2022年8月9日
By Damien读高级副总裁-数据产品
博客

编辑策展vs. 自动化:提高用户粘性的最成功方法是什么?

Which is better at driving content engagement in streaming apps: a row of content selected by editors or a row selected by algorithms? 这是个刁钻的问题. In our experience, the answer to driving engagement is not picking one or the other--it’s using both! You need editorial and data science working in harmony to select and arrange the content in a given row in the way that is most likely to appeal to an individual consumer.

尽管这种方法可能会成功，但要实现它，你可能会面临一场战斗. 数据科学团队在 24i has worked with a lot of streaming services on personalization and all of them seem to go on a version of the same journey. 编辑团队和数据科学团队开始互相憎恨. The editorial teams think there’s no way a recommendation engine can understand the nuances of how humans categorize content. Data teams believe humans can’t possibly choose a single selection of content that will appeal equally to all users of a streaming service. 他们都是对的.

There is--and always will be--an important role for content experts to curate VOD and live content libraries and present them in an attractive way for the unique audience of each streaming service. 编辑团队对即将播出的节目有很强的判断力. There’s also a strong commercial incentive to ensure masthead content is promoted in order to maximize the return on investment in rights. 如果他们对 权力的游戏在美国，有一种倾向认为每个观众都是如此. 但如果你把数据科学放在这些编辑决策之上呢?

让英雄旗帜更聪明地为你工作

让我们从顶部开始. 你的英雄横幅是每个应用中屏幕上最显眼的部分. It’s typically a carousel of key content you want to surface to users--for example that exclusive TV series or sports franchise you’ve invested so heavily in. 因此，让您的编辑团队选择在此位置显示的内容是有意义的. But it can make an enormous difference to engagement if you then let algorithms refine that selection dynamically for each individual user. Let the data define which five of your editorial team’s top 10 items should be promoted to a given user, 按照什么顺序.

例如, 如果一个特定的用户从来没有在你的服务上看过一个真人秀节目, the algorithm can make sure you don’t promote the latest singing talent show to them as the first item they see on login. 相反, someone that has watched related content in the past will likely be matched with the talent show promo straight away. 同样, 如果一个用户昨天看了你的旗舰新剧, the algorithm can ensure you’re promoting something else from the editorial list to them until the next episode drops in a few days’ time.

许多编辑团队还根据不同的日子，如“早晨”，改变英雄横幅,日间电视,“傍晚时分”,和“深夜。.“这已经被证明可以提高用户粘性, 但算法可以根据时间变化英雄横幅, 同时也基于那个家庭当时的典型收视模式. This is most obvious in family homes where kids' content dominates post-school and before that (hopefully) early bedtime. 然而, 如果观众或家庭没有孩子, 在这个时候推广《百家乐软件》将会失去粘性.

This winning combination of editorial and algorithmic positioning can and should be applied throughout your apps. 当我们采访BBC iPlayer前产品总监Dan Taylor-Watt时, he told us the BBC saw a 36% increase in “play completes” when they added personalization algorithms that adjusted the order of iPlayer’s “New and Trending” rail based on the user’s personal history.

编辑和数据——一个动态的组合

任何一行由人类填充的内容都可以通过微妙的方式进行优化, 每个用户的自动调整. 这里有一个例子. We performed A/B testing for one of our customers to demonstrate the value of personalizing curated rows. 其中一组游客参加了这项服务, 就在英雄旗帜下面, 按顺序进行个性化设置的一行内容. Further down the page they saw a row that had just been curated by humans and had no external intervention to determine the order.

在另一组测试中，这些行是相反的. 纯编排的行被放置在较高的位置，个性化的行被推到页面下方. The results showed a 50% higher rate of overall conversions (the number of content items played vs. the number of content items displayed) when the personalized row was displayed in the more prominent position.

了解你

那么，那些还没有时间建立浏览记录的新用户呢? 或者不需要用户登录的广告支持服务? 在这种情况下，算法能做什么?

The key for this cohort is to show them a wide range of content to increase the chances of them finding something they like. 一旦你的编辑选择了最能展示你的图书馆广度的“特色”内容, let the algorithms ensure that the order of content items in a row is switched each time a user logs in, 或者为每一个独特的页面浏览量. 精心挑选的内容将保持不变, 但回访时出现重复应用的风险较小. 你还可以增加用户发现新内容的机会.

全动态应用是未来趋势吗?

这种方法的逻辑扩展是纵向思考和横向思考. 正如可以使用数据来定义给定水平行内内容项的顺序一样, 它还可以用于优化页面上显示行的垂直顺序. If the data suggests an individual user loves comedy but has never shown any interest in costume drama, let your algorithms shift your entire row of stand-up shows towards the top of the page and drop the row of historical biopics down.

这种动态UI方法能走多远? 从理论上讲, 你可以有一个完全动态的页面，没有两个消费者看到相同的体验, 很像谷歌的搜索结果. You could move the “Trending” rail down if the data tells you that this particular user has never clicked on an item of content in that category before.

然而，到目前为止，我还没有看到很多流媒体服务兑现他们对动态UI的承诺. If the whole idea of a “Trending” rail is to help users find their next favorite bingeable series, 你要把它放在显眼的地方，以防万一. 作为人类，我们喜欢一些熟悉的东西. 如果你曾经重新启动过一个网站的UI，你就会知道用户可能非常, 他们对改变现状非常愤怒. Those same users will then be equally angry two or three years later when your next update comes around, 因为这又一次扰乱了他们对熟悉事物的渴望. So I wouldn’t advise that any streaming service dives straight-in to a fully dynamic page layout.

你从哪里开始这个策略?

如果你还没有尝试在你的服务中结合算法和编辑, 我建议首先对你的英雄横幅进行一些测试. 我保证你会对结果印象深刻.

This is the second in a series of 文章 for 流媒体 in which I’m breaking down five new and emerging personalization strategies that we’re seeing used to great effect by our customers and other leading streaming services. 你可以找到这里概述其他四种策略.

下个星期, I’ll be looking at how different data science techniques and messages can be used to achieve different results for your business. 如果你等不了那么久，你可以看看我们的电子指南: 现在，每个流媒体服务都应该采用五种提高参与度的策略.

[编者注:这是来自 24i. 流媒体接受供应商署名完全基于它们对我们读者的价值.]