As the world becomes more privacy-conscious, there may be changes in a gaming marketers ability to measure campaign performance. By anticipating these changes, and adapting quickly to them, you will be able to continue making the appropriate marketing decisions.
These changes tell a larger story -- people are concerned about privacy. In a 2019 survey, 84% of consumers care about privacy and want greater control over how their data is being used.
By giving people control over how their data is used, the ecosystem of ads and measurement has evolved. For example, mobile device identifiers which rely on passive data collection have become less available, which means advertisers must innovate when it comes to the data they use for advertising.
Measurement and privacy
Effective measurement has become more difficult because of the current complex, digital-first, multi-screen, multi-device environment; the available metrics and measurement tools have grown, which has caused advertisers to struggle to strategically measure their campaigns. Today, measurement tools can often deliver insights that are tangentially related to your business goals, or provide a skewed picture of which campaigns and channels are adding true value, such as last-click attribution.
"In a 2019 survey, 84% of consumers care about privacy and want greater control over how their data is being used"
Evolving your measurement framework
Although there is no foolproof measurement framework to combat these changes, there are steps you can take to mitigate their impact and adapt for the future.
1. Analyze your current measurement strategy to understand the impact of the evolving ads ecosystem
2. Develop a short-term plan which blends your current tactics with measurement techniques that don't rely on device IDs , while anticipating future strategy changes over time
3. Be open to new solutions and frequently re-evaluate the effectiveness of your measurement strategy
One key approach is Marketing Mix Modeling (MMM), which has long been used across traditional verticals to quantify the return on investment / return on ad spend (ROI/ROAS) of marketing across channels; and is now being adopted by digital first advertisers in the Disruptor and Gaming verticals. MMM is built on aggregated data, typically in a form of time series, instead of relying on user-level information. It's a future-proofed technique that can be leveraged to move advertisers towards incremental measurement in a privacy-first way. MMM is also metric-agnostic and the methodology can be used to understand the impact of marketing activity on any business metrics that could potentially be influenced. These could include Installs, Purchases, Revenue, Free Trials, Subscriptions or even Lifetime Value (LTV).
Geo-testing experiments are likewise effective, relying on aggregate geo-level data to compare test and control markets and measure incremental performance due to ad exposure. This means that they do not rely on privacy-impacted user-level data.
Anchor on True Value
For those who haven't already started on this path, gaming advertisers should think about anchoring their measurement strategy on incremental business value. This leads to more precise insights, allowing for better marketing decisions.
Incrementality is the degree to which a measurement method estimates the true causal effect of an isolated marketing activity - it can separate how many installs, deposits, purchases happened as a direct result of marketing from those that would have regardless.
By understanding incremental value, marketers have the ability to make the most efficient marketing decision possible and have a measurable impact. According to our research, almost 25% of the time non-incremental and incremental measurement disagree on a winning marketing tactic. When marketers choose the wrong tactic as a result, businesses lose out on an average 64% improvement in cost-per-action (CPA).
Incrementality can be an experimentation-focused approach. Experiments are the'gold standard' for measuring incremental business value, but we know they're not always practical. If an experiment cannot be run, ensure your methods are as close to measuring incrementality as possible. Imagine metrics as being on a spectrum of non-incremental to incremental, moving from rule-based attribution or simple counts all the way to randomised control trials (RCT). The closer you can get to experiments, the better off you are, but there are many valuable methods available before you get there.
The method isn't the only thing that matters; the metric is just as important. To inform business decisions, we recommend measuring true business outcomes (i.e. incremental purchases, revenue or installs) as they can more closely reflect a business' bottom line.
As with experiments, this might not always be possible, but getting as close to the top of that spectrum is the goal.
Utilizing all of these elements, you can select the best available incremental measurement by evaluating both the incrementality of the method and of the metric you're measuring.
Adapt and Evolve
The measurement ecosystem may be changing, but you can build an adaptable measurement strategy that integrates your learnings, leading to the next decision and inspiring new business goals. Remember:
● Identify your business goals: Start with the decisions you are looking to make
● Consider constraints: For each type of decision, identify the business and data constraints. This could be the types of channels being measured, the speed at which you need an answer or the level of accuracy and precision which you need the results to be
● Select and test an approach: determine the measurement tool or tools that best meets those needs
Different questions require different tools to answer them, and it's about finding the right tool for each particular job. This could be a simple A/B test to find which version of your creative works best. Experiments might serve you better to make strategic decisions around the incremental contribution of Retargeting versus Acquisition campaigns, or new creative strategy using upper funnel creatives or influencers. It could be working with an Attribution provider for day-to-day performance tracking and decision making. Looking more broadly at budget allocation across and within channels, MMM might offer the best trade-off of insights and speed if it's informing large strategic decisions, not da- to-day tracking.
Finally, assess and adjust: are you accessing the insights you need to make a decision, and guide you toward a new question or goal? Your strategy should integrate your learnings, leading to the next decision and inspire new business goals.
About the authors:
Rory Donegan joined Facebook's EMEA Gaming team as a marketing science Partner in 2019, to promote better measurement across the industry. He spent the previous 7 years building MMM programs across EMEA as a Director at an analytics consultancy, helping advertisers measure & improve their marketing strategy.
Sharad Jaiswal is a curious person who has always been in love with maths and how it applies to everything in the universe. He finds great energy where he engages in its application through data analytics to empower businesses to answer difficult questions and drive growth. Sharad has spent the last 12 years answering those questions through data and empowered businesses across different industries. Gaming is Jaiswal's new stop, and in his current role at Facebook, He is building advanced data-driven marketing & measurement strategies for leading gaming companies to thrive and grow in a changing privacy-first world.