"The Adjacent Users are aware of a product and possibly tried using it, but are not able to successfully become an engaged user."
邻接用户:已经听说过、可能试过,但就是没法变成活跃用户的那群人。
邻接用户:已经站在边缘但跨不过去的那群人
"The Adjacent Users are aware of a product and possibly tried using it, but are not able to successfully become an engaged user."
"This is typically because the current product positioning or experience has too many barriers to adoption for them."
他们不是新市场,而是 PMF 边缘、被产品门槛挡在外面的人——离成功只差临门一脚。
PMF 之上还有一条理论留存曲线 · 那才是真正的潜力
"Your current retention doesn't represent the true potential of your current product-market fit. There is a hypothetical retention curve that sits above that represents this true potential."
"What creates this gap? There are a set of users who show intent for your product but are not quite able to get over the hump."
实际留存曲线 vs 理论留存曲线之间那条缝,就是邻接用户没接住造成的——邻接工作就是把这条缝填上。
复利效应 · 接住一批 = 影响所有未来同期群
"It not only changes the engagement of near term cohorts but flows through to creating impact for all future cohorts of users."
"Every year there are massive efforts to getting voters to register and get to the polls. Those voters not only impact the outcome of one election, but can change the engagement of future elections and generations of politics."
类比"选民登记"——今天接住的邻接用户会通过裂变 / 留存 / 商业化三个回路,持续影响后面好几代同期群。
PM 都是自己产品的重度用户 · 这是引力
"Product teams by nature are power users of their own product. The parts of the product that the product team uses, tend to automatically get improved as the pain is right in front of them."
"While that can feed the ego, if you are only building for yourself or power users, you won't grow."
为自己造产品很容易,但你和团队的痛点只代表 power user。要看见邻接用户,必须主动跨越一个认知阈值。
Cohort Decay · 邻接用户已经在涌入的最早信号
"When you look at these variables on a cohorted basis, you will almost always see a decline from cohort to cohort over time."
Elena: "When you start investing into new channels (especially paid) it is typically a signal to the product org that adjacent users are coming."
不要等用户研究——free-to-paid / signup-to-activated 这些指标在同期群之间逐月下滑,本身就是新一批邻接用户已经进来的早期信号。
不追求完美能见度 · 雪球滚起来再说
"The goal of defining your adjacent users is to get visibility, but not perfect visibility... I like to think about it as a snowball."
"If you seek out understanding perfect visibility you will never get started."
先列假设、挑一个聚焦、用实验验证、再迭代——像滚雪球,初始信息少,在过程里越滚越大。
每次邻接迭代 · 只动 1-2 个用户属性
"If your adjacent user definition is different on all 5 of those vectors, or even the majority, choosing that segment is a bad choice. That is like trying to hit a home run on every swing."
Elena: "It's not an 'if' you should be going after them, it's a question of 'when.'"
动 1-2 个属性是邻接,动一半以上就是另起炉灶。Elena:大跨度迁移不是要不要做,是什么时候做——但绝不是现在。
解屋里人优先 · 已经在漏斗里挣扎的最值钱
"It is typically better to solve 'in-house' problems first. These are users that are already showing up in your funnel and product vs brand new users who aren't there yet."
"Those that are already showing up are displaying intent, but having trouble finishing. Solving for them typically creates more short term impact."
人都进了漏斗就是最强的需求信号。Elena 的 B2B 三步法:先挖存量商业化 → 再解锁间接价值(裂变 / 贡献)→ 最后才是全新邻接。
长期看 · 小而快胜过大而停
"Often times one segment might be larger but not growing, while another could be smaller but have a much larger growth trajectory."
Fareed: "But users in France weren't growing... India was growing way faster and had a clear hypothesis as to why they weren't paying."
Slack 国际化时选了印度而不是法国——印度规模小但增速快、商业化假设清晰,长期 ROI 更高。
每个实验结果都要追问"为什么" · 答案藏着下一个邻接用户
"Too often teams move on from the positive/negative result of an experiment without understanding why the experiment generated that result."
"The why helps you understand the next adjacent user. If you don't do this you can miss incredibly important shifts in user mindsets as you move from adjacent segment to segment."
不追问 why,就会错过用户心智正在发生的迁移信号——而这些信号正是下一批邻接用户的入口。
When I joined Instagram in 2016, the product had over 400 million users, but the growth rate had slowed.
2016 年我加入 Instagram 时,产品已经有超过 4 亿用户,但增长开始放缓。
We were growing linearly, not exponentially.
我们在线性增长,不是指数增长。
For many products that would be viewed as an amazing success, but for a viral social product like Instagram, linear growth doesn't cut it.
对很多产品来说这已经是惊艳的成绩了,但对 Instagram 这种靠裂变驱动的社交产品,线性增长根本不够。
My job was to help the team accelerate and get back to exponential growth.
我的任务是帮团队重新加速,回到指数增长曲线上。
Over the next 3 years, the growth team and I discovered why Instagram had slowed, developed a methodology to diagnose our issues, and solved a series of problems that reignited growth and helped us get to over a billion users by the time I left.
接下来三年,我和增长团队搞清楚了 Instagram 为什么慢下来,沉淀出一套诊断问题的方法论,然后一个一个解掉了那些卡住增长的问题——到我离开时,Instagram 已经突破了 10 亿用户。
Our success was anchored on what I now call The Adjacent User Theory.
这套方法的核心,就是我现在说的"邻接用户理论"(The Adjacent User Theory)。
The Adjacent Users are aware of a product and possibly tried using the it, but are not able to successfully become an engaged user.
邻接用户是这样一群人:他们知道这个产品、可能也试用过,但就是没法成功变成一个真正用起来的活跃用户。
This is typically because the current product positioning or experience has too many barriers to adoption for them.
原因通常是:产品当下的定位或体验,对他们而言门槛太多,迈不进来。
While Instagram had product-market fit for 400+ million people, we discovered new groups of users who didn't quite understand Instagram and how it fit into their lives.
Instagram 对那 4 亿多人确实有 PMF,但我们发现还有一批批新用户,他们没真正搞懂 Instagram 是什么、Instagram 在他们生活里能扮演什么角色。
Our insight was that it is critical for growth teams to be continually defining who the adjacent user is, to understand why they are struggling, to build empathy for the adjacent user, and ultimately to solve their problems.
关键洞察是:增长团队必须持续定义"邻接用户是谁",理解他们为什么在挣扎,对他们建立共情,最终解决他们的问题——这件事必须不停做。
And Adjacent User Theory doesn't just apply to hyper-growth machines like Instagram, I've seen the dynamic play out again and again at plenty of other product-driven companies.
而且邻接用户理论不只适用于 Instagram 这种超级增长机器——在其他很多产品驱动型公司里,我反复看到同样的剧本。
Solving for the Adjacent user is critical for a few reasons.
解决邻接用户至关重要,有几个原因。
When you have Product-Market Fit, you have healthy retention curves (they flatten out).
当你拿到 PMF 的时候,你会有一条健康的留存曲线——它会变平稳。
But this isn't the end goal.
但这不是终点。
Your current retention doesn't represent the true potential of your current product-market fit. There is a hypothetical retention curve that sits above that represents this true potential.
你眼下看到的留存曲线,并不代表当前 PMF 的真正潜力。在它上方,还有一条假想的、理论上的留存曲线——那才是真正的潜力线。
What creates this gap?
什么造成了这条缝?
There are a set of users who show intent for your product but are not quite able to get over the hump.
是这样一群人:他们对你的产品表现出了意图,但就是过不了那道坎。
Those are your Adjacent Users.
他们就是你的邻接用户。
Solving for the Adjacent User through growth and scaling work helps your product realize its true product-market fit potential.
通过增长和规模化的工作把邻接用户接住,产品才能兑现它真正的 PMF 潜力。
Every year there are massive efforts to getting voters to register and get to the polls.
每年都有大量精力被投入到选民登记、把人拉去投票站这件事上。
Those voters not only impact the outcome of one election, but can change the engagement of future elections and generations of politics.
这些选民不只是影响那一届选举的结果——他们会改变此后许多届选举的参与度,甚至改变好几代人的政治面貌。
In a similar way, when you enable adjacent users to successfully experience the core value proposition, it not only changes the engagement of near term cohorts but flows through to creating impact for all future cohorts of users.
邻接用户也是同样的道理:当你让他们成功体验到产品的核心价值,影响的不止是当下这批同期群,还会顺着流到所有未来的同期群里去。
This doesn't just impact retention, but flows through your growth loops to impact acquisition and monetization as well.
这种影响不仅仅作用于留存,会顺着你的增长回路一路流过去,继续作用在获客和商业化上。
Most product teams know their existing users pretty well.
大多数产品团队对现有用户都很熟。
But your future audience is always evolving.
但你未来的受众一直在变。
The challenges that these potential users face in adopting the product increase over time.
这些潜在用户在使用产品时遇到的挑战,只会随时间推移变得越来越多。
Without a team dedicated to understanding, advocating, and building for your next set of users, you end up never expanding your audience.
如果没有专门的团队去理解、代言、并为下一批用户构建产品,你的受众就永远扩不出去。
This stalls growth, and the product never reaches the level you aspire it to.
于是增长停滞,产品永远到不了你心里那个高度。
You can think about your product as a series of circles.
你可以把产品想成一组同心圆。
Each of these circles is defined by the primary user states that someone could be in. For example Power, Core, Casual, Signed Up, Visitor.
每一圈代表一种主要的用户状态——比如 Power(重度)、Core(核心)、Casual(轻度)、Signed Up(已注册)、Visitor(访客)。
Each one of these circles have users that are "in orbit" around it.
每一圈的边缘都有一群用户在"绕轨道运行"。
These users have an equal or greater chance they drift off into space rather than crossing the threshold to the next state.
他们要么飘走、要么跨过门槛进入下一个状态——飘走的概率不比跨过去低。
There is something preventing them from getting over the hump and transitioning into the next state.
总有什么东西卡在他们和下一个状态之间。
These are your adjacent users and the goal is to identify who they are and understand their reasons struggling to adopt.
这些就是你的邻接用户。你的目标是识别他们是谁、理解他们为什么用不起来。
As you solve for them, you push the edge of the circle out to capture more of that audience and grow.
当你把他们的问题解决掉,你就把这一圈的边界往外推,接住了更多受众,产品才能继续增长。
Lets go through a couple of examples, starting with Instagram. The primary thresholds that a user has to cross to becoming a core user:
先来看几个例子,从 Instagram 开始。一个用户要变成核心用户,必须跨过的主要门槛包括:
At each one of these thresholds, there are users that are circling around them, that have an equal or greater chance of not crossing the threshold.
每一道门槛的两侧,都有一群正在打转的用户——跨过去的概率,并不比飘走更高。
"At Instagram, if a user had more than 10 followers in the first 7 days after signing up there was over a 65% chance that the user would become activated."
"在 Instagram,一个新用户如果在注册后的头 7 天里凑齐 10 个以上的关注,他变成激活用户的概率会超过 65%。"
"There was always a group of users on that margin that would struggle to build their audience. But the reasons they struggled varied across different sets of user and changed over time."
"总有一群用户卡在这条线两侧,在'怎么建立自己的受众'这件事上挣扎。挣扎的原因因人群而异,而且随时间还在变。"
Lets go through an example for Slack. The primary thresholds that user has to cross through are:
再看 Slack。一个用户要走完整个旅程,需要跨过的主要门槛是:
At each one of these thresholds, there are users that are circling around them, that once again have an equal or greater chance of just drifting off into space.
每一道门槛上,同样有一群打转的用户,飘走的概率一点不比跨过去低。
"At Slack, we found that if a user was active 3 days out of the last 7 (3d7), they were right on the edge and had a roughly 50/50 chance of churning or retaining the next week."
"在 Slack,我们发现如果一个用户最近 7 天里活跃了 3 天(3d7),他就正好卡在那条边上——下周留存还是流失,几乎是五五开。"
There are a few things that tend to lead teams away from focusing on the adjacent user:
有几件事会让团队偏离邻接用户的视角:
Product teams by nature are power users of their own product.
产品团队本质上就是自己产品的重度用户。
The parts of the product that the product team uses, tend to automatically get improved as the pain is right in front of them.
团队自己用的那些功能,几乎是会自动被优化——因为痛点就摆在他们眼前。
But this leads to building for yourself (or your friends).
但这就导致你最后在为自己造产品(顶多再加上你朋友)。
While that can feed the ego, if you are only building for yourself or power users, you won't grow.
这虽然能满足虚荣心,但如果你只为自己或重度用户造产品,你不会增长。
You need to constantly be building for that next user that doesn't have the same level of knowledge, intent, or needs that you, your team, and your power users already have.
你必须不停地为"下一个用户"造产品——他们没有你、你的团队、你的重度用户已经具备的那种认知水平、意图强度、或需求紧迫度。
Working on the adjacent user requires you to cross a cognitive threshold.
为邻接用户工作,要求你跨越一个认知阈值。
You have to specifically seek out the definition to "see" them and understand their experience, which is likely to be dramatically different from what you see as an employee.
你必须刻意去寻找邻接用户的定义,才能"看见"他们、理解他们的体验——而这种体验,跟你作为员工每天看到的可能天差地别。
Once you see them, you can build empathy for them and their struggles, which in turn informs what you build.
一旦看见,你才能对他们的挣扎建立共情,然后这种共情才会反过来指导你做什么、不做什么。
"At Uber, a lot of employees were power users of the Uber product. This led to a lot of voices thinking they knew what we needed to grow just because they used the product a lot. But these were rarely the things that pushed growth of Uber into new audiences."
"在 Uber,很多员工都是 Uber 的重度用户。这导致很多人因为自己用得多,就以为知道怎么让 Uber 增长。但他们提的那些建议,几乎从来都不是真正能把 Uber 推向新受众的东西。"
When trying to answer the question of who they are trying to solve for, product teams often use their stated personas as the answer. But personas, as they are typically defined, have one or more of the following issues:
当被问"你在为谁解决问题"时,产品团队常常拿出自己已有的 persona 当答案。但按常规方式定义出来的 persona,通常有下面这些问题中的一个或几个:
Product teams overvalue hitting home runs vs hitting 100 singles back to back.
产品团队过分推崇"打出全垒打",而低估了"连续敲出 100 支安打"的价值。
This leads them to take bigger swings by going after bigger markets of new users.
这导致他们去挥更大的棒——直接扑向规模更大的新用户市场。
They get bogged down by trying to establish product-market fit for a new set of users and never fulfill the potential of their current product-market fit.
结果他们陷在"为一群全新用户建立 PMF"的泥沼里,反而永远兑现不了当前 PMF 的潜力。
Remember, adjacent users are the users who are struggling to adopt your product today.
记住:邻接用户是今天就已经在挣扎、在尝试用你产品的人。
Non-adjacent users could literally be everyone else in the entire world.
非邻接用户,字面意义上可以是世界上其他所有人。
Sure, non-adjacent users might be a larger market, but the barriers to their adoption are also dramatically higher.
没错,他们的市场盘子可能更大,但他们采纳产品的门槛也指数级地更高。
Companies that try to go too big too soon and often, skip the next obvious steps and fail to solve their current adoption problems.
那些动不动就想跨大步的公司,常常跳过显而易见的下一个台阶,结果连当下的采纳问题都解决不了。
Solving for the adjacent user is often seen as "optimization", which in some organizations is viewed poorly because they represent short-term thinking.
为邻接用户工作,常常被贴上"优化"的标签——在某些组织里"优化"是个贬义词,代表短期思维。
Solving for your adjacent user is not short term thinking; it is this disciplined sequential execution that will enable your longer-term roadmap and faster growth.
但解决邻接用户根本不是短期思维。它是有纪律的连续执行,正是这种执行在支撑你长期的路线图和更快的增长。
It is short turns on a longer term path, not short term.
它是长路上的小转弯,不是短期主义。
Until you recognize that they are adjacent users and commit to helping them, they will remain adjacent. They aren't going to get there on their own.
在你意识到他们是邻接用户、并下定决心去帮他们之前,他们就会一直停留在邻接状态——不会自己走完那段路。
You have to be passionate about them and learn to view the product from their eyes.
你必须对他们投入热情,学会用他们的眼睛看产品。
If you don't focus on them, growth slows and your cohorts decay.
如果你不关注他们,增长就会放缓,你的同期群就会衰减。
At a high enough volume of users, you will start to see the effect of the adjacent user show up in your cohorts.
用户量到一定规模后,邻接用户带来的影响会在同期群指标上显形。
Sitting at the edge of each user state is a quantitative metric that indicates conversion from one state to the next.
每个用户状态的边缘,都对应一个定量指标,代表从这个状态进入下一状态的转化。
For example, free to paid conversion or signed up to activated.
比如 free-to-paid 转化率,或者 signed-up-to-activated 转化率。
When you look at these variables on a cohorted basis, you will almost always see a decline from cohort to cohort over time.
如果你按同期群去看这些指标,几乎一定会看到——从一群到下一群,数据在持续下滑。
This is because there is some segment of adjacent users that are entering that state and struggling to convert to the next.
这背后就是:有一群新的邻接用户进入了这个状态,但卡在下一个状态外面,转化不了。
"When you start investing into new channels (especially paid) it is typically a signal to the product org that adjacent users are coming."
"当你开始投入新渠道(尤其是付费渠道),这本身就是一个给产品组织的信号:邻接用户要来了。"
"New channels bring in users that will be different on some vector. Lower intent, less solution aware, less brand aware, pain point not completely formulated, or something else."
"新渠道带来的用户,在某些维度上一定跟老用户不一样——可能意图更弱、对解决方案的认知更低、对品牌的熟悉度更低、对自己的痛点都还没想清楚。"
"A common thing I see across freemium SaaS companies I advise, is free to paid conversion decline from cohort to cohort. This is your signal that there are a set of adjacent users on the edge of this state that you need to start solving for."
"我顾问的那些 freemium SaaS 公司里有一个共同现象:free-to-paid 转化率会一群一群往下走。这就是信号——告诉你这条边上有一批邻接用户,你得开始为他们解题了。"
What Fareed's story is pointing out is that at the edge of Core Free → Paying User, the metric that monitors that edge is free to paid conversion.
Fareed 这个故事指出的是:在"免费核心 → 付费用户"这条边上,监测这条边的指标就是 free-to-paid 转化率。
Over time, if you look at that metric on a cohorted basis, you will start to see the metric go down from cohort to cohort.
时间一长,如果你按同期群去看,这个指标就会一群一群地下行。
This can happen at the edge of any user state (signup to activated, activated to core, etc).
同样的现象会出现在任何一条用户状态的边上——signup-to-activated、activated-to-core,都会。
The first step to seeing the product through the eyes of the Adjacent User is to build a hypothesis of who they are and why they are struggling. How do we do that?
用邻接用户的眼睛看产品,第一步是建立一个假设:他们是谁、他们为什么在挣扎。怎么做?
The goal of defining your adjacent users is to get visibility, but not perfect visibility.
定义邻接用户的目标是拿到能见度,而不是完美的能见度。
You need to define the landscape in front of you to understand all your options and figure out which type of adjacent user to focus on.
你要做的是把面前这片版图描摹出来——看清你有哪些选项,然后挑一类邻接用户去聚焦。
Knowing just one adjacent user segment isn't enough because you often have several to choose from.
只知道一个邻接段是不够的,因为通常摆在你面前的有好几个。
But there are equal problems trying to get perfect visibility. You will never have perfect visibility and perfect definitions.
但反过来,追求完美能见度同样会出问题——你永远不会有完美的能见度和完美的定义。
If you seek out understanding perfect visibility you will never get started.
如果你非要先看穿全貌再动手,你永远开不了头。
The process is to lay out multiple hypotheses of who the adjacent users are, choose which one to focus on strategically, force your team to look at the product through their lens, experiment and talk to customers to validate and learn, then update the landscape to make your next choice.
流程是这样:摆出关于"邻接用户是谁"的多个假设,从战略角度挑一个聚焦,强迫团队用他们的视角看产品,做实验、跟用户对话、验证、学习,然后更新这张版图,做下一次选择。
I like to think about it as a snowball. You know very little at first, but as the snowball turns you collect more information about the adjacent user, which helps you collect more snow (users).
我喜欢把它想成滚雪球。一开始你知道得很少,但雪球滚动的过程中,你会收集到更多关于邻接用户的信息,这些信息又帮你滚到更多雪(用户)。
To understand your adjacent users, it is helpful to understand the attributes of who is successful today and why they are successful.
想理解你的邻接用户,先去搞清楚——今天用得好的那批人有什么属性,他们为什么成功。
The reason this is helpful is that your adjacent user is different on one or more of these attributes (but not all).
为什么这么做有用?因为你的邻接用户,正是在这些属性里的某一两个上跟现有用户不同(而不是全部不同)。
These attributes create vectors of expansion. Lets go through an example.
每一个属性都能构成一条扩张的向量。我们看个例子。
At Instacart, we knew that over 75% of our core, healthy users were:
在 Instacart,我们知道 75% 以上的核心健康用户是:
Some of these things we knew from data. Some of these thing we knew from customer conversations. Some of them we knew by inference.
这些有的来自数据,有的来自跟用户的对话,有的来自推断。
Each one of these attributes creates vectors of expansion:
每一个属性都对应一条扩张向量:
The more granular you can get, typically the better.
通常切得越细越好。
But there are a set of common categories for attributes. Which categories are relevant and most impactful depend on the product:
不过有一些常用的属性维度,具体哪几个维度跟你产品最相关、最有影响,看产品本身:
Once you have hypotheses for who is successful and why they are successful, you can hypothesize possible adjacent users segments.
一旦你对"谁在成功 + 为什么成功"有了假设,就能开始假设可能的邻接用户段。
This will involve changing one or more of the vectors that you identified.
这就涉及到把你识别出的那些向量中的一个或几个换掉。
I typically recommend starting with a bottoms-up analysis of your data.
我通常建议从自下而上的数据分析起步。
You do not need to spend weeks talking to users to get a sense for who your adjacent user is.
你不需要花几周跟用户聊天,才能对邻接用户有感觉。
Look at what is happening on the edges of these states in the data.
先去数据里看一下:每个状态的边缘到底发生了什么。
The data will help you identify places in the product that people are dropping off.
数据会帮你定位产品里人们掉队的具体位置。
This is the starting point to help you develop hypotheses about why different segments of users are dropping off.
这就是起点——从这里出发,你才能针对"为什么不同人群在掉队"建立假设。
When you have an early hypothesis of who the adjacent user is from the data, use that to inform who you recruit for user research.
当你从数据里得到一个关于"邻接用户是谁"的早期假设,就用它去指导用户研究该招什么样的人。
Those customer conversations help you do two things: One, validate and fill in your hypotheses on who the adjacent user is; and two, start to build empathy for the adjacent user and understand why they are struggling.
这些跟用户的对话会帮你做两件事:一是验证并补全你对"邻接用户是谁"的假设;二是开始对邻接用户建立共情,理解他们为什么在挣扎。
It is not enough to know who the adjacent user is, but you need to know why they are struggling.
光知道"谁是邻接用户"还不够,你还得知道他们为什么在挣扎。
To do that, you have to build empathy with the adjacent user. This is the most important part.
想做到这一点,你必须对邻接用户建立共情。这是整件事里最重要的一步。
Building empathy for the adjacent user is hard because by definition your team is not living the experience of the adjacent user.
对邻接用户建立共情很难,因为按定义,你的团队就不在过着邻接用户的生活。
Your team are power users of the product. They know the product in and out.
你的团队是这个产品的重度用户,他们对产品里里外外了如指掌。
To build empathy with the adjacent user and create hypotheses of why they are struggling, I recommend four techniques:
想跟邻接用户建立共情、建立"他们为什么在挣扎"的假设,我推荐四个动作:
Lets talk about each of these individually.
我们一个一个来。
You need to force the team to be the adjacent user by experiencing the product in the conditions and settings that the adjacent user is experiencing.
你要强迫团队成为邻接用户——在邻接用户所处的条件和环境里去用一遍产品。
This is commonly referred to as dog-fooding.
这就是常说的 dog-fooding(吃自己的狗粮)。
This starts by making sure the team is constantly experiencing new user flows, empty states, and product states that require a certain amount of usage before they become valuable.
第一步是确保团队不停地体验新用户流程、空白状态、以及那些"用到一定量之后才有价值"的产品状态。
This eventually progresses to building tools to be able to simulate the experience of your adjacent users.
再往后,你需要构建工具来模拟邻接用户的真实体验。
For example, at Instagram as our adjacent users increasingly became more international, we needed to find a way to experience the product across many permutations of devices, network speeds, languages, and much more.
举个例子:Instagram 的邻接用户越来越国际化之后,我们需要一种方法去体验产品在不同设备、网速、语言等组合下的样子。
Facebook built something called Air Traffic Control, which simulated elements of these permutations like network speed so the team could experience the product through the eyes of the adjacent user.
Facebook 内部为此造了一个叫 Air Traffic Control 的工具,可以模拟其中一些参数(比如网速),让团队用邻接用户的眼睛去体验产品。
At Instacart, we had to find ways to experience the product through the eyes of someone in an expansion market like Overland, Kansas.
在 Instacart,我们也要想办法用扩张市场用户的眼睛——比如堪萨斯州 Overland 镇——去体验产品。
There the store options, delivery windows, and other factors were completely different than what a PM or engineer on the team in San Francisco would be experiencing.
那里能选的门店、配送时间窗、以及其他因素,跟旧金山 PM 和工程师每天看到的完全不一样。
Living every day as the adjacent user uncovers hidden connections and dependencies in the product that impact the experience for the adjacent user that would have otherwise gone unnoticed.
每天以邻接用户的身份生活,会让你发现产品里那些隐藏的关联和依赖——它们影响着邻接用户的体验,但你平时根本注意不到。
The second technique is to watch the adjacent user using your product through usability tests.
第二个动作是通过可用性测试,观察邻接用户使用你的产品。
Ideally this is done with trained researchers when possible.
理想情况下,这件事由受过训练的研究员来做。
Watch the adjacent user try to sign up, activate, see what they struggle on, have them talk about why they are having challenges and what their expectations of the experience are.
看他们怎么尝试注册、怎么尝试激活,看他们卡在哪,让他们说出自己为什么觉得难、对这个体验本来抱着什么预期。
Do not help them until they get stuck so you can observer what kind of workarounds and hacks people create to get the outcomes they want.
他们没卡住之前不要帮——这样你才能看到:为了拿到自己想要的结果,他们会发明什么样的 workaround 和 hack。
This is how you start uncovering behavior that explains aberrant data, or behavior for which data doesn't exist.
这就是你开始解释那些异常数据、或者发现那些数据根本没记录到的行为的方式。
The third technique is to talk to the adjacent user about why they are trying to use your product, what jobs they are trying to solve, and which alternatives they are considering or have already tried.
第三个动作是跟邻接用户对话——问他们为什么想用你的产品、要解决什么任务、考虑过或试过哪些替代方案。
Surveys are fastest to deploy to get signal on where you should spend more time and focus.
问卷部署最快,能帮你拿到一些信号,知道时间应该花在哪。
But surveys alone are not sufficient. You need to talk to users in person to go deeper.
但光靠问卷不够。要往深处挖,必须当面跟用户聊。
At the beginning of the post I talked about the example at Instagram where we started to see a large increase in access churn (users logging out, then failing to log back in successfully).
文章开头我提到 Instagram 的一个例子:我们开始看到 access churn 显著上升——也就是用户登出之后再也没法成功登回来。
Two directions emerged. We could either make it harder for people to log out, or easier to log back in.
出现了两条路:要么让登出变难,要么让登回来变容易。
But to determine which path was best, we needed to understand why people were logging out in increasing volumes.
但要判断哪条路对,我们得先理解:为什么有越来越多人在主动登出?
We decided to talk to a lot of users who were intentionally logging out. What we found were two things:
于是我们去跟大量"主动登出"的用户聊,发现了两件事:
People had a real use case for logging out. They logged out either because they had a prepaid phone plan and were worried about background data usage, or they were sharing the phone with a family member.
第一,登出对他们来说是真实需求——要么是用预付费手机套餐、担心后台流量;要么是手机跟家人共用。
These users also commonly used fake email addresses. Email addresses are more of a western paradigm, and new people to the internet internationally don't use email, they just text.
第二,这些用户经常用假邮箱注册。邮箱本来就是西方互联网的产物,国际新用户根本不用邮箱,他们只发短信。
Once we understood these two things, it was clear the right strategic direction was to work on making it easier to log back in vs harder to log out and we were able to come up with some creative solutions for the use cases.
搞清楚这两件事后,正确的战略方向就清楚了——做"更容易登回来",而不是"更难登出"。在这个方向上我们想出了一些有创意的解法。
The last technique is to visit the adjacent user in their environment.
最后一个动作是拜访邻接用户——在他们自己的环境里看他们用产品。
Seeing how your adjacent user uses a product in their environment expands your understanding of their workflow, constraints, and needs.
看他们在真实环境里怎么用产品,能极大扩展你对他们工作流、约束、需求的理解。
Are B2B customers constantly sharing screens with colleagues for a product that you previously thought of as a personal tool?
那些 B2B 客户,是不是在用一个你以为是"个人工具"的产品时,反复跟同事共享屏幕?
Are users having performance or usability issues in the real world that you otherwise wouldn't have considered?
那些用户,是不是在真实世界里遇到了你根本没考虑过的性能或可用性问题?
Users tend to employ their authentic workarounds and habits in their own environment, which you won't see in a lab or other manufactured setting.
人在自己的环境里会用上真实的 workaround 和习惯——这些你在实验室或其他人造场景里永远看不到。
One of the biggest failure points is sequencing your adjacent users incorrectly.
这套方法最大的翻车点之一,就是邻接用户排错了序。
You want to pick the right adjacent users to go after so that you are building towards longer term value over time.
你想挑对邻接用户去攻坚,这样你就是在为长期价值积累。
If you are familiar with Geoffrey Moore Crossing The Chasm, he referred to something similar called the bowling alley strategy.
如果你熟悉 Geoffrey Moore(杰弗里·摩尔)的《Crossing The Chasm》(《跨越鸿沟》),里面讲过一个相似的概念,叫 bowling alley 策略(保龄球道策略)。
Find one niche audience that if you solve for them, helps you get to the next audience.
先找一个小众群体,只要你为他们解决了问题,就能撬动下一个群体。
The center of Moore's framework was Customer Maturity: Innovators, Early Adopters, Early Majority, Late Majority, and Laggards.
Moore 的框架核心是"客户成熟度":Innovators(创新者)、Early Adopters(早期采纳者)、Early Majority(早期多数)、Late Majority(后期多数)、Laggards(落后者)。
Moore theorized that by solving for the problems of next set of likely adopters you enable the following segments.
Moore 的理论是:你只要解决了"下一批最可能采纳者"的问题,就给后面那一段段群体铺好了路。
Adjacent User theory is similar. By enabling your immediate next set of adjacent users, you create the conditions that enable future segments.
邻接用户理论是同样的逻辑:让眼前下一批邻接用户用起来,你就为再之后的群体创造了条件。
You can push the boundaries of the core user outcomes down to a lot of vectors, customer maturity being just one.
"核心用户成果"的边界可以沿着很多向量往外推——客户成熟度只是其中一条。
Let's say you have 5 different vectors you can expand on.
假设你手上有 5 条可以扩张的向量。
If your adjacent user definition is different on all 5 of those vectors, or even the majority, choosing that segment is a bad choice.
如果你的邻接用户定义在 5 条向量上全都跟现有用户不同,甚至只是大多数不同——这个邻接段就是个糟糕的选择。
That is like trying to hit a home run on every swing.
那就是在每一棒都想打全垒打。
It is probably going to take too many changes that are too large to enable that segment.
为了让这个段能用起来,你大概率要做太多、太大的改动。
You need the conviction that you can build something to validate or invalidate the adjacent user definition pretty quickly.
你需要这样一种把握:你能很快做出点东西来验证(或证伪)这个邻接用户的定义。
The adjacent user is not about capturing one large definition at once, it is about layering on micro definition after micro definition.
邻接用户不是一口气吃下一个大定义,而是把一层层微小的定义叠加上去。
"A segment that is different on multiple attributes typically requires enabling a new value prop to bring them into the product. That's a very big swing."
"一个在多个属性上都不同的群体,通常需要你提供一个全新的价值主张才能把他们拉进来。这是一次极大的挥棒。"
"But it's not an 'if' you should be going after them, it's a question of 'when.' If you can first add smaller features for adjacent users that only differ on one attribute you can maintain momentum and growth velocity while working up to a new value prop for those multi-attribute users."
"但这不是要不要追这些用户的问题,而是什么时候追的问题。如果你能先为那种'只在一个属性上不同'的邻接用户加一些较小的功能,就能保持势头和增长速度,同时一步步爬向那批多属性用户所需要的新价值主张。"
As you explore your adjacent users, you are going to find a lot of possible segments.
在探索邻接用户的过程中,你会发现非常多潜在的段。
But just because they exist, does not mean you should choose to serve them.
但仅仅因为它们存在,不代表你就该选它们去服务。
The key here is that the segment still needs to align with the strategic direction of where the product is going.
关键是:这个段必须与产品的战略方向对齐。
Sometimes you will have a lot of insight that an adjacent user exists, but you are unsure if serving them is meaningful and aligns with the strategic direction.
有时你对一个邻接用户有非常多洞察,但你不确定服务他们是不是有意义、是不是跟战略方向一致。
When choosing your adjacent users, it is typically better to solve "in-house" problems first.
挑邻接用户时,通常优先解决"屋里人"的问题。
These are users that are already showing up in your funnel and product vs brand new users who aren't there yet.
这些人已经出现在你的漏斗和产品里了——跟那些还没来的全新用户相比,他们更近。
Those that are already showing up are displaying intent, but having trouble finishing.
他们能进到漏斗里就是在展示意图,只是没法走完。
Solving for them typically creates more short term impact.
为他们解题,短期影响通常更明显。
"For B2B products, the way I like to think about sequencing is:"
"对 B2B 产品,我喜欢这样安排排序:"
Part of the prioritization should be the impact that you think the adjacent user segment can drive if solved for.
优先级的一部分,要看你估计这个邻接段一旦被解决能带来多少影响。
The impact is partially driven by the size of the segment today.
影响一部分来自今天这个段的规模。
But one mistake when thinking about impact is to not think about the impact on a longer time horizon.
但思考影响时有个常见错误——不去想长时段上的影响。
Often times one segment might be larger but not growing, while another could be smaller but have a much larger growth trajectory.
很多时候,一个段当下规模大但不增长;另一个段规模小,但增长轨迹陡峭。
When taking that trajectory into account, the second segment may be the better choice.
把增长轨迹纳进来,第二个段反而是更好的选择。
"When we were looking at international growth opportunities at Slack, we found that both users in France and India had far worse monetization. A lot of teams would have probably chosen to solve for French users since they are a higher income audience."
"在 Slack 看国际增长机会时,我们发现法国和印度用户的商业化都差很多。很多团队大概率会选先解法国——毕竟人均收入高。"
"But users in France weren't growing and we didn't have a clear hypothesis of why they weren't monetizing. On the other hand, India was growing way faster and had a clear hypothesis as to why they weren't paying."
"但法国用户不增长,而且我们对'他们为什么没商业化'连一个清晰假设都没有。反过来印度增长快得多,而且对'他们为什么不付费'有一个清晰假设。"
"When looking at it on a slightly longer term horizon, solving for users in India was clearly the higher ROI opportunity."
"放到稍长一点的时间窗口看,解印度的用户明显是更高 ROI 的机会。"
The landscape and understanding of your adjacent users are always evolving.
邻接用户的版图、以及你对他们的理解,从来都是在演化的。
When I started at Instagram, the Adjacent User was women 35 – 45 in the US who had a Facebook account but didn't see the value of Instagram.
我刚到 Instagram 时,邻接用户是 35-45 岁的美国女性——她们有 Facebook 账号,但看不出 Instagram 对她们有什么价值。
By the time I left Instagram, the Adjacent User was women in Jakarta, on an older 3G Android phone with a prepaid mobile plan.
我离开 Instagram 时,邻接用户已经变成了:雅加达的女性、用着老款 3G 安卓手机、预付费套餐。
There were probably 8 different types of Adjacent Users that we solved for in-between those two points.
从前者到后者之间,我们大概为 8 类不同的邻接用户解过题。
Your Adjacent User is constantly changing for a few different reasons:
你的邻接用户一直在变,原因有几个:
As you experiment and solve for one adjacent user, you are constantly gaining new information.
在为一个邻接用户做实验、解决问题的过程中,你会不断拿到新信息。
This new information informs updates to your current adjacent user hypotheses and possibly creates entirely new adjacent user segments.
这些新信息会让你更新当前的邻接用户假设,甚至可能催生全新的邻接段。
As you unlock value for one type of adjacent user, they often start bringing in a new type of adjacent user into your orbit.
当你为一类邻接用户解锁价值,他们常常会把另一种邻接用户带进你的轨道。
All healthy products have some acquisition through word of mouth.
所有健康的产品都有一部分获客来自口碑。
So when you solve for one adjacent user, their word of mouth brings in their friends who just might be your next type of adjacent user.
所以你解决了一类邻接用户,他们的口碑就会把朋友带进来——而这些朋友很可能就是你的下一类邻接用户。
Unlocking the 35-45yo women in US and Europe on IG brought WOM growth through families.
在 Instagram 解开 35-45 岁的美欧女性这一段后,通过家庭网络又涨了一波口碑用户。
This is an important age group for mothers who would create private IG accounts to share family and kid photos.
这个年龄段对母亲们尤其关键——她们会建一个私密 IG 账号,专门用来分享家庭和孩子的照片。
This influenced their friends to do the same, inspired other relatives to sign up just to see these photos, and their partners ended up joining as well.
这件事又影响她们的朋友做同样的事,带动其他亲戚为了看这些照片注册账号,连她们的伴侣最后也跟着加入了。
As the product team enables new value props in the product, it can fundamentally change what the experience needs to be at the edges of user states for adjacent users to experience the product.
当产品团队上线新的价值主张时,它会从根本上改变用户状态边缘的那种"邻接用户能体验到产品"的条件。
At Instagram, this occurred when we launched Stories.
Instagram 上线 Stories 时就发生过这种情况。
Stories didn't help activate new users. It actually made it harder.
Stories 不仅没让新用户激活变容易,反而变难了。
It was hard for new users to have available Stories content because it disappeared after 24hours.
新用户很难有持续可看的 Stories 内容,因为这些内容 24 小时就没了。
Users needed to follow a lot more accounts to have enough content on any given day.
用户得关注更多账号,才能保证某一天有足够内容刷。
The bar was higher and it changed the experience of how we created activation and engagement.
门槛被抬高了,我们做激活和参与度的方式也跟着变了。
Knowing that the adjacent user is constantly changing, we would reevaluate our understanding of the adjacent user every quarterly planning cycle based on learnings from experimentation and research.
知道邻接用户在持续变化后,我们每个季度的规划周期都会基于实验和研究的发现,重新评估一次自己对邻接用户的理解。
In addition, we would tend to have one off insights a couple of times per year from various events like unexplainable experiment results, press, surveys, or something else.
除此之外,每年还会有几次零星的洞察冒出来——可能是一个解释不了的实验结果、可能是媒体报道、可能是问卷,或别的什么事情。
This evolving landscapes highlights the importance of a few different things:
这种持续演化的版图,凸显了几件事的重要性:
Taking Time To Understand The Why. Too often teams move on from the positive/negative result of an experiment without understanding why the experiment generated that result.
花时间搞清楚 why。团队常常在实验出了正/负面结果后就翻篇了,没去搞清楚这个结果背后为什么是这样。
You must take the time to understand "the why' behind your experimental results.
你必须花时间去搞清楚实验结果背后的"为什么"。
The why helps you understand the next adjacent user.
"为什么"会帮你理解下一个邻接用户。
If you don't do this you can miss incredibly important shifts in user mindsets as you move from adjacent segment to segment.
如果不做这件事,在你从一个邻接段往下一个邻接段挪的过程中,会错过用户心智里那些极其关键的迁移信号。
If you don't take the time to understand the why behind your results, you miss the opportunity to build empathy and solve your adjacent user's real problems.
如果你不花时间搞清楚结果背后的为什么,你就错过了对邻接用户建立共情、解决他们真问题的机会。
Constantly Working On the Fundamentals Of Registration, Activation, Engagement and Monetization. Too often teams treat key flows in their product as projects.
不停打磨注册、激活、参与度、商业化这些基本功。团队常常把这些关键流程当成"一次性项目"。
But the adjacent user highlights why you need to be constantly working on the fundamentals of registration, activation, engagement, and monetization.
但邻接用户的存在告诉你:注册、激活、参与度、商业化,这些基本功你必须一直在做。
It's a continuously evolving user challenge that you need to be constantly re-evaluating. The work never stops.
这是一个持续演化的用户挑战,你得不停地重新评估。这些工作没有结束的时候。
"In the early days of Instacart, the best performing landing page was an all white page, that said 'Instacart, Groceries delivered to your door, put your zip code in'. Nothing else performed better."
"Instacart 早期表现最好的落地页是一张全白的页面,只写了 'Instacart, Groceries delivered to your door, put your zip code in'。其他什么版本都没它好。"
"The user at that time was very high intent, tech savvy, urban millennial who knew what Instacart was because they heard about it from a friend through the press."
"那时候的用户都是极高意图、懂技术的城市千禧一代——他们已经从朋友、从媒体上知道 Instacart 是什么了。"
"As Instacart grew over time, you had to explain what Instacart was, why does it matter, who it is for, what stores we have. The same experiment on the white page a year later had dramatically different results because the adjacent user had changed."
"随着 Instacart 增长,你得解释 Instacart 是什么、为什么重要、给谁用、有哪些合作门店。同一张白页落地页,一年后再实验,结果就天差地别——因为邻接用户已经变了。"
Continually Cross The Cognitive Threshold Of Your Adjacent User. At the beginning of this post, we talked about how working on the adjacent user requires you cross a cognitive threshold of seeing the product experience through their eyes.
不断穿越邻接用户的认知阈值。文章开头我们讲过——为邻接用户工作,要求你跨越一个认知阈值,用他们的眼睛去看产品体验。
As the landscape of the adjacent user evolves, you and the team need cross this threshold over and over.
随着邻接用户版图持续演化,你和团队必须一次又一次跨越这道阈值。
It is easy to get sucked back into the gravity of your existing user base.
引力会很容易把你拉回到现有用户群里。
But your job is to constantly expand the definition of who is successful with your product.
但你的工作就是:持续扩大"谁能用你的产品成功"这个定义。
All successful products must eventually shift their focus from core to adjacent users in order to maintain growth rates.
所有成功的产品,最终都必须把焦点从核心用户转向邻接用户,才能维持增长。
Rapid success in your first audience will inherently lead to saturation and declining growth in that segment.
在你最初那批受众里取得的快速成功,本身就注定会带来饱和和这个段的增长下行。
While this is certainly an enviable problem to have, solving it is one of the most complex challenges in technology.
这当然是个让人羡慕的"问题",但解决它,是科技行业里最复杂的挑战之一。
The most successful companies are the ones that can continuously evolve to serve more adjacent users.
最成功的公司,是那些能持续演化、不断服务更多邻接用户的公司。
The art is selecting the right groups of adjacent users to go after next.
这门艺术,在于选对下一批要攻坚的邻接用户。
If you try to solve all problems for everyone, you'll drown across too many issues and waste time acquiring users who have no chance of being successful today.
如果你想为所有人解决所有问题,你会被太多的议题淹没,把时间浪费在那些当下根本没机会成功的用户身上。
Adjacent User Theory demands an entirely different approach to being 'user centric'. Static personas are OUT.
邻接用户理论要求一种完全不同的"以用户为中心"的做法。静态 persona 已经过时了。
Dynamic evolving personas that incorporate product adoption behavior are the standard to strive for.
基于产品采纳行为、动态演化的 persona,才是该努力的标准。
Every 3-6 months during hyper growth, you have to reorient your team around the next adjacent user, what they care about, and what problems you are solving for them.
在高速增长期,每 3-6 个月你就得围绕"下一个邻接用户"重新校准团队——他们在乎什么、你要为他们解决什么。
As you are succeed, you'll see improving cohort retention, engagement, and monetization in your target adjacent users.
当你做对了,你会看到目标邻接用户的同期群留存、参与度、商业化都在改善。
You'll maintain your growth rate on larger and larger install bases.
你会在越来越大的用户基数上,继续保持增长率。
And you'll continuously discover the next adjacent user who could use your product with just a little more help.
而且你会不停地发现下一批"再推一把就能用起来"的邻接用户。