Automated lead generation, according to Dr. Connor Robertson, may not require an enterprise software budget or a dedicated technical team. Robertson, an entrepreneur and strategic advisor based in Pittsburgh, has built a system aimed at generating a more consistent inbound pipeline that runs on a small, connected set of tools at a relatively low monthly cost. His setup is less interesting for its price tag than for the principle behind it, and that principle is one he argues many businesses get wrong.
The core idea is to trigger on intent rather than on a schedule. Much outreach, Robertson notes, fires on a fixed timetable and sends the same message to everyone regardless of what they are doing. An approach designed to be more efficient responds to signals of intent as they
happen. Someone visiting a specific high-intent page, engaging with a particular piece of content, or partially completing and then abandoning a form is, in his view, sending a signal worth answering. An automation that responds to that signal within seconds, he says, may convert at higher rates than a sequence that fires days later on a preset cadence, because it reaches the person while their interest may still be live.
The stack Robertson uses to do this rests on four components, each handling one job. A pipeline and customer management platform, GoHighLevel, provides the trigger logic and manages the pipeline. An automation tool, Make, handles the webhook processing
and moves data between platforms. An AI model, Claude, generates the personalized outreach content. A warmed sending domain handles the actual email delivery. At the scale of a single business, Robertson puts the combined cost at roughly 47 to 55 dollars a month, which he describes as the infrastructure for an intent-triggered system that is designed to run around the clock.
The way those pieces fit together is straightforward once the logic is clear. When an intent signal fires, it sends a webhook to the automation tool carrying a payload of relevant context. That tool processes the payload, extracts the fields that matter for personalization, formats them into a structured prompt, and passes the prompt to the AI model through its interface. The model generates a message that references the specific signal and its context, and the automation routes that message to the appropriate channel. In Robertson’s setup, the entire sequence from signal to finished output can take under a minute.
What that produces, in practice, can be different from a mass email. In one example Robertson describes, a prospect visits a particular service page, reads it for more than two minutes, and leaves without converting. Within roughly a minute and a half, a message arrives in their inbox referencing what they were looking at and offering a specific, relevant next step. It does not read like a broadcast. It reads, he says, like someone noticed they were there and took the time to write something specific, an effect the system is designed to achieve because the AI has real contextual data to work from rather than a generic template.
Robertson measures the whole thing against four numbers. Reply rate by sequence tells him whether the messaging itself may be working. Cost per reply tells him how efficient the system may be. Cost per qualified conversation tells him whether the leads may be the right ones. And the cost per closed client tells him whether the entire funnel may be converting. Together, he says, those four figures can help tell him whether the system is worth running and exactly where to adjust it. The discipline of tracking cost at each stage, rather than simply counting messages sent, is part of what can help keep a lean system honest, since a setup that looks cheap can still be inefficient if the replies it generates never turn into real conversations.
The broader lesson Robertson draws is that the advantage may not come from the particular tools, which will change over time, but from the principles underneath them. Respond to genuine intent rather than broadcasting on a schedule. Personalize using real context rather than templates. Keep the infrastructure lean. And measure the cost of every stage rather than only the activity at the top. A business that internalizes those ideas, he suggests, may be able to build something useful without the enterprise budget or the technical team that many assume such a system requires. For owners intimidated by the idea of automation, that reframing may be a useful part of his approach, since it treats the concept as a matter of clear principles rather than expensive software.
About the Author
Dr. Connor Robertson is an entrepreneur, author, and strategic advisor based in Pittsburgh. He is the founder of Elixir Consulting Group and host of The Prospecting Show. More about his work is available at drconnorrobertson.com.
