HockeyStack connects with your entire tech stack and website to reveal what’s driving pipeline. All with multi touch attribution models, forecasting, incrementally testing, and marketing mix modeling.
HockeyStack visualizes the entire buyer journey from the first impression to closed won. You can filter by industry, account tiers, company size, and any other filter you need to see the companies you want to see.
You can use multi-touch attribution to measure the revenue influence of each page, paid media, blog post, video, webinar, e-book, case study, whitepaper, and any other content you have on your website.
HockeyStack measures the pipeline influence of all channels and allows you to build any type of dashboard with no code with data flowing from all your platforms. Get answers to all your questions, optimize with data, and drive more pipeline.
If you have a large brand and media spend, marketing mix modeling can help you understand the influence of different channels, online and offline, on your pipeline with core metrics, like impressions and spend. HockeyStack offers MMM models in the enterprise plan.
HockeyStack uses historical data to forecast your performance marketing and give budget optimization recommendations based on your pipeline goals and quarterly budget.
HockeyStack’s lift reports measures how much a channel or a campaign increases the baseline conversion rate with hold-out groups so that you know where to focus on.
Pair self-attribution with software-attribution. Make better decisions.
We can track more than most, but we can’t track everything. Use self-attribution to find untrackable touch points that matter. We’ll take care of the rest.
We can track more than most, but we can’t track everything. Use self-attribution to find untrackable touch points that matter. We’ll take care of the rest.
Important historical website data from Big Query or a data warehouse
Store website data forever, without data retention limits
Track website activity across subdomains in a single account
Track and measure more accurately by sampling your entire dataset, not a subsection of it.