All Products AIM (Always-On Incremental Measurement)

Unlock Growth With
Next-Generation Marketing Mix Modeling (MMM)

Continuously learn from your marketing results and gain powerful MMM insights to create privacy-first growth strategies

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Enhance performance: Get actionable MMM data for greater incrementality and ROI

Integrate seamlessly: Slip MMM effortlessly into your existing workflows with no disruptions

Bridge attribution gaps: Overcome signal loss left by touch attribution and evolving data privacy changes

Kochava’s MMM Solution Is MMP-Agnostic and Works Seamlessly With Any Mobile Measurement Partner (MMP)

Mounting UA Challenges

User Acquisition (UA) marketing faces significant challenges. Touch attribution has become less reliable due to the evolving privacy landscape, and traditional MMM and incrementality tests struggle to keep pace with the dynamic UA landscape.

Today’s UA marketer requires a more agile solution to navigate a rapidly changing environment.

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Introducing AIM: A Next-Generation Marketing Mix Modeling (MMM) Tool

AIM (Always-On Incremental Measurement) is designed specifically to address the challenges faced by UA marketers. Its unique approach leverages advanced machine learning that continuously adapts to new market information. The result? Precise insights your UA buying team can take action on.

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Powered by Trusted Excellence in UA Marketing

AIM is powered by Kochava, a leading authority with deep-rooted knowledge of UA marketing. We understand your challenges—because we’ve helped countless clients overcome them.

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AIM Features

1. Optimized budget planning: Leveraging real-time market data, AIM provides automated, optimized budget recommendations, enhancing performance by addressing variables such as seasonality, channel saturation, and incremental gains.

2. Continuous learning: With its sophisticated system that adapts and updates daily, AIM ensures that your insights are always current and accurate.

3. Effective data: AIM presents actionable, meaningful MMM data to streamline your marketing investments, bolstering your buying decisions with powerful data science.

4. Accurate forecasting: AIM delivers precise performance forecasts, enhancing your decision-making process and ultimately improving your return on investment.

5. Powerful scenario planning: AIM enables the simulation of different investment scenarios, giving you a clear view of the potential impact on short-, mid-, and long-term performance.

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How Is AIM’s Next-Generation MMM Superior to Traditional MMM?

See how AIM drove an 11.3% increase in sales while reducing average CPA. View Case Study

Traditional MMM

Consultative/Agency Solution

Manual approach
Point-in-time project from a set date
Can be expensive
Static result output—results do not change

In-House Solution

Robyn from Meta or build your own
Point-in-time project from a set date
Requires data scientist
Static result output—once a month to a quarter

Next-Generation MMM

SaaS (Software as a Service) Solution

Designed for marketers
Auto-updates models in real-time
Actionable data
Low resources required
Cost-effective

Frequently Asked Questions

How long does it take to onboard?

Short Answer:
Approximately 4 weeks.

Full Answer:
Typically, from end-to-end, this process spans about 4 weeks. This duration allows us to understand your specific requirements, train and build your models, and ensure that everything is functioning perfectly.

Does AIM use privacy-first data?

Short Answer:
Yes, AIM uses only privacy-first market level data.

Full Answer:
AIM doesn’t require any user-level data to function effectively. Our reliance on aggregated market-level data not only ensures robust performance but also naturally aligns us with stringent privacy policies, reinforcing our commitment to user protection.

Can AIM use and analyze offline media sources?

Short Answer:
Yes, AIM can analyze offline media sources.

Full Answer:
AIM is capable of analyzing offline media sources. However, the effectiveness of this analysis hinges on the availability of the relevant offline data to be incorporated into the AIM system.

How does AIM ensure the reliability of its model?

Short Answer:
AIM tests accuracy against actual results, targeting 95%+ accuracy on 2-week forecasts.

Full Answer:
To instill confidence in the model’s reliability, AIM undergoes rigorous testing against real-world results, not attributed results. Specifically, we aim for a 95% or higher accuracy rate for our 2-week forecasts.

What core methodology does AIM use for its modeling?

Short Answer:
AIM uses Bayesian and nonlinear regression modeling.

Full Answer:
AIM’s approach is deeply anchored in a Bayesian methodology coupled with nonlinear regression. This unique blend facilitates the incorporation of prior knowledge and the consistent refreshing of models with incoming data. Consequently, AIM can produce predictions that are not only accurate but also adaptive and informed. Unlike some traditional models that remain static, AIM’s Bayesian foundation enables dynamic adjustments and refinements based on fresh data inputs.

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