作者：Haydon Young

当我们谈到手机游戏和app的时候，我们通常通过收集得来的数据来了解用户在软件内的行为和交互，以此引导我们将手游广告宣传和创意最优化。

虽说数据是有效获取用户的核心要素，不过我们做得可不是简单的大数据收集，而是要把在手机和app数码世界中对用户的了解和在“现实世界”中的对他们的观察相结合，从而创造一个宏大的视角。

我最初在房地产的事业让我学会了细心观察的重要性——观察手势、细听语调以及拼凑线索来确定客户意图和“需求状态”。

在对话和交流中对这些“信号”的注重让我能够恰当地回应每一位客户——让他们知道我有多了解和在乎他们的想法。

Pew Research Center（from venturebeat.com）

很快，相同的方法帮助我做成了几单房地产生意，这让我在用户获取策略上惊人的成功打下了坚实的基础，也让我荣获了“Mobile Hero”的称号。

我在CrowdStar（一个目标用户为女性的手游和社交游戏软件公司）工作的日子里，我负责过预算达数百万美元的一系列软件项目，其中包括《Covet Fashion》——一款属于时尚达人和购物狂的理想手机软件。

多亏了宣传鼓舞了用户积极性——我们的参与指标（女性用户一天内花30至60分钟的时间使用我们的APP）创下了新高。

而且，我们宣传视频的表现始终超出同类型软件的平均水准。甚至在不同广告网站和广告界伙伴中，我们的移动视频广告始终都是佼佼者，点击率（CTR）和转化率（CVR）也都比我们的竞争者多出10%到25%以上——这属于我们的一大优势。

很显然得益于我们在对目标受众的宣传力度以及相关性上的优异表现，我们的广告都会从跟竞争者的竞争过程中由网络算法被筛选出来，最后被采用。

也因为我们的宣传表现，我们有办法保持整体较低的CPI而获取较高的ROI。而我也从这些启发性的经验中明确了几个你们可以遵循的步骤来让游戏表现出众从而赢得观众的青睐。

跳出“分类之外”

目标受众数据（年龄、性别、是否有家庭）让你可以把观众精细地类分化。当然了解你的观众是什么样的很重要——但是这些数据你的竞争者也在用。也就是说，这些数据不会是你竞争力的利刃。

要把目标转向宣传，你需要更深入地了解“为什么”用户使用你APP的。这就跟心理学有关了，你要能够根据用户的态度、索求、和其他心理标准来对他们进行分组。

不论你是否崇尚 “马斯洛需求层次理论”——该理论指出了驱使人类行为的五层关键需求，或者相不相信模板就是拿来打破创新的，但你要知道——从心理学层面来制定app市场营销策略一定能开个好头。

你的游戏对用户“真正”意味着什么？它能达成用户怎样的抱负？它能满足用户怎样的情感或欲望？试着提出尖锐的问题并认真地作答，说出你对自己用户的了解。

好了，既然现在我们对什么是消费心理有所了解，那么让我们来好后探索如何做才能好好利用他们吧。

数据结合

人口统计给出干巴巴的资料；消费心理让你了解用户在想什么。结合两种数据就能让你找到目标用户并刺激他们的消费。

如果你掌握你的UA状况和用户数据，那你就相当于已经知道自己游戏的目标玩家了。就拿《Covet Fashion》来举例子把，我们知道“妈妈们”是我们的主要群体用户，而我们也知道他们很多人正处在“30岁”的愤怒期。

构架好我们受众人口统计我们就可以对他们的深层渴求进行头脑风暴（寻求归属感、受人尊重、被人重视、变得出色、被认为与众不同）。同时我们还能因此完善我们的app来达成对用户渴求的兑现（呈现出一种全新风格的时尚娱乐，让用户能够在软件里用现实中的名牌服饰从头到脚打扮自己——包括Calvin Klein、Michael Kors、French Connection等等品牌。

设身处地为用户考虑问题

我们之前讨论的内容中是靠两种方法来把数据和用户相连接。

第一种方法是——我们对由我们的顶级玩家组成的焦点小组进行了一次面对面访谈，而且我们做了一个软件内调查问卷来研究用户是如何跟我们的软件进行交互的。这样我们就对玩家喜爱和讨厌的游戏经历有所了解了。

第二种方法——我们研究和观察在现实生活中的玩家“真人”——他们的家庭、朋友以及经常出入柏林格姆大道、旧金山地区的消费者（距离我们以时尚、高档时装精品店著称的总部办公楼很近）。

我们在这部分做的就是设身处地地为用户考虑问题、穿梭在大大小小的商场里观察时尚美丽的服饰物件都是如何进行展示和销售的——然后我们所观察的模式和趋势融合起来使用到我们的数码广告里。

我在这次广告领域的旅途里意识到——原来小细节的改变居然能在我们宣传中让用户转化率发生如此大的转变。要知道很多商店的橱窗里模特都是没有脸的，这让我懂了些什么。

我们软件的用户里还有很多妈妈、女儿、姐妹、阿姨、奶奶这类群体——这里包括了大量不同的人种和体型组合，不过它们都有个一致的目标——就是对美和时尚的追求。

在宣传创意里把模特的脸去掉干嘛不可能呢？这样的话我们的用户不就能想象出自己穿上这些衣服的样子了吗？我们的宣传要做的不是让用户有一种“这种风格不适合自己”或者让她们有“自己跟超模没得比”的感觉，我们是要让用户看到他们展现出自己真实之美的可能性。

勇于打破常规

一开始，我的这个除去模特脸部的主意让我的团队（成员大部分是女性）非常吃惊。毕竟，我已经不是管理UA的“新人”了；我抛出的是一个激进的新想法。

我们最终还是决定抹去模特的脸部，而这让我们的点击率和用户转化率突飞猛涨地多了10到20个百分点。

我们的无脸概念的成功给了我们自信在其他多个宣传上也沿用了这个概念。我们对用户消费心理的深度了解让我们找到了自己的方法——就是让我们的用户感到满意从而刺激他们下载行为。

多亏我们将手游数据分析与对用户心理的深度理解相平衡，我们不仅找到了激励用户激活使用我们app的助力，而且让他们会因为对我们有更多期待而选择留下。

本文由游戏邦编译，转载请注明来源，或咨询微信zhengjintiao

When it comes to mobile games and apps, we generally rely on the data we collect about our users and how they act and interact inside our apps to guide us in optimising and maximising our mobile ad campaigns and creatives.

But it’s *not* just about amassing Big Data, although data is certainly at the heart of effective user acquisition. It’s about creating a Big Picture view of your users by blending what you know about them in the digital world of mobile and apps with what you observe about them in the “real world”.

My career, which started in real estate, taught me the importance of careful observation – watching the gestures, listening to the intonation and piecing together the clues to determine client intent and “need state”.

Focusing on the “signals” in our conversations and interactions allowed me to tailor my response to each individual client – showing how well I understood them and proving how much I cared.

Fast-forward, and the same approach that helped me clinch major property deals provides the foundation for an incredibly successful UA strategy and results that earned me the title “Mobile Hero.”

During my time at CrowdStar, a maker of mobile and social gaming apps for women, I managed a multi-million dollar UA budget for a string of apps including Covet Fashion – an aspirational app for fashionistas and the shopping obsessed.

Our engagement metrics – a female-only audience that spends between 30 and 60 minutes a day in our apps – were off the charts thanks to campaigns that tapped emotions and triggered actions.

What’s more, our campaigns and videos consistently performed much higher than our benchmarks across our app category. Even across different ad networks and ad partners our mobile video ads consistently topped the charts, achieving CTRs and CVRs that were 10% to 25%+ higher than our competitors. This gave us an important edge.

We saw that network algorithms – no doubt due to our high performance and high relevancy among the target demographic – ended up picking our ad to be shown (even if we bid lower) over those of our competitors.

As a result, we were able to achieve lower overall CPIs and higher ROI for our campaigns. Drawing from this eye-opening experience I have identified simple steps you can follow to influence your users and achieve high performance for your game.

Move “beyond segmentation”

Demographic data (age, gender, household) allows you to segment your audience with a high degree of accuracy. It’s fine for understanding “who” your audience is – but it’s also the same data your competitors use to target their audiences. In other words, it’s not going to be the source of your competitive edge.

Our engagement metrics were off the charts thanks to campaigns that tapped emotions and triggered actions.
To move the needle on your campaigns, you need to go deeper and seek to understand “why” users interact with your app. This is where psychographics comes in, allowing you to group users according to their attitudes, aspirations and other psychological criteria.

Whether you’re a fan of Maslow’s Hierarchy of Needs, which identifies five vital human needs that move people to action, or believe the paradigm needs a revamp, framing your app marketing efforts through the lens of psychology is a good starting point.

What does your game *really* mean to the user? What aspiration does it allow them to fulfill? What emotion or desire does it satisfy? Ask tough questions and map your answers to what you know about your audience.

So now that we understand what psychographics are, let’s explore ways you can go about acquiring them.

Combine your data

Demographics will give you dry facts; psychographics will give you user insights. Combining the two in order to target your audience and trigger their actions.

If you’re on top of your UA, and your user data, you already know who your target audience is. In the case of Covet Fashion we knew that “mums” made up a significant share of our users, and we also knew that a large portion of that demographic was in the “30-something” rage.

Framing our audience demographics through the lens of psychology allowed us to brainstorm about their deepest desires (to belong, to be respected, to feel important, to stand out, to be regarded as special).

It also allowed us to improve on how our app delivered on that promise (presenting a whole new genre of fashion entertainment and allowing users to style their head-to-toe looks with actual brands – including Calvin Klein, Michael Kors, French Connection and more).

Take a walk in their shoes

During these sessions we relied on two major methods to help us make the connection in the data and with our users.

One, we conducted in-person interviews with focus groups made up of our top players, and we conducted in-app surveys to study how users interacted with our app. This gave us insight into what our players liked and disliked about the experience.

Two, we studied and observed *real* people in their real surroundings – family, friends and shoppers that frequented Burlingame Avenue, the San Francisco district close to our head office known for trendy, upscale fashion boutiques.

We ended up removing the faces from the creatives, and we watched as click-through and conversion rates skyrocketed.
As part of this research we took a walk in our users’ shoes, strolling through shops and malls to note how fashion and beauty items were displayed and sold – integrating these patterns, trends and observations into our own digital advertising.

It was during one of our field trips that I noticed a small detail that would make an incredibly huge difference in our campaign conversion rate. Many of the mannequins in the shop windows were faceless. Something clicked.

Our app audience is an also an audience of moms, daughters, sisters, aunts, grandmothers and everything in-between – a vast and diverse group of races and body types united by the singular desire to be a part of the fashion and beauty world.

Why not make this possible by removing the faces from the models in our campaign creatives? Wouldn’t this allow our audience to picture themselves in the clothes and looks they wanted?

Instead of reinforcing a feeling that they didn’t fit a specific look or were unable to be a “super-model”, our campaigns would show them what is possible and help them unlock their real beauty.

Challenge the norm

At first, my idea to strip the creatives of the gorgeous faces shocked my mostly female team. After all, I was not only the “new guy” managing UA; I was the guy pitching a radical new idea.

We ended up removing the faces from the creatives, and we watched as click-through and conversion rates skyrocketed. Improvement points were in the 10% to 20% range.

The success of our faceless concept gave us the confidence to roll out similar creatives across multiple campaigns. Our deeper understanding of audience psychographics allowed us to identify new approaches – all aimed at making our audience feel complete and moving them to action.

It’s all about balancing mobile data analysis with a deep understanding of user psychology to identify the triggers, nudges and levers you can activate to motivate your users to engage with your app – and keep them coming back for more.（source：gamasutra.com ）