Phase One: Early Creative Testing in the Soft Launch

We’ve been doing well with “soft” launches. It gives us a great opportunity to pre-test creative, test campaign structures, identify audiences, and help evaluate our client’s monetization strategy and LTV model. By the time we’re ready for the worldwide launch, we’ll have found several winning creatives and have a strong sense of the KPIs necessary to achieve and sustain a profitable UA scale.

Soft launches tend to work best if we focus on a limited international market. Usually, we’ll pre-launch in an English speaking country outside of the US and Europe; Canada, New Zealand, and Australia are ideal picks for this. Choosing countries like those let us conduct testing in markets that are representative of the US, but without touching the US market. As we are not launching in the US, it will not spoil our chances of being featured by Apple or Google.

Once we’ve got the market selected, we pivot to:

 

Identifying the most efficient campaign setup

A simplified account structure, rooted in auction and delivery best practices will enable you to efficiently scale across the Facebook family of apps. We typically hear things like “My performance is extremely volatile.”  “My ad sets are under-delivering.” “My CPAs were too high, so I turned off my campaign.” “I’ve heard I need to use super-granular targeting and placements to find pockets of efficiency.” The best way to avoid this is to structure your account for scale based on Facebook’s best practices. Facebook defined those best practices in their Facebook’s Power5 recommendations earlier this year. But – in evidence of how rapidly the platform evolves – they fine-tuned their best practices again lately in their Structure for Scale methodology.

Structure for Scale

The gist of Structure for Scale – and of what Facebook wants advertisers to do now – is to radically simplify campaign structures, minimize the amount of creative you’re testing, and to use targeting options like Value Bidding and App Event Bidding to control bids, placements, and audience selection for you. Facebook is building up a considerable body of evidence that this approach results in significant campaign performance improvements, though if you’re a UA manager who likes control, it can be an adjustment.

Compliment the Algorithm

The underlying driver of all these new recommendations from Facebook is we need to build and manage our campaigns to compliment the algorithm – not to fight it. One of the key benefits of adopting new best practices is to minimize Facebook’s Learning Phase. Ad sets in the learning phase are not yet delivering efficiently, and often underperform by as much as 20-40%. To minimize this, structure your account to give the algorithm the “maximum signal” it needs to get you out of the Learning Phase faster.

Results During the Learning Phase

Expect somewhat volatile results during this exploration period (aka the Learning Phase) as the system calibrates to deliver the best results for your desired outcome. Generally, the more conversions the system has, the more accurate Facebook’s estimated action rates will be.  At around 50 conversions per week, the system is well-calibrated. It will shift from the exploration stage to optimizing for the best results given the audience and the optimization goals you’ve set.

Through all of this, keep in mind that Facebook has built its prediction system to use much data as possible. When it predicts the conversion rate for an ad, it takes into consideration the ad’s history, the campaign’s history, the account’s history, and the user’s history.

When the system says that an ad is in Learning Phase, it’s only a warning that the ad has not yet had enough conversions for the algorithm to be confident that its predictions are as good as they will be later. The standard threshold for confidence is 50 conversions, but having 51 conversions is not that much different from having 49. The more conversions you give the system, the better its predictions will be.

While it is best practice to let the algorithm manage placements and bids, we do still have quite a lot of levers of control over specific parts of campaign management.

 

Lever #1 Increase Audience Size

 

  • Increase retargeting windows beyond 1 day, 3 days, or 7 days and make sure retargeting increments align with website traffic volume.
  • Bucket Lookalike audiences into larger groups. For example:. 0-1%, 1-2%, 3-5%, 5-10%.
  • Group interest and behavior targets that have high overlap together, but make sure your creative strategy is the same for each segment.
  • Minimize the audience overlap. Use proper audience exclusions and make sure you are excluding past purchasers.
  • Increasing audience size can help us gather more data and prevent inefficiencies caused by targeting the same audience across multiple ad sets.
  • Exclude past purchasers and website traffic from prospecting campaigns. This allows us to better track KPIs and to ensure we reach new users, not those who have recently purchased and are no longer in the market for your app or offer.
  • Structure initial launch audiences for maximum performance. Here’s an example of how we do it:

  • Once you have about 10,000 installs you can move to AEO (App Event Optimization for purchases). Then your audience structure can shift to something more like this:

  • And once you have about 1,000 purchases, you can move to Value Bidding and reselect your audiences again:

Lever #2: Combine Placements: Select automatic placements for better results.

 

  • The more placements your ads appear in, the more opportunities you have to reach or convert someone. As a result, the more placements your ads are in, the better your results can be. And you won’t get penalized for letting the algorithm test new placements. After the Learning Phase, the algorithm will just not show your ads where they don’t perform. It can do the placement testing for you.
  • Facebook’s system of Discount Bidding (Also known as “Best Response Bidding”) will always try to find the lowest cost results based on a campaign’s objective and within the audience constraints set by the advertiser. But if you’re willing to widen the delivery pool by including additional placements, you’re giving the algorithm more to work with. That gives it a better shot at finding lower-cost results and delivering more results for the same budget.

 

Asset customization gives you control over placements

 

  • The ad sizes and ratios you use, of course, determine which placements those ads can appear in. So you’ll want to choose the images or videos people see in your ads based on where those ads may appear.
  • If you elect to manually select placements, use asset customization. It will let you specify what ads are shown for specific placements to ensure your ad displays the way you want. Asset customization also allows organizations to easily choose the ideal image or video for some placements within one ad set. If you have a content strategy that requires specific assets to appear in specific placements, this option is your best bet.

 

Lever #3: Increase Budget Liquidity: Select automatic placements for better results.

 

  • Increase your campaigns’ budget-to-bid ratios. Calculate daily budgets based on the cost to achieve Facebook’s 50 conversions per week threshold.
  • Use Campaign Budget Optimization. Our current best practice for CBO is to separate prospecting, retargeting, and retention into separate campaigns. Otherwise, CBO will push the budget toward retargeting and retention. Focus on a split of roughly 70% prospecting, 20% retargeting, and 10% loyalty (loyalty is optional). Segment your budget at this high level, then let CBO do the work within those objectives.
  • Test creative at the ad level instead of creating separate ad sets for individual creative assets. Some clients will have one ad set for each piece of creative they want to test. This isn’t best practice because they are likely targeting the same audience within each ad set (which creates 100% audience overlap) and each ad set only has one ad. Instead, set up multiple ads with different creatives in a single ad set. It’s a fast, streamlined way to test how multiple creatives will perform. 
  • Use Placement Asset Customization. This is the setting to use if you want to build complementary messages across platforms and benefit from utilizing placement optimization, but you want to be able to specify which creative asset is used for each platform or placement type.

 

Lever #4: Bid smarter.

Never underestimate the power of choosing the right bid strategy. Make your pick carefully (and test it) based on your campaigns’ goals and cost requirements. Whatever bid strategy you pick is basically giving the Facebook algorithm instructions on how it should go about reaching your business goals. Here are a few things to consider:

  • Lowest Cost: Directs the Facebook algorithm to bid so you achieve maximum results for your budget. Use the Lowest Cost when:
    • You value the volume of conversions over a strict efficiency goal.
    • You have certain audiences you just want to get in front of, and the conversion rate is high enough to justify the spend.
    • You’re unsure of the LTV of a conversion.
    • You’re already using the lowest cost bidding and are satisfied with the cost per result.
  • Target Cost: This aims to achieve a cost per result on average. So even if cheaper conversions exist, Facebook will optimize for the specified cost per result. Use it when:
    • You want a volume of results at a specific cost per result on average, and you want consistency at this cost.
    • You’re willing to sacrifice some efficiency for consistency.
  • Lowest Cost with Bid Cap: Sets a limit on how high Facebook will bid for an incremental conversion. Use it when:
    • You know the maximum amount you can bid per incremental result, and any incremental conversion above this value would be unprofitable and unwanted.
    • You’re targeting a broader audience with a lower likelihood to convert, so you want to appropriately manage costs.
    • You have a highly segmented audience with a defined LTV for each segment, and you understand the associated bid.

Whenever possible, assign a value to your audience. Ignoring LTV when you bid just doesn’t make sense long-term.

If you’re using a bid cap, make sure that the cap is high enough. We suggest setting your cap higher than what your goal actually is. Still not sure what’s high enough? The average cost per optimization event your ad set was getting when you weren’t using a cap can be a useful starting point. Just keep in mind that bids are often higher than costs. So setting your bid cap at your average cost per optimization event could result in your ads winning fewer auctions.

 

A word about campaign structure

Campaign setup matters. A lot. We need to figure out which campaign structure is going to work best for the particular app we’re launching. That usually means using Campaign Budget Optimization settings, but we also have to decide if we want to initially optimize for Mobile App Installs (MAI) or App Event Optimization (AEO).

Typically, if we don’t already have a large database of similar payers, we will need to start with a limited launch using (MAIL) app installs as our campaign optimization objective until we’ve got enough data to shift to AEO (app event optimization). For initial testing, we like to buy 10,000 installs to allow for testing of game dynamics, KPIs and creative.

Once we have 2-3 rounds of initial testing and data complete, we recommend switching UA strategies to focus on purchases using AEO and eventually VO to drive higher value users. This one-two punch of AEO and then VO is a great solution that allows ROAS to start to flow through the system for LTV modeling and tuning. Ultimately, what we’re doing is training Facebook’s algorithm for maximum efficiency and testing monetization and game dynamic assumptions.

Audience Demographics

Audience demographics get a lot of attention at this phase, too. We’ll review the performance of our campaigns at various age and gender thresholds, first using broad audience selections to build up a pool for evaluation and eventually allowing Facebook to focus on AEO/VO audiences to test monetization.

Facebook’s recommendation is to start as broad as possible and run without targeting, and we agree with this. Also, keep your account structure simple by using one or two campaigns and minimal ad sets where you reduce or eliminate audience overlap and set your budgets to allow for 50 conversions per week per ad set. Facebook refers to this as “Structure for Scale” and it gives their algorithm the best opportunity to learn and adapt to the audience you’re seeking. It will help get your ads out of the Learning Phase and into the optimized mode as quickly as possible.

Testing and optimizing creative

We believe creative is still the best competitive advantage available to advertisers. Because of that, we relentlessly test creative until we find break-out ads. Historically, this focus on creative has delivered most of the performance improvements we’ve made. But we’ve also found that new creative concepts have about a 5% chance of being successful. So we usually develop and test at least twenty new and unique creative concepts before we uncover a winning concept.

That’s far more work than most advertisers put in, so to stay efficient we’ve developed a methodology for testing creative that we call Quantitative Creative Testing. QCT, combined with some creative best practices, allows us to develop the new high-performance creative concepts that clients need to dramatically improve their return on ad spend (ROAS) and to sustain profitability over time.

Our overarching goal with all this pre-launch creative is to stockpile a variety of winning creative concepts (videos, text, and headlines) so we’re ready for the worldwide launch and can launch in the US and other Tier 1 countries with optimized creatives, audiences, and a fine-tuned Facebook algorithm.

Collect lifetime value data

This is where optimizing the game’s monetization comes in. While we’re working on campaign structure, what to optimize for, and developing creative, we’re also collecting lifetime value data. This helps us meet the client’s early ROAS targets based on their payback objectives. Most mature gaming companies want a payback window of one to three years, which is pretty easy to attain if all the other aspects of a campaign are on track.

Low expectations for pre-launch

Post-launch metrics tend to be noticeably stronger than pre-launch metrics. Several factors contribute to this:

  • The same creative we tested at pre-launch will usually perform better when it’s used for the worldwide launch.
  • The US audience we had held back from advertising for pre-launch will ultimately make up about 40% of the total ad spend once the worldwide rollout is underway. This gives us a lot of potential user base to go after in the most cost-effective ways.
  • We tend to see a correlation between higher reach and higher ROAS on Facebook. So the worldwide targeting we use post-launch also gets a boost in performance over the limited market targeting we did pre-launch.

 

Shifting Towards The Worldwide Launch

Pre-launch campaigns can run from anywhere between a week to a month. They are an investment, but they let us hit the ground running with proven creative, an efficient campaign structure, and a monetization strategy that further boosts profitability. For advertisers who want to scale fast, this is absolutely the way to go.

 

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