After the release of this week’s Facebook earnings report, it should come as no surprise to industry observers, ad-tech enthusiasts and general advertising geeks that Facebook is dominating the mobile ad business at an unprecedented scale. A quick snapshot of yesterday’s numbers [via Adweek]:
- $3.6 billion in 2014 4th quarter ad sales, this is 53% year over year growth
- 69% was from Mobile ads, so ~$2.49 billion 4th quarter mobile revenue
- ~1.4 billion monthly active users (desktop + mobile) this is 13% year over year growth
- 745M daily active mobile users
It’s clear that Facebook has become the dominant leader in mobile advertising. As a result, our clients here at AdParlor, who span verticals such as gaming, ecommerce, retail, travel, technology and CPG, are seizing the opportunity to reach new and existing customers with their marketing message on mobile devices. We love talking about all things relating to campaign optimization, and in light of yesterday’s awesome mobile stats, we’d like to share with you a piece from our “Best Practices & Optimization” support library. The piece below describes how advertisers can best tackle one of the leading mobile ad formats surging today on Facebook: The Mobile App Install Ad.
Why should I use a Mobile App Installs (MAI) campaign?
Mobile App Install campaigns can be broadly categorized into two types:
- New User Acquisition (grow your user base to increase the number of active users of your mobile application)
- Re-Engagement (bring back old users to your app)
Both types typically share a common long-term goal, which is to generate revenue through some kind of revenue model:
- In-app purchases
- Advertising revenue
- Subscriptions and/or other direct revenue streams
How can I be successful with my Mobile App Installs campaign?
‘Success’ is a subjective term; it depends on what KPIs you are using to measure your performance. If your primary focus is to generate revenue, your optimization should be towards a revenue-based metric such as the Average Revenue Per User (ARPU) or Average Revenue Per Paying User (ARPPU). For the best results, you should also apply optimization principles to reach an efficient Cost Per Install (CPI) that enables you to scale your user base and generate revenue without running at a net loss.
Optimization is an iterative process which lets you maximize your Return on Investment (ROI) efficiently and effectively:
- Structure your campaigns using the Facebook Best Practice guidelines
- Analyze your data
- Make changes as needed based on your learnings
Key factors to consider when optimizing MAI campaigns are:
- Defining your criteria for success
- Campaign structure to set up on Facebook
- Ad Set Targeting
- Creative elements used
- Bidding and Budgeting selected
- Using your learnings to refine your campaign settings
The following recommendations have been compiled by our highly trained team of ad operations experts here at AdParlor so you too can become a better trafficker.
1. Start by choosing your conversion criteria and your measurement tools
Defining your conversion attribution windows before running a campaign ensures that all conversions are tracked in the same, known way. Attribution window options are shown below with default values from Facebook shown in bold.
- Click-conversion attribution window – choose from 1, 7, 28 days
- View-conversion attribution window – choose from 0, 1, 7, 28 days
Measurement options for tracking installs and in-app events:
- Facebook SDK – specific to Facebook, can measure click and view attributed actions
- Mobile Measurement Partner (MMP) – can be used for any publisher, can only measure click based actions
Read more on:
2. Plan your campaign structure
Start by planning your campaign structure at each level – Campaign, Ad Set, Ad – and identify what aspects you want to test. You should consider testing variations in your Targeting, Placement, Bidding, and Creatives.
An example of a well structured campaign on Facebook:
|Contains||Defined at this level|
|Campaign||“Mobile App Installs”||Campaign Objective e.g. “Mobile App Installs”|
|Ad Sets(segmented by targeting)||“UK Males 18-24”
“UK Females 18-24”
“UK Males 25-34”
“UK Females 25-34” …
|Flight Dates, Lifetime Budget, Targeting. Placement, Bids|
|Ads (testing different creative aspects)||“Creative 1”
“Creative 3” …
|Images, Text, Buttons etc|
Targeting – Choosing your Target Audience
Targeting for mobile app install campaigns can be very flexible you can utilize a combination of features: geographic, demographic, device/device OS, interests, audiences and more.
|Geographies||To segment or not to segment? Splitting up your target geographies (e.g. by country) across different Ad Sets allows you to measure performance for each country and easily modify your bids or budgets for each. However, this will limit the reach of your individual Ads.Conversely, targeting multiple geographies at once can help you increase your reach. Using the AdParlor Segmentation Reporting feature, you can still perform a country-by-country breakdown of your results. However, to apply your findings you will have to recreate Ad Sets for each.|
|Age & Gender||Your target age groups and genders may be highly dependent on your app content. As with geographies, combine genders and age groups for maximum reach or segment them for optimization simplicity. Again, Segmentation Reporting allows you to breakdown your results by age, gender, or age and gender.If your end goal is to maximize revenue from in-app purchases or otherwise, keep in mind that the minimum age for credit card ownership is 18 in most countries.|
|Device/Device OS||Device Targeting – Create a new AdParlor Advertiser for each app and device combination (e.g. App Name 1 for iOS 8) – each device has different LTVs and therefore different rates/bids.Device OS Targeting – Target above the minimum required OS to download on iTunes/Google Play App Store so your budget is not spent on users who cannot actually use your app.|
|Interests||You can create lists of interests using our Libraries feature which can be imported during the Ad creation process. Limit interests overlap between lists to limit competing with yourself for delivery.|
|Custom Audiences (CAs)||Custom Audiences can be created from a data file of customers from any of the following input types: emails, phone numbers, Facebook IDs & mobile advertising IDs.CAs should be comprised of your high retention, high LTV users, or any other top user-centric metric that allows you to pinpoint your top users on Facebook. We recommend you also create Look-A-Likes off these ‘seed’ CAs to find new users who ‘look’ like your top performing active users.|
|Look-A-Like Audiences (LALs)||Look-A-Like Audiences are created using a Custom Audience as a seed, then expanded to include users which are similar in characteristics. You can select a ratio between 1-20% (the lower the ratio, the more similar the LAL is to your seed audience). Facebook limits Look-A-Likes for one country at a time, with a minimum of 100 users per country in the seed audience.For more precise targeting, combine Look-a-like Audiences with interests targeting to better reach your desired users.|
|Mobile Custom Audiences (MCAs)||Mobile Custom Audiences are created by identifying users who have performed or not performed certain actions within your app. This is particularly useful if you are interested in targeting users who have actually used your app, and not just installed it. You can specify:
Additional “Events” can be added within the app and MCAs can be created off actions taken from these “Events”.
Benefits of using an MCA vs. a standard CA:
Creatives – Some Tips from our Ad Ops Specialists
|Image Background||Do: use in-app screenshots or content directly from your app as backgrounds
Don’t: use blank or blurred backgrounds
|Image Characters||Do: use one prominent feature to help convey your app’s personality
Don’t: too many points of focus causes clutter
|Text||Do: use CTAs and promotion text (e.g. install, play, free)
Don’t: use cliched game action text (e.g. fight, conquer, save)
|Image Colours||We’ve found that dark and warm colours seem to work better than cold and bright, but there is no hard and fast rule|
Bidding & Budget Considerations
For mobile app install campaigns, you should choose between oCPM and CPA bidding. With these bid models, Facebook automatically optimizes your delivery towards users within your target audience who are most likely to install your app. If you are unsure which bid model to use, it may be beneficial to create identical Ad Sets with different bid types and compare the performance as a test.
|oCPM||Potentially larger pool of users than CPA bidding as the advertiser takes the risk (you are charged per impression)More aggressive algorithm which usually helps provide more volume||Rates are not guaranteed – will need to use Ad Set budgeting to control ratesRates fluctuate daily according to market conditions|
|CPA||Rates are guaranteed to come in at lower than bid, which allows you to control the maximum you are willing to pay||Need to adjust rates constantly according to market conditionsNeeds 7 days worth of data with 5% conversion rate in order to run
Potentially smaller pool of users due to Facebook being more conservative with them taking on the risk (you are charged per install action)
Bidding and Budgeting go hand-in-hand to achieve CPI/volume goals. Your Ad Set budgets will determine the pacing of Facebook spend throughout the day:
- Aggressive budget Facebook will try its best to fulfill the aggressive budget and might loosen the criteria on who to show Ads to, leading to more volume but possibly higher CPIs.
- Conservative budget If Facebook knows the budget is easy to fulfill, it will slow pacing, showing ads to users who might be cheaper to acquire. You should see lower CPIs.
To keep your CPIs in check, you must first identify Ad Sets that are getting you low CPIs, then set conservative budgets to those Ad Sets so that Facebook continues to provide the most efficient CPIs.
3. Create your campaigns and analyze your data
4. Refine your campaigns for smarter use of your advertising budget
Use the following rule-based decision tree as a guideline for making bid adjustments to optimize your spends, with the goal of minimizing CPIs without sacrificing conversion volume:
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