How to Use AI for Lead Generation in 2025 [Tools and Tips]

That’s because AI is no longer a futuristic concept; it’s a must-have tool for businesses looking to grow massively in 2025.

But, when everyone’s talking about AI, few actually know how to use it effectively for lead generation.

That’s why I’ve put together this step-by-step guide to help you use AI in most effective ways in your lead generation campaigns.

But first, do you really need AI for lead generation?

How does AI improve the lead generation process?

AI can help businesses cut out people who will never be your customer without having to use really expensive enrichment services.

Brent Biggs,Founder and CEO, Datascore

1. 40% increase in lead quality
2. 50% more leads
3. 47% higher conversion rates

But how can I use AI for lead generation, specifically B2B lead generation?

How to use AI for B2B lead generation?

AI makes lead generation faster, smarter, and easier. Instead of wasting hours on research and outreach, you can use AI to:

1. Find your audience and create ICPs
2. Plan smarter campaigns
3. Score and prioritize leads
4. Generate content
5. Automate entire lead generation process

1. Find your audience and create ICPs

Targeting the wrong audience wastes time and money.

AI eliminates guesswork by analyzing data to find patterns in your best customers and identifying similar prospects.

Even if you’re starting fresh and don’t have any data, it can still help you find your target audience by analyzing industry trends and your competitors.

For example, I used ChatGPT’s latest model o3 to help me identify my target audience for a lead generation campaign.

That’s not the limit. You can further use it to plan lead generation campaigns for you.

2. Plan smarter campaigns

You can use AI tools to not only find the strategies that work best for you but also plan lead generation campaigns A to z.

You can use it to plan a campaign based on your strategy step by step and even use AI to help you out on every step.

3. Score and prioritize leads

If your strategy involves outreach, you can even score and prioritize leads using AI. It not just saves you hours of manual effort, but also does it better than a human.

For example, for this article, I used OpenAI’s API to match the prospects and ICPs I have and score my leads, so I only focus on best-match profiles.

4. Generate content

This use case is pretty well-known and I guess most widely used by everyone. You can use AI to generate blog posts, do content research, and write ad and email copies.

You can also use AI to optimize your content’s SEO and translate it to other languages for better local audience penetration.

5. Automate entire lead generation process

Finally my favorite use case — automate the entire lead generation process.

You can eliminate 90% of manual effort from lead generation using AI.

Now the real question that almost everybody in the B2B lead generation space is asking — which AI tools are best for lead generation?

Which AI tool is best for lead generation?

There are lots and lots of “AI tools” for lead generation tasks. That many options have made it difficult to find the ideal tools for certain businesses.

And that’s exactly what we’re going to do. Instead of giving you a top 10 style listicle, I’m going to focus on tools that you might be already using but not to their full potential.

For this article, I actually planned, created and launched a real lead generation campaign with the help of ChatGPT and DeepSeek.

Along with these chatbots, I used:

1. A B2B leads database
2. A lead collection and enrichment tool
3. A cold email outreach tool

Let me walk you through the entire journey.

Step by step guide to do lead generation using AI

I’m going to plan, create, launch, and conclude a B2B lead generation campaign for Lobstr.io using AI.

But first, I need to pinpoint a product, the goal, and our budget for this campaign.

My goal for this campaign is to get users subscribed for a free plan so that they can try the product and upgrade to the premium plan.

Now since I’m a broke guy and love saving money, I’ll be creating this entire campaign on a $250 budget.

But how? Here’s a breakdown of the cost.

Now let’s get to the process. I’m going to run this campaign in 7 steps.

1. Finding target audience
2. Choosing best B2B lead generation strategy
3. Prospecting
4. Lead scoring and segmentation
5. Generating content
6. Sending outreach emails
7. Automating the workflow

Let’s roll!

1. Finding target audience

Before anything else, we need to know who we’re targeting. AI helps by analyzing existing data, social media activity, and market trends to identify the right audience.

I’m going to use ChatGPT and DeepSeek for audience research. Why both? Because I want to compare the responses and choose the best output.

You can feed them your existing customer data or ask them to give you an idea of your target audience based on industry insights and competitors.

Now let’s write a prompt for both AI assistants and compare the output.

The prompt:

You're a lead generation expert hired by a SaaS company for a B2B SaaS lead generation campaign. The first thing I need you to do is help me find my target audience, people who will be interested in my product.

About my product:

A Twitter search results scraper that collects all tweets (top and latest) from a Twitter search or hashtag. We collect the following data points:

Tweet Content

Tweet url

Original tweet URL (if retweet)

Published date

View count

Like count

Retweet count

Quote count

Reply count

Bookmark count

Author Name

Username

Media thumbnail

Media type

Media url

Binded media title

Binded media domain

Binded media url

Binded media thumbnail url

Binded media description

Other features of my product:

- Can automatically exports all the data to a Google Sheet, Amazon S3, and even Webhook

- Collection can be scheduled i.e. you can schedule the tool to collect and export data weekly, monthly, daily, on a certain time automatically without your interference.

- Collects 100+ tweets per minute

- No-code and cloud-based solution

Now I need you to help me identify my target audience. Get market insights, analyze competitors, and identify my target audience.
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ChatGPT’s response:

ChatGPT gave me a simple answer to who would benefit the most from my product?

Though the target audience it gave me matches our existing customers data, the response was still too basic. So I asked it to go deeper.

Now the 2nd response is quite detailed and has pretty solid points. It highlighted who they are, their needs and challenges, and how my product solves them.

Now let’s see how DeepSeek handles this prompt.

DeepSeek’s response:

DeepSeek actually painted the entire picture for me.

It performed a market analysis, found my potential competitors, gave me industries list, identified and even segmented my target audience.

It also gave me geographic information and next steps. Since the audience details were super simplified, I asked it to expand that section for me.

The response was pretty similar to ChatGPT.

Now, I need an Ideal Customer Profile of my target audience.

Based on my own research plus data from both AI assistants, I believe we should target digital marketing agencies.

I used both GPT and DeepSeek to create ICPs too. Both tools gave me generic responses initially but after some finetuning, I got my ideal ICPs.

DeekSeek was better in this one because it understood the industry and audience better than GPT. The demographics data it provided was also on point.

Here’s our Ideal Customer Profile (ICP):

### **Ideal Customer Profile (ICP): Digital Marketing Agencies**

#### **1. Firmographics**

- **Company Size**: Small to medium-sized agencies (5–50 employees).

  - These agencies are large enough to need scalable tools but small enough to prioritize cost-effectiveness.

- **Revenue**: $500K–$5M annually.

  - They have budget for tools but are price-sensitive and avoid enterprise-level pricing.

- **Location**: 

  - Primary: North America (U.S., Canada), Europe (UK, Germany, France), and APAC (India, Australia).

  - Secondary: Emerging markets with growing digital marketing sectors (e.g., Southeast Asia, Latin America).

- **Client Base**: 

  - Serves clients in industries like e-commerce, SaaS, tech, healthcare, and retail.

  - Typically manages 10–50 clients, with a mix of local and international brands.

---

#### **2. Technographics**

- **Current Tools**:

  - Social Media Management: Hootsuite, Buffer, Sprout Social.

  - Analytics: Google Analytics, Twitter Analytics, Brandwatch.

  - Reporting: Google Sheets, Excel, Tableau, Power BI.

  - Automation: Zapier, Integromat.

- **Tech Stack Gaps**:

  - Lack of a dedicated, affordable Twitter data scraping tool.

  - Limited ability to collect and analyze Twitter data at scale.

  - No seamless integration with their existing reporting workflows (e.g., Google Sheets, S3).

  - Reliance on manual processes or expensive enterprise tools for Twitter data.

---

#### **3. Psychographics**

- **Goals**:

  - Deliver measurable ROI for clients through data-driven campaigns.

  - Streamline workflows to save time and reduce manual effort.

  - Differentiate themselves by offering advanced analytics and reporting.

- **Challenges**:

  - Manual data collection for Twitter campaigns is time-consuming and error-prone.

  - Existing tools lack the depth of data needed for actionable insights (e.g., view counts, bookmarks, media engagement).

  - Difficulty in scaling data collection and reporting for multiple clients.

  - High costs of enterprise tools that offer similar capabilities.

- **Values**:

  - Efficiency, scalability, and affordability.

  - Data accuracy and actionable insights.

  - Client satisfaction and retention.

---

#### **4. Behavioral Insights**

- **Buying Behavior**:

  - Prefer SaaS tools with transparent, subscription-based pricing.

  - Likely to start with a free trial or demo before committing.

  - Value ease of use, automation, and integration with existing tools.

- **Decision-Making Process**:

  - Decisions are typically made by agency owners or senior management.

  - Social media managers and data analysts often influence the decision.

  - Budget approval may involve finance or operations teams.

- **Adoption Triggers**:

  - A new client project requiring advanced Twitter analytics.

  - Client demand for more detailed reporting and insights.

  - Competitive pressure to offer more value than other agencies.

---

#### **5. Key Pain Points Your Product Solves**

1. **Manual Data Collection**:

   - Agencies spend hours manually collecting Twitter data for client reports.

   - Your product automates this process, saving time and reducing errors.

2. **Limited Reporting Capabilities**:

   - Existing tools don’t provide comprehensive data (e.g., view counts, bookmarks, media URLs).

   - Your product exports clean, structured data to Google Sheets, S3, or Webhook for seamless reporting.

3. **Scalability Issues**:

   - Agencies struggle to manage data for multiple clients with existing tools.

   - Your product collects 100+ tweets per minute, ideal for high-volume needs.

4. **High Costs**:

   - Enterprise tools are expensive and often overkill for small to medium-sized agencies.

   - Your product offers affordable pricing with no hidden fees.

---

#### **6. Use Cases**

1. **Client Reporting**:

   - An agency uses your tool to scrape tweets from a campaign hashtag and automatically export the data to Google Sheets for client reports.

2. **Competitor Analysis**:

   - An agency tracks competitors’ Twitter activity in real-time to identify trends and optimize campaigns.

3. **Lead Generation**:

   - An agency scrapes tweets mentioning specific keywords to identify potential leads for a client.

4. **Campaign Optimization**:

   - An agency analyzes engagement metrics (e.g., views, bookmarks) to identify high-performing content and adjust strategies.

---

#### **7. Buying Triggers**

- **Client Demand**: Clients are asking for more detailed Twitter analytics and reporting.

- **Competitive Pressure**: Competitors are using advanced tools to gain an edge.

- **Campaign Launch**: A new campaign requires real-time monitoring and reporting.

- **Budget Approval**: The agency has allocated budget for new tools to improve efficiency.

---

#### **8. Objections to Overcome**

1. **Pricing Concerns**:

   - Highlight your product’s affordability compared to enterprise tools.

2. **Ease of Use**:

   - Emphasize the no-code, cloud-based nature of your product.

3. **Integration**:

   - Showcase integrations with Google Sheets, S3, and Webhook.

4. **Data Accuracy**:

   - Provide case studies or testimonials to demonstrate reliability.

---

#### **9. Messaging and Positioning**

- **Value Proposition**:

  - “Automate Twitter data collection and reporting for your agency. Save time, scale effortlessly, and deliver measurable results for your clients.”

- **Key Messaging**:

  - “Stop wasting time on manual data collection. Our tool scrapes 100+ tweets per minute and exports data directly to Google Sheets, S3, or Webhook.”

  - “Affordable, scalable, and easy to use—perfect for agencies managing multiple clients.”

  - “Get real-time insights into Twitter engagement, trends, and competitor activity.”
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Now let’s move to the next stage i.e. finding the most effective strategy.

2. Choosing best B2B lead generation strategy

Let’s ask our AI friends to help us with the strategy. Since both tools know the context, we don’t need to write a long prompt.

But if you’re using AI assistance specifically for this step, you can use this type of prompt.

The prompt:

You're a lead generation expert hired by a SaaS company to plan an outbound lead generation strategy for their SaaS products.

The company offers a no-code SaaS product called "Twitter Search Results Scraper." The primary use case of this product is Brand mentions, Topic, and Hashtag monitoring and collecting all latest and top tweets containing a certain keyword or hashtag from Twitter search results.

I need you to conduct a thorough research, use the internet, and find out the most effective outbound lead generation strategies for B2B SaaS. Then choose the best one for me.
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The response:

Both tools gave me similar responses but the final recommendations were different.

ChatGPT suggested ABM with targeted cold emails while DeekSeek suggested a combination of cold emails for outreach and LinkedIn messaging for follow-ups.

The logic in both responses is quite similar. ChatGPT has a slight edge here because it gives you a roadmap for both targeting and outreach.

So we’re going with cold emailing which is common in both.

For better targeting, I will be prospecting company accounts instead of direct leads as suggested by GPT.

3. Prospecting

ChatGPT or any AI tool can’t magically generate leads for us. You need a leads database and a lead collection and enrichment tool to find your prospects.

So which B2B leads database is ideal for my campaign? GPT answered this too.

Let’s find some leads based on the ICP I created using AI.

So I started with account search and found ideal company accounts that matched my ICP description.

Now I have the leads but how do I email them when I don’t even have their contact information? Plus I need to export them to a Google Sheet for further analysis.

For that, you can use Lobstr.io.

This super handy tool can save you a lot of time. With Lobstr.io, you can:

1. Collect all leads from Sales Navigator search
2. Scrape 30+ key data points from each profile (including all profile + company details)
3. Enrich data with verified work emails
4. Export all the data to CSV, Google Sheets and Amazon S3
5. Automate data collection with scheduling
6. API access to integrate scraper with your own apps and CRMs

Well, in short, Lobstr collected all the leads, added verified emails, and gave me an enriched prospect list within 6 minutes.

But, should I trust this list blindly and start sending emails? Absolutely not!

4. Lead scoring and segmentation

B2B marketers who emphasize lead volume over lead quality reduce sales efficiency, increase campaign costs, and fuel the gap between sales and marketing. To generate qualified demand, marketers need technology and processes that capture lead quality information; validate, score, and classify leads.

Laura Ramos,VP and Principal Analyst, Forrester Research

How do I do that?

Well, I’d have used an expensive tool but since I’m a broke guy with a superpower called “AI”, I can do it using a simple python script.

But I don’t know how to code.

The prompt:

I need you to write a python script for lead scoring using OpenAI's API. The script will use the API to:

- Read a text file that contains ICP information

- Read a CSV file that contains my prospects data from Sales Navigator

- Analyze every prospect

- Give it a score

- The updated data will be saved in a scored.csv file that has a new column named lead_score.
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Once done, I uploaded the CSV file to Google Sheets and now I have a list of prospects, scored properly, and I can easily remove the least matching leads from my list.

You can tweak the script to do further data analysis and do proper lead segmentation for you.

Now let’s work on the next step i.e. email copy and landing page content.

5. Generating content

You must know AI can write high-converting content that feels human and personalized.

So instead of spending hours on content creation, I used AI to generate, test, and refine outreach content in seconds.

The prompt:

I'm doing a cold email campaign to generate leads for my SaaS business. I need your help in crafting the email copies for main cold email and follow-ups. First write the first cold email based on the data I provided below: 

Product: Twitter Search Results Scraper

Use case: Twitter brand mentions and trends tracking

Features:

- Collects all top and latest tweets from any given keyword or hashtag

- Collects tweet content, likes, retweets, bookmarks, replies, quotes count of the tweet, media of the tweet, user profile details, and many more crucial data points.

- You can schedule data collection to automatically collect data daily, hourly, weekly, or monthly without any manual effort

- You can collect 100+ tweets per minute

- It's affordable compared to other tools (8000 tweets per month for free and less than $8 per 100k tweets)

- Highest limits compared to other tools (Up to 10M tweets per month)

Landing page: [https://www.lobstr.io/blog/track-twitter-mentions](https://www.lobstr.io/blog/track-twitter-mentions)

This is actually a how-to article that guides readers how to use the tool, offers a comparison with competitors, and everything about tracking twitter mentions and trends.

ICP:

{ICP file or just paste the text here}
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The response:

Initially both AI assistants gave me a tough time crafting a good cold email copy. It was either too generic, or too long and full of fluff.

When they got it right, the email wasn’t personalized enough.

So I simply fed them a summarized versions of these articles:

1. 100+ Best Cold Email Subject Lines That Get Results
2. How to Start a Professional Email [20+ Examples]
3. How to Write the Best Outreach Email? [10+ Templates]
4. How to Write a Professional Email Sign Off [50+ examples]

Now I have a complete checklist to write a perfect cold email.

After a few tweaks, I got a perfect copy for my cold email. I chose the best points from both copies and crafted a really cool, optimized email copy.

I did the same for follow-up emails too and generated 5 follow-ups.

Since the models now knew what I really wanted, it took me less than 5 minutes to get the follow-up copies.

But how do I send the emails?

6. Sending outreach emails

Let’s skip the “how important is choosing the right tool” blah blah blah part. You know it already.

The question is, how do you choose the right cold emailing tool for your campaign?

My top 3 choices are:

1. Saleshandy
2. Instantly AI
3. Smartlead

I personally prefer Saleshandy because it’s convenient, easy to use, and the most scalable option.

Let’s create a sequence and add our email copies and prospects to it.

And I forgot to mention, the emails generated using ChatGPT and DeepSeek were fully optimized for deliverability.

If yours are not, you can just tell the AI to optimize them and it’ll do it in seconds.

Make sure to add a gap between your follow-ups emails and add 5 to 7 follow-ups in your sequence.

You can create different variations of an email copy or use Saleshandy’s AI-powered tool to do it for you with spintax triggers.

Now Saleshandy will automatically send your cold emails to all the prospects in the list.

For better deliverability, use the recommended max limit, time interval, and daily ramp-ups.

But what if I want to do this on autopilot without any manual interference?

7. Automating the workflow

Well this is undoubtedly the best use case of AI tools in lead generation. They automate your workflows in the smartest ways possible.

Unlike usual bots that follow a set of instructions, AI can adapt and make your workflow automation smarter.

So how to automate the entire AI lead generation process?

Well, it’s too much to fit in a single article. We’ll be automating the entire campaign in the next article on “automated lead generation” topic.

That’s a wrap. Before concluding this article, let me answer some FAQs.

FAQs

How can I use AI for lead nurturing?

AI can automate lead nurturing in various ways. It can track website visitors, analyze engagement, and trigger personalized email sequences based on predictive analytics.

It also improves lead qualification by identifying high-quality leads and guiding them through the sales funnel until they are ready for closing deals.

What is predictive lead gen using AI?

AI algorithms can analyze large datasets to predict which potential customers are most likely to convert into qualified leads.

Using machine learning and predictive analytics, you can optimize lead generation efforts by focusing on targeted leads rather than wasting resources on unqualified prospects.

What are the best AI lead generation tools?

It depends on your use case. There are many AI-powered lead generation tools in the market for various use cases.

How is artificial intelligence changing email marketing?

AI-driven marketing automation helps marketing teams optimize email marketing campaigns by qualifying leads, crafting personalized content, and automating follow-ups.

AI-powered chatbots and natural language processing enhance the customer experience by delivering relevant messages at the right time, increasing sales process efficiency.

Conclusion

That’s a wrap on how to use AI for lead generation. This is just part 1, in part 2, we’ll be automating the process and in part 3, we’ll be comparing the best AI lead generation tools.