Intent-based lead generation identifies prospects based on their online activity, which can be used to suggest that they’re actively researching or considering making a purchase.
AI has the potential to identify a prospect’s intent by analysing signals from different sources, such as the websites they visit (based on their preferences), their social media activity and the articles they read/comment on online. By this method, AI can help sales teams see when someone might be interested in your product or service.
Then, with the caveat that AI content still needs careful human oversight to ensure accuracy and quality, it can be used to help create personalised sales messages, when adequate information is input about your prospects and your ideal customer profiles (ICPs).
What Are the Challenges of AI Lead Generation?
It’s vital you don’t use AI for everything. Your prospects must feel that your sales process is human, otherwise they’ll be turned off immediately.
If you’re over-reliant on AI for content you’re also at risk of sending out boring, generic, blanket communications that don’t really speak to your prospects, and which have very little chance of turning them into leads, let alone customers. And worse, AI often gets things wrong, adding incorrect information based on the data it has parsed. All AI content should be carefully fact-checked to avoid this, and it should be edited thoroughly to remove its often stilted and unnatural writing style.
Another noteworthy issue is that some legacy sales pipelines struggle to accommodate new AI tools, so it’s important to evaluate compatibility with your operation.
How Can AI Enhance Intent Detection?
AI has the potential to enhance how prospect intent is detected thanks to its sophisticated pattern-recognition capability. It can track engagement across multiple digital touchpoints, analyse behaviour signals and suggest how ready a prospect is to buy.
It also uses predictive models that combine historical conversion data with real-time insights to indicate current purchase signals, while also suggesting wider market trends. Furthermore, AI learns all the time, so it can refine its ability to accurately measure intent to buy, as opposed to, for example, someone casually browsing.
Regulations and Legislation to Be Aware Of
While companies can benefit from AI in intent detection, it’s important to make sure you’re adhering to the relevant regulations.
- UK GDPR/Data Protection Act 2018 – requires a lawful basis for processing personal data, transparency about AI usage, and data minimisation principles when tracking prospect behaviours.
- UK AI Regulation Bill (2024) – requires appropriate safeguards, transparency measures, and accountability for AI systems that profile prospects or predict intent.
- Online Safety Act – contains provisions on algorithm transparency affecting automated decision-making in prospect targeting.
- Financial Services-specific regulations – there are additional requirements regarding intent detection from the Financial Conduct Authority (FCA) for businesses in the financial sector.
- Data Protection and Digital Information Bill – a bill that aims to balance the need for innovation with privacy protection.
So, let’s dig back into how AI can enhance intent detection, with four key benefits that are well worth considering:
1. Quickly Build Highly Targeted Lists of Leads
There are a number of ways that AI can help you build target lead lists fast.
Automatic ICP matching
It can identify suitable prospects by matching them to your buyer personas and ICPs. It does this by analysing thousands of data points across digital behaviours, company information, technographics, firmographics and more. Its ability to identify and process much larger data sets than humans enables AI to do this faster and often more effectively, resulting in a prequalified target list with great potential.
Pattern Recognition
AI can also spot patterns that humans might miss. For example, connecting LinkedIn activity, job changes, funding events and content engagement with buying intent signals. These patterns help identify which prospects are ready for outreach. By continuously monitoring and updating lead information, AI can also help ensure that lists are kept up to date.
Similarity-Based Targeting
Machine learning tools can also enable you to identify new prospects that are similar to your best customers or recent wins. This, as well as the ability to score and prioritise leads, allows you to target and personalise approaches for businesses you have the best chance of converting.
2. Improve Personalisation
Personalisation is of course key in effective sales. The more you personalise your approach, the more likely you are to get a response. So how can AI help here?
Hyper-relevant Messaging
AI is good at pulling observations and insights into messaging to create a level of personalisation that boosts your chances of getting a response. This could include, for example, blending observations about a company’s regional expansion with competitive intelligence, enabling you to ask whether the expansion was due to X happening in the market earlier in the year.
Immediate Effective Insights
The previous point partly covers insights, but it’s worth mentioning that AI tools such as Clay, Lyne.ai or Smartwriter can pull such observations instantly. They can identify company news, social media interactions and industry developments in seconds, enabling you to send personalised outreach at scale.
3. Automated lead scoring and qualification
We’ve touched on lead scoring and qualification but this is a benefit worth briefly expanding on. With AI lead scoring, the scores are based on solid data and not guesswork. There is no bias involved – instead, scores are assigned to prospects using predictive modelling and machine learning, which has parsed historical conversion data. These tools can analyse what really correlates with closed deals and provide your sales team with a list of priorities, which they can research further – remember, AI can’t do all the work for you and you shouldn’t let it!
4. Trigger-based Follow-ups
Rather than generic three-days-later follow-up sequences, AI tools can schedule follow-ups based on the behaviour of your individual prospects. This means comms can be sent when a prospect demonstrates interest, increasing their relevance and response rates.
AI can continuously monitor engagement channels and detect intent signals (and combinations of signals) such as content downloads, link clicks and specific page views, and trigger a follow-up message when the lead is warm. Follow-ups can also be tailored to prospect behaviour to improve the chances of a response further. For example, if someone has been looking at an ROI calculator, your message can emphasise the financial benefits of your offering.
The best AI tools to leverage prospect intent
There are of course numerous AI tools on the market claiming to help you excel at intent-based lead generation. But which are the best? Here are four that we like and are worth reviewing:
- Clay offers a suite of features for AI lead generation and customer relationship management. It’s designed for growth teams, sales development representatives (SDRs) and enterprise companies, and it focuses on ensuring that outreach is personalised and efficient.
- Lyne.ai is a platform that helps businesses personalise cold email outreach by generating tailored introduction lines. It enables you to send personalised emails quickly, boosting outreach efficiency and potentially improving response rates.
- Seamless.AI offers to help your business find, verify, and connect with sales leads. It provides a real-time search engine for B2B leads, and provides access to a ‘vast’ database of contact and company records.
- Amplemarket aims to help sales teams improve their workflow using several tools that make B2B lead generation and sales outreach more effective. The platform relies on data and simple processes to help you find and engage with potential customers.
Should You Invest in AI Lead Generation?
AI can be a brilliant help in generating intent-based leads, provided it’s blended with a human sales process. Finding the right balance is vital. Here are a few points to remember as you consider whether investing in AI lead generation makes sense for your business:
Quality over quantity is key with intent-based leads
While AI can help you outreach to prospects at a greater scale than ever, that doesn’t mean you should go crazy. AI can indicate prospects offering you the best chance of a sale, but then it’s down to you to do further research and be selective with your outreach.
People still want to buy from humans
AI may well help you improve your lead generation, but if your prospects feel like any part of the process is just artificial intelligence, you won’t get a response and you won’t close the deal.
You Need to Find the Sweet Spot
To find the right balance between AI and your human team you should encourage experimentation with tools such as those mentioned above. Find the sweet spot between personalisation and automation and you’ll be sure to see the business benefits.