From building an entire BI system in-house to supplementing its data with an outside tool, you’re probably using at least one platform to make sure your marketing team is getting the most accurate insights. 

But is there one approach that stands above them all? In short, no - it’s a combination of buying and building that can give you the most comprehensive, accurate, and actionable data. 

In this article, Einat Dror, VP Global Customer Success at ironSource Luna, and Matthew Skurnick, Platform Growth Team Leader, discuss the advantages of building a BI system internally and then bringing on an external data insights tool to support what you’re already using.

Building an internal BI tool for greater safety, granularity, and autonomy

A BI system is the primary way for app businesses to collect and store data. Building your own tool internally for analyzing performance gives you full control over this valuable data. This can help you customize your metrics so they’re tailored to your business needs and fill the gaps that a generalized, external insights tool - like MMPs - may leave. 


When you’re able to customize a BI system to your business needs, you can institute failsafes that improve and/or streamline a part of your UA strategy. For example, we once saw a client build a system internally that included blockers which didn’t let the creative team send ads to the UA team without tagging them. There were three main benefits of designing this type of tool as a failsafe:

  • Maintaining creative organization and boosting efficiency
  • Aligning with the business’ creative production methodology
  • Providing a feature their MMP did not provide

Custom KPIs

Building a BI tool also lets you explore other data points that matter to your business, like k-factor, which is a metric indicating organic uplift brought on by paid activity. PR is one of the best examples of this, with paid features like articles or events contributing to organic growth. While an MMP can track organic activity from specific sources, it could miss out on other components that complete the picture of your k-factor measurement. If your business has a booth at a popular industry conference, for example, this will contribute to organic traffic - but an MMP won’t pick up on the source of the organic traffic.

Building a BI system around tracking a specific metric like k-factor can ensure you’re getting all the pieces of the puzzle and improving the accuracy of your data.

The resource cost

Developing any tool internally is costly in terms of time, expense, and resources. It often requires hiring a BI team/developers and product managers, but with each new human resource added to your team, there are additional considerations that affect both budgets and efficiency, like salaries and learning curves/training. This may take time and money away from other parts of your operation.

Additionally, the time to market for an internally built tool is often much longer than an external data platform that’s plug-and-play. It can take over six months to build a tool internally, which doesn’t include time for QA, like dealing with bugs that can arise across channels. It’s not just the initial costs to consider, either - internal tools require maintenance to remain functional and up to date. You need to keep updating the tool to reflect changes in UA channels, like when social platforms update their app campaign structures. 

Make the costs of building a BI tool internally worth it by using external platforms that can make BI data even more flexible, granular, and accessible.

Make the costs of building a BI tool internally worth it by using external platforms that can make your BI data work for you in an even more flexible, granular, and accessible way.

Buying a data platform to enhance your team’s capabilities

Since a BI system mainly synthesizes data already collected into one place, buying other data insights tools to supplement it lets you take the metrics further - you can turn static numbers into flexible data points that provide you with actionable insights more quickly, consistently, and easily. So instead of just seeing a row of metrics, like CTR, CPM, and engagement rate, a flexible data point will give you a contextualized view - like comparing those metrics to performance from one month ago. 

For example, there are incrementality tools that are solely focused on measuring - you guessed it - incremental growth, and creative insights tools that let you dive deeper specifically into the creative side of campaigns. Most pre-existing tools are plug-and-play, which means you can onboard and start running immediately without having to deal with development, bug fixes, and maintenance.

Historical data and specialized insights

An external data insights tool is built to help your team succeed. Their entire business plan revolves around customers using their platform for a specific purpose and improving their business. Part of helping you succeed is that an external platform has already done the research and figured out what works so you can extract the most useful insights as efficiently as possible. 

This is especially valuable for new or innovative marketing teams that don’t have as large a database of best practices as the traditional methods, like creative analysis. Only recently, app marketers started focusing on creative data - in the past, creatives were built and run as a component of a UA strategy but performance metrics weren’t emphasized. Since this is a recent trend, there's not an extensive amount of information available about creative analysis. 

So if you’re building a BI system, you’ll likely include the basic creative metrics as you track performance - but how can you be sure you’re not missing out on more features and insight into more KPIs? An external tool for creative analysis is built using best practices and feedback from across the industry that turns data into action and exposes trends, like automatically optimizing creatives and including visualizations of traffic. And it accomplishes this all while shortening the learning curve and improving accuracy - you know you’re looking at the most relevant information.

Understandable for the whole team

The specific insights that an internally-built BI system can provide are often inaccessible for team members beyond those that crunch the data every day. For example, a client was once showing off an internal dashboard that they built for their specific use case looking at net yield, incrementality, and multiple cohorts for tracking trends. This client has a huge data team that was able to devote extensive time and resources to the project. But their custom-made BI system had two shortcomings:

  • It didn't provide actionable insights - the only information they got were data points
  • It was only accessible to the data-focused people on the team

If this client had gone a step further and used an external tool to build upon the work done internally, they could’ve easily turned the data into trends or visualizations that were already designed to highlight the changes needed for boosting performance.

Using an external tool to build upon the work done internally can easily turn the data into trends or visualizations that highlight the changes needed for boosting performance.

This would also make the performance insights accessible across the entire marketing team, from CMOs to creative designers. 

The best of both worlds: Build and buy

The primary purpose of building BI systems is to gather and store data. Then, you need to turn these numbers into insights, which often takes time, energy, and operational resources - it’s also not a guarantee that you’ll consistently extract valuable insights. Meanwhile, the purpose of external marketing tools is to turn the numbers from your BI system into actionable insights for your entire marketing team. This means that you can get to the trends and insights more efficiently and consistently, and you can count on the tool’s accuracy because it’s built upon an inventory of best practices gathered from across the industry. 

Together, using an external data platform and internally-built tool gives you the most comprehensive and useful insights into app performance.

Using an external data platform in addition to what you build internally gives you the most comprehensive and useful insights into app performance. From here, you can make data-driven decisions more easily as you scale your app, build an internal set of best practices, and optimize your entire marketing strategy.

For example, ironSource Luna can work with your internal systems to complete the picture of app performance and unify marketing activity across channels. Luna is a plug-and-play platform that lets you maintain control over your data by integrating directly with your existing data insights platform or BI system and receiving data only on aggregate. It still lets you go granular because it’s getting data directly from your marketing channels, but gives you the added advantage of visualizing performance on the individual creative level so you can see clearly what’s driving results. And, it makes creative analysis accessible to your entire team, from growth managers to creative designers.


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