新媒体怎样走向盈利?

Lorna注:广告其实也是一种有用的内容,如果将广告定向投放在需要它的人眼球里,对于这些人来说,非但不是视觉污染,反而成为媒体粘性的构成因素。

自打有了互联网,“盈利模式”这四个字就成为许多公司绕不过的一个坎儿。而这个问题,在传统经济中如果提出来简直就是个笑话。那么,为什么在互联网领域,每当出现一个新媒体形态,都要为“盈利模式”困扰,都要被拷问、质疑,而且大批大批的公司就死在这上面呢?

这还得从互联网媒体的基本特性说起,涉及到快速传播、海量用户与低边际成本三个关键词,这三个词足以颠覆一切传统的东西。比如说,A公司提供一种内容服务,卖100元,有100个用户;B公司发现如果把价格降到了10元钱,可以获得2000个用户;而C公司发现如果价格降到1元钱之后,用户量可以到达30000;这时候,D公司出现了,做为后进者他在价格上已降无可降,但他把视点放到了简单的买卖关系以外,他直接免费提供服务,但用户量冲到1000000,而在内容重加载了广告,这1000000的用户关注度每一个值0.1元。相比之下,D公司获取了最大价值的收益,此时,其它三家公司也意识到这一点,纷纷以免费来吸引用户,用户的眼球就成为了各方争夺的关键。

但是,企业的重点是通过广告盈利,内容本身只是载体,而在用户看的是内容,广告只不过是附属品,这就产生了矛盾。问题在于,而花样百出的所谓“盈利模式”,也就是为了想方设法地解决这个矛盾,这个矛盾有时候会非常激烈,互联网媒体希望通过广告获利,但广告多了,会影响用户兴趣,直接用投票将这家媒体拖向无人理睬的深渊。

在这个时候,就会出现一个怪圈,新兴互联网媒体当它没有生存压力之扰的时候,它会完全以内容为核心,注重新闻精神与媒体独立性,会迅速崛起;而一旦受到盈利需求和生存要求,以利润为核心,将内容与广告做嫁接时,也将迅速衰落。因为在互联网的世界里,资本的力量将驱动新的入场选手不顾一切地取悦用户、取代曾经的王者。

这个怪圈真的是不可突破的吗?显然——不是!因为在刚才的逻辑中有两个假设,一是假设内容的同质化;二是假设广告与内容是无关的。

首先来说,广告其实也是一种有用的内容,如果将广告定向投放在需要它的人眼球里,对于这些人来说,非但不是视觉污染,反而成为媒体粘性的构成因素;其次,在广告的形式上,粗暴、简陋的嵌入方式固然会招人讨厌,但细腻、有针对性的植入反而会给用户带来便利。所以,对于新媒体而言,挑战就转化为如何开发“差异化”的内容、如何设定更为便捷的广告形式上。同时,在这个时候就会有人发现,当“差异化”的产品做到一定的细腻度,“分众”到达一定颗粒度的时候,内容产品本身就可以直接获利。到底采用什么样的运营策略,就由这个企业自身的基因和特点所决定了。

我们再次回到刚才的假设:

A公司的长项在于强大的数据采集与分析能力,所以他们可以有针对性地在细分领域做付费深度内容;

B公司对产品市场有着很深的认识,所以他们通过做产品的电商入口赚了钱;

C公司长于新闻嗅觉与敏感度,他们以用户兴趣数据分析为基础,做针对不同读者群的定向投送,更容易找到了广告。

D公司擅长用户推广,所以他们做通用内容平台,利用移动互联网的机会,干脆走向了垂直内容整合app的方向。

……

都说现在新媒体赚钱越来越难了,难就难在中国的互联网已经渡过了信息缺乏、用户需求低的蛮荒阶段。你必须提供高于用户预期的产品才能得到认可,而且在激烈竞争环境下,这一强迫性提升的过程是持续不断的,稍有松懈就会被超出。但更重要的,还是找到你自己,看清你自己,做到你自己!懂得拓展,更要收敛野心。在强调“人人互动”的移动互联时代,面貌模糊的人最终不会得到喝彩。

Via 虎嗅网

论推荐之难

大家都知道让机器推荐好东西给活人──即「推荐算法」──不容易。但活人推荐好东西给活人同样很难。

最近 Daring Fireball 十周年,英文博客圈开始讨论 John Gruber 发明的「link blog」这一形式。说来简单,link blog 无非是每天选些自己看到的好文章,给条链接,加两句聪明话作为评语,然后在博客上分享出来。

难吗?非常难。

推荐的难度不在于「分享」这一环节,而在于如何知道什么是好东西。比如何知道什么是好东西更重要的是如何日复一日地挑选出好东西。Daring Fireball 做了十年。

以 link blog 而言,除了要有慧眼识别好文章外,还要通过「发链接」这个动作形成自己的一套叙述体系。Gruber 说他只会推荐自己从头到尾读完了的文章,而 Daring Fireball 的长期读者都了解他的体系:和免费软件相比,更倾向于推荐付费软件;和线上软件(web app)相比,更乐于使用原生软件;一把 Apple Extended Keyboard II 用了十多年;爱库布里克,爱 David Foster Wallace,爱美国。(他绝对不会把这些直白地写出来,那多傻。)

读久了,他对每日科技新闻的反应几乎都能猜到个八九不离十。于是你形成了预期,每次打开 Daring Fireball 时,预期都会得到满足。这是一种安全感。安全感是人们花四美元买杯星巴克咖啡眼都不眨,花一美元买个 app 却要思前想后的原因之一

知道什么是好东西的能力就是品味。有好的品味已经不易,还要日复一日地做同样的事情──相信我,那是枯燥的。即便做的是你热爱之事,也不令这枯燥减少一分。而一件事能否做成,很多时候就取决于你忍耐这枯燥的能力。

(中文博客圈里,link blog 做得最好的是「对牛乱弹琴」的洪波。已成绝响。)

作者:李如一

来源:Apple4us

Get your read-it-later on with Pocket’s new Mac app

Pocket for Mac is officially released, and makes viewing multimedia easier, faster, and more refined for those saving on the go.

From commuting to appointment waiting to leisure, people are always looking for different ways to kill time by reading, viewing, and saving things from the Web. Read-it-later apps like Instapaper and Readability have dominated the market, but Pocket — formerly Read It later — continues to push ahead and win over users with its simplicity. If you’re one for saving articles on top of multimedia, Pocket may be your best bet at a beautiful way to save webpages for later viewing, complete with a tagging system to help organize your links. Now that the app’s come to the Mac platform, you can sync your iOS or Android accounts so saved pages can be viewed on-the-go, or saved on your mobile device to be read back on your desktop.

Pocket for Mac is as intuitive an app as you can imagine when it comes to saving pages. To get started, simply copy the link of the webpage you’re trying to store, and click File > Save Item from Clipboard, or shortcut Command+S. Your list of saved pages displays on a vertical screen to the left of the Pocket window, with the content on the right when you select.

Neat additions to the Mac version of Pocket is definitely the one-key shortcut, such as A for Archive and F to Favorite. You can also tag each page so they’re easier to search the more you accumulate saved links. Videos also translate nicely onto Pocket, especially if you already have Flash installed on your Mac. The app allows you to view the video straight out of its interface, otherwise requesting that you download necessary plug-ins to play multimedia. I personally haven’t run into file type errors, as most publications will post videos from YouTube or Vimeo anyway, and those seem to work just fine.

If you want to share a link after already viewing the content, the Item > Share button also does a good job of sending the item out to Twitter, Facebook, Evernote, and Buffer. It’s even got a tweet attribution when you send it from Pocket, which is a small but useful touch.

Overall, Pocket does a good job recognizing pictures in an article, article link, headline, byline, and publication. One function I wish was available is the ability to rename files, such as a photo I saved from a blog that didn’t have a get an assigned name, according to Pocket. Between constantly traveling and attempting to save things to read later, Pocket makes a nice alternative for those who enjoy minimal design with multimedia capability, and the willingness to learn some cool shortcuts and make saving for later quick and painless. Pocket for Mac is available now for free via the App Store.

Via Digital Trends

Flurry最新报告:“新闻传播类应用忠诚度高,个性化应用客户易流失”,决定不同商业模式

著名的移动分析公司Flurry今天更新了他们《移动app:钱,模式和忠诚度》报告。这份报告在3年前推出以来,一直专注于iPhone、iPad上70万个应用的运营。

和之前的报告一样,Flurry根据用户的使用频率以及用户在一段时间后的应用保留率,在图中对不同类型应用进行标示。图表中,横轴表示90天后应用的保留率,数轴表示用户每周的使用频率。

其中涉及的样本中应用在每周被使用的次数为17亿次。Flurry能拥有大数量级别的应用数据是因为目前已有超过8万家公司针对23万个已发布应用,使用Flurry Analytics。应用类型大致根据苹果App Store的标准进行划分,并针对一些分类进行子分类划分,如“社交游戏”和“单人游戏”在这里是分开的两个游戏子分类。

这项结果可被分成四个象限:

象限I:应用被经常使用同时用户也随着时间推移保留着高的忠诚度。新闻和传播类app属于这一范畴,而根据Flurry,它们有稳定的增长的受众,而最好的定位就是生成广告收入或做订阅。消费者认为这些应用是具有持久价值的。

象限II:应用被经常使用,但一段时间后就被丢弃。它们传递的是突发价值,应用类别包括流媒体音乐,约会及社交游戏应用。比如就约会应用而言,一旦人们通过约会应用确立恋人关系,约会应用就不会再被用户需要了。

象限III:应用不常被使用同时还容易流失。个性化应用属于这一范畴(比如要换个背景或主页面墙纸的时候使用一个个性化应用,用完就删)。一旦安装完成,它们就很少会被使用。所以在Flurry看来,这类应用应该有一个定价模型在用户访问内容之前收取一定费用。

象限IV:应用不常被使用,但一旦使用就能给予高的价值。这些app可能会无限期地留在用户的手机内。比如航空、酒店预订及租车服务app不会持续地被使用,但当用户在旅行过程中它们的价值就会上升。

而这些象限中还有一些其他的app类别,而效率和商业类别的应用则在象限III和象限IV间的边界上。

通过看应用所在的象限,开发者可以在决定自己的商业模式上有所帮助。Flurry的建议是:象限I 和象限IV适合订阅和广告支持模式,而象限II和象限III则更适用于一次性的下载费用。同时,象限II和象限IV(左上及右下部分)适合做应用内购买模型。在象限II中,开发者可以为用户提供额外的内容和功能。而对于象限IV的应用来说,可以通过用户再次访问时呈现新的内容或功能让用户回心转意。

09年的报告对比,Flurry的新数据表明,应用90天后的保留率整体从之前的25%上升到了35%,而用户的使用频率则从6.7狂跌到3.7。Flurry认为保留率更高可能与app质量上升有关,而使用频率的下降则因为目前有大量可供选择的应用,导致用户把时间分散在越来越多的应用上。09年的报告只有19个类别,而现在,有超过30个类别进行比较,下面是具体每个类别在用户保留率和使用频率上的数据:

Via TC/36氪

App Engagement: The Matrix Reloaded

Regardless of a company’s earlier success, thriving in the new mobile app economy depends on engagement and retention. After acquiring users, the real battle to keep and ultimately monetize consumers begins.  In the brave new world of “mobile first,” engagement is the new battleground.

This research is a redux to one of Flurry’s most popular reports, entitled Mobile Apps: Money, Models and Loyalty. Released three years ago, the initial report organized app category usage into a loyalty matrix. We do the same again now, while also acknowledging that a lot has changed in the app economy since then. To start, there is an order of magnitude more available apps in the App Store, now brimming with over 700,000 app choices for consumers. We are three generations beyond the then-new iPhone 3GS. We have since met the iPad, and perhaps tomorrow will meet the iPad Mini.

Combined, smart devices – iOS and Android smartphones and tablets – are the fastest adopted technology in history; adopted faster than electricity, televisions, microwaves, personal computers, cell phones, the Internet, dishwashers, stoves, and a whole lot more. Last month, Mark Zuckerberg, CEO of Facebook – the number two most visited website on the web – declared “we are now a mobile company” explaining that “you just could do so much better by doing native [application] work” versus using languages like HTML5 on top of browsers.  Each month, approximately 600 million of Facebook’s 1 billion monthly active users already accesses Facebook via mobile.

Know Thyself

Each app category has different user engagement and loyalty characteristics. Understanding a given app audience based on the category to which it belongs can inform a company’s app acquisition, retention and monetization strategies. For this analysis, we use a sample of apps used more than 1.7 billion times each week. In total, more than 80,000 companies use Flurry Analytics across more than 230,000 apps to understand consumer behavior and improve their apps.

QuadrantChart EngagementRetentionStats ByCategory resized 600

The above matrix plots application categories by how often they’re used compared to how long consumers continue to use them over time.  Specifically, we plot the 90-day retention rate of app categories on the x-axis against the frequency of use per week on the y-axis. We lay the “scatterplot” out in a Cartesian coordinate system with four quadrants. For our categories, we started by taking the application categories defined by Apple in the App Store. In cases where a cluster of applications within a parent category showed meaningful usage differences, we created a sub-category. For example, Flurry divides games into Social Games and Single Player Games given how differently consumers use these sub-categories.

Quadrant I includes apps that are used intensively and to which consumers are loyal over time. News and Communication apps are the two categories that appear in this category. On average, because these apps tend to have stable, growing audiences, they are best positioned to generate advertising revenue or charge a subscription. Consumers perceive these apps to deliver enduring value over time.

Quadrant II is comprised of apps that are used intensively, but for finite periods of time. They are perceived by consumers to deliver value in bursts. Streaming MusicDating and Social Games best typify this quadrant. Consider for a moment why Dating is a category that appears in this quadrant. For most people, we can assume that finding a long-term “significant other” is the ultimate goal of dating. As a result, the app maker should expect customer churn. While usage may be high during the time when a consumer looks for a suitable partner, once that person is found, usage stops. An implication could be that to maintain a growing audience, apps in this category require heavy, constant acquisition to find consumers who are “in the market” for dating. Ironically, the better the app is at match making, the more churn it should expect.

Quadrant III contains apps that are used infrequently and have high churn. They contain the most “one-and-dones.” Personalization is an example that makes sense for this quadrant, since a consumer uses this app to change her screen saver or select a theme for her operating system. Once this set-up is complete, it’s unlikely that the user will need to re-use this application. Since the app’s value is diminished almost immediately, applications with this kind of usage pattern are best served with premium pricing models; that is, charging the consumer before providing access to the content.

Quadrant IV is made up of apps that are used infrequently but deliver very high value when used. Even though they’re used only occasionally, these apps can remain on a consumer’s handset almost indefinitely. For example, consider how useful an airline, hotel or rental car-booking app is to a business traveler. While the app remains unused between business trips, its value spikes as soon as the next business trip needs to be scheduled.

Which Pill to Take

The quadrant an app falls into can help the content creator decide what business model is best. On average, Quadrants I and IV (the right-hand side) are better suited to subscription and advertising-supported models. The main reason is that these apps have perceived enduring value by consumers over a long period of time, and therefore more successfully retain their user bases. For ad-supported apps, high repeat usage translates into more ad impressions served. Categories on the left-hand side, Quadrants II and III, are better suited for one-time download fees. Additionally, quadrants II and IV (top left and bottom right) are likely best for in-app purchase models. For Quadrant II, the intense usage means that consumers find very high value during a short window. This creates the opportunity to offer new content or functionality during “binge” usage. Adroit social game makers are masters at driving in-app purchases during a consumer’s greatest moment of engagement. For Quadrant IV, because the user will return again and again, there also exists the possibility to find new ways of increasing value, which includes offering add-on functionality or content for a fee.

For more data, the table below provides 30, 60 and 90-day retention rates as well as weekly frequency of use numbers.  Note that some of the categories included in the table below are not included in the matrix chart above.

Table EngagementRetentionStats ByCategory resized 600

Compared to Flurry’s 2009 analysis, 90-day retention rates have increased from 25% to 35%. Additionally, frequency of use has decreased from 6.7 in 2009 to an average of 3.7 now. We attribute increased retention rates to increased quality in the market, driven by more competition. With tens of thousands of more companies building apps and hundreds of thousands of more available apps, the quality of apps has risen dramatically. Simply put, app makers are getting better at holding a consumer’s attention longer. Additionally, we believe usage rates are lower because consumers have more choice than ever and are splitting their time across more applications. While Flurry included 19 categories in its 2009 report, we now include 30 distinct categories as the industry has matured and more distinct verticals have appeared.

Brave New World

With more than a billion smartphones and tablets now in use, as well as the eventual move of apps into the living room through connected TV efforts by the likes of Apple and Google, digital distribution is changing the way the world does business. No matter what category your app belongs, understanding and improving user engagement is the new currency of doing business in the new digital world.

by Peter Farago

Via Flurry

Distimo推出竞争App跟踪服务AppIQ,可监控App下载、收入、排名等

Distimo推出竞争App跟踪服务AppIQ

要说最了解全球市场的各个App Store生态系统的,可能非荷兰应用商店分析机构Distimo莫属了。Distimo经常会发布全球市场上各大平台应用商店的应用生态系统分析报告,对定位在全球市场的应用开发者来说很有价值。

今天,Distimo推出了一款新的应用数据分析服务:AppIQ。这是一款可以跟踪分析多个竞争应用在全球市场各大商店里的下载量、收入(包括应用内收入)和排名的工具。同时,Distimo 还推出了一款可以显示各大平台或应用商店应用排名和趋势的监控平台Distimo Leaderboard。

使用AppIQ,你可以追踪每个竞争App的各种动态指标,包括各个平台和国家的表现、哪些进行了限免或促销、最终效果怎样、不同平台和国家的特点、哪些App开始爆发、哪些App是可以借鉴的哪些又是可以避免的。通过对竞争对手的跟踪,开发者能够清楚的了解自己在市场竞争中的位置、竞争对手的特点、各个国家的市场环境和用户情况,并根据这些深入的分析,来调整自己的开发策略、商业模式和推广战略,以求在市场中获得更有利的地位和潜在用户。

由于Distimo本身为全球开发者提供免费监控自家App的服务,所以数据的准确度非常高。以iOS应用为例,在Distimo上54%的应用数据误差在3%以下,95%的应用误差在10%以下。AppIQ普通账号最多可监控50个竞争App,多达10个国家。如果使用企业版,跟踪的App数和国家还会更多。

Distimo联合创始人兼CEO Vincent Hoogsteder说:“我们的目标,就是为开发者在全球范围的碎片化应用市场上提供独立、可靠的洞察力和预见性。虽然提供App监控服务的公司有很多,但监控竞争对手App的公司目前还仅此一家。”

AppIQ 能够监控的App目前还只支持iOS 和Android 商店,但覆盖范围多达40个国家。Distimo Leaderboard 则支持Amazon App Store、苹果App Store、苹果Mac App Store、黑莓App World、Google Play、诺基亚Ovi Store、三星Apps、WP7市场,几乎涵盖了Distimo 所能支持的所有应用商店。

Via TNW&TC