leads, no matter how great its products or services are. Lead generation is the process of filling your sales pipeline with qualified prospective clients, some of which will mature into paying clients as they move along the pipeline.

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The longer the sales cycle is for a business—that is, the longer it takes a prospect to become a customer—the more important it is to engage in regular lead generation to maintain a steady flow of new clients. AI is shaking up many aspects of sales and marketing, and AI lead generation is no exception. By using AI tools to generate leads, businesses can dramatically reduce the time and resources involved in creating a pipeline of prospects.

What is lead generation?

Lead generation is a part of the sales process that acts as insurance against the inevitability of customer churn. Even if you have a full roster of clients today, you can’t necessarily rely on them to be there forever. Some will naturally churn out, whether it’s because they move to a competitor, bring marketing in-house, or go out of business. With regular lead generation, you can make sure there are always new clients being onboarded to sustain—and grow—your business.

Traditionally, lead generation involves researching potential clients and cold calling them to introduce your business. It can also include lead capture mechanisms such as content marketing that are designed to get in front of prospecting customers and capture their contact information. Then, it’s the job of the sales team to qualify the lead and move them along the pipeline.

How does AI automate lead generation?

AI technology streamlines the identification of potential leads through algorithms that analyze data that conforms to your desired parameters, identifying prospects. This hands-off approach significantly reduces the time and resources traditionally required for prospect research and outreach.

AI tools can also play a role in the qualification and nurturing of leads, ensuring that only the most promising prospects are forwarded to the sales team. For example, a machine learning algorithm can take into account data like email opens and clicks to identify the hottest leads and flag them for prioritization.

Benefits of using AI in lead generation

Using AI lead generation tools can help your sales team make better use of their valuable, limited time by focusing their personal efforts on closing deals and building strong client relationships. Meanwhile, the AI tool can take over much of the busy work of filling the lead pipeline. Here are some pros of using this valuable new technology:

  • Higher quality leads: Since algorithms can analyze and interpret a large amount of data quickly, they can efficiently identify high-quality leads with a greater likelihood of conversion.
  • Higher conversion rates: Because AI lead generation tools can identify the hottest leads, sales teams can focus on accounts with a high probability of converting, improving overall conversion rates.
  • Time saving: Much of lead generation is time-intensive grunt work, like researching individual businesses. By handing this off to an AI tool, sales teams can dramatically free up time for high-value activities.
  • Cost saving: By using automation tools, agencies can save on the staff time that would otherwise be spent on lead generation.

Challenges of using AI in lead generation

As much as AI lead generation can free up your team’s time, it’s not completely hands-off. That's why understanding the challenges and potential problems it can bring can help you maximize its benefits.

Data quality and accuracy

Inaccuracies or biases in the input data can lead to flawed predictions and misidentification of potential leads, so quality datasets must be used for best results.

Continuous monitoring and optimization

You should regularly check your AI lead generation tool against your expectations to make sure it’s delivering the desired results. If not, you may need to make updates to how data is sourced or the parameters used to identify top leads. Regular optimization may be needed to make sure your AI system stays aligned with your goals.

10 tactics for using AI in lead generation

There are many ways you can go about incorporating AI into your lead gen efforts. Let’s take a look at 10 AI lead generation tactics you can implement right away.

Personalized content recommendations

AI-powered personalized content recommendations are based on the analysis of user behavior and preferences, ensuring that the recommendations seen by each user are highly tailored. This approach boosts engagement and can help you capture more leads by aligning recommendations and content to the individual interests of each prospect.

Predictive lead scoring

Once leads are identified, a challenge faced by digital marketing agencies is determining which ones to pursue first. AI can solve this problem by using predictive lead scoring models to analyze historical data and identify the leads that should be top priority for sales teams.

Chatbots and virtual assistants

The early stages of lead development generally involve getting the prospect up to speed with the same basic information about your product or service. By using chatbots in your AI lead generation strategy, you can move prospects along the pipeline by:

  • Having human-like chatbots engage with visitors,
  • Answering common queries,
  • Collecting information that can be used by your sales team

Natural language processing (NLP)

NLP algorithms analyze and understand customer interactions using natural language. Chat GPT is the most widely known example, but agencies can use similar algorithms to “converse” with prospects, glean valuable insights, and identify leads.

Automated email campaigns

Email is a long-running champion of lead generation, but in the AI era, digital agencies can take it to the next level. AI can be used to automate more parts of the campaign by creating personalized content, optimizing send times, and tailor the lead nurturing process to each prospect.

Social media listening

The beauty of AI lead generation is that it can process—and use—huge swaths of data that would otherwise be difficult to parse. AI tools for social media can monitor a wide range of platforms and online forums to identify leads, track brand mentions, and engage with prospects in real-time, moving them along the sales pipeline faster.

Lead qualification and segmentation

AI lead generation doesn’t end when the lead is identified: the technology can be used to qualify the value of each lead and to segment leads according to any criteria of interest to your agency so that you can create even more targeted marketing and nurturing campaigns.

Behavioral analytics

AI can be used to supercharge your A/B testing and help you optimize your website faster by quickly capturing and analyzing user behavioral data and providing actionable insights.

Conversion rate optimization

The same insights can be applied to boost conversion rates. Iterative changes over time can lead to more conversions, but by implementing AI solutions, agencies can swiftly identify areas for improvement and make necessary optimizations.

Sales forecasting

Accurate sales forecasts help you make better, more informed decisions about the future of your agency. AI algorithms can enhance the quality of forecasts by making use of historical sales data, market trends, and customer behavior to determine the likeliest outcomes.

10 AI tools for lead generation

1. Vendasta

Vendasta’s expansive platform includes all-in-one AI solutions for every stage of the lead generation and management lifecycle. With Vendasta, you can

  • Identify hot leads when they’re most likely to buy
  • Create completely custom Snapshot Reports to engage leads
  • Boost online reputation by writing custom responses to reviews with a single click
  • Improve online presence through better AI-written business listings
  • Create AI-powered email marketing campaigns that convert
  • Craft lead-capturing social campaigns with a single prompt
  • Manage lead flow in a sleep, functional pipeline management dashboard
  • Gather lead behavior data
  • And more

As a white-label digital marketing platform, Vendasta is ideal for digital agencies that want to scale and diversify their offering quickly and efficiently, without having to expand their in-house teams.


Swordfish uses AI to help sales teams get in touch with prospects by identifying up-to-date email addresses and phone numbers. It also provides access to a contact database to help marketers find new prospects.

For example, a company with a list of target client businesses could benefit from this platform by using it to find the contact information of key decision makers.

3. Outreach

Outreach is a sales execution platform that helps sellers create and close leads. Users can follow automated workflows to identify prospects, track the sales process, gain insights, and forecast sales.

4. 6sense

6sense is a B2B prospecting tool that uses predictive AI to identify motivated buyers, personalize outreach, and obtain up-to-date contact information. It also integrates with a wide range of platforms that may already be a part of the agency tech stack.

5. Surfer

Surfer is an AI-powered tool for content writing, editing, SEO auditing, and keyword research. Organizations can use it to quickly create SEO-optimized content that can be used to capture and nurture leads.

6. is a platform for creating AI-driven sales agents. Simulated AI sales agents can manage inbound and outbound prospect management, helping organizations fill their pipelines without needing to hire in-house.

7. can be used both by B2C and B2B businesses to collect prospect data and improve remarketing campaigns through integration with the Meta platform. As a result, businesses can increase their lead capture rate and reduce the cost it takes to capture each lead.

8. ZohoCRM

The ZohoCRM platform incorporates AI-powered tools to identify and engage with the most promising leads. The platform assigned scores based on a range of parameters and provides predicate analytics to help teams know who to engage with and when.

9. Jasper

Jasper can be used in AI lead generation efforts to create content for lead-capturing marketing campaigns. Marketers can use to write copy, product descriptions, blog posts, and more, all while using a designed brand voice.

10. Albert

Albert uses machine learning algorithms to improve the effectiveness of advertising campaigns across a wide range of channels. It can be used to plan and execute campaigns, manage budget allocation, identify optimal keyword usage, and provide actionable reports and insights.

Future trends in AI lead generation

Since AI lead generation is still in its relative nascence, future trends will see this technology become more robust.

Expect to see machine learning and natural language processing become even more sophisticated, with highly capable chatbots and sales agents helping teams achieve faster, more targeted outreach.

Other newer technologies, like the blockchain, may also be incorporated to help AI lead generation data remain safe and secure.

Finally, personalization will be the name of the game: as AI algorithms improve, they’ll be able to serve audiences the content and experience that are best suited to their needs.


While lead generation has always been a part of the sales process, AI is transforming how it takes place. Implementing AI lead generation practices, like predictive lead scoring, chatbots, and AI-powered conversion rate optimization, will help your agency find optimal clients and scale faster than ever before.

About the Author

Lawrence Dy is the SEO Strategy Manager at Vendasta. His career spans from starting as a Jr. Copywriter in the automotive industry to becoming a Senior Editorial Content Manager in various digital marketing niches. Outside of work, Lawrence moonlights as a music producer/beatmaker and spends time with friends and family.

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