Date
18th September 2024
It’s the buzzword of the year – well, probably the decade.
AI has completely transformed our personal and professional lives. With its incredible potential for driving efficiency and saving time across all industries, it’s safe to say it’s got the attention of B2B marketers everywhere.
Within the lead generation space specifically, several suppliers are claiming to include AI within their solutions, but is it all that it seems? How can you gain clarity into their use of AI?
In this blog, we’ll explore:
- What AI is in the context of B2B marketing.
- How AI is changing things in lead generation.
- And, importantly, why you should be wary of lead gen suppliers who promise the world with artificial intelligence.
Firstly, What Is AI, & What Is GenAI?
With so much noise in the industry, AI is being interpreted and promoted in many ways within B2B marketing. This has created some confusion as to where AI can truly make the biggest impact to your marketing strategy.
AI is the field of computing concerned with replicating human intelligence - such as reasoning, analyzing, learning and creating.
Artificial Intelligence has been around for a long time, and a lot of modern data analysis counts as AI. Whether we’ve been aware of it or not, we’ve all been using AI in our day-to-day lives for years – from autocorrect on our phones and autofill in search engines, to Siri, Alexa and other smart assistants in our homes.
Generative AI in B2B Marketing
In the last couple of years, however, generative AI has completely disrupted the world of B2B marketing, allowing us to do more than ever before.
In business, and specifically B2B marketing, it’s huge: AI-powered chatbots, algorithm-produced recommendations, keyword research tools, GPT models for content creation, and suggested email responses. All designed to save you time, but with the cautionary tale of using these tools to assist and supplement your existing processes, rather than replace.
AI is defined as a general-purpose technology (GPT), which means it can be applied to many different application areas across different industries and sectors.
Generative AI has fast-tracked the rate of AI use within B2B Marketing exponentially, due to its ability to respond to human conversation and language, serving as a tool for personalization, workflow optimization and content development.
A prime example of the use of GenAI in B2B Marketing are platforms like OpenAI’s ChatGPT, which employ a type of machine learning known as a Large Language Model (LLM). The beauty of ChatGPT is that you don’t need an engineering degree to program it, you simply provide a prompt, and the AI tool will produce an output - be that text, image or code. However, ChatGPT’s primary strength is in producing natural language text.
On the other hand, the wide accessibility that ChatGPT provides comes with it the risk of poor-quality outputs, such as content, and data inaccuracies.
ChatGPT is still a work in progress, learning day by day based on the feedback it is gathering from various sources. Since the launch of ChatGPT, there are new AI models being created every day, some cater to more specific requirements, like image generation, ad creation, email campaign creation and even feedback on ad copy.
What Does AI Mean for the Lead Generation Industry?
Should you be wary when a prospective lead generation supplier offers to “use AI” to generate your leads, or to increase the number of leads they can generate for you? Let's dive into it...
The secret to successfully using AI is in the data the tool learns from. It must be high quality, accurate, compliant, regulated, unbiased and of a large scale, otherwise the AI tool can develop hallucinations, poor outputs and even bias.
AI is a fantastic tool for segmentation, trend mapping, collating data and producing recommendations, but it isn’t magic, and doesn’t currently have the ability to create anything completely new, and it certainly can’t conjure up new contacts for you to sell to.
AI uses information that is already out there - so what is your lead generation supplier getting from it? What AI solutions are they really offering you? And what are the benefits of an AI enhancement for you?
The answer is usually intent data targeting and personalized marketing, normally on an automated basis.
But the sheer breadth of what AI encompasses, alongside the infancy of understanding of AI itself means suppliers can brand any data-driven solution or machine learning tool as ‘AI’, with little to no explanation of exactly how they are using AI.
Within technology lead generation, we’re seeing a rise in new offers to “enhance lead generation efforts with AI.”
But, What Does "Enhance Lead Generation Efforts With AI" Really Mean?
Some suppliers are simply rebranding their existing data-harvesting tools as ‘AI’ to get on the bandwagon.
As an example, we’ve seen claims being made about using AI tools for intent data, identifying “unique signals” to help technology marketers find quality leads. To us, this seems like an existing intent data model, which likely uses some elements of AI, but is being rebranded as AI to join the hype.
Some lead generation suppliers are also positioning themselves as AI disruptors in the sector but if you scratch beneath the surface the same red flags appear. If AI only works successfully by learning from data that already exists, and they’re outsourcing your lead generation to anonymous subcontractors, how are they gathering additional AI intelligence to further enhance your campaign?
It’s the Garbage In, Garbage Out concept, or GIGO: if you only have garbage data to start with, AI isn’t going to magically transform it into valuable insights.
The Inconvenient Truth: Beware of the “Anonymous Subcontractors”
While we’re deep in the discussion of the use of AI in lead generation, it can be easy to forget some of the most basic challenges in the lead generation industry.
The inconvenient truth is something most lead generation suppliers are uncomfortable talking about - the “anonymous subcontractor”.
The anonymous subcontractor is the faceless, murky, unidentified lead provider who delivers in-bulk, low-quality, cheap leads – that are then marked up to be sold on to you.
Unfortunately, it is likely that the leads provided will not have had a genuine interaction with your brand, or your content. Even worse, a lot of suppliers out there have become very good at hiding the fact that they use anonymous subcontractors to source your ‘leads’.
Look out for the use of words and phrases like ‘network’, and ‘preferred partners’. Also, if you are sent a hosted asset landing page to view – make sure there is a real content library website behind it.
We've created an ungated Checklist for Quality Lead Generation with all the key questions you should be asking any lead generation provider you plan on working with.
The Rise of New AI Lead Generation Providers
Aside from the existing suppliers that are rebranding their solutions as AI, you also need to be cautious of the emergence of any new lead generation providers.
Just like the anonymous subcontractors we’ve just spoken about, AI has made it easier than ever for new B2B lead generation providers to appear on the scene. On the surface, they might have built an impressive-looking website and promise you high-end AI lead generation solutions, but then fail to deliver the quality you need; feeding you high volumes of low-quality, outsourced data.
This makes the industry even more saturated and confusing for B2B tech marketers to navigate. Finding the right, genuine suppliers and being able to trust them is harder than ever.
The key is, as always, to check where your supplier is getting their data and challenge the source – preferably from their own 1st party audiences. And to then ask for an example journey of your leads for extra reassurance before you commit to a partnership.
For example, Headley Media’s Reader Journey gives you a breakdown of exactly how our leads are generated. The process showcases how our readers become leads from downloading your content through to lead validation and delivery. As you’ll see your content is hosted on real websites, instead of microsites or landing page extensions with no breadcrumbs.
Be careful with generative AI - most GenAI engines pull information from all over the internet, and you won’t always know where it has come from. As with everything in lead generation, trustworthy data is the key! If you can’t trust the data it gives you, it’s worthless.
Chloe Addis Head of Marketing, Headley Media
5 Questions To Ask Suppliers Using “AI” Within Their Lead Generation
To figure out what your potential lead generation supplier is doing with AI, and whether you can trust them, there are a few qualifying questions you can ask.
Q1: First of all, AI simply cannot conjure new leads and valuable data out of thin air. So, what is it that is being generated from AI?
Q2: When did they start using AI? How has it made a difference to their existing lead generation process?
Q3: Why are they using AI? What’s the benefit to you – is it cost? Time? Quality of data? How can they prove the benefits to you. If it’s saving them time by creating efficiencies, that’s all very well, but how is this a benefit to you?
Q4: Where are they getting the data? Is it from their own databases? Is it from a 3rd party? Can they give you details of all the 3rd parties it comes from?
Q5: How do they validate all their data? Is it all quality-checked by humans? Does AI play a part in the validation process and if so, how?
Real & Potential Uses of AI in Lead Generation
Let’s take a look at some of the main ways AI is being used in lead generation, and the ways it could be used in future – along with the perks and pitfalls of these uses.
Intent Data Targeting
Many lead generation companies are claiming to have boosted their intent data services, list segmentation and personalization with AI, using big data, machine learning, actionable insights and predictive intelligence.
Often this means they have used AI to automate and speed up existing processes, creating efficiency in-house.
Some providers might also claim that AI allows them to do these things “at scale”.
However, for quality and transparency, these processes all still require human oversight and lead validation to check that the data pulled in is accurate.
After all, AI is still in its infancy and requires constant feedback and input, so it should be closely regulated.
Account-Based Marketing
Similarly, lead generation companies are offering to improve your account-based marketing (ABM) through AI.
The offering here ranges from automating data analysis among buying committees, to aggregating data and identifying patterns and insights to better understand and prioritize your leads. (Which are all things a good lead generation specialist should be doing already - just automated/sped up/branded as AI!)
There is also fairly widespread use of genAI to generate personalized content and messaging to nurture ABM leads. As with any content creation this style of AI should assist not replace, to ensure quality and brand reputation is maintained.
Content Creation for Syndication
It’s a big driver of efficiency for marketers at the moment: using the likes of ChatGPT to generate briefs, content ideas, email messaging, etc.
There is something of a taboo in the marketing industry around using AI to generate whole articles. It can be done, but for example, it won’t lead to good SEO outcomes, and it won’t produce stand-out syndicated content for lead generation.
If you’re gating your content for content syndication, it should be high-quality and original.
Generative AI can be really useful at the beginning of the creative process, for example when you’re struggling to start a piece, or you want to sense check or build upon an idea.
However, one of our favorite marketing uses for GenAI in content creation comes at the other end of the process: when it’s used to create meta descriptions and content summaries, ensuring articles can be optimized for search and made ready for content syndication as quickly and easily as possible.
Again, any content creation that is being managed by an AI solution should be proofread by a human before distribution, to protect your brand reputation.
Predicting Your Leads’ Future Activity
By analyzing existing datasets, from leads’ previous behavior and behavior from ‘lookalike’ leads, you may be able to use AI to forecast leads’ future buying patterns for their clients.
This one is young technology, with a lot of potential - but it’s not an exact science. The versions of it we’ve seen so far are essentially automated lead scoring and intent data analysis.
Personality Profiling
To personalize messaging, some lead generation companies are claiming to use AI to profile their clients’ leads, based on their social media, browsing habits and purchase history.
Without needing to perform personality tests or observations, AI is giving them an overview of not just leads’ buying and intent signals, but their personality traits and characteristics, for clients to use in targeting them.
This one is not widely in use yet, as it’s a data privacy minefield. How can the supplier demonstrate that the leads have consented for their data to be used this way? Legitimate interest within the current GDPR legislation (and similar legislation globally) states that any data held on an individual for B2B use must be relevant. Are you confident in proving the relevance of holding personality traits and characteristics for your prospects?
In a world that’s increasingly concerned about data privacy online, this feels like a use of AI you should approach with caution.
The Key To High-Quality Data & Personalization
A lot of these AI solutions sound very impressive, because:
- they’re marketed as unique, proprietary tools;
- there’s no doubt they drive efficiency;
- and, crucially, they’re data-centric.
But, as we said before, AI can only enhance data analytics and management if the data is high-quality to start with.
We know too many lead generation suppliers outsource their clients’ lead generation to the anonymous subcontractors, the mysterious and murky 3rd parties, producing poor-quality, unvalidated leads that often turn out to be unreachable.
To guarantee high-quality, Marketing Qualified Leads (MQLs), AI or no AI, your supplier should be using their own lead generation platforms and validating those leads in-house. If they’re not using their own 1st party sites, it is likely they’re using subcontractors or third parties, and they’re often not being transparent about it.
They should be able to show you the complete lead generation process, from the lead’s perspective.
Our advice to you, is to challenge the source – consider the garbage in, garbage out concept when it comes to lead generation, especially when utilizing AI.
At Headley Media we own 265 content syndication platforms to host our clients’ content on, attracting targeted, sector-specific audiences in 60 countries.
We use 1st party intent data, cross-referenced with trusted 3rd party data from Bombora, to ensure a high level of personalization and targeting for our clients.
Choose a lead generation supplier you can trust - look for one that offers unbeatable data quality, rather than vague promises.
Bonus tip: use our Lead Generation Quality Checklist to measure up any potential suppliers.
