Client: Topmate
Creator Type: Tech / DevOps Educator
Campaigns Run: 5 outbound campaigns across LinkedIn and WhatsApp
The Problem
One of the creators on Topmate was running a DevOps and Cloud projects program aimed at IT professionals and beginners who wanted to break into the tech industry. The program itself was solid, focused on practical, real-world project experience rather than surface-level certificates. However, the creator faced a fundamental challenge: distribution.
There was no predictable way to reach interested students at scale. Organic content worked sporadically and depended heavily on algorithms and timing. Paid ads were expensive, inconsistent, and difficult to sustain over time. Webinar registrations fluctuated from launch to launch and were often driven more by luck than by a structured system. What the creator needed was not better content or a better offer, but a reliable outbound mechanism that could consistently start conversations with the right students and guide them toward webinar and program sign-ups without sounding spammy or overly sales-driven.
Our Approach (What We Actually Did)
Instead of running a single, one-off campaign, we treated this engagement as a controlled outbound experiment. We designed a multi-phase strategy spread across five separate campaigns, each with a distinct purpose and messaging angle. The objective was not just to “get replies,” but to understand how students respond at different stages of awareness and intent, and to progressively refine the messaging based on real engagement data.
Phase 1: Foundation – Simple, Clear Value Messaging
We began with a foundation phase focused on clarity and simplicity. At this stage, the goal was to validate demand and establish baseline response rates without relying on heavy psychology or personalization. The messaging clearly explained what the program was, who it was designed for, and what outcomes students could realistically expect, with a strong emphasis on real DevOps projects and practical learning. The call to action was intentionally soft, inviting conversation rather than pushing an immediate signup.
This phase helped us answer two critical questions early on: whether students would reply at all, and whether the offer resonated in a cold outreach environment. The response was strong, with high reply volume and meaningful early conversations. This gave us confidence that the core offer had real pull and that outbound was a viable growth channel.
Phase 2: Student-Trigger Messaging (Psychology Shift)
Once we had baseline data, we shifted the messaging strategy completely. In this phase, we leaned into student psychology rather than program features. The messaging began addressing common student fears and frustrations, such as uncertainty around which skills actually matter, anxiety about falling behind peers, and dissatisfaction with generic certificates that don’t translate into real opportunities.
The tone became shorter, more conversational, and more emotional. Instead of sounding like a course pitch, the messaging framed the program as something people “like them” were already using to get ahead. We deliberately avoided buzzwords and hype, choosing to speak in the same language students naturally use. This shift didn’t just increase replies; it significantly improved the quality of conversations, with students engaging more deeply and asking more intent-driven questions.
Phase 3: Personalization at Scale
In the next phase, we layered in light personalization while maintaining scale. By this point, we had identified students who had already shown interest through LinkedIn engagement, comments, or prior interactions. Instead of treating them as cold prospects, we reframed the outreach as a reminder rather than a pitch.
This is where WhatsApp link-sharing campaigns became especially effective. Our key insight was that students who had already engaged didn’t need further persuasion. They needed clarity, speed, and low friction. By using reminder-style messaging and providing direct WhatsApp or access links, we reduced resistance and made it easy for them to take the next step without overthinking.
Phase 4: Follow-Ups as a Strategy (Not an Afterthought)
A major differentiator in this campaign was how follow-ups were handled. Most outbound campaigns fail because follow-ups are weak, repetitive, or robotic. Here, follow-ups were treated as a core strategic lever. Every follow-up was pre-planned, human in tone, and context-aware.
Instead of using generic lines like “just following up,” each follow-up introduced a new angle, a new reason to respond, or subtle social proof. In some cases, we used deadline-based nudges without resorting to fake urgency. This approach alone recovered a large percentage of replies that would typically be lost in standard outbound flows.
Results (Across All 5 Campaigns)
Across all five campaigns, the outbound system generated more than 4,601 reachouts and resulted in 188 replies. From these conversations, 37 calls were booked and 59 likely conversions were identified. The total pipeline generated from these efforts amounted to $13,098, with an offer price of $222.
Beyond direct revenue, the campaigns also redirected hundreds of students to WhatsApp, created a significant spike in webinar attendance, and resulted in a reusable outbound framework that could be applied to future launches and creators on the platform.
Why This Worked
The success of this campaign came from allowing messaging to evolve based on real data rather than assumptions. We spoke in the language students naturally use instead of relying on traditional marketing copy. Volume was balanced with relevance, ensuring outreach never crossed into spam. Follow-ups were treated as a strategic asset rather than an afterthought, and each campaign built on the learnings of the previous one instead of starting from scratch.
How We Did It (The Real System)
At its core, the system was built on clear ICP definition, a multi-phase campaign structure, continuous message testing, and progressive personalization. Strong reminder-based WhatsApp flows reduced friction, while aggressive but human follow-ups ensured conversations didn’t die prematurely. Continuous optimization across campaigns allowed performance to compound over time.
Final Takeaway
This case study wasn’t about a single viral message or a lucky campaign. It was about building a repeatable outbound engine that consistently starts conversations, warms up students, and drives sign-ups in a predictable way, all without relying on paid ads.
