Most founders assume influencer marketing is a big-budget, enterprise game. Ours wasn’t. We ran a real influencer program for one of our portfolio companies, picdrop, with about €25,000 over two quarters, no dedicated headcount at the start, and no existing creator relationships outside our home market. Here’s what actually happened, and what it means if you’re thinking about testing the channel yourself.
The problem: strong at home, invisible abroad
picdrop is a photo delivery and proofing tool with real traction in the DACH region. Outside of it, in the US, UK, Canada, and Australia, almost nobody had heard of it. No influencer program existed. No benchmark data on what creators cost or deliver in the photography niche. No playbook.
That’s a familiar spot for a lot of bootstrapped SaaS founders. You’ve won a market. Expansion into a new one feels like starting from zero, except now you also have a business to run.
Why we picked influencers over organic growth
Photography creators have something most channels don’t: direct, trust-based relationships with the exact audience picdrop needed to reach. Pro photographers trust the creators they already follow more than they trust an ad. That trust travels faster than organic content usually can.
We focused on micro creators (3,000 to 100,000 followers) and mid-tier creators (100,000 to 500,000), and skipped macro influencers entirely. Macro creators cost more and make attribution murkier, exactly the kind of complexity a bootstrapped budget can’t absorb. We gave creators a brief, not a script. Letting them shoot in their own voice, using their own workflow, turned out to matter more than we expected. That approach shaped everything about how the program was run day to day, and it’s a big part of why the team behind it was able to take ownership so quickly.
The part that made the difference: hiring before scaling
We didn’t try to run this centrally forever. Early on, alongside testing the channel ourselves, we hired a dedicated partner manager inside picdrop. Once she was onboarded, she and our central marketing lead worked the channel together before she took it over entirely, handling scouting, outreach, and creator relationships day to day.
By the end of the first half, picdrop had a functioning influencer operation running with almost no central involvement. That’s the real outcome of this test. Not just the views or the sign-ups, but a repeatable system the team could own going forward: scouting criteria, outreach templates, a tracking process, and a documented playbook. If you’re testing a new channel in your own business, that’s the thing to build for, not just the campaign in front of you.
What we’d tell another founder testing this
A few things held up consistently enough to call them rules rather than one-off findings. Direct messages outperformed email for outreach, 30% response rate versus 23%, so DM-first should be your default, not an afterthought. Creators who used the product themselves before filming made noticeably better content than ones working off a brief alone; product access beats a good script every time. And frame the first round of any influencer test as a brand awareness investment, not a performance channel. Expecting immediate, attributable conversions from a channel built on trust and discovery sets you up to kill something too early that just needed more time.
CPM in a niche category will run higher than the platform average. Build that into your budget from day one instead of getting surprised by it three campaigns in.
The bigger lesson
This wasn’t really about influencer marketing. It was about testing a new, unproven channel on a real budget, with a real team, and building a durable process out of it instead of a one-time spike in views. That’s the pattern we look for across every company in our portfolio: get the initial signal cheaply, hire the person who can own it, then hand them a system instead of a spreadsheet full of open questions.
If you’re weighing whether a channel like this is worth testing in your own business, the honest answer is: probably, but budget for the learning curve as much as the results. The system you build along the way tends to outlast the campaign that funded it.
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