Measure, forecast, and predict incremental contribution
HockeyStack uses marketing mix modeling (MMM), incremental modeling, predictive modeling, and attribution modeling to measure, forecast, and predict marketing contribution across your entire go-to-market motion.
Marketing mix modeling (MMM)
Marketing mix modeling (MMM) uses machine learning statistical algorithms to analyze and pattern match historical data at the macro, aggregate level. With MMM, we can zoom out and estimate the incremental impact of hard-to-track brand activity and channel-level performance, as well as forecast revenue, simulate different budgets, and identify wasted spend.
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Incremental lift modeling
We use lift modeling to estimate the causal impact of a certain touchpoint or activity on a specific outcome like demos booked. For example, if we want to measure the lift a blog posts had on demos booked, we can compare people who visited the blog post (treatment) with those who didn’t (control), and measure the difference- retroactively.
Predictive modeling
Predictive modeling predicts the future based on historical data. We use it to predict buying intent (and keep sales fed with high-intent leads), identify buyers who fit your ICP criteria before they reveal themselves, simulate “what if” scenarios, forecast future revenue, and set better goals.
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ML attribution modeling
Out-of-the-box MTA models like linear, time-decay, U-shaped, and W-shaped weight touchpoints using arbitrary values. HockeyStack uses a statistical algorithm to weigh the value of each touchpoint more accurately based on its overlap with historical close/won touchpoints.
What’s possible?
Better marketing through better measurement
Baseline revenue
Measure baseline revenue (revenue from sales that come to you on their own, without direct response ads) so you can better measure the long term effectiveness of brand activity.
Incrementality
Statistical modeling helps better understand the cause and effect relationship between activities and outcomes so you can cut spend from programs that don’t drive incremental revenue.
Online and offline
Measure effectiveness online and offline, from cTV and paid media to traditional TV and print
Paid and organic
Zoom in on specific ad creative or blog posts to estimate their incremental influence on pipeline
Forecasting
Leverage historical data to forecast future revenue targets and the activities and spend you’ll need to hit them.
Budget optimization
Simulate what new customer growth would look like at different budgets, and identify points of diminishing return on ad platforms before you hit them so you don’t waste money.
What’s possible?
Better marketing through better measurement
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Baseline revenue
Measure baseline revenue (revenue from sales that come to you on their own, without direct response ads) so you can better measure the long term effectiveness of brand activity.
.png)
Incrementality
Statistical modeling helps better understand the cause and effect relationship between activities and outcomes so you can cut spend from programs that don’t drive incremental revenue.
.png)
Online and offline
Measure effectiveness online and offline, from cTV and paid media to traditional TV and print
.png)
Paid and organic
Zoom in on specific ad creative or blog posts to estimate their incremental influence on pipeline
.png)
Forecasting
Leverage historical data to forecast future revenue targets and the activities and spend you’ll need to hit them.
.png)
Budget optimization
Simulate what new customer growth would look like at different budgets, and identify points of diminishing return on ad platforms before you hit them so you don’t waste money.
Cognism’s Demand Campaign Optimization with HockeyStack
Discover how the demand generation team at Cognism uses HockeyStack to gain radical alignment around revenue and optimize their inbound and outbound pipelines.
“HockeyStack is an amazing end-to-end attribution tool! The amount of insights you could get is unmatched. It basically shows your funnels in another perspective.”
Oneflow Doubles Visitor to MQL Rate Using HockeyStack
How OneFlow used cohort reports, incremental lift, and multi-touch attribution to gain visibility into what channels, campaigns, and creatives influenced purchases so they could optimize ad campaigns for pipeline and revenue, not just platform metrics
“We use HockeyStack as a web analytics + revenue attribution platform with complete view into the customer lifecycle. Most of our quarterly OKRs and target metrics are measured directly from HockeyStack.”
How Whatfix Optimizes Their Content With HockeyStack
Discover how the content team at Whatfix uses HockeyStack to understand how content influences their pipeline and to showcase content’s impact across opportunities where they previously had no data.
“Now we can nail down attribution to identify both contacts and companies that have engaged with any of our content at any time in their buying journey.”