为手机游戏的品牌市场营销创造分析框架

作者:Kristian Segerstrale

许多游戏公司都在使用创办资本,不管是刚刚问世且基于隐形模式的公司,还是像Supercell这样的国际性大公司。主要原因便是用户获取成本不断提升,“我们需要在某些情况下明确品牌市场营销。”大多数手机游戏和应用公司主要通过终身价值和每安装成本套汇而专注于基于性能的用户获取,并很难在这种情况下通过思考品牌导向型市场营销进行包装。但是随着市场日趋成熟,实现更加综合的市场营销模式变成了获取成功的关键。就像我在之前的文章中所提到的,以及我在GIMC所强调的—-我相信这将成为2014年充满抱负的赢家们强大的竞争优势。

为手机游戏的品牌市场营销创造分析框架

brand advertising(from 3d-car-shows)

手机/应用中的一些品牌背景

前艺电首席执行官,同时也是一位强大的产品市场营销思想家兼投资者的John Riccitiello在最近的游戏业内人士峰会上发表了有关品牌市场营销的演说。他出色的洞察力有时候很难与用户获取的定量模型结合在一起,因此徘徊于更加定量的市场营销部门。之前Supercell的Matt Kellie便曾调节过市场营销的创造性和性能,但是他并未触及品牌。

我仔细思考了这一问题,并通过对Glu,Playfish,LOVEFiLM,艺电以及Supercell和其它投资组合公司的研究而得出自己的结论。在艺电,特别是作为数字执行副总裁,同时也在处理所有的核心市场营销业务,我曾与许多兼顾创造性与性能的超级厉害的人物共事过,这也帮助我们能将所有元素汇聚在一个团队中,并得出一个有效的方法。

三个重要警示:

1.从根本上看,市场营销既是一种艺术也是一种科学,最佳结果将源自富有创造性思维的人相对于带有刻板定量思维的人而言。我们应该尝试着将性能与指标结合在一起,但是即使是拥有最强定量思维的人也需要承认并非所有东西都是可测量的,我们需要接受可信赖的创造性本能。就像创造游戏,明确应用市场营销的品牌终端更多的是关于创造性人才而不是任何准则。准确执行的指标将成为创造性的有效引导,而不是准则。

2.应用市场营销树上最底端的果实总是会获得应用商店(游戏邦注:如苹果,谷歌或亚马逊)的推荐,而一系列UA指出结构的智能测试将花费在Facebook,像Chartboost等基于性能的广告网站以及像Everyplay和AdColony等基于视频的网站上。当你拥有产品牵引力,并且你的主要任务变成与收益递减作抗争,那么更广阔的品牌市场营销将成为你优化这种情况的第二重要步骤。我不会从这里开始—-只会将其藏在脑后,因为当最底端果实被摘光时我便需要最大化游戏的潜能。

3.不过我所说的都不如创造一个真正优秀的产品。在免费游戏领域(即游戏是作为一种服务,而体验就是品牌所在),不管你在游戏外部如何描述游戏或如何执行游戏都不及真正玩家所说的,所分享的以及所感受的重要。品牌市场营销的工作在于扩大并分享这些体验和感受的真实性—-而不是尝试着将其描绘成违背事实的情况。

“品牌市场营销”的分析框架

因为“品牌”是抽象的并不意味着它不能作为受定量驱动的市场营销方法进行衡量。实际上,几乎应用市场营销中的一切都可以受到性能的驱动。诀窍便在于使之成为主观,即将性能归因于“最后的点击”只是对于发生了什么事的误导性观点。它并不能轻松地追踪某物并不意味着它就不属于这里。在消费者的脑子里存在着从“哇,这是什么?”(我将其成为“意识”),到“我喜欢这个/我必须看看它是什么”(我将其称为“兴趣”),到“给我安装链接”(我将其成为“转换”)以及一系列后续步骤再到最终沉浸于其中并获利。品牌市场营销的影响可以被简单地说出是对意识和兴趣的影响(这两个元素都会推动着更多人进入转换阶段,同时为那些已经留在游戏中的人拉低CPI)。安装后指标在某种程度上不会受到影响。它有可能提高信任值并因此提高消费/LTV,但是我将不在本文谈论这点。(同时我要说的是,意识,兴趣和转换只是语意,你还可以使用其它单词,并为每个元素使用特定的测量值,不过你必须保持同样的原则)。

如今大多数手机应用市场营销所采取的做法(只是购买受转换驱动的广告)都是将意识,兴趣和转换汇聚在吸引消费者的同一个步骤中。这是最容易测量的方法,也是成就最底断水果的方法,但却会因此限制你的最大增长。基于性能的广告单位擅长转换,但却不能有效地创造意识或激励兴趣。如果意识和兴趣越突出,开发者花在转换上的费用便会越低。如果人们相信产品是有趣的,他们便会愿意点击链接。

媒体组合之所以能够发挥功效不仅因为它分别处理了上述步骤,同时还因为现代认知科学暗示,当人们在做决定时,大脑将通过多个来源诱发信息的一致性。

你可以对自己的方法进行a/b测试看看它是否具有合理的创造性,并对其进行长期的媒体组合,但这要求你在一开始做出态度转变才能真正尝试。比起那些习惯于基于数字的纯粹性能,传统的市场营销者更加适应态度转变。而做好这点所获得的回报也是巨大的。

一开始的最优策略将会是购买基于广告的正常性能,包括基于广告的视频性能,这将赋予游戏更棒的视角。你将基于这种方式创造出最底端的果实。但随着时间的发展去伸向那些你想要接触到的人就变得更复杂了。当你瞄准的用户更加硬核,或者你认为他们需要更多说服力才会愿意尝试你的游戏,那么随着时间的发展去做好这些便会变得更加重要。以下是由此延伸的一些建议框架。

1.基于意识,兴趣和转换为你的获取渠道创造定量目标

意识:对于你可触及的用户或潜在玩家的有限宇宙(例如240兆或在美国很活跃的iOS或Android设备)可能是全球市场,但是市场营销却会演变成更加区域化。为了实现意识元素,休闲/宇宙游戏可能需要瞄准整个目标用户群体。更加硬核/具有有限吸引力的游戏可能要基于需求而瞄准较小部分的用户。意识指标基本上是关于哪一部分的可触及用户能够通过有机或付费途径知道你的产品的存在。意识应该将可触及的用户作为标准—-如果你让100万个人知道了你的游戏,但是他们却是没有价值的用户,那这么做只是在浪费金钱罢了。做到这点的工具包括电视,在线视频,社交市场营销以及PR。传统的结果度量标准是Nielsen(游戏邦注:是一家总部位于美国纽约市国际市场调查研究公司,主要研究包括消费品市场的情况和动态、解决市场和销售问题,以及确定市场发展机会)。在手机上看到有关意识的不同指标的出现是件很有趣的事。

兴趣:在听说你的游戏后,潜在玩家的反应应该是“我该从哪里获得它!”创造出兴趣vs漠不关心态度的工具主要是,找到一种方法去呈现游戏玩法并引出人们对它的反应,将其与其它产品区分开来,同时使用评级/评论/星星/赞美等方法去证实这些信息。找到一种方法去衡量人们对意象/视频的反应,而不只是点击“评级”是一种重要的创新领域。用于主机中的传统Nielsen“在意识中评级(RAA)”和“定义购买意向(DPI)”指标并不适合免费游戏。手机可能要开发适合自己的更加精确的评价指标,即继视频广告之后更加有利的等级查询。就像在www.loopme.com网站上有些广告单位便考虑到了消费者的反馈。

转换:理解那些意识到你的游戏并给予游戏评级的用户最终会转变成玩家以及付费用户。能够做到这点的工具箱很好理解,像Grow Mobile,Fiksu,Fetch,Mobile App Tracking,Has Offers等等公司都能提供这些工具。而最基本的方法便是测试无数创造性和渠道,基于下游行为检查结果,然后通过渠道和人口统计原理优化CPI/LTV。

游戏的基本有机性能以及游戏所呈现出的感觉必须能够传达这些目标漏斗指标(如下面的步骤2)。在这一例子中,假设最初效能的损失是90%。这反映了任何花在用户意识(最终都不可能满足目标条件)的资源将不会得到有效部署。

当市场营销活动足够活跃时,我们不仅需要优化每个转换步骤,同时也需要离开那些朝着最终不可能实现转换的用户/渠道,而转向专注于那些可能实现转换的用户。源自测试和早期性能市场营销努力的基线度量指标将提供假设并定义目标用户的观点去减轻效能的损失。在转换端,这被叫做“类似”目标,但它同时也应该向创造性和意识/评级努力延伸。一款非常优秀的游戏也不可能实现零效能损失,它将独自创造出意识,即使某些意识永远都不会发生转换。

值得注意的是,伴随着上述所提到的映射完整的漏斗,仍然存在真正的追踪问题,以及在Facebook以外的主要目标挑战。这是一个进化空间。解决方法是找到创造性方法为数量不大的消费者追踪完整的转换途径,以及适应完整追踪并不可行的计量经济模型的结合。创办资本通过我们在应用市场营销分析和a/b测试提供的投资而积极地参与到了这一领域中。

2.创建一个信息平台—-基于上述的目标漏斗指标视角去明确如何描述你的游戏,考虑你的游戏到底是关于什么以及所瞄准的目标用户。结合直觉和测试创造一个高分辨率的图像资产,视频资产,你所使用或不使用的文字,以及特性等等。想想如何调整这些信息并让它能够与你的玩家基础达成共鸣,如此你将能够通过在Facebook或Youtube上推广/好友分享等方式而提高意识度。这是不同于性能购买的一种技能,需要尽可能地接近于产品团队。来自主机世界的一个有效例子便是《战地4》,即伴随着并主要竞争对手《使命召唤:幽灵》中并不存在的独特游戏功能。

在手机领域中,这还只是开始,但是《Candy Crush Saga》的广告却开始向我们呈现了这一领域的发展。

在手机上,真正的病毒性资产分享才刚刚开始。来自Everyplay和Kamcord的解决方法正通过分享视频剪辑而推动着我们在这条道路上向前发展。消息传达的必杀技在于呈现定制且引人深思的内容,而最理想的情况便是这些内容是由自己的朋友所创造的,基于这种渠道你便会更加愿意采取行动。这一领域将会发生快速进化。

3.为了进行实验而创造一个渠道策略与模型—-考虑上述第1点所提到的指标框架以及第2点的消息平台,现在你便可以明确尝试创造性需要怎样的渠道以及需要分配给它们多少预算并继续对其优化与进行a/b测试。当你获得一些数据时,你便可以开始通过不同渠道预测需要创造多少印象才能建立第1点所提到的目标渠道指标,你也可以开始分析创造一个特定规模需要花费多少成本。举个例子来说吧,你应该发现适当的相对投资水平以及电视vs在线视频vs手机视频vs社交活动的具体执行和病毒式传播功能,从而根据与你当前优化基于网络的不同性能间的转换部分类似的方法去瞄准意识。

你必须拥有一个跨渠道属性模型让你能够将价值不只归属到“最后的点击”和安装上,同时还能将其归属到所有上游活动目标意识和兴趣中。考虑到数据的限制(例如明确谁看了电视广告),只有一些元素可以进行我们所倾向的非实时测试。而对于其它元素,你必须花几周或几个月时间进行摸索,并通过计量经济学使用推论值而不是直接属性,并且有时候还要跨越不同国家(即用户具有类似的行为,如德国和澳大利亚)进行测试。但是你将因此获得巨大的利益。如果在你的市场营销团队招募名单中还没有数据科学家的位置,你可能需要开始寻找这些人了。

我们需要从第1点开始进行反复迭代,并始终强调专注于那些最终会对你有价值的人—-即具有较高用户粘性且肯花钱的用户。你不需要投入过多钱于那些最终不会对游戏价值做出贡献的人身上。但结果便是品牌市场营销将在手机游戏领域变成既是科学也是艺术般的存在。品牌市场营销专家不会去判断你的游戏最初是否获取成功,但是这将真正影响着你是否能够成为全球赢家。

未来之路

直至现在,手机应用用户获取创造性的最快节奏发生在伴随着手机广告网络的“最后点击”性能广告,即同时包含详细目录与追踪。2013年的最大创新是手机视频广告网络的崛起以及最近Facebook发行了较为强大的手机广告产品。我们将在未来看到更多类似的产品出现,同时也会看到购买这些印象的实时投标(RTB)的崛起。

到2014年手机市场营销的一些最大创新将源自更加强大的追踪以及更加普及的市场营销策略。有趣的是主要的应用商店排行榜追踪服务App Annie目前正在测试一个基本的手机广告分析产品。我们都知道学习需要花一定的时间,而那些深刻理解了媒体组合以及资深漏斗指标的公司将开始探索能够创造并巩固自己在市场上的全球赢家地位的“发行商杠杆作用”。所以事先掌握这些做法真的很重要。。

(本文为游戏邦/gamerboom.com编译,拒绝任何不保留版权的转载,如需转载请联系:游戏邦)

An analytical framework for brand advertising in mobile games

By Kristian Segerstrale

Initial Capital work with many game companies, ranging from stealth mode yet-to-launch companies to global stars like Supercell. A common theme across all is that user acquisition costs are rising and “we need to figure out brand marketing at some point.” Most mobile games and apps companies are rightly focused on performance based user acquisition (UA) through a Life-time Value (LTV) and Cost-Per-Install (CPI) arbitrage and have a hard time wrapping their heads around how to think about brand oriented marketing in that context. However, as the market matures, getting to a more comprehensive model of marketing is critical for success. As mentioned in my previous post and my keynote at GMIC I believe this to be a key competitive differentiator for aspiring winners in 2014.

Some background on brand in mobile / apps

John Riccitiello, former EA CEO, and a strong product marketing thinker and investor gave a great talk on the subject of brand marketing at the recent Gaming Insiders Summit writeup here. His excellent insights are sometimes hard to tie back to a quantitative model of user acquisition and hence get bounced around more quant marketing departments. A good primer on reconciling creative and performance in marketing byMatt Kellie of Supercell is here. But even he doesn’t quite touch on brand.

I think about this a lot and my take on reconciling the subjects based on my cumulative learnings from Glu, Playfish, LOVEFiLM, EA as well as observing Supercell and other portfolio companies below. At EA in particular as EVP Digital including all central marketing I got to work with a really fun mix of super talented folks across both ends of the creative vs performance based spectrum in particular, and it was fun helping bring all elements together into one team and get to one approach.

Three important health warnings :

1.Marketing is fundamentally an art as well as a science and the best outcomes will come from creatively minded people respecting the quant wonks and vice versa. We should try to proxy performance with metrics wherever possible but even the most quant minded folks need to acknowledge that not everything is measurable and we need to live with trusting creative instinct. Much like with making games, figuring out the brand-end of app marketing is all about star creative talent more than any formula. Executed correctly metrics will be a great guide for creative but only that not a formula.

2.The lowest hanging fruit in app marketing will always be getting featured by the app stores (Apple / Google / Amazon) and a series of smart tests of spending mix of UA spend across Facebook, performance based ad networks like Chartboost and video based networks like Everyplay and AdColony. Broader brand marketing will be an important second step optimisation once you have product traction and your main task becomes fighting diminishing returns. I would not start with it only keep it in the back of my mind as something I need to get to to maximise the potential of the title once the low hanging fruit is exhausted.

3.Nothing I’m about to say should take precedence over making a great product. In F2P games as a service in particular the experience is the brand whatever you say or do about the game outside of the game will pale in significance over what real players say, share and feel. The job of brand marketing is to augment and share the truth of those experiences and feelings not attempt to portray them as something they are not.

An analytical framework for “brand marketing”

Just because “brand” is abstract doesn’t mean it can’t be measured as part of a quant driven marketing approach. In fact almost everything in app marketing can be performance based. The trick is to internalise that attributing performance to “last click” only is a misleading view of what’s going on. Just because it isn’t easy to track something doesn’t mean it isn’t there. Somewhere in a consumer’s head there has been a process of “wow what is that?” (I’ll call this “Awareness”) to “I love this / have to check it out” (I will call this “Interest”) to “give me the link to install” (I’ll call this “Conversion”) and a set of subsequent steps to ultimately become engaged and monetize. The impact of brand marketing can simplistically be modelled as impacting Awareness and Interest (which both drive more people into the conversion stage, as well as driving down CPI for the folks already there). Post install metrics are far less likely to be impacted to a meaningful degree. There is some potential for it to increase trust and thereby spending / LTV but I haven’t seen it personally and will ignore that effect here. (By the way Awareness, Interest and Conversion are just semantics there are other words you can use, and specific measurements you could use for each, but the principles should remain the same.)

The way the vast majority of mobile app marketing is done today by buying purely conversion oriented advertising forces Awareness, Interest and Conversion to all occur in a single step for the consumer. It’s easiest to measure and it is the lowest hanging fruit approach, but will both limit your max growth and achieve it less efficiently. Performance based ad units excel at conversion but are not the best at creating either Awareness or spurring Interest. And the higher these two are, the cheaper the Conversion and the further out it pushes the saturation point where you can no longer acquire users profitably. After all people will only click on the link if they believe it is interesting. A picture illustrating the effect of more comprehensive marketing below. The CPI curve for any segment is lower with broader Awareness and Interest, making UA more profitable and pushing the point of saturation further out.

The reason media mix works is both because it addresses the above steps separately, and also because modern cognitive science suggests that the brain places a premium on the coherence of the information from multiple sources when making decisions. An interesting digression on the topic from Nobel laureate Daniel Kahneman here.

You can a/b test your way to the right creative and media mix it in the long term but it requires a leap of faith initially to try it out. Traditional marketers are more comfortable with leaps of faith than those used to pure performance based numbers. But the payoff for getting it right is huge.

Initially the optimal strategy will almost always be to buy normal performance based ads including video performance based ads which give a better view of the title. You should get the lowest hanging fruit that way. But over time to expand who you reach you need to be more sophisticated. The more core the audience that you are targeting or the more convincing you think they will need to try out your title, the more important it will be to get this right over time. Here is a suggested framework to get there.

1. Develop quantitative targets for your acquisition funnel in terms of Awareness, Interest and Conversion

Awareness: This is the finite universe of your addressable audience or potential players for example the 240M or so active iOS or Android devices in the USA (Mary Meeker 2013) clearly the market is global, but marketing is likely to evolve to be more regional. Casual / universal games likely need to target this entire population for awareness. More core / limited appeal games can probably break it down to a smaller addressable audience based on wants and needs. The awareness metric is fundamentally about what portion of this addressable audience is aware that your product exists through organic or paid means. Awareness should always use the addressable audience as the denominator having a million people who are aware but will never be a valuable user for you is a waste of money. Tools to get there span from TV to online video, social marketing and PR. The traditional outcome metric is Nielsen. It will be interesting to see if a different metric will emerge for Awareness in mobile.

Interest : After hearing about your game the reaction among your potential players should be “yey, where do I get it!”. The tools to generate interest vs indifference are primarily finding a way to show gameplay in a way that evokes a reaction and differentiates the product, as well as using ratings / reviews / stars / accolades to substantiate the message. Finding a way to measure reaction to the imagery / videos beyond click through to actual “rating” is an important area of innovation. The traditional Nielsen metrics of Rating Among Aware (RAA) and Definite Purchase Intent (DPI) used in console are not applicable for F2P. Mobile will likely develop its own more precise rating metrics of what is a favorable rating polling after video adverts and equivalent. An interesting development in this direction is www.loopme.com who have ad units allowing for consumer feedback for example.

Conversion : Understanding the portion of aware users that rate your game that ultimately convert to players and down the road paying users. This toolset is well understood and amply supplied by companies like Grow Mobile, Fiksu, Fetch, Mobile App Tracking, Has Offers and others. The basic approach is to test tons of creative and channels, observe the outcome in terms of downstream behavior and then optimize the CPI / LTV arbitrage by channel and demographic.

These target funnel metrics should be informed by baseline organic performance of the title and a sense of what the title is (step 2 below). In this example the assumed initial efficiency loss is 90%. This reflects the fact that any resources spent on making consumers aware that ultimately did not end up satisfying the target condition (here somewhat arbitrarily retention beyond D7) were not deployed efficiently.

Once the marketing campaign is live it is important not only to optimise each conversion step, but also to optimise away from top funnel investments toward audiences / channels that ultimately don’t convert toward a greater focus on those who will. The baseline metrics from beta and early performance marketing efforts should provide assumptions and also begin to refine the view of the target audience to mitigate efficiency loss. At the conversion end this is called ‘look-alike’ targeting but it should extend to creative and awareness / rating efforts also. A zero efficiency loss is neither possible nor desirable in that a great product will generate awareness on its own, some of which will never convert.

It’s worth noting that there are still very real tracking issues associated with mapping the full funnel above, as well as significant targeting challenges outside of Facebook. This is an evolving space. The solution is a combination of finding creative ways to track the full conversion path for at least a statistically significant number of consumers, as well as being comfortable with econometric modelling where full tracking isn’t available. Initial Capital is actively participating in this space through our investment in app marketing analytics and a/b test provider swrve.

2. Establish a messaging platform Develop how you portray the game based on the above view of target funnel metrics, respecting exactly what your game is and who it’s for. Develop the high resolution graphic assets, video assets, words you use and don’t use, personality etc based on a combination of intuition and testing. And figure out how to tailor this message and make it resonate with your player base so they will do the heavy lifting on awareness through distribution / sharing to friends for you both through product integration and outside of product on Facebook, Youtube etc. This is a fundamentally a different skill set to performance buys and needs to be as close to the product team as possible. A good example from the console world is Battlefield 4 with the differentiator “Only in Battlefield” based on unique game play features not available in main competitor Call of Duty: Ghosts.

In mobile this is just starting, but the advert below for Candy Crush Saga begins to show how this space is evolving

Genuine viral sharing of assets is still in its infancy on mobile. Solutions by Everyplay and Kamcord to share video clips are charting the path forward here. The holy grail of messaging is to show a tailored, evocative piece of content, endorsed and ideally generated by a friend, on a channel where you are likely to take action. This space will evolve quickly.

3. Establish a channel strategy and model for experimentation given the metrics framework from point 1 above and the messaging platform from point 2, you can now figure out both 1/ what channels to try out for that creative and 2/ what relative budget allocations to attribute to them and continue to optimise and a/b test your way forward. Once you get some data you can begin to forecast how many impressions across different channels you need to establish the target funnel metrics from point 1, and you can begin to understand what building up to a certain scale will cost you. For example, you should uncover the correct relative level of investment and detailed execution of TV vs online video vs mobile video vs social campaigns and viral sharing features to get to the target Awareness in a similar way as to how you are currently optimising the conversion part between different performance based networks.

It’s critical here that you have a cross channel attribution model that allows you to attribute value not just to the “last click” to install, but rather also to all upstream activities targeting Awareness and Interest ahead of that. Given limitations in data for example figuring out who saw a TV ad only some aspects of this can be tested in the near-real time we all love so much. For others you have to be comfortable learning in weeks and months instead of days, and using inferred value through econometrics rather than direct attribution and sometimes testing across countries that tend to behave similarly (like Germany and Austria). But the benefits are huge. If you don’t already have a data scientist on the recruitment list for your marketing team you should probably start looking for one.

It’s worth re-iterating from point 1 that at all times the key is to focus on the folks who ultimately become valuable to you the highly engaged folks and the spenders. The D7 target is just an illustration for simplicity. The less money you spend on folks who ultimately don’t contribute value in one way or another the better. But the upshot is that brand marketing can and will become a science as well as an art for mobile games. Brand marketing expertise will not determine if your title is successful initially or not, but it will play a critical role in transforming a success into a global lasting winner.

The road ahead

Up to now the fastest pace of innovation in mobile app user acquisition has happened in ‘last click’ performance advertising with mobile ad networks, both in inventory and tracking. The big innovations of 2013 were the rise of mobile video ad networks and most recently Facebook launching their well functioning mobile ad product. We will see more of these in the future, and likely also the rise of real-time-bidding (RTB) in purchasing these impressions.

Some of the biggest innovations in mobile marketing in 2014 will come from enhanced tracking and an increased use of broad marketing strategies. It is interesting that App Annie, one of the leading app store chart tracking services, just launched a basic mobile advertising analytics product in beta another sign of things to come. Learning will take time and the companies which develop a profound understanding of media mix and their own funnel metrics will begin to build that sought after “publisher leverage” that will create and cement the position of global winners in the market. Count on some exciting years of learning ahead!(source:gamesbrief)