Shumel Lais, Founder & CEO at Appsumer
Effective performance marketing is data-driven by design, demanding marketers monitor and measure mountains of disparate data points and performance “signals.” But marketers can no longer compete on their knowledge of “surface” data such as the cost per acquisition grouped by ad networks and partners. To gain and maintain competitive edge performance marketers must strive to distil granular data, including creatives and sub-publisher information, into deeper insights.
This requires marketers to master what I call “Perfect Performance Marketing” – but before I explain what it is, let’s be clear about what it isn’t.
Every time marketers optimise campaigns without knowing the full context of the factors driving the results, they are pursuing a strategy counter to Perfect Performance Marketing. In other words, each time performance marketers rely on a metric and dimension that fails to give them the “full picture” of performance, they are making an imperfect decision that can significantly reduce their chances of success. Unfortunately, falling into this trap is all too easy.
Performance marketers need assistance to make data-informed decisions with the confidence that they have collected and considered all the data possible to make perfect, data-informed decisions that will move the needle on their campaigns. With this in mind (and based on my personal experience managing performance marketing for some of the largest mobile spenders globally), I have developed a framework to guide marketers on the path to make Perfect Performance Marketing decisions. (For a deep-dive into the steps you can follow to be a perfect performance marketers, check out my detailed Medium blog.)
Key components you need to know
Making perfect decisions is all about having full visibility and full understanding of all the factors at play and which can impact your campaign. It’s a journey, not a destination.
It all starts with Completeness – view into the metrics (all in one place) that gives you a full picture of the entire funnel. To visualise this, compare the level of completeness to the width of your spreadsheet or pivot table. You increase the level of completeness in your performance marketing intelligence when you increase the number of metrics you can access on demand. Keep in mind it’s not just any metrics; it’s key metrics that unify cost vs. behaviours – ROAS (return-on-ad-spend) or CPX (cost per action) – in order to determine the true performance of your campaign.
Once you have identified and visualised the metrics that matter most, you can focus on achieving Depth. At this stage, it’s all about the level of granularity you can apply to the metrics. To visualise this, think of depth as a measure of the number of dimensions or breakdowns in your spreadsheet. Whilst striving for ‘completeness’ allows you to map the user journey and shifts in performance every step of the way, it’s the focus on ‘depth’ that will help you identify the precise variables that are causes of the outcomes you observe. Naturally, the more variables you evaluate, the deeper your insights.
As a rule, to achieve maximum depth, you must strive to break down your metrics by every variable and dimension possible. Description is King, so go for depth and detail in how you name, tag and track your campaigns. Add labels and strive for visibility into performance that goes beyond what default ad network labels that favour short-hand descriptions over the level of detail you need to know what works and why.
The last building block in this framework is Certainty. You can compare it to pacing and forecast. At a basic level, you can assess your pacing and forecasts in a linear fashion by evaluating how much budget you have allocated to a specific supplier and the results they have delivered vs. how much budget/time left in the campaign. To improve the accuracy of your forecast, you need to increase the granularity and frequency you apply to the metrics that feature in your forecast. Don’t just build your forecast by media partner. Apply your forecast down to the operating system and country level, and refresh the model on a regular basis.
Indeed, Perfect Performance Marketing can never be a case of “set it and forget it.” It’s not enough to have a comprehensive overview of the data at a specific moment in time. You need it fresh and much more frequently than that. Achieving Frequency is critical, but it can also be costly requiring investments to build out internal capabilities or boost BI teams – or both. It’s why more companies are choosing an alternative route, investing resources in purpose-built unified analytics platforms to automate the process of combining data from a variety of different – and often disparate – sources. This ensures real-time insights that are essential to perfect performance marketing.
The framework and formula I have developed provides a solid starting point to help you make the most informed decisions possible to drive the best possible outcomes for your campaigns. Of course, what you want will always depend on a variety of variables ranging from your app category to your call to action. But there is one constant: no matter the outcome you strive to achieve, understanding the anatomy of perfect performance marketing (and all the “moving parts” you need manage every step of the way) equips you and your team aim high and realise impressive results.
MMA UK Blog 