Ad-click fraud is a billion-dollar issue, costing us all time, money, and resources in identifying and resolving fraudulent issues compromising ad campaigns and data. It's imperative that we build up the expertise of our internal marketing teams on the key fraud activities that could be affecting our ad campaigns, and understand how we can uncover and resolve these issues. Furthermore, it's critical for marketing teams to have the right tools to identify and manage fraud.
Here's our recommended "Top 5" list for tools that every marketer should have in their arsenal for managing and mitigating mobile fraud.
Tools for training, both internal and external
How knowledgeable is your marketing team on the most common types of ad fraud today? Are they aware of the most common practices for identifying fraud? It may be time to take a moment for leveling up the general knowledge of your team -- not only in ad fraud, but the most current mobile marketing practices in general.
With fraudsters becoming more and more savvy on the advertisers, it's easy to fall behind and lose a solid understanding of the latest key performance indicators (KPI) and the correlation between KPIs and what good benchmarks are for those KPIs in different scenarios. Send your people to conferences, hold an offsite training workshop, and share knowledge among mobile marketers.
Tools to develop collected datasets within your own business intelligence (BI)
Given the complexities of running mobile marketing campaigns, inevitably, there are a wide variety of different pieces of data in the ecosystem that may help you root out fraud in your campaigns. What makes this even more complex is that everyone has their own unique data points across various parties in the value chain.
For various reasons, from privacy regulations to business problems, some types of data can only be kept by different parties in the chain. For instance, the mobile marketer is the first party and will have internal databases with quite detailed user data, whereas an ad network is a third party and usually keeps the targeting and publisher data to themselves. Third-party attribution platforms sit in the middle, with a little bit of both. Only the advertisers, though, are able and allowed to collate this data for a full-picture view. Advertisers should have some sort of homegrown or licensed business intelligence system that they host themselves, and most systems will allow you to export that data, which you'll need for the next steps in fraud mitigation.
Tools to actively intervene fraud
Once you have the ability to collect your data from different sources and draw conclusions from the data, fraud prevention tools can then enter the picture and be more useful. One of the primary prerequisites of fraud prevention solutions is the ability to directly intervene. This is, partly, in order to directly prevent fraudulent traffic from resulting in payouts to shady publishers. Perhaps even more importantly, if fraudulent or fake conversions are accepted by multiple tracking systems (as will be the case when you build an integrated stack), it'll erode the potency of your data-driven conclusions. It's a Herculean, if not Sysphosian, task to clean all of the affected datasets in retrospect.
Whichever way you decide to filter out fraudulent traffic, you need to be able to apply these filters before the data is forwarded to other parties. This can either take place within an attribution platform, or through an intermediary before forwarding the data to platforms like Segment or even an internal BI system that handles data distribution.
Tools to deliver metadata on IP addresses
Similar to fraud prevention systems, marketers should have some sort of an IP database that will deliver metadata to IP addresses at various points along the value chain. This is important because being able to match the IP data will confirm the validity of the IP addresses delivering users. Validating IP addresses is possibly the easiest and strongest way of confirming not only that the traffic isn't coming from a suspicious source (like a datacenter or a Tor exit node), but also if it's coming from the right geographies that you've designated. This type of metadata, when delivered indirectly, can often have an unclear provenance, so it's often best to acquire a dedicated metadata tool.
Tools that calculate KPIs for specific traffic sources
Finally, marketers should have a decent database front end (perhaps even internally built) that provides you with calculated KPIs for traffic sources, and enables you to compare benchmarks between sources globally. Ideally, this tool will also allow you to import and manage raw data from different sources to enable research and comparisons in case of fraud mitigation.
Preparing your marketing arsenal
Given the complexities of the mobile advertising ecosystem and the maturation of ad fraud, it's a fairly tall order to identify simply the tools needed to identify and protect advertisers from fraud today. But, we hope that the tools here help illustrate the key building blocks of an infrastructure that enables you to proactively manage fraud issues.
Most marketers default to simply looking at attribution -- where did the mobile traffic come from? -- but attribution is really only the beginning of the puzzle. Attribution platforms will enable you to compare the performance of different sources, preferably as far down the conversion funnel as possible, but fraudulent traffic can take many shapes and forms, and is not always easy to pry out. The tools we're recommending here should be the immediate priorities for a team looking to secure themselves from the lost ad budgets caused by fraud, and to clean up their data for more effective data-driven decisions.