B2B sales prospecting and lead generation are complex and time-consuming. Sales teams spend countless hours daily researching, attending events, networking, building targeted contact lists, qualifying, and sending outreach campaigns.
However, do all these activities bring results? They do, but at the cost of spending a lot of time and resources. SDRs often put effort into targeting irrelevant audiences that don't match their ideal customer profile (ICP) and buyer persona. A significant percentage of these leads don't even convert into full-time customers.
According to Crunchbase, sales reps spend 6 hours on average to research the prospects. While that is good, it also leaves them less time for what they should do - selling.
Using Artificial Intelligence (AI) for lead generation is a great way to minimize research time and focus more on value addition.
The use of AI in B2B marketing and sales is increasing worldwide. The reason is AI's ability to automate mundane tasks with accuracy. According to McKinsey's State of AI 2022 report, 41% of businesses have experienced a minimum of 5% revenue growth because of AI adoption.
AI is the future. It is high time that sales teams leverage it to simplify critical and challenging activities like lead generation. In this article, I will share an end-to-end guide on AI-lead generation and its applications in B2B sales.
Why Does AI Lead Generation Matter?
"AI-based lead generation is like having an experienced scout on your team, working 24/7. It filters through vast data sets, pinpointing prospects with precision. Beyond identifying leads, it predicts their behavior, tailoring interactions to resonate on a deeper level.
From automating follow-ups, crafting personalized content suggestions, and predicting which leads are most likely to convert based on past interactions, AI streamlines tasks that once consumed hours, allowing teams to prioritize effortlessly.
For businesses, it's not just about efficiency; it's about ensuring we're always in sync with our prospects' needs and aspirations." - Goran Kezić, Demand Generation at Play Media.
Indeed, understanding prospects' needs and aspirations is the key to a successful demand generation campaign. However, SDRs often miss out on high-intent leads. Primarily because lead generation through multiple channels (LinkedIn or Emails) sometimes overwhelms them.
Additionally, despite hoarding multiple sales prospecting tools, SDRs end up doing most of the operational tasks. These tasks include research, outreach, scheduling meetings, and analyzing campaign performance.
As a result, the B2B sales cycle gets longer, and you lose opportunities in between.
However, you can easily overcome these challenges with AI. Here's how:
- AI-powered lead generation tools like Plena can analyze large volumes of datasets within seconds to research and find high-intent leads. That means, instead of being involved in time-consuming activities, SDRs can focus on decoding the results of this AI workflow and analysis and incorporating their findings in their sales pitches.
- Machine learning (ML) is beneficial for finding data patterns. Unlike humans, AI can uncover trends and insights from data to predict the conversion potential of a lead. AI/ML models can also gauge whether the leads match your ICP well. The same activity can take hours or even days for SDRs to figure out without any assurance of accuracy.
- SDRs and BDRs often get overwhelmed with information overload. This can affect their productivity. AI makes it possible to manage all information in a categorized way. Furthermore, AI can multitask to reduce the pressure of overwork on the sales reps' shoulders.
AI Lead Generation Process
The significant stages of lead generation are - research and finding, qualification, and prospecting. Here's how the application of AI can help SDRs simplify these stages:
Lead Research and Finding
This stage aims to scavenge across multiple platforms and websites to identify the contact details of high-intent leads. With an AI-based research and lead generation tool, SDRs can pull the contact information of high-quality leads from multiple reliable sources within seconds.
Lead Qualification
Once you capture the leads, the focus shifts to qualifying those leads. Lead qualification is about sieving leads through your ICP and persona criteria and gauging their buying intent. AI-based lead qualification tools help you make data-driven decisions by:
- Identifying intent by analyzing activity, social engagement, job postings, browsing behavior, and more.
- Matching leads with the brand's ICP and assigning scores based on the overlap.
- Qualifying only suitable leads for the next stage.
Outreach and Prospecting
Prospecting is all about reaching out to high-intent leads with personalized messages. AI outreach and prospecting tools can initiate outreach sequences automatically, integrate with your CRM, provide vital insights about prospects and their industries, and provide advanced analytics for greater visibility.
I interviewed Adam Purvis, Founder of AdamJohnPurvis.com, to share his experience related to AI-based lead generation. He shared an interesting perspective related to AI-led prospecting:
"I am an Enterprise B2B SaaS Sales Representative, selling exclusively to banks and credit unions. As an Account Manager, I primarily focus on upselling and cross-selling to existing customers and have heavily leveraged AI in my sales process. Before that, I was a top-performing SaaS BDR, generating ~$2.2m CAD in the pipeline in 2022, opening opportunities for some of the world's largest banks and credit unions.
The primary use case I have found for AI in my lead generation process is using it to summarize reports that I can then reference in my prospecting emails.
Tailoring your prospecting is crucial in generating a pipeline for SaaS deals. Luckily, since I sell to banks and credit unions, there's a wealth of information available on the Internet that I can use to tailor my pitch.
One source of this information for banks is their public 10-k report or their annual report. These are monster reports; think 80+ pages for each account.
If you've ever read a 10-k - you'll know how long they can take to get through! However, they're well worth reading around, as there's a ton of valuable information in each report, filled with key statistics, trends, and strategic priorities for the organization that I can then sprinkle into prospecting emails.
One way that I have used ChatGPT/generative AI to speed up my prospecting (and therefore my lead capture process) is simply by copying and pasting 10-k reports into the AI and prompting it to summarize the information for me and pull out any critical insights into a neat and organized list.
This has saved an immense amount of time, as ChatGPT can quickly pull out the information I need to focus on, eliminating my sifting through a ton of information in the report that I won't use. I can then go back through the report and verify that what ChatGPT tells me is accurate before I include it in a prospecting email to a customer."
Tried and Tested AI Lead Generation Strategies with Examples and Templates [ + 1 Bonus ]
Here are a few AI-lead generation strategies for B2B organizations:
Create Hyper-Targeted ICP
Most of the time, brands generate low-quality leads because their ICPs are not hyper-targeted. A carefully targeted and well-documented ICP leaves less room for doubts and expedites the lead-generation process with a good flow of targeted leads.
A typical ICP looks like this:
While it contains all the essential aspects, SDRs should know that these factors keep changing as a business scales. Therefore, your ICP needs to evolve with time.
With AI-based robots, creating a hyper-targeted ICP is much easier.
AI tools help feed success data of outbound sales and redefine the ICP regularly. ICPs are generally based on assumptions, and little to no science is involved. While in the beginning, it might work, ICPs need more refinement as a brand grows.
For example, irrespective of your documented ICP, if your real-time outbound data shows that you had more successful sales calls and faster turnarounds with CMOs and CXOs and not CEOs, sales reps can consider that.
With AI-powered tools, you can regularly validate your existing ICP with real-time feedback data and pivot whenever required.
Optimize Campaigns with High-intent Data and Lead Scoring
In the AI-lead generation process, optimizing campaigns from time to time is an integral part. AI software can locate correct target audiences based on success data and segment the leads in your pipeline.
AI-based lead scoring can rank your leads in the order of conversion potential. These tools can also predict how long a sales rep might need to convert a prospect into a customer.
Undoubtedly, static lead scoring works, but it is not always accurate. Getting it right requires rigorous correlation and multiple revisions.
With AI, analyzing lead behavior, demographics, and interactions is much easier, allowing lead scores to be assigned and leads to be segmented into different categories.
ML models provide better conversion signals by not fitting every lead into the same mold and treating them differently.
Predicting the probability of lead conversion using AI algorithms that do lead scoring is possible. A typical method of determining behavior patterns leverages historical data, product usage, and communication interactions.
In addition to the signals of first-, second-, and third-party intent, lead scores can also factor in buying intent signals.
Sales teams can improve their funnel metrics significantly with predictive lead scoring, prioritizing leads with the highest conversion chances.
Leverage AI-Chatbots
AI chatbots use conversational AI to interact with website/app visitors and provide them with round-the-clock support. While most businesses consider AI chatbots a customer support tool, they can also boost lead generation.
Chatbots initiate conversations with website visitors, analyze their intent through these conversations, narrow down potential leads that qualify sales reps' criteria, and feed the data to sales teams to convert.
Chatbots can route a lead to sales reps or customer support executives in real time based on urgency. Chatbots can identify the need for human interaction in the sales cycle and involve suitable sales team members to expedite the process.
Global technology company Emerson achieved remarkable results by implementing Drift's AI chatbot. Emerson already had millions of web visits when it opted for Drift's chatbots. However, the brand wanted to create a more personalized experience for the website visitors and capture their intent data to focus on more high-value leads.
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Drift's AI chatbots uncovered high-intent traffic from the existing traffic at the Emerson website and accelerated the sales cycle of this brand. This engagement resulted in 600+ meeting bookings for Emersion, all from high-intent leads.
Analyze Old Data, Assign Patterns, and Segment Leads Accurately
AI tools can analyze historical sales data to assign patterns and play a key role in lead segmentation. AI tools have built-in predictive technology to research potential customers' sentiments, pain points, intent, and overall engagement levels.
With such in-depth analysis, it becomes easier for AI tools to identify which prospects are most likely to convert, what potential objections SDRs can expect during the sales process, and the possible strategies to resolve those.
A survey by McKinsey shows that 19% of businesses consider customer segmentation as a critical use case to be performed by AI.
You can leverage an AI tool's ability to analyze and segment lead data in various ways.
Suppose a prospect is convinced with your product's features and is just one step away from purchasing. They are conducting a final comparison with the competitors to understand if there will be any financial gains.
An AI-based lead segmentation tool will mark this prospect as "Highly convertible" and notify the sales reps. At this stage, they can offer the prospect a good discount or project the Free Trial option to convert them into paid customers sooner.
AI-Driven Email Campaigns
AI tools can help run successful email campaigns - from list building to analytics. Here's how:
- The first step of an AI-driven email campaign is identifying the high-intent leads. AI tools can delve into multiple social media platforms, job listing sites, review sites, and public websites to find prospects that are in-market to buy your product.
- Once you have a narrowed-down list of prospects, AI-based email finder tools like Plena, Apollo, and Zoominfo can search across their large databases to identify reliable contact details (emails, LinkedIn profiles, contact numbers, designation, and other data points) of these prospects.
- As a next step, AI tools like ChatGPT can craft outreach messages based on the prompts provided by sales reps. AI robots can further personalize the outreach messages and CTAs depending on the target prospect's intent and initiate the outreach campaigns automatically.
- Additionally, AI tools can integrate with your CRM and provide intuitive analytics into the performance of your AI-lead generation campaigns.
Bonus: LinkedIn Lead Generation with AI
Coming to bonus, a great lead generation tool you need to leverage is - LinkedIn. 65M+ business decision-makers use LinkedIn, a major source for B2B sales teams, to identify hyper-targeted prospects.
LinkedIn's popular premium plan, Sales Navigator, costs $79.99 monthly and offers 50 InMail credits to SDRs for sending personalized outreach messages to prospects without connecting with them.
To make the most of LinkedIn Sales Navigator, brands can opt for Plena AI robots. Once LinkedIn is integrated with Plena, sales reps can automate prospecting with the following steps:
Step 1: Add lead qualification criteria and appropriate filters.
Step 2: Plena will share a list of targeted prospect profiles.
Step 3: In the next step, Plena will cross-reference the contact details across various websites and platforms.
Step 4: After that, Plena will initiate an automated InMail and LinkedIn outreach campaign.
Final thoughts
The core goal of AI-based lead generation is to automate your sales funnel, speed up sales cycle shift SDRs' time, and focus on more value-adding activities. AI-based lead generation is an exciting approach that removes low-intent leads from your pipeline and simplifies the lead conversion process without compromising on the overall productivity levels of the SDRs.
As a next step, we recommend that sales leaders explore the AI-lead generation tools mentioned here and understand which tools are relevant in removing the repetitive tasks from their sales team's day-to-day activities.
After exploring, you can book a demo with Plena if your business requires an efficient AI-based harvester and prospector tool to build a targeted lead list and automate outreach campaigns.
