The Shift From Single Truth To Several Signals Post-IDFA

With the deprecation of IDFA, there will be a shift from a single truth to several signals. We explore this topic in our Conversations With UA Leaders series with Anthony Cross, former VP of UA, Data Science and Product Management at Big Fish Games.  Thank you again Anthony for sharing your keen observations and analysis with us.  Today, we still live comfortably in a world with a single truth, namely, last touch (deterministic, IDFA-matching-based attribution). However, post-IDFA, we will see several signals including SKAdNetwork.  Should you implement SKAdNetwork?  Will there be other signals layered on top of that?  Watch the video below for Anthony’s suggestions and let us know your thoughts:

Our measurement solution is built for operating in the uncertain post-IDFA era that you will face.  Here are the key benefits for marketers:

  1. Free – We invite you to test drive our accurate, cutting edge algorithms with your data for free. The observed mean accuracy of our algorithms is 97%.
  2. Future-proof – It is privacy-centric due to its reliance only on daily aggregated data. No device-level data is required. Our necessary data inputs will never be restricted.
  3. Comprehensive – Our solution measures all marketing including traditionally non-attributable spend like influencer and TV.  It also unveils interactions between multiple media sources.
  4. Incremental – This is the cherry on top since our solution is focused on incrementality in terms of uplift over other marketing activity and organic demand. It avoids the problems inherent in last touch attribution that gravely misalign measurement and true value.

What should you do today to prepare for IDFA deprecation:

  1. Test SKAdNetwork early.
  2. Register for a test drive to test our incremental measurement solution for free while you still have precious time prior to IDFA deprecation.
  3. Compare your results from parallel testing multiple measurement solutions and develop your strategy for utilizing those multiple signals.
  4. Do you want to start building your long term measurement strategy after the lights are already out and the risk to your business is critical? Of course not. Prepare for IDFA deprecation now so you are thriving while your competition is floundering. We can help you do that.

We look forward to your questions and to making the future of your measurement brighter!

How To Keep The Lights On Post-IDFA

When the lights go out with the deprecation of IDFA, you will lose marketing visibility that is critical for your decision-making.  The good news is that you don’t have to fumble in the dark with a feeble 12.57 lumen candle (aka SKAdNetwork).  Instead, your visibility can be vastly improved with a 100,000 lumen flashlight (top-down incremental measurement) to give you both the marketing clarity and accuracy you need for sustained growth.

SKAdNetwork

Which Would You Choose

When The Lights Go Out?

Top-Down Incremental Measurement By MetricWorks

Of course, you would choose the powerful 100,000 lumen flashlight on the right. SKAdNetwork is set to leave marketers with only 100 campaign IDs of granularity and no way to cohort KPIs by install date. Most importantly, the critical post-install performance KPIs that form the foundation of mobile growth strategy today like retention, revenue, LTV, and ROAS, will disappear and be replaced by a single conversion value with its own significant limitations. That candle just doesn’t make much of a dent in the pitch black.

That said, we can make the decision even easier for you.  While you still have precious time before the lights go out with IDFA deprecation, you can test our flashlight for free.  We encourage everyone to test SKAdNetwork early so they are acquainted with its glaring limitations and have plenty of time to understand the impact to their growth strategy. We can help answer questions on best practices. However, there is an opportunity to obtain a significant lead on your competition by testing our top-down incremental measurement in parallel.  Here are more reasons why our top-down incremental measurement solution is the best remedy for the oncoming dark.

Our solution has been derived from months of anticipation, research, planning, design and testing. Let’s take a peek at the biggest benefits to marketers:

  1. Free – We invite you to test our accurate, cutting edge algorithms with your data for free. The observed mean accuracy of our algorithms is 97%.
  2. Future-proof – It is privacy-centric due to its reliance only on daily aggregated data. No device-level data is required. Our necessary data inputs will never be restricted.
  3. Comprehensive – Our solution measures all marketing including traditionally non-attributable spend like influencer and TV.  It also unveils interactions between multiple media sources.
  4. Incremental – This is the cherry on top since our solution is focused on incrementality in terms of uplift over other marketing activity and organic demand. It avoids the problems inherent in last touch attribution that gravely misalign measurement and true value.

To recap:

  1. Test SKAdNetwork early.
  2. Register for our beta to test our incremental measurement solution for free while you still have precious time prior to IDFA deprecation.
  3. Compare your results from parallel testing multiple measurement solutions and develop your strategy for utilizing those multiple signals.
  4. Then, look to the future. Do you want to start building your long term measurement strategy after the lights are already out and the risk to your business is critical? Of course not. Prepare for IDFA deprecation now so you are thriving when your competition is floundering. We can help you do that.

We look forward to making the future of your measurement brighter!

[White Paper] iOS 14 – The Catalyst For The Evolution of Measurement

Embracing Change

The mobile advertising industry has always been a dynamic one that has attracted brilliant minds to embrace its constant change and bring to life businesses that wrestled with the messiness of advertising data to deliver increasing value as they evolved.  Now is no different.  So we think it is important that as we approach this IDFA/iOS14 cliffhanger, we commit once again to center ourselves, continue to embrace change and innovate.

Let’s begin by taking stock of the positives of this upcoming IDFA change that Apple has postponed till early next year.  Firstly, it offers increased user privacy.  This is in alignment with our core values as end users ourselves and as a mobile ad tech company.  Secondly, it allows the industry to ditch the issues with last click attribution and forge a new chapter of measurement innovation.

Thirdly, we want to reassure you that MetricWorks’ platform, UA Command Center (UACC), will NOT be negatively affected by iOS14 and will still provide all of the value it does today.  Additionally, our new measurement module will ensure that you have granular revenue visibility in order to continue to successfully optimize and execute. You will see more detail about this lower down in this post.

Our Quest For The Future Of Measurement

The planned IDFA restrictions, likely to roll out in early 2021, introduces a huge but welcome change to the mobile advertising ecosystem. After an Apple user upgrades to iOS 14, any iOS 14-compatible app that wants to access their device’s persistent identifier (IDFA), most often for the purposes of retargeting, user profile linking, or measurement, will need to ask for their permission (as shown in the example below).

IDFA User Consent Messages

This presents an interesting challenge for the industry since so many players in the ecosystem rely on the IDFA to varying degrees. At MetricWorks, we’ve focused on how measurement data will flow in the new post-IDFA world. Our ability to provide end-to-end UA automation including LTV prediction and bid optimization for our advertisers, at the country and publisher app level offered by SDK networks, is contingent on accurate, granular measurement. Based on the spirit of Apple’s new terms, we decided to evaluate this challenge with the assumption that MMPs will no longer be able to send us events with attributed channel, campaign, country, and publisher app information. In its current state, SKAdNetwork, Apple’s on-device measurement offering, does not seem to provide enough granularity, nor does it handle post-install events well, making retention and LTV prediction impossible.

Early in our search for a suitable measurement solution, we identified incrementality as an important piece of the puzzle.  For those not as familiar with the concept – incrementality refers to the incremental value directly caused by each advertising touchpoint in the user journey. This is impossible to measure in the last touch attribution model (Fig.1 below), which credits the final touchpoint with 100% of the value for the user without consideration to the possibility that the user could have been acquired with fewer, more valuable touchpoints or even zero advertising as an organic install.

Last Touch Attribution Model. MetricWorks

A methodology known as incrementality testing is an ideal solution to prove the causal relationship between advertising touchpoints (ad buys) and uplift.  It prescribes a rigorous scientific process similar to randomized clinical trials used by pharmaceutical companies where a population of users is randomly split into a test group that is delivered an ad and a control group that receives a “placebo” (often an unrelated public service announcement or PSA). However, it can be costly since, if you’re displaying PSAs, you still have to pay for those impressions.  There is an even bigger problem with the advent of iOS 14. Most forms of incrementality testing require a large list of device IDs so that the audience can be split. iOS 14 will make this difficult to accomplish.

Another powerful tool in the measurement toolkit that also considers incrementality is media mix modeling (MMM). This technique uses regression models to find correlations between ad spend and business value. As a “top-down” technique (Fig. 2), versus a “bottom-up”(Fig. 3) approach like last touch attribution that works at the device level, it eschews device IDs in favor of aggregated data, and is therefore naturally aligned with user privacy. As you can see in Fig. 2 and Fig. 3 below, both top-down and bottom-up measurement techniques attempt to allocate the same users and app activity data (installs, opens, revenue) to the same four campaign/publisher app combinations in the proper proportions, but come up with different answers.

Top-Down Measurement Process By MetricWorks
Bottom-Up Measurement Process By MetricWorks

Key Idea: Based on the measurement output of the two different methodologies, we can see that they somewhat agree on the value of ironSource campaign B, publisher C (red). However, ironSource campaign A, publisher A (purple) didn’t get credited much in the bottom-up last touch methodology (just 1 install with little revenue) while top-down shows that, even though it might not be getting the last touch, it is providing significant incremental value. On the flip side, bottom-up attribution gives Vungle campaign A, publisher A (orange) a solid amount of credit for last touches, but statistically, it is providing almost no incremental value. We would have acquired those users either through other campaigns or organically anyway.

Coming back to the top-down media mix modeling (MMM) technique (Fig.2), let’s look at its advantages:

  1. Requires few inputs – mostly just a time series of spend and target outcome measurements.
  2. Robust to incongruities among ad channels, both online and offline, in terms of functionality and data availability.
  3. Can be used to predict the change in outcomes as a function of different spend inputs which is quite handy for planning purposes including what-if analysis.
  4. Can also be used in conjunction with other algorithms to optimize towards a given goal, which can be used for budget allocation optimization.

MMM has its own problems though, which also eliminated it from contention in our quest for the future of measurement. When we attempted to apply it to mobile app advertising, some major issues became apparent including:

  1. Requires several years of data at a minimum due to aggregation at the week or month granularity.
  2. Not used for quick decision making since it takes weeks or months to update a model with new data.
  3. Usually custom built for an individual advertiser by very expensive specialist consultants.
  4. Can only prove correlation, not causation (eating seafood may be highly correlated with personal wealth, but that doesn’t mean eating a lot of seafood will make someone more wealthy).

While MMM wasn’t a perfect fit, we recognized early on that the MMM concepts held a lot of potential. The key is that we found that most of the downsides could be mitigated through a combination of creative feature engineering and automated model validation through constant backtesting and live experimentation.

Keep in mind that the entire measurement process including modeling and validation must be completely automated in order to be scalable. No need to worry though because our existing automation technology in UACC is being enhanced to make this a powerful reality for you.

Our Solution For Mobile Measurement

Thank you for bearing with us and making it this far.  Let us now look at the high level overview of our solution:

  1. We believe that measurement of campaigns at the country and publisher app level (when applicable) remains critical for UA decision-making.
  2. Compatibility with the current iOS14 technical specifications and alignment with the spirit of the new rules are equally crucial for any future measurement solution  including ours.
  3. Regression models similar to those called for by media mix modeling can be augmented with techniques that address problems unique to mobile app advertising in order to finally deliver a measurement solution that considers incrementality.
  4. Using daily data helps solve the data volume issue inherent to MMM and allows the model to be updated more quickly so it can inform the types of fast decision-making required by UACC’s LTV prediction and bid optimization features.
  5. Backtesting allows us to automatically evaluate a wide array of approaches and select only the most accurate models based on their ability to predict known historical outcomes.
  6. Automated controlled experimentation enables live testing of incremental value predictions in the real world so that models can be validated and improved by rejecting poor models and feeding results back into the next model.
  7. iOS14 will not handicap any of the existing capabilities of UACC. All of our UACC platform capabilities remain intact including analytics (dimensions, metrics, etc.), LTV prediction, and bid optimization.  The only difference is that we will be providing a new measurement module (based on our analysis outlined above) that ties aggregated cohort activity with the channel, campaign, country, and publisher app dimensions, instead of the MMP.
  8. Our measurement module will be provided as an option at the app level so that advertisers can rely solely on MMP measurement for their Android apps, should they wish.

We will continue to share details of our progress and invite you to connect with us to ensure that your concerns are addressed, and that you have a chance to shape our solution.

 

 

 

 

 

UA Automation: Reality vs Hype

You have probably heard all the buzz about UA automation and are trying to determine the best path forward for your business.  As Eric Seufert outlines in his MDM article, The Five Levels of Digital Marketing Automation, UA automation is the ambition of many UA teams but there is still a considerable gap between hype and real-world application.  As a partner to some of the leading mobile gaming companies and having spent the last six years in the UA automation and AI space, MetricWorks is firmly planted in the real-world application of automation.

However, if we were to apply Eric’s classification model to our UA automation platform, we find that even our technology most closely resembles Level 3: Marketing strategy automation:

Credit: MobileDevMemo's  UA Automation Level 3 by Eric Seufert

In particular, we feel that our innovation over the last six years enabled us to cover the bottom two rows in the graphic above, namely, Campaign setting experimentation (except for budget optimization) and ROAS projection and reporting.  So why is that?

Well, firstly, ad creative production has proven to date impossible to automate.  As we all know, producing captivating creatives requires human creativity.  This production process resists automation.  Therefore, UA teams around the world have found it better to spend their budgets on human resources to deliver these tasks that are difficult to  automate.

Secondly, automating audience testing requires the machine (or automation platform) to know a lot of different things that may require cross-sectional industry data or domain knowledge that is not easily accessible or is simply not possible to share due to intense competition among gaming companies.  

That leaves the bottom two sections that we feel our automation platform brings to life via a powerful range of features:

  1. Cost & data aggregation in a consolidated dashboard
  2. Real-time source-level LTV predictions (95% accuracy with 30 days of historical data)
  3. Automated Bid Management Across All Channels At Source By Country Level
  4. Impact Analysis: Easily conduct detailed analysis of the impact of bid optimizations on performance (volume, ROAS or custom KPIs)
  5. Automation Rules: Automate time-consuming marketing strategies on a near real-time basis and set guard-rails based on ROAS, Retention, DAU or other KPIs
  6. Performance Monitoring: Live monitoring and customizable alerts for designated publisher behavior
  7. Bid History: Visually graph & analyze bid history along with metrics like ROAS or installs
  8. Supply Groups: Customize, manage and analyze traffic groups with shared performance traits 
  9. Targeted Micro-Strategies: Execute specific actions on a defined supply group

One of the features that our clients are really excited about is Automation Rules that allow marketers to encode their own user acquisition strategy.  However, the heart of our platform and the core feature is our AI-driven mobile LTV prediction (down to the source-level) and how that flows into the automated optimization and execution.

Others have built reporting dashboards and some have even added the ability to take action within these dashboards when it comes to UA execution. While this is a productive step, it is still an incremental one in the traditional direction.  In contrast, MetricWorks rethought the entire paradigm and can proudly say that we are the only ones that built our platform from the ground up to seamlessly go from raw data aggregation and analysis across all mobile channels to model/prediction to optimization and finally execution without human intervention. 

 Of course, the proof is in the pudding and our field success bears testimony to the value of our approach. Learn more about how our clients have realized a ROAS of 145% while generating an unprecedented 22.5 million LTV models and saving 40 hours per month per UA manager.

Mitigating UA Risk: AI vs Human Emotion

User Acquisition Automation & LTV Prediction For UA Optimization

It is really challenging to consistently make UA decisions without the effect of human emotion.  However, we have found in the field that managing human emotions and employing a disciplined data-driven UA approach is the best way to mitigate your UA risk.  No need to worry as MetricWorks has got you covered.  Our platform, the UA Command Center, which is powered by AI and is the leading UA automation & LTV prediction engine can ensure that you stay on an objective decision-making path to UA success.  For instance, in cases where many advertisers may be cutting their ad spend, our platform can unveil cost-effective and LTV-rich buying opportunities across a variety of ad channels to ensure that you meet your ROAS target or other UA goals. So reduce your stress and risk while boosting your UA success with our AI.  Contact us today to discuss your needs and find out how we can help.

Right now, you can enjoy all of the fantastic business benefits starting at only $250/month by signing up for our promotion.

Additionally, remember that manually managing multiple ad channels is fraught with serious planning and execution risks.  Let our automation help you navigate these risks with full transparency and control in one dashboard. Get a taste of the power of AI and automation.

Our Rebranding: TargetCircle’s Mobile Division Is Now MetricWorks!

User Acquisition Automation & LTV Prediction For UA Optimization

We are excited to announce that Target Circle’s mobile division has now been rebranded to MetricWorks!  There are a few reasons for our rebranding but the most important is to streamline our product portfolio to strengthen our focus on properly serving the mobile user acquisition market. The Target Circle brand will still continue to be used for our white label solution.

You’ll be happy to hear that our commitment to innovation and making it easy for mobile UA teams to leverage automation and AI still burns strong!  In fact, that was the inspiration for both our new company name (MetricWorks) and the new logo which reflect the merger of human teams and technology in order to realize a higher state of UA success. 

Our flagship product, UA Command Center, which is the leading UA automation and LTV prediction engine has been significantly enhanced with a number of sophisticated features such as automation rules, supply groups and optimization impact analysis. To learn more about these and other valuable features, please visit the MetricWorks’ product page.

To celebrate our rebranding we are also offering a limited time promotion. You can enjoy all of our leading platform features starting at only $250/month by signing up before May 1st, 2020.  Of course, you can also try the UA Command Center free for 30 days via our Free Trial

Contact us for a demo, questions or to learn how MetricWorks’ UA Command Center helps mitigate your ad spend risk while scaling your mobile UA. We look forward to helping you as MetricWorks!