Discover how Cinemark optimized its audience targeting and used marginal return curves to expand its channel mix without sacrificing profit.
Cinemark expanded its channel mix from 7 to 13 channels in under three years while protecting profit, using marginal return curves to see the impact of each incremental dollar spent rather than average performance across the whole mix. Budgets were continually redirected away from lower-performing channels toward the highest impact-to-cost opportunities, on a weekly basis. The full results are detailed in the case study below.
Business Challenge
Cinemark’s messaging priorities shift week by week, tied to Hollywood’s release calendar, while the company works to stay engaged with existing moviegoers, attract new ones, and support ticket sales both online and in-store. Doing this across a fast-diversifying media landscape meant entering new channels with confidence, not guesswork, while keeping a stable framework underneath the constant change. Standard measurement approaches that only showed average performance over time couldn’t tell Cinemark where its next marketing dollar would actually pay off, or when a channel’s returns had already started to fade.
Objectives
Stay engaged with existing customers while attracting new ones across a fast-changing release calendar
Confidently enter new marketing channels without losing sight of overall spend efficiency
Understand marginal returns (mROAS), not just average returns to know exactly when to dial spend up or down
How LiftLab’s Agile MMM Platform Approached It
LiftLab’s Agile MMM Platform gave Cinemark four capabilities to work with:
Agile Marketing Mix Modeling: Marginal return curves built specifically for Cinemark, showing the impact of the last dollar spent in each channel
Incrementality Testing Suite: Ongoing experimentation combined with MMM results, replacing average-performance views with real-world validation
Weekly reallocation: Spend dialed up or down as demand shifted, rather than waiting on the next planning cycle
A unified performance view: With LiftLab’s Trust Engine, Cinemark obtained a comprehensive picture spanning both MMM and testing, closing the gap between budgeting, reporting, and channel-level decisions
The full detail behind this approach including how the marginal return curves are built, how testing and MMM results are combined, and how weekly reallocation actually work, is covered in the downloadable case study at the bottom of this page.
Results & Business Impact
Channel count grew from 7 to 13 in under three years, with budgets continually redirected toward the highest impact-to-cost opportunities
Marginal return curves enabled Cinemark with marketing channel optimization to identify exactly where the next dollar of spend would pay off, replacing average-performance guesswork
Weekly reallocation became possible, with spend dialed up or down as demand shifted from release to release
Shifting spend toward channels with higher marginal profitability drove top-level improvements to overall spend efficiency
LiftLab’s platform now serves as Cinemark’s single source of truth for budgeting, reporting, and to determine optimal spend allocations across channels, while Cinemark’s own in-platform tools stay focused on creative testing and execution.
Testimonials
“We were measuring incrementality, but to optimize our media spend, we needed both a single comprehensive view of our performance as well as a means to estimate the marginal profitability of our last dollar spent. LiftLab was the only vendor that offered this, along with a way to combine the MMM results with the findings from our ongoing testing. We can now optimize our budget by shifting spend to channels with higher marginal profitability, resulting in top-level improvements to spend efficiency as well.”
Key Takeaways
Average performance metrics hide diminishing returns while metrics like mROAS reveal exactly when a channel’s next dollar has stopped paying off.
Expanding channel mix is only efficient if reallocation decisions move as fast as the channels open up. A weekly cadence catches shifts that a quarterly one misses.
A single, unified view of performance builds more trust across teams than combining incrementality tests and MMM results separately.
The real value of a measurement partner shows up when something isn’t working, not just when results look good. Being able to explain a needed pivot matters as much as flagging one.
Need a detailed look at how LiftLab helped Cinemark expand into new channels, build marginal return curves, and reallocate spend weekly without losing profit?
FAQs about Cinemark Case Study
What results did Cinemark achieve with LiftLab?
Cinemark expanded its channel mix from 7 to 13 channels in under three years while protecting profit, guided by marginal return curves that showed exactly where each additional dollar of spend would pay off. Budgets were continually redirected away from lower-performing channels toward the highest impact-to-cost opportunities and shifting spend toward higher marginal profitability channels improved overall spend efficiency.
What marketing challenge was Cinemark facing?
Cinemark needed to stay engaged with existing moviegoers, attract new ones, and support ticket sales, all while its messaging priorities shifted week by week with Hollywood’s release calendar. Entering new marketing channels confidently, without losing sight of overall efficiency, required understanding where spend was working and where it wasn’t, rather than relying on average performance across the whole channel mix.
What is marginal ROAS (mROAS) and how is it different from average ROAS?
Marginal return on ad spend measures the return generated by the next dollar spent in a channel, not the average return across everything already spent. Average ROAS can look healthy even after a channel’s returns have started to decline; mROAS shows that decline directly, which is what makes it useful for marketing budget optimization decisions about where to shift spend next.
How does LiftLab support channel optimization for growing channel mixes?
LiftLab combines Agile Marketing Mix Modeling with an Incrementality Testing Suite and weekly reallocation signals, giving teams marginal return curves built for their specific channel mix. This lets teams see the impact of the last dollar spent in each channel, validate that impact with ongoing experiments, and reallocate spend as performance shifts, rather than waiting on a quarterly review.
Can LiftLab help my brand optimize spend across an expanding channel mix?
Yes. LiftLab’s Agile MMM Platform is built for brands adding channels faster than traditional measurement can keep up with, using marginal return curves to show exactly where the next dollar should go. If your team needs weekly reallocation signals or a single view combining MMM and testing results, request a demo to see how it works for your channel mix.
