5 priorities of lead generation in the AI era

Contents

Lead generation has always been more complicated than e-commerce. The cycles are long and the data is dirty, with no way to immediately distinguish good leads from invalid ones. Here is how this world changes with the correct implementation of AI.

The automation problem

Lead generation uses various channels to acquire contacts, and among the most cost-effective we find SEO, email marketing and webinars. (2) AI is not meant to replace these tools, also because it is not a real channel in itself, but if implemented correctly it can bring up to 55% more qualified leads compared to a traditional campaign. The problem is that there is often no real cohesion between all the various contact acquisition campaigns. (2)

It is worth remembering, for example, that campaigns like Performance Max on Google Ads are designed to optimise the value of conversions, not their volume. (4)

This means that if I start recording a certain number of incorrect conversions (dirty leads, poorly relevant channels, incorrect conversion actions), the system learns from wrong data, and where tracking is not done properly, the machine learns from flawed data, scaling the problem further. This will lead the machine to continue in the wrong direction, faster and faster, and in an increasingly effective way.

There is a series of mistakes being made that produce bad data, unqualified leads and campaigns that, instead of returning on the investment, make us think it is all cost with no return, and that the investments are more like scams than advertising campaigns.

We will now give some advice on how to improve the settings of a campaign aimed at contact acquisition, which at its core must have the simplicity of being specific to one thing. Having a page, a landing page, that has multiple objectives, from the phone call to the form, from WhatsApp to social media interactions, looks more like something designed to hope that a user clicks on it by accident, rather than something built around a reason or a strategy.

Having too many conversion paths on a landing page does not help the user decide. (1) It creates ambiguity for automated systems. The AI stops understanding which action you are trying to obtain and starts distributing the budget less efficiently.

5 priorities for good lead generation

1. Conversion data comes first

Before touching budget, creative or targeting, check whether your conversions are being recorded correctly. Verify that CRM data is being passed to the platforms cleanly. Check that lead status updates are being sent back as signals. If the AI thinks it is doing well when it is actually making mistakes, every subsequent optimisation will make the problem progressively worse. (1)

2. Simple landing pages, not elaborate ones

A page with three different calls to action is not a page rich in options. It is a page that does not know what it wants. The page must be designed around clear needs, speaking to the user and explaining in very few sentences:

• The problem the user has;

• How our product or service can solve it;

• The results they can expect from our intervention.

That is it. Adding more detail can lead to errors in identifying the ideal user, those who are potentially qualified leads. More detail increases the likelihood of reaching users who are not the right fit.

To test this, take the landing page and run it through Gemini or the Google Ads AI for campaign creation. If it generates titles and descriptions that do not align with what you are looking for, that same mistake will be made once the campaign goes live. (1)

3. Budget across the entire funnel, not just the final conversion

AI systems calibrate themselves based on how likely a potential lead is to convert (sentiment signals, visibility and context), not only on the channel that ultimately drove the conversion (last-click performance). (4) If all the budget is concentrated at the bottom of the funnel, such as a brand campaign or a search targeting a handful of selected keywords, you are losing valuable data that could improve the quality of incoming leads. In B2B this is even more relevant, given that purchase cycles are long by structural necessity. And do not make the mistake of thinking that B2B is still a predominantly professional channel where professionals choose based on purely rational reasons. B2B has now become emotional too. (6)

4. Lead gen also has a feed, meaning a structured collection of information

Even if you do not have a product catalogue like an e-commerce store (where information is collected per product), you still have structured data about your company, the services offered and the architecture of your site. A well-built feed, even a simple one, helps AI systems understand who you are and what you offer. The same applies to map profiles, as is the case for those in the HoReCa sector, who offer various types of services that, if not managed properly, have clear consequences: incomplete or inconsistent information creates confusion in attribution, especially for leads that come in via phone. (1)

5. Creative must work on its own

AI can break apart, recombine and shorten your creative assets. In some placements you might have just one headline to explain what you do and why someone should contact you. If your message needs three consecutive titles to make sense, that is a problem. Every single asset should communicate something useful, even when isolated from its context. (1)

Where to start

AI has not changed the fundamentals. It has made performance gaps less forgivable. (5)

Those who had solid processes are seeing their advantages amplified. Those who had gaps in their data or confused messaging are seeing their mistakes scale automatically.

The starting point is not technological, it is editorial. Understanding what you are asking of the user, making sure the system understands the same thing, and building a data flow that reflects reality.

If you want to understand where the specific problem lies in your campaigns, you need to start by asking yourself whether what you are asking of the user is clear or not.

We at Duobu try to do a little better every day. It is not something that happens overnight, it takes time and only produces results when it is actually applied. Complaining that certain systems are inherently broken and that they "steal money" gets you nowhere. You are the one investing in a particular channel (such as Performance Max with Google Ads) and it is right to make it work properly, to the best of its capabilities.

Stop "gambling" with ads, stop "paying for results". Try to be more organised and build a clear, orderly structure.

The most valuable resource is not money, it is the time you put into what you do. You've got this!

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Sourses

1. Search Engine Land (2026) - 5 priorities for lead gen in AI-driven advertising - Navah Hopkins - https://searchengineland.com/lead-gen-ai-driven-advertising-priorities-473660

2. Martal (2026) - Lead Generation Statistics 2026: Trends, Benchmarks & Insights - https://martal.ca/lead-generation-statistics-lb/

3. Digital Applied (2026) - B2B Lead Generation with AI: Complete Guide 2026 - https://www.digitalapplied.com/blog/b2b-lead-generation-ai-guide-2026

4. DM Cockpit (2026) - Demand Gen + PMax 2026: Better Lead Quality - https://www.dmcockpit.com/articles/demand-gen-pmax-2026-better-lead-quality

5. Hatch App (2026) - How AI is Reshaping Lead Generation & Conversion in 2026 - https://www.usehatchapp.com/blog/ai-reshaping-lead-gen-conversion

6. Duobu (2025) - Lead Generation 3.0: Why 'advanced' 2.0 strategies are already outdated - https://duobu.eu/en/lead-generation-3