Introduction

Userpilot shifted from SEO to LinkedIn ABM, landing $900K pipeline in 90 days. Here's the honest playbook they built by trial and error.

What's the problem it solves?

SEO growth slowed as Userpilot moved upmarket. Their team needed a new way to target and convert high-value accounts. This guide breaks down how they built an ABM engine from scratch using LinkedIn ads, tight targeting, and smart campaign structure-while avoiding common pitfalls.

Quick Summary

Userpilot’s growth had always come from SEO and inbound. But in 2024, traffic stalled and conversions dropped as the product got more advanced and prices rose. Their inbound setup didn’t work for enterprise-level deals. Cold outreach helped, but it was slow and expensive. So, they tried LinkedIn-based ABM-and learned a lot the hard way.

They started by targeting many accounts with awareness ads, then used clicks and engagement to move accounts into deeper funnel stages with more specific ads. Campaigns were built around personas and job pain points. Data from LinkedIn was sent to Hubspot using ZenABM, allowing the team to personalize outreach based on ad interaction. The structure let them adapt messaging as accounts moved down the funnel, automate ad swaps, and track engagement with accuracy.

To manage all this, they used a tool stack of LinkedIn, Hubspot, ZenABM, Notion, and Clay, spending ~$2,500/month on tools. Their first campaign cost $52K and touched 1,417 accounts, generating $440K in pipeline. ABM outperformed cold outbound: it was faster, cheaper per dollar, and easier to scale without adding lots of headcount. The team sees ABM not as magic demand gen, but as the faster way to harvest interest already in-market.

Key Takeaways from the article

• SEO stopped working as deals got bigger and sales cycles longer
• ABM let them target high-value accounts more directly and personally
• Started with simple “one-to-many” campaigns to test interest
• Used LinkedIn ad data to move accounts through funnel stages
• ZenABM pushed ad engagement signals into Hubspot CRM
• Campaigns were built around personas and their specific pain points
• Split ad content by funnel stage: awareness, interest, consideration
• Deanonymized web traffic didn’t work-relied on LinkedIn data only
• Ran 100+ ads for 8 personas using images, videos, and thought leader posts
• CTR and CPC were best for single-image and video ads
• Used Notion to manage asset creation and naming for clean tracking
• Cold outbound cost 51% more and took twice as long for same pipeline
• Budgeting and account targeting was reverse-engineered from revenue goals
• Total cost: ~$52K for $440K in pipeline; $8.43 pipeline per dollar spent
• ABM needs a solid RevOps setup-don’t try it without a Marketing Ops lead
• Matching ads to intent and persona stages drove better results
• Campaign structure evolved from messy to clean through iteration
• Future plans include smarter retargeting and selective use of other ad formats
• TLAs worked well for top-of-funnel awareness, not conversions
• Final verdict: ABM is hard but beats cold outbound for speed and ROI

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