Killing Copy-Paste Content with Original Insights
Peter Caputa’s Playbook for Turning a Social Feed into Databox’s Growth Engine
When Peter Caputa took the reins at Databox, Google’s algorithm felt less like a faucet and more like a slow drip.
“Around the same time we also started seeing organic search drop… it was really hard to grow traffic and the leads we get from organic search,” he recalls, explaining why he “jumped onto LinkedIn and just said, all right, I’m going to do this.”
Fast-forward to today: Caputa has published more than 330 posts in the last year, racked up 3 million impressions, and attracts roughly 100 new Databox trials every month from a following that now tops 33,000 people.
The numbers matter less than the underlying discovery: LinkedIn isn’t a broadcast channel tacked onto marketing—it can become marketing, sales, and customer success rolled into one continuous conversation.
Linkedin is full-stack marketing
Caputa’s first surprise was realizing that LinkedIn is “so much more… it’s really a full-stack kind of service” where every post can nurture followers, educate existing customers, and spotlight reseller partners simultaneously.
Instead of fragmenting his effort across separate newsletters, webinars, and partner portals, he lets the feed carry that weight.
Polls invite product feedback; feature breakdowns double as customer enablement; partner case studies give resellers social proof they can repost. “I’m learning as much as I’m teaching,” he says of the dialogue that erupts below each post.
Staying in touch beats hunting for strangers
Caputa is quick to admit LinkedIn isn’t always the fastest path to net-new names in a CRM.
What it does dominate is “stay-in-touch marketing” for the thousands who already shook his hand at an event or bought the software years ago.
Those dormant contacts “come out of the woodwork” in his DMs precisely because they’ve been quietly absorbing daily updates in their feed.
Email could never support that cadence without feeling spammy; LinkedIn can.
“If I can get them to follow me… that’s 30 posts a month that reinforce the value of our product and maybe get them to log back in,” he notes.
The platform becomes a passive but persistent retention loop—one that partners benefit from as well, since every customer-focused story also validates the reseller ecosystem.
Community over algorithms
“People are too focused on getting new followers… everybody’s thinking, how do I play the algorithm?” Peter shared.
The real opportunity, he argues, is writing for the audience you already earned—existing customers, partners, and advocates—because that cohort generates both the feedback that shapes the product and the referrals that swell pipeline.
When reach dips, he doesn’t blame the feed; he simply keeps telling customer stories.
The metric he watches is resonance, not virality.
Build a content engine
Peter’s marketing team treats LinkedIn publishing like product development.
They mine call transcripts, support tickets, and in-app chat to surface real user questions, then design surveys or expert round-tables to collect data that answers them.
Most companies, he says, still “wake up in the morning and think, I guess I’ll post something,” even though they admit posting is the most important LinkedIn activity.
Databox does the opposite: research supplies raw insight, writers draft posts, and Caputa keeps a steady ten-day queue scheduled—an efficiency that reduces his own writing time to “about an hour or two tops per day.”
Scaling Voice with “Pete GPT”
To maintain volume without diluting authenticity, the team built a private language model trained on everything Caputa has written.
“Pete GPT” ingests fresh survey data or customer transcripts and spits out first drafts that Caputa still rewrites by at least 50 percent, adding personal anecdotes and sharpening angles.
The model isn’t a shortcut to disengage; it’s a prosthetic that lets him focus on nuance rather than blank-page dread.
Original Data as the Endless Well
Caputa’s disdain for recycled blog statistics underpins the entire system.
For nearly a decade his team has run primary research: surveys of 100–300 practitioners, expert panels, and nonstop customer interviews.
“If you ask twenty people the same thing, you start to see patterns,” he says—and those patterns power posts that no AI rewrite can replicate.
Proprietary numbers give Databox instant authority, spark comment-section debates, and spin off long-form reports that rank in search long after the social moment fades.
Until next time, let’s stay connected…
Caputa’s approach rewrites the default order of operations. Rather than drive trials, then build community, he builds community first, confident that trust will convert when timing aligns. It works because the community content is useful long before a purchase decision, is visible every day without inbox fatigue, and is grounded in data rather than opinion.
For leaders wondering whether the return is worth the hours, Caputa’s own motivation offers a clue. “My main driver is the impact I can have on other people… I know that’s happening because of my LinkedIn effort,” he reflects after recounting how a single comment solved a follower’s sales-funnel dilemma.
Impact begets motivation, which sustains consistency, which compounds reach—a flywheel invisible to the algorithm but obvious in the results.
Treat LinkedIn as the front door, the living room, and the help desk of your company all at once. Publish data nobody else owns, talk to the customers already cheering you on, and let the feed stitch every stage of the journey together. Do that daily for a year, and the algorithm won’t matter nearly as much as the relationships you’ve built in plain sight.
If this episode resonated with you, follow Peter follow on LinkedIn. And don’t forget to check out Databox too.
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