How HockeyStack's GTM team uses real-time ad signals to identify and reach in-market companies
"adyntel stood out because it was fast, precise, and directly integrated into our workflow. Setup took days, not weeks, and our SDRs could immediately see ad activity alongside our CRM."
If you're in B2B SaaS, you can't help but hear about HockeyStack.
They raised a $26M Series A this year, and Ahrefs named them the #10 hottest tech startup in their top 50 list. Since graduating from YC in 2023, their hockey stick growth is impressive in a market where every channel seems to suck.
While most early-stage startups focus on outbound, HockeyStack worked on building a strong ecosystem around their brand. They went all-in on inbound, spending $2M on LinkedIn ads in 2024 when most other brands were cutting spend.
While they saw a lot of initial success, being 100% reliant on inbound was unpredictable and unscalable. By early 2025, the team shifted focus to outbound, and just 6 months later, it became their most profitable channel.
While HockeyStack's automated outbound engine was already sophisticated (90% of prospecting was fully automated using internal and third-party signals), they lacked a reliable, scalable way to use ad intelligence in their scoring model.
Some of the main challenges HockeyStack needed to solve were:
The team lacked a clean and scalable way to use ad activity as part of their prospect prioritization mix.
Ad-library data was collected manually, which was slow, inconsistent, and outdated.
Winning GTM teams understand that using data others don't have in plays that others can't run at scale is how you win.
While firmographic and technographic data gave HockeyStack an overview of potential customers, it didn't reveal which companies were actively investing in growth in real-time.
"We knew which companies looked good on paper, but not which ones were actually spending and growing," explained Viktor Salnich, HockeyStack's Senior GTM engineer.
While reviewing closed-won data, the GTM team noticed a pattern: their best-fit accounts were actively running ads across social channels.
"We discovered that companies running 50+ ads were almost always ICP. It's a reliable signal of marketing maturity and consistent spend," shares Viktor.
He adds: "Running that many ads usually means there's a team behind it, not just a founder experimenting. It correlates strongly with revenue size, campaign volume, and readiness for HockeyStack."
It seems obvious: companies that invest heavily in paid growth are more likely to be in the market for revenue attribution tools. But the alpha isn't in that insight; it's what you do with it and the speed with which you act on it.
"Before Adyntel, we didn't have a clean or scalable way to use ad data in prospecting," says Viktor.
HockeyStack knew that without an automated way to identify companies that were actively spending and growing, it would be impossible to qualify prospects at scale.
When you have 500,000+ prospects to qualify and you need to check the Meta and LinkedIn Ad Libraries manually, you need an army of SDRs to piece together a picture of each company's marketing activity.
"Our team would manually check Meta or LinkedIn Ad Libraries and rely on SimilarWeb or BuiltWith for rough insights. It was slow, inconsistent, and often outdated," says Viktor Salnich.
Using Adyntel's API enabled them to automatically pull live paid ad activity across Meta, LinkedIn, and Google into their custom-coded solution and push it into their CRM, right where their team needed it.
"Adyntel stood out because it was fast, precise, and directly integrated into our workflow," shares Viktor. "Setup took days, not weeks, and our SDRs could immediately see ad activity alongside our CRM."
With Adyntel, the GTM team can now instantly identify which companies are running active campaigns, understand their channel mix, and prioritize outreach to target companies showing clear buying signals.
"Ad volume carries strong weight, but it's all about context," says Viktor. "Adyntel gives us that context—who's spending, where, and how consistently."
Aside from identifying and ranking companies based on ad volume, Viktor and his team layer on additional data and look at:
"It's one thing to run ads. It's another to test, iterate, and diversify across channels, so each platform also carries a different weight:
carries the highest weight since it indicates a B2B focus
indicates D2C or B2B2C activity
shows steady, ongoing investment
Each platform signals a different GTM maturity level, and that nuance helps tailor outreach by industry type.
"These patterns help us understand how structured a company's marketing team really is and enrich our scoring model to tailor outreach and timing," says Viktor.
"If we see heavy recent ad activity, we approach with urgency because those companies are in a growth push. For low or paused activity, the tone becomes more educational and strategic. It's about helping them restart or optimize their paid motion."
While Viktor and his team recently started using Adyntel, it's already brought efficiency and a scalable foundation to their outbound strategy:
Reduced reliance on manual work from SDRs, cutting operational expenses
Ensures alignment with high-value accounts
Fast, precise ad data that allows SDRs to immediately see ad activity alongside their CRM and target companies actively investing in growth
Repeatable processes that can scale with company growth
"No doubt we'll experience a huge uplift in the qualified opportunities booked because 100% of the companies we target hit size criteria and run ads," concludes Viktor.
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