The problem you don’t know you have: your attribution provider is outdated

It’s mind-boggling to think that the world of apps dawned on us back in 2008 thanks to Steve Jobs’ extraordinary visionary ability. It’s even more mind-boggling that for many providers, the state of the art in measuring app installs — mobile app attribution — hasn’t progressed much since then.

The universe of apps, ads, networks, and platforms born over a decade ago continues to expand, showing no sign of slowing down. The industry keeps innovating to find new areas and markets to break into, new formats that hook users in enticing new ways, and increasingly now, new ways of protecting consumer privacy.

But one critical area of the mobile ecosystem that should be inherently leading edge has resisted evolution: the mobile attribution provider.

In 2019, the traditional MMP is arguably still fit for purpose. At least in the same way a mobile phone from 10 years ago still works.

Yes, you can make calls and send the odd text (remember T9 texting!). But to settle for a decade-old experience is to ignore that most messaging now occurs on social apps that can also facilitate calls on WiFi — video calls at that, with your 12-megapixel camera!

Mobile attribution is no different.

In the early days of mobile attribution, counting installs accurately and attributing the right source was all that was necessary for user acquisition managers to run their campaigns well. But fast forward to today and the ecosystem and sophistication of acquiring users has increased exponentially (as have the fraudsters) while traditional MMPs still shout about passively counting installs like they were sheep.

The problem with your provider just counting installs

Part of the issue is that many advertisers accept this basic offering as if it were gospel.

They might be looking for that mobile measurement partner badge and some anti-fraud capabilities, so the majority typically choose one of the traditional providers or a more cost-friendly option and then start adding on top of that.

Not a horrible strategy, but it doesn’t take you anywhere close to a 21st-century world-class tech stack.

It all comes down to uncovering your true return on investment and for this, you need to go beyond the attribution provider who just counts installs. You need to know what you’ve spent (and where! and how! and with what creative! and when you changed bids!) and the bad news is … they are not very good at telling you that.

Counting backward from installs to cost just isn’t very accurate. Plus it throws away critical data that you need for optimization. And buying a solution for cost separately leaves your BI engineers trying to stitch the two data sets together to give your marketing team some idea of the outcomes of their campaigns.

But all of this is an exercise in trying to make a square peg fit a round hole: you get a load of user-level data from your measurement partners and a shipment of aggregate data from your cost solution. These two elements don’t play together very nicely, failing to provide the insight that you need to execute and optimize your campaigns properly.

To make matters worse (yes, it gets worse!) the Adjusts and Appsflyers of the world lack what should be the very bare basics of reporting.

For instance, want to compare how different apps perform in the US on one screen or how different networks perform in Germany? You may not be able to with some of these players. Need to see your post-install metrics side by side with your campaign data? Hmm, that may not be possible either.

The list goes on and these shortcomings have fallen on the advertiser’s teams for far too long and they’re not something you should aim to solve yourself.

The problem with trying to address their shortcomings yourself

You might be thinking right now, as inconvenient as the above sounds, the task is not beyond your capable engineers.

You are correct.

At Singular, we see many examples of BI teams coming up with systems that account for the limitations of their tracking provider and aggregate cost data to surface ROI at the deepest levels they can. But if you are seeing growth across your organization or if you’re aiming to ramp up quickly, you’ll find this approach is not scalable. Pulling in increasingly larger sets of data from your attribution provider and cost solution vendor and then querying your own data systems means slow download times, crashing systems and gaps in your data.

(Never mind all the work to keep updating for new APIs and processes, endpoints and schema changes.)

This is not a winning tech stack. Not only are your BI team are tied up in the stitching together of data, your UA team only has limited data which is slow to update to do their optimizations. At first, this delay in optimizing and what appears a marginal loss in optimization quality due to limited granularity may not seem significant enough for you to rebuild your tech stack. It’s a hassle, and little gains may not seem worth it.

But if your competitor runs on the same network as you and optimizes 2% more efficiently and 5% faster (and many of them are) … multiply that by the numerous optimizations you do every week over months and it soon adds up to sizeable and steadily increasing disadvantage.

The answer to all your marketing data problems

You don’t have to be a massive organization to feel the pain of a fragmented marketing stack and the effect it has on your ability to execute stellar marketing campaigns.

For every successful start-up out there that figures it out, there are 20 that struggle. The marketing landscape is fierce and to have the best chance of establishing yourself as a serious player, you must equip yourself with the right tools that will give you the edge right from the get-go.

This means that a provider that just counts installs has no place in your top-notch tech stack and you should ask for more. Much more.

At Singular, a marketing intelligence platform, we understand how important this is. That’s why we’ve made it our mission to unify marketing data to enable our customers to get the insights from the most top-line cross-channel view to the deepest levels of granularity.

Our reporting reigns supreme not only in granularity but flexibility too.

If you cannot see your Facebook and Vungle data side by side and compare it like for like, and within minutes drill down to the ROI and retention of a specific creative across those two (or more) networks — we have customers who can.

And it makes a difference.

You’ll find in our suite custom dimensions and unlimited filter options that let you slice and dice data in a way that is meaningful to you and makes sense of the wilderness that is the mobile ecosystem. Even small companies without a BI team that utilize Singular’s full-stack have access to better, cleaner data and more advanced reporting insights than some of the largest players out there,

The age of the attribution provider is over.

The time of the marketing intelligence platform is here.

To build or not to build: making build vs buy decisions for mobile attribution and aggregated campaign analytics (part 1)

Some of the larger marketing organizations we talk to in EMEA think about building aggregated campaign analytics and ROI insights themselves. They generally don’t see the full difficulty and continuous maintenance this project involves. In this article, I explore the challenges of building and why a solution like Singular meets and exceeds these need. This is part one; part two will arrive in a month.

EMEA is a hub of marketers big and small representing every type of app developer and web-centric marketer you can think of. The data explosion has affected each one. It has made actionable insights, which make all the difference in this competitive landscape, the holy grail of every growth marketing team.

Build vs buy

One question that is a serious challenge for them all: should we build an in-house mobile attribution solution or buy it from a third party?

Our customers are smart and between them own over 50% of the top 100 grossing apps. So it’s no surprise that they employ intelligent engineers and data-savvy growth teams who already have the knowledge of how to achieve aggregated campaign analytics and could have a good shot at the greater challenge of getting ROI in an accurate, timely manner … although getting ROI at the most granular levels would be a massive challenge.

Therefore, it’s not a question of whether they can do it, but rather should they do it. We found that when addressing this question, the same considerations led even the largest enterprises out there to outsource this crucial work to a marketing intelligence platform like Singular.

The first thing to take into account is the cost of undertaking such a huge project and the time to completion.

Engineering time is not cheap and a company can rack up several hundred thousand dollars to build the required infrastructure even before considering the ongoing cost of maintenance. Not to mention that a project of this size and complexity will take months to complete and in such a fast-paced industry, this is long enough to start falling behind the competition.

Cost is not just measured in currency

However, the cost of this is not just monetary.

Valuable technical resources likely need to be diverted from core product projects, which impedes innovation and custom developments that address the specific needs of the business, allowing even more breathing room for competitors.

Getting the foundations right is no easy feat: you have to get a framework for your BI system, make sure that your MMP matches that framework, and then map your cost APIs into it correctly to get full aggregated campaign analytics. Furthermore, if your marketing efforts extend beyond Google and Facebook, you will have to set up multiple APIs with all the different networks you run with and for any new networks you want to test in the future.

If engineering time is limited, as it often is, and new networks are not integrated – what is the impact of the inability to test on the business? The cost of passing on new inventory and networks with new targeting and ad format capabilities cannot be underestimated.

Once you have your APIs connected, additional work is required to configure the internal dashboards to display the new data. It’s a manual process that is prone to human error which can easily render datasets inaccurate and therefore unsuitable for optimization purposes. If you’re going down the build route, you’ll need to put in place time and resources for checking accuracy before you even start thinking about which data visualization platform you’ll use to make sense of it all.

From aggregated campaign analytics to marketing intelligence platform

That’s another reason why our customers choose Singular, a marketing intelligence platform built with the modern growth marketer in mind, addressing their requirements of instant access to reliable data for granular optimization.

Even if all the above is accomplished so that data is flowing in and is accurate which we’ve seen can be done, the issue of combining it with internal data sets poses a true challenge.

Filling in the gaps and delivering the insights requires a complex infrastructure with strong identifiers for combining purposes to enrich campaign and publisher granularity, which almost certainly still leaves creative level combining — and therefore creative ROI — beyond reach.

All this means a lot of data and heavy queries that slow down the internal systems.

Our research and customer feedback reveals that the above challenges, opportunity cost, and continuous and expensive maintenance of self-built infrastructure are what drives small and big enterprises alike to a conclusion that a third party is a better solution for this essential need.

What you actually buy from Singular

Here at Singular, we understand these challenges well — after all, we went through the pain of building it ourselves.

Our product is our bread and butter and we’ve gone far beyond the basics to build a true marketing intelligence platform that frees up engineering time of our clients to build marvelous things that uniquely aid their goals while giving growth marketers the tools that they need.

What you buy from Singular is beyond the aggregation and standardization you’d expect to build yourself: you buy a world-class solution that is focused on continued innovation and automation, to give you unrivaled insights and optimization capabilities.

You buy teams that build and support integrations, improve infrastructure and system performance, and constantly work to add new features. You buy a data science team that make it their business to spot discrepancies, a support team that handles data flow errors and API issues, and a stellar (if I may so so myself) customer success team that makes sure the platform is serving your business.

If you had engineering and BI time to spare — what would you build?

See how DGN Games grew 85% and saved 15 hours each week with Singular.

Next month we’ll hear from an EMEA customer about how Singular has enabled their business and aided their growth strategy. If you have ambitious goals and are thinking of buying or building, reach out to us about a demo to see what Singular could do for you.