Getting started with mobile attribution: What you need to know
Authored by Shubham Ja, Sales Manager India at Adjust
In an increasingly complex digital environment, marketers need data they can rely on. But for many brands, the accuracy of data is an ongoing struggle: a recent study showed that a whopping 21 cents of every media dollar spent by organizations in the last year were wasted due to poor data quality, resulting in inaccurate targeting (35%) and lost customers (30%).
The issue is even more critical for mobile, which has seen a marked rise in the past few years. In many countries, time spent on mobile has overtaken time spent on all other media - and while Indian consumers aren’t quite there yet, they’re catching up fast. The insights mobile offers - from how consumers interact with ads, or the points at which they drop off in the customer journey or within the product - are essential to understanding customers and refining a product. However, these insights are useless if the data isn’t accurate in the first place.
The best way to ensure accuracy of data is to find the right attribution provider who can show brands how they got their users, where they came from, and how to build relationships with more of them. But, finding the right provider is easier said than done - what are the key points to bear in mind when starting the process?
Attribution and the magic behind it
Put simply, an attribution provider is an unbiased third-party that tracks data between advertising networks and end-users. Attribution providers also track that same user’s journey through the app, measuring and attributing every single touchpoint that happens, and tie them back to the original entry point. This means advertisers can accurately track their return on investment and invest more money in the channels that bring them profitable users.
On web, brands track users using cookies, showing them targeted advertising based on their browsing patterns, interests and demographics. The process isn’t so straightforward on mobile. Instead, attribution providers have come up with a system to match the user with the activity, based on identifiers located on the devices, known as advertising IDs.
Choosing an attribution provider: what are three key features to look out for?
Flexibility when it comes to data and storage
The type of data customers can receive from their attribution provider is often the difference between success and failure.
Most importantly, brands need data to map the user journey and identify what drives frequent use and lasting loyalty. This has been key to success for Circle, a news app focused on bringing users local updates, events and job ads. Harsh Payal, Growth Associate for the company, said: “We analyze marketing campaigns at the ad level - not in terms of acquisition, but in terms of the user journey before and after seeing an ad. It’s not enough for users to be acquired, use the app, and then bounce soon after. There are a number of steps to convert and without information on what’s happening with each user, we would be working blindfolded”.
Sawan Katiyar, Head of Growth at FreshToHome said, “Our main motivation for working with Adjust was the ability to track all of our download channels within a single platform. Easy integration and accuracy of data were two other big advantages that we enjoyed while working with the company”
Start by setting up tracking for all relevant events, from sign-ups, placing an order or leveling up in a game. This data will give marketers a much clearer idea of how their users interact in-app and where potential drop-off points may be. From there, they can harness this data to consistently improve the product and enhance the user experience. Importantly, you need to make sure that partners offer unlimited data access, and don’t put any restrictions on lookback windows or data queries.
A good attribution solution won’t delete certain kinds of data, no matter how long it’s existed within a database. Switched-on buyers reject solutions that delete data after a certain time – for them, a lot of future decisions rely on having historical data to support their decisions. Infinite data storage means that those marketers have unlimited historical analysis.
The key question to ask here is “How often can I make requests for data, and for how long are they available?”
An open-source approach
Open-source software is code that everyone can see - not only to use, but to analyze, alter, and improve. When choosing an attribution provider, transparency is open-source’s biggest advantage. Open-source software means the code is fully customizable, agile and secure. Developers can pull it apart, take out what they don’t need and add code which is directly applicable for them that improves upon the stock version.
Developing a closed-source project usually means that developers don’t want others to see their code. For most, this is a proprietary issue, but in some instances, it could be a case of wanting to hide bloated projects, or just bad code.
One common misconception about open-source software is that it is a security risk due to its viewability. The opposite is true. Closed-source software often appears secure because it isn’t public, yet fraudsters are able to crack it through reverse engineering. This makes the closed-source code more vulnerable, not less — assuming that no one can crack code because it’s hidden from view is false. There are many attribution providers who claim to be transparent, but this cannot be true without an open-source approach at the core of the product.
Real-time fraud prevention
There’s big money in apps, and many players are working hard to get their piece of it - including fraudsters. At Adjust, we estimate that globally, fraud affects an average 20% of an app’s paid user acquisition budget - and in 2019 alone, blocked US$450 million worth of false attributions.
While most providers offer some kind of anti-fraud product, many solutions are short of a full prevention toolset. This means that they don’t prevent fraud, but only provide brands with information on whether fraud took place, which they then need to dispute with networks. And without active prevention, marketers’ datasets will be ruined by fraudulent activity. This can lead to a downward spiral of poor decision making, with marketers spending more on fraud and less on the users that count.
Ultimately, the only way to prevent fraud from reaching your ad budgets or data sets is to work with a fraud prevention vendor. These make fraud financially unsustainable - meaning it actually costs far more time and resources for fraudsters to find workarounds to filters, making it much harder to make money. After realizing that certain apps are protected, fraudsters will concentrate their efforts on those apps that don’t have any fraud prevention measures in place.
When choosing an attribution provider, the key question to ask is if their fraud solution stops fraud, or only tracks it as it happens. If the onus falls on a brand to recoup their money, it’s not worth it.
Choosing the right attribution provider is a crucial decision you should only have to make once. Invest in research before reaching the negotiation table. Take the time to understand new perspectives that can make you think differently about your approach and inform the right questions to ask of your potential provider. Ultimately, an MMP should go beyond being a mere data provider and be more of an advisor in helping power your brands’ growth.