How to Leverage Marketing Mix Modeling & ASO for App Growth

In today’s mobile world, user privacy and data protection are taking center stage, prompting marketers to rethink their strategies. Mobile marketing has traditionally relied heavily on individual user data, but as more users opt out of data sharing, understanding their behavior accurately has become challenging.

This is where Marketing Mix Modeling (MMM) and App Store Optimization (ASO) step into the picture. ASO ensures your app is well optimized to engage users effectively, with appealing visuals, clear descriptions, and positive reviews that build user trust. Meanwhile, MMM takes a data-driven approach to measure performance while safeguarding user privacy.

Together, MMM and ASO provide mobile marketers with a powerful toolkit to adapt, thrive, and make informed decisions in the evolving mobile landscape. In this blog, we’ll explore how the marketing mix model measures performance while safeguarding user privacy, the insights it can provide, and the role of ASO in achieving consistent and continuous growth in the face of these changes.

This is a guest blog written by Airbridge.

What is marketing mix modeling?

Marketing mix modeling is a data analysis method that helps measure how different marketing strategies impact a company’s success. It looks at past data and creates a formula to show how things like advertising spending and ad performance are connected. This approach can answer questions such as:

• How effective is each marketing campaign in generating revenue?
• What is the optimal allocation of budget across different channels to maximize returns?
• How do external factors like economic conditions and seasonality influence sales?

Marketing mix modeling has been around for years and is relevant to any business using paid advertising. Recently, mobile marketers have taken a keen interest in it because of the challenges posed by reduced data accuracy. Apple’s SKAdNetwork and Google’s Privacy Sandbox are not providing a complete solution, so the search for privacy-friendly measurement methods continues.

Deep dive into the concept of marketing mix modeling

What is ASO?

App Store Optimization (ASO) primarily focuses on optimizing an app’s visibility, appeal, and discoverability within the app stores. The goal is to boost app downloads and get both new and returning users interested in your app. A strong keyword strategy helps your app rank higher, while a great conversion rate ensures that increased visibility results in more app downloads.

ASO can involve various tasks tailored to a company’s goals and needs:

• Researching popular keywords to improve app descriptions
• Enhancing app visuals like icons, screenshots, and videos to attract more downloads
• Localizing the app’s product page for global audiences
• Managing reviews to maintain a positive reputation
• Boosting visibility through editorial content and featured placements
• Monitoring app store changes and competitor updates to stay visible

Read this comprehensive guide to learn everything you need to know about ASO

How can ASO & MMM work together to fuel app growth?

• Data integration: ASO provides valuable insights into organic user acquisition, such as keyword rankings and conversion rates. This data can be fed into your marketing mix modeling analysis to understand the role of organic growth in your overall app growth strategy.
  
• Attribution: Marketing mix modeling helps attribute app downloads and user acquisition to specific marketing channels, including paid advertising and promotions. By combining ASO data, you can differentiate between organic downloads (users finding your app naturally in app stores) and paid downloads (users acquired through marketing efforts).
  
• Budget allocation: Marketing mix modeling allows you to allocate your marketing budget more effectively across both organic and paid channels. With insights from ASO data incorporated, you can take your budget planning to the next level.
• Optimized marketing strategy: ASO and marketing mix modeling data can guide your marketing strategy. For instance, if ASO data indicates that certain keywords drive significant organic growth, you can align your paid advertising campaigns to target those keywords. Marketing mix modeling can then help assess the impact of this alignment on overall app growth.
• Continuous improvement: As you gather insights from both ASO and marketing mix modeling data, you can make informed adjustments to your app’s marketing mix.

Examples of using MMM & ASO in mobile marketing

With your prepared model at hand, it is time to discover how to work with marketing mix modeling and ASO in different situations.

Influencer marketing campaign

To boost a gaming app’s visibility, they’ve partnered with influencers for social media promotion. This data-driven approach can help assess the impact of their influencer marketing campaign on app downloads. Here’s how the game can use marketing mix modeling, tailored to ASO:

In this scenario, the cost of each influencer engagement varies based on their follower count.

ASO ensures that the app’s store listing is well-optimized with relevant keywords, appealing visuals, and positive reviews to enhance the influencer-driven campaign’s effectiveness. The marketing mix model tracks the influencer marketing campaign’s performance by measuring its impact on app installs and related metrics. It considers the costs associated with influencer marketing in the overall marketing mix.

By analyzing ASO-optimized store page visits alongside influencer-driven app installs, we gain insights into how ASO aligns with broader marketing efforts and contributes to ROI.

Read this step-by-step guide to keyword optimization for your app or game

Fine-tuning data analysis for a fintech app

In the finance app industry, consumer preferences tend to exhibit stability over time, with infrequent changes. For a mobile payment app that has experienced remarkable growth over the past 3 years, optimizing marketing efforts during different seasons becomes crucial. This is all the more because traditional financial institutions introduce similar apps. Here’s how ASO and mix marketing model can collaborate:

Seasonal trends strongly influence spending patterns. ASO strategies are adjusted seasonally to align with user search trends and preferences during peak and off-peak periods. This includes fine-tuning keywords and visual assets to resonate with seasonal financial activities and promotions. The goal is to ensure that the app remains visible and appealing to users year-round.

MMM evaluates the performance of various marketing channels, including ASO, across different seasons. It measures the impact of ASO adjustments on app installs and user engagement, considering the competitive landscape with traditional financial apps. This data-driven analysis helps in understanding how the mobile payment app fares during various seasonal trends.

In this scenario, the historical data spanning 3 years reveals a consistent pattern: a dip in app installs from April to October, followed by a significant increase during the holiday season. This informs the allocation of resources and strategies for optimizing ASO efforts during these critical periods.

Keep in mind that the strength of your ASO-focused marketing mix model depends on the quality and depth of your data. For a more accurate long-term outlook, consider adjusting:

• data to better understand how consumers behave
• seasonal trends
• competitive dynamics

This empowers data-driven decisions for sustained app growth and success.

Conclusion

In the ever-changing app industry, the partnership between marketing mix modeling and ASO becomes a valuable tool for both app developers and marketers. MMM offers data-driven insights into the impact of your marketing strategies and helps you allocate your budget effectively. ASO’s insights on organic growth seamlessly blend with marketing mix modeling, creating a unified system where data guides every decision. This collaboration empowers app developers and marketers to make informed choices for app growth.