[VIDEO]: Should mobile-first companies build or buy UA management software?

App businesses come in all shapes and sizes. The success of these businesses depends heavily on the effectiveness of the user acquisition function, however, the amount of data surrounding the UA function has been increasing exponentially for the last half-decade. In order to process this onslaught of data, a question we see most larger organizations asking themselves is whether to build UA management software in-house or buy it from a third-party vendor.

Let’s see what Appsumer’s Head of Product, Clément Boutignon, had to say on the matter…

 

 

We can see why some choose to build. There is something seriously tempting about building your own solution – it will be perfectly customized to fit your needs, and you’ll have complete control over how your data is handled. However, the face value of the project doesn’t quite match up to the complexities that lay hidden beneath. We’ve seen a handful of businesses invest copious amounts of time, money and resources into building their own solution, only to realize halfway through that they had bitten off more than they could chew.

Most of our clients have robust in-house BI solutions, with engineers fully capable of building bespoke UA software. Even still, they have struggled to unify and normalise spend data with attributed cohorts and internal data at a granular level (down to sub-publisher  ids, keywords, placements, and creative). This poses the question, should I build or buy user acquisition management software?

In this article, we’ll explore the major challenges of building software internally and highlight how a third-party tool like Appsumer can meet (and smash) the required needs of UA.

 

Building UA management software will distract you from your core mission

What differentiates a product is not necessarily the BI, it’s how much time a company is going to put into developing their next game, executing high-growth UA campaigns and analyzing their performance data. This is especially true for consumer apps who need to continually focus on delivering to the customers’ needs.

Internally building a solution will mean valuable technical resources are shifted from the product’s development, which slows down innovation considerably and means your core business is likely to suffer. And, while your engineers will undoubtedly be magicians in what they do, chances are they won’t be UA experts and will have to rely on external research during the building process.

When we set out to build Appsumer, we first tackled the problem of capturing fragmented, unstructured data from multiple sources, unifying both spend and revenue data into one platform. This provided a clean foundation to work from. From there, we developed powerful visualization and analysis tools set to answer UA-specific questions. This means that analysts can look at data from multiple perspectives, across multiple apps, using common views and benchmarks to contrast and compare results. This also took care of reporting, with the ability to create custom dashboards for different stakeholders and produce automated reports. Finally, having addressed the time-pulls of data unification and reporting, we’ve developed an optimization layer. This allows teams to forecast, test-scenarios quickly, predict results, and make changes across ad platforms directly from Appsumer.

It’s taken three years to evolve to this stage and we’ve met a few obstacles along the way. All of which we’ve overcome because we have teams dedicated to finding and solving these problems. Building a system from scratch would take so much time, just to build a tool that’s even 50% as robust and sophisticated as Appsumer is today.

 

Non-UA specific platforms still require a lot of engineering work to customize

Arguably the clearest benefit of buying a solution is having a system in place that was built by UA experts, who are entirely focused on creating the best possible solution out there.

Some companies try to build internal tools on top of existing systems, such as Excel or other generic visualization tools. Because these tools are not UA specific, they don’t meet the nuances’ needs related to UA workflows, such as gearing towards cohort data, creative performance reports, ensuring retrospective changes and forecasting future campaigns perfrmance. You will find that you still have to invest a lot of time customizing and building out further capabilities if you attempt this method.

Before creating Appsumer, our team was managing global-scale UA for top tier app advertisers. Their immense understanding of the nuances of this space means the platform was built with them factored in.

 

Building is actually less cost-effective

It might seem as though building a platform yourself is cheaper than paying for a monthly or yearly contract. In the long run, when considering the time and resources you would devote to building an in-house tool, third-party solutions tend to be more cost-effective.

To get the equivalent from a traditional BI tool, the cost of resource, engineering time and manpower to set up and maintain all of this actually becomes more expensive.

 

Continuous and expensive maintenance

It’s not just building the tool that will be heavy on time and resource. You’re now facing large infrastructure costs to develop, store and maintain your tool, not to mention the need for ongoing internal support and maintenance.

Marketers that advertise on more than 5 networks have, on average, a 37% lower CPI and 60% higher installs when compared to those who advertise on 5 or less. Every new network added means a new custom API has to be built. Also, some advertising partners don’t even have API access, which means  parsing emails, scraping interfaces or even scraping the data manually.

And the work doesn’t end when the APIs are built. Partners such as Google Ads, Facebook and Apple Search Ads are constantly upgrading their APIs to newer versions. These provide mobile UA teams access to greater detail, granularity and insights ie. delivered country, sub-publisher level or creative sets but no always. Sometimes you have to update to the next version and spend engineering time for little value… because the version you’re using is scheduled for deprecation. What’s worse than a broken data pipeline? To stay ahead of the game, you often must be using the latest API to get the latest available features. Appsumer monitors hundreds of integrated partners and ensure the latest versions are implemented ahead of time, both in order to support new partner features, and avoid data pipelining issues.

 

Your data past determines your AI future

Finally, we know that your data is the foundation of a predictive, AI future. Building a clear picture of historical data is the basic requirement for taking advantage of emerging machine learning capabilities. Appsumer has already built a proprietary normalised data-set ready for Machine Learning to be applied. Watch this space.

 

Still not convinced?

Ask yourself this question, can you afford to divert engineering time, focus, energy and costs away from your core offering that is to build a successful app business?

Appsumer is a purpose-built BI for mobile app performance marketers. We have – after intense research and development  – found the best and most accurate way to match data together without extra work for campaign managers. Now we are accelerating deeper and deeper into what we’ve already built. As Appsumer is built for a specific function within an organisation we’re able to iterate our product to build the best solution for UA teams and take into consideration feedback from dozens of leading mobile-first companies which you can also benefit from.