to teach
to teach
to teach
How to teach escaped the SaaS payback period trap with incremental acquisition signals.
How to teach escaped the SaaS payback period trap with incremental acquisition signals.
About
to teach is an AI-powered education platform that enables teachers to create personalized worksheets, exercises, and lesson plans in seconds – transforming YouTube videos, texts, and images into curriculum-aligned teaching materials.
Industry
EdTech / SaaS
Users
300,000+ teachers
Headquarters
Leipzig, Germany (DACH)
Model
Freemium SaaS
About
to teach is an AI-powered education platform that enables teachers to create personalized worksheets, exercises, and lesson plans in seconds – transforming YouTube videos, texts, and images into curriculum-aligned teaching materials.
Industry
EdTech / SaaS
Users
300,000+ teachers
Headquarters
Leipzig, Germany (DACH)
Model
Freemium SaaS
About
to teach is an AI-powered education platform that enables teachers to create personalized worksheets, exercises, and lesson plans in seconds – transforming YouTube videos, texts, and images into curriculum-aligned teaching materials.
Industry
EdTech / SaaS
Users
300,000+ teachers
Headquarters
Leipzig, Germany (DACH)
Model
Freemium SaaS
Challenge
As a subscription-based SaaS, to teach's growth equation hinges on one critical ratio: CLV to CAC. With payback periods stretching beyond optimal thresholds, the team faced a classic scaling dilemma – aggressive customer acquisition would burn cash faster than lifetime value could recover it. Brand search campaigns showed strong ROAS on paper, but much of this performance was attributable to organic demand. Every euro spent on non-incremental conversions inflated CAC and extended payback cycles, limiting the company's ability to reinvest and scale.
Challenge
As a subscription-based SaaS, to teach's growth equation hinges on one critical ratio: CLV to CAC. With payback periods stretching beyond optimal thresholds, the team faced a classic scaling dilemma – aggressive customer acquisition would burn cash faster than lifetime value could recover it. Brand search campaigns showed strong ROAS on paper, but much of this performance was attributable to organic demand. Every euro spent on non-incremental conversions inflated CAC and extended payback cycles, limiting the company's ability to reinvest and scale.
Challenge
As a subscription-based SaaS, to teach's growth equation hinges on one critical ratio: CLV to CAC. With payback periods stretching beyond optimal thresholds, the team faced a classic scaling dilemma – aggressive customer acquisition would burn cash faster than lifetime value could recover it. Brand search campaigns showed strong ROAS on paper, but much of this performance was attributable to organic demand. Every euro spent on non-incremental conversions inflated CAC and extended payback cycles, limiting the company's ability to reinvest and scale.
Solution
To compress payback periods and unlock sustainable growth, to teach implemented Innkeepr as the signal optimization layer in their marketing stack. By supplying Google and Meta with incrementality-optimized signals, they could guide platform algorithms toward high-value prospects and scale acquisition with confidence.
Solution
To compress payback periods and unlock sustainable growth, to teach implemented Innkeepr as the signal optimization layer in their marketing stack. By supplying Google and Meta with incrementality-optimized signals, they could guide platform algorithms toward high-value prospects and scale acquisition with confidence.
Solution
To compress payback periods and unlock sustainable growth, to teach implemented Innkeepr as the signal optimization layer in their marketing stack. By supplying Google and Meta with incrementality-optimized signals, they could guide platform algorithms toward high-value prospects and scale acquisition with confidence.
Results
6-month A/B test vs. control campaigns with statistical significance at p<0.05
77.4% CPA reduction – Google Brand Search
40.8% CPA reduction – Meta Ads
+8.1% CLV increase – Customer Lifetime Value
to teach's Journey
As a freemium SaaS in the competitive EdTech space, to teach needed to acquire paying subscribers efficiently enough to fund continued growth. With hundreds of thousands of free users across the DACH region, the opportunity was clear – but converting them profitably required precision. The challenge wasn't volume. The challenge was efficiency. With CAC eating into margins and payback periods limiting reinvestment capacity, the team needed a way to focus spend on users that justify acquisition costs.
to teach's Journey
As a freemium SaaS in the competitive EdTech space, to teach needed to acquire paying subscribers efficiently enough to fund continued growth. With hundreds of thousands of free users across the DACH region, the opportunity was clear – but converting them profitably required precision. The challenge wasn't volume. The challenge was efficiency. With CAC eating into margins and payback periods limiting reinvestment capacity, the team needed a way to focus spend on users that justify acquisition costs.
to teach's Journey
As a freemium SaaS in the competitive EdTech space, to teach needed to acquire paying subscribers efficiently enough to fund continued growth. With hundreds of thousands of free users across the DACH region, the opportunity was clear – but converting them profitably required precision. The challenge wasn't volume. The challenge was efficiency. With CAC eating into margins and payback periods limiting reinvestment capacity, the team needed a way to focus spend on users that justify acquisition costs.
Implementation Approach
to teach integrated Innkeepr to analyze visitor behavior patterns and predict incremental lifetime value at the user level. The platform's causal engine identified which prospects were likely to convert incrementally and which represented organic demand that would convert regardless of ad exposure. These predictions were automatically synced as audience and conversion signals to Google Ads and Meta. High-incrementality users received prioritized targeting, while low-lift segments were suppressed – ensuring every euro of ad spend drove genuine, measurable impact.
Implementation Approach
to teach integrated Innkeepr to analyze visitor behavior patterns and predict incremental lifetime value at the user level. The platform's causal engine identified which prospects were likely to convert incrementally and which represented organic demand that would convert regardless of ad exposure. These predictions were automatically synced as audience and conversion signals to Google Ads and Meta. High-incrementality users received prioritized targeting, while low-lift segments were suppressed – ensuring every euro of ad spend drove genuine, measurable impact.
Implementation Approach
to teach integrated Innkeepr to analyze visitor behavior patterns and predict incremental lifetime value at the user level. The platform's causal engine identified which prospects were likely to convert incrementally and which represented organic demand that would convert regardless of ad exposure. These predictions were automatically synced as audience and conversion signals to Google Ads and Meta. High-incrementality users received prioritized targeting, while low-lift segments were suppressed – ensuring every euro of ad spend drove genuine, measurable impact.
The Innkeepr Moment
The results validated what the team had suspected: a significant portion of their brand search spend was capturing demand that already existed. By redirecting that budget toward truly incremental conversions, to teach didn't just lower CPA – they fundamentally improved their unit economics. The 77.4% CPA reduction on brand search was the headline number, but the 8.1% CLV increase told the deeper story: Innkeepr's signals weren't just finding cheaper conversions, they were finding better customers.
The Innkeepr Moment
The results validated what the team had suspected: a significant portion of their brand search spend was capturing demand that already existed. By redirecting that budget toward truly incremental conversions, to teach didn't just lower CPA – they fundamentally improved their unit economics. The 77.4% CPA reduction on brand search was the headline number, but the 8.1% CLV increase told the deeper story: Innkeepr's signals weren't just finding cheaper conversions, they were finding better customers.
The Innkeepr Moment
The results validated what the team had suspected: a significant portion of their brand search spend was capturing demand that already existed. By redirecting that budget toward truly incremental conversions, to teach didn't just lower CPA – they fundamentally improved their unit economics. The 77.4% CPA reduction on brand search was the headline number, but the 8.1% CLV increase told the deeper story: Innkeepr's signals weren't just finding cheaper conversions, they were finding better customers.
"Innkeepr helped us understand which of our ad conversions were truly incremental. The results speak for themselves – we're now acquiring better customers at a fraction of the cost."
Felix Weiß
CEO to_teach
"Innkeepr helped us understand which of our ad conversions were truly incremental. The results speak for themselves – we're now acquiring better customers at a fraction of the cost."
Felix Weiß
CEO to_teach
"Innkeepr helped us understand which of our ad conversions were truly incremental. The results speak for themselves – we're now acquiring better customers at a fraction of the cost."
Felix Weiß
CEO to_teach
How to teach Uses Innkeepr
Innkeepr's signal optimization engine sits at the core of to teach's acquisition strategy. The platform processes behavioral data from their website, transforms it into incrementality-focused signals, and syncs these directly to Google and Meta. The result: campaigns that optimize for genuine business impact, not just conversion volume. With compressed payback periods and improved CLV, to teach now has the unit economics to scale acquisition further. Compressed Payback, Accelerated Growth For to teach, Innkeepr has become the layer that connects user behavior with paid acquisition efficiency. Instead of optimizing for raw conversions, the team now optimizes for incremental value – and the compounding effect on their growth model has been significant. Lower CAC plus higher CLV equals shorter payback periods. Shorter payback periods mean faster reinvestment cycles. And faster reinvestment cycles unlock the kind of sustainable growth that defines category leaders.
How to teach Uses Innkeepr
Innkeepr's signal optimization engine sits at the core of to teach's acquisition strategy. The platform processes behavioral data from their website, transforms it into incrementality-focused signals, and syncs these directly to Google and Meta. The result: campaigns that optimize for genuine business impact, not just conversion volume. With compressed payback periods and improved CLV, to teach now has the unit economics to scale acquisition further. Compressed Payback, Accelerated Growth For to teach, Innkeepr has become the layer that connects user behavior with paid acquisition efficiency. Instead of optimizing for raw conversions, the team now optimizes for incremental value – and the compounding effect on their growth model has been significant. Lower CAC plus higher CLV equals shorter payback periods. Shorter payback periods mean faster reinvestment cycles. And faster reinvestment cycles unlock the kind of sustainable growth that defines category leaders.
How to teach Uses Innkeepr
Innkeepr's signal optimization engine sits at the core of to teach's acquisition strategy. The platform processes behavioral data from their website, transforms it into incrementality-focused signals, and syncs these directly to Google and Meta. The result: campaigns that optimize for genuine business impact, not just conversion volume. With compressed payback periods and improved CLV, to teach now has the unit economics to scale acquisition further. Compressed Payback, Accelerated Growth For to teach, Innkeepr has become the layer that connects user behavior with paid acquisition efficiency. Instead of optimizing for raw conversions, the team now optimizes for incremental value – and the compounding effect on their growth model has been significant. Lower CAC plus higher CLV equals shorter payback periods. Shorter payback periods mean faster reinvestment cycles. And faster reinvestment cycles unlock the kind of sustainable growth that defines category leaders.
© 2025 Innkeepr. All rights reserved.
© 2025 Innkeepr. All rights reserved.
© 2025 Innkeepr. All rights reserved.