Mobile UA Tips from the Inside | Paivi Putsepp-Seufert
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Delivered at Casual Connect Tel Aviv 2016 | Ever wondered what people from a video network consider best practices for mobile UA? This talk will go over mobile UA tips that are observed by someone managing UA campaigns for top gaming mobile advertisers in Europe. You will walk away with suggestions that you can use in all large-scale UA networks.
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Mobile UA Tips from the Inside | Paivi Putsepp-Seufert
- 1. Mobile UA tips from the inside Päivi Pütsepp-Seufert Business Development Manager UnityAds
- 2. Howan AdNetworkWorks 50k live publishing games 3k Advertising games 400M users
- 3. MobileUAtipsfromanetworkperspective Tip 1. Three creatives better than one Tip 2. Source-level optimisation: blacklisting & whitelisting Tip 3. OS level optimisation Tip 4. No demographic exclusion, rely on data & the algorithm Tip 5. 10% increase in bid ≠ only 10% increase in volumes Tip 6. Communicate with your network AM regularly Tip 7. Video asset suggestions
- 4. Tip 1. Multiple videos better than one Each video = unique evaluation & eCPM eCPM = CVR x CPI x 1000 Larger audience & more segments more volumes NB! No guaranteed volumes (10 videos ≠ 10 times more volumes), the ad needs to be engaging with a competitive eCPM. Video 1 shown to source ID 456 with higher eCPM Video 2 shown to source ID 123 with higher eCPM Video 1 Video 2 Source ID 123 Source ID 456
- 5. Installs over time. Strategy game Tip 1. Multiple videos better than one Android iOS
- 6. Tip2. Sub-sourcelevel optimisation:blacklisting Do not pause a source with less than 100 installs Or do not pause at all – create a low- bid campaign instead - Pay 30% of the RON campaign 200 - 300 installs per day extra Installs over time. Casual game
- 7. Tip2. Sub-sourcelevel optimisation:whitelisting Bid higher for high-quality sources Installs over time. Social casino game Difference in bid 20% - 200% 1+ sources If you can afford to, make the most of it
- 8. Tip3. Operatingsystemlevel optimisation Pay higher for high-end operating system users If you have: Post-install event data per OS Quality difference per OS level build your campaigns towards this
- 9. Tip3. OS level optimisation Example Phase 1 Android Android - Tier 1 - OS 4.0-4.4 Android - Tier 1 - OS 5.0-5.1 Android - Tier 1 - OS 6.0+ Phase 2 iOS Tier 1 - RON - OS 8.0 - 9.0 Tier 1 - RON - OS 9.0+ Tier 1 - WL - OS 9.0+ Tier 2 - RON - OS 8.0 - 9.0 Tier 2 - RON- OS 9.0+ CPI 1$ difference per OS group Installs over time. Strategy game Android iOS
- 10. Tip4. Demographictargeting mightbe limiting, dataexplorationis maximising “Target only male 25+” or “Target only females” or “Target only casual games” Do not exclude based on assumption! Rely on actual data Let the networks optimize towards the install, you optimize towards the quality of the install Two-fold approach: 1. Predict and evaluate the potential of the campaign (predict eCPM) 2. Learn the eCPM and optimize it
- 11. Tip4. Demographictargeting mightbe limiting, data explorationis maximising 1. PREDICT and evaluate the potential of the campaign (eCPM) Machine learning • No manual adjusting because it’s hard to know all the factors • Utilize all dimensions • Teach the computer what to optimize and let it do the job and learn Context: Country; Day of the week; Publishing game Personal: Interest profile; Ads seen; Device Target: Campaigns past performance; Age of the campaign 2. Learn the eCPM and OPTIMIZE towards best eCPM • Don’t assume some input will have certain impact • Explore the data and try things out • Figure out the data (combinations, derivatives, transformations)
- 12. Tip5. 10%increase inbid ≠ only 10%increase involumes It is not linear but exponential growth - Change in adplan position
- 13. Tip 5. 10% increase in CPI ≠ 10% in volumes Installs Spend CPI 8K 2K 2K 30K 5K 4$ 1$
- 14. Tip6. Whatto ask fromyour networkAM regularly Changes in the network: - New features & internal tools (hitting caps, CPI increase) for AMs - Algorithm, evaluation changes - Video recommendations (from other advertisers) - Internal design updates/tests (tests for default features)
- 15. Tip7. Video assetsuggestions • in-game special events (new characters, levels, items, etc.) • real gameplay footage or video footage of someone playing • show the user interaction with game play (drag, tap, gestures) • show unique selling points • use short on-screen messages • localized videos • length • 15s: Usually good for casual games • 30s: great for mid-hardcore games, conveying the user of unique value • 22s: good optimal length
- 16. MobileUAtipsfromanetworkperspective Tip 1. Multiple creatives better than one Tip 2. Source-level optimisation: blacklisting & whitelisting Tip 3. OS level optimisation Tip 4. No demographic exclusion, rely on data & the algorithm Tip 5. 10% increase in bid ≠ only 10% increase in volumes Tip 6. Communicate with your network AM regularly Tip 7. Video asset suggestions
- 17. Thank you!
Editor's Notes
- Hello everybody My name I Päivi PS and I have worked at UnityAds for the past two years helping large European advertisers do global user acquisition wth videos ads. When thinking about the topic for this talk, I realised there are repeating questions of UA that all advertisers face on an ongoing basis. So this is why I decided to give you some tips about doing mobile UA and that from the network side view.
- I’ll get straight to the point. How an ad network such as UNITYAds work is that everything is there are two sides: – publishers who are monetising their games and advertisers who promote and are looking for more users. Unityads has 50K games live that reaches 400MM users. And then there are 3K advertisers who are looking to reach those 400MM users
- Since we work with so many different advertisers and we have so much performance data that we revolve our work around, there are also some repeating topics that come up with all advertisers one way or another. We serve more than 3000 advertisers and there are questions that they face on and on so here are the answers put together for them Not all might apply to you but it is wise to be aware of the opportunities.
- First I would like to start off with why use more videos than one on the same targeting. Not all users like the same type or style of video, but it doesn’t mean they will not like your game! Each videe and a campaign has its own unique evaluation on eCPM and thus we show this video one to a source ID that brings higher eCPM. And video 2 is shown to a different source ID as the user is more engaged on this source. What this means is that you reach a larger audience and target more segments that all lead to more volumes if your videos are engaging enough. Doesn’t mean that adding 10 videos will increase your volumes by 10 times – videos need to be engaged Each video has its own evaluation and eCPM. Larger audience targeting with mutiple videos target more segments makes higher volumes
- Strategy game
- One of the most common optimisation methods is sub-source level. Video ad users are still quality users as the user is conveyed to play the game if they already installed. Just pay less for them. This graph here is a casual game who had paused ca. 30 sources due to lower quality. Then they needed to scale up volumes again as they focused on retention so Low overall volumes but without that Low-bid campaign, you wouldn’t have those 200-300 installs per day
- Wesee a lot of advertisrers only do pausing of sources. People think the only way to optimise is to pause lower qualityy users but the flip side of this is to also bid higher for high quality users. Difference in bid is 1$ - 5$ 10-20 sources per geo/device If you can afford to, make the most of it Graph shows how one socal casino game is getting majority of their traffic from whitlisted sources as they ar every competitive in those particular high quality sources
- If you see a difference in quality per OS versions, you should also build your campaign towards that.. We just had a very successful case where a strategy game was finding it hard to scale up volumes as very often the high quality sources are not very scalable. The OS targeting method allows you to target a much larger group of users, while still targeting the higher quality users (the ones that tend to be on higher OS version). iOS After some optimisations and CPI bid changes, they are at this point: Tier 1 - RON - OS 8.0 - 9.0 CPI: 1.50$ - 3$ (varies per geo) Tier 1 - RON - OS 9.0+ CPI: 2.50$ - 5$ (varies per geo) Tier 1 - WL - OS 9.0+ CPI: 3$ - 5$ (varies per geo) Tier 2 - RON - OS 8.0 - 9.0 CPI: 1$ - 2$ (varies per geo) Tier 2 - RON- OS 9.0+ CPI: 2$ - 4$ (varies per geo)
- One example where a strategy game was trying to scale up and whitelisted and RON camps were maxed up. The results were very positive and they saw a significant difference in LTV in the OS 6.0+ users vs the OS 4.0 users. They immediately raised bids by $0.50 at a time until they reached a max where they weren't ROI positive anymore
- Another point I would like to make is demographic targeting that might be limiting your scale and we believe relying on perfromance data is maximising your scale Predict based on historical data eCPM is an outcome of an action. In CPI BUY performance buy (CPI), advertisers often want to target a specific demographic like male 18-35 or females only or X kind of games. We do not recommend it because with this behaviour, you are excluding potential great users based on assumption. Trust data more and let the experienced algorithm with tons of performance data do the targeting for you Päivi: Someone, somewhere, is playing one of the publishing games right now. When she chooses to watch an ad, which ad we should show? No manual adjusting because it’s hard to know all the factors Utilize all dimensions Teach the computer what to optimize and let it do the job and learn
- Test your bid boundaries. We have a tool NB! Some people think increasing 10% bid, gets you only 10% increase of volumes. This is not true, there is an exponential growth (not linear) so it might happen you get 30% more installs EXPLAIN the columns Camp 1 etc to one cell Change the column heads We have this tool that will give you estimations for increase in impression levels per campaign. Based on past data so only an estimation but still helping to make estimations Graph of Aaron’s Toy Blast increase
- Increase of CPI was 10%- 40% per campaigns And you see a jump of stable 2K installs to 8K installs!
- Emphasise to do this moderately
- The video is a showcase of your app. Try and show different things. (if not showing what the game looks like, the CVR is low) highlighting in-game special events (new characters, levels, items, etc.) - a shorter video with real gameplay footage or video footage of someone playing , show the user interaction with game play (drag, tap, gestures) - show the unique selling points of the game vs other similar games - use short on screen messages to be shown over video explaining the selling points to the user e.g. "earn free coins!" as they might have audio turned off (most users play games without the sound on so have "subtitles" in the video. - when running a vertical game, add graphics to either side of the gameplay to fill all of the landscape video, giving the illusion of a larger game screen - localized videos - length-wise what we have noticed in general: 15s: short and sweet, generates higher CTR, but maybe lower CVR and can impact retention negatively. 30s: beyond the recommended, leads to reduced CTR but higher CVR, can also help with retention. 22s: ideal length, perfect balance of CTR and CVR
- These are the seven points, I hope you learned something new. And can work etwork perspective. Thank you for your time. Recap of all the points. You can use this for all major networks. Hope this gives some ideas. Thank you