用户研究,卡诺模型

前日在Medium看见一篇用研方法的介绍—— 卡诺模型(The Kano Analysis)。用来深入分析一个出品作用是不是能使顾客知足,这种方法的长处是能得出贰个活脱脱的数码结论,援救决策。总结办法也挺轻便的,问卷操作也正如便于轻松,开销相当的低。小编自个儿特别喜欢这种能高效验证的低本钱措施,能在少数的时间与人力能源条件下,也能飞速得出可信的数目参照他事他说加以考察与清丽的定论。正如本身上一篇文章介绍的措施同样,能大大提升调换功效,缩短无谓的斗嘴。本办法对职能的八种划分也蛮风趣,让本人记忆锤子科学技术,锤子的手提式有线电电话机正是特地强调软件上的Delightful Features而忽略任何硬件上的Required Features。那就正好解释了为啥锤子销量与认识度不成正比。

您正在浏览针对你的产品建议的18项特征。坦白地讲,对于在终结日期前要公布的中期版本的话,18项特征太多了,所以,你想要明确这几个特色中最优的那部分。

原稿小编就不全翻了,笔者只把关键的从头到尾的经过翻下,由于Medium需求梯子,所以本人在征求作者同意的情况下把原著粘贴在此。有楼梯的同窗请点此传送。 

你困惑一个人总经理的年轻人男女建议了部分风味,你从竞争产品处识别出来了任何的特色。直觉告诉您,18项特征中尚无其他一项能够转移游戏准则。何况,你投入进行刚开始阶段生成讨论的安顿受到了推迟。

受行为科学家赫兹伯格的双成分理论的开导,东京(Tokyo)理管理高校教书狩野纪昭(Noriaki Kano)和他的同事Fumio Takahashi于1980年三月登出了《品质的保健因素和激情因素》(Motivator and Hygiene Factor in Quality)一文。

这是个难题。你要做什么?

该形式把产品效果区划为以下七种:

您能够尝试比非常多敏捷团队和客户体验专家所做的:使用一种被称作“卡诺模型”的章程。这种艺术第二遍出现在上世纪80时代的东瀛,用来度量客户对私有特征的心思反应。在projekt20第22中学,大家这么做就收获了高大的中标。大家的成功来源于通过试错重复了卡诺的原创性钻探。大家发现,怎样统一筹算和举行一个卡诺探讨很关键,怎么样剖析和可视化结果也很首要。

Desired Features 期待作用 

当提供此作用,客商满足度会进级,当不提供此意义,客商满足度会下落;

大家还开掘,卡诺模型是一个表明中期生成钻探的ROI(投资报酬率)的无敌区工作具,以及卡诺商量的结果如何带领产品路径图的决策。总的来讲,卡诺研商是我们切磋工具中极度有效的多少个。

Required Features 必备作用 

当优化此作用,客商满足度不会进步,当不提供此功用,客商满意度会小幅度减退;

一、卡诺的底子

Delightful Features 魔力功效 

客商意料之外的,假若不提供此意义,客户满足度不会稳中有降,但当提供此意义,客户满足度会有十分大提高;

小编们在研讨度量快乐的法门时发掘了卡诺模型。早在1982年,狩野纪昭(Noriaki Kano),一人东瀛学者和师爷,不容许那时候有关有限辅助客户忠诚度的已被接受的反驳:通过解决花费者控诉和强大最受应接的性格。卡诺凭直觉感知到保证忠诚度更复杂。他做了独具斟酌人士做的:定义了一旦,并规划了贰个商讨来验证那么些理论。卡诺的劳作,随后被美利坚合众国品质管理顾问们采取和延长。我们越审视这些诞生25年的诀要怎么着被应用在前几天市道商讨中,并被敏捷团队动用的,大家越认为远远不够严俊性,並且被迫去学学这几个中期的商讨者,以保障我们正确的应用了该办法。

Indifferent Features 一点差别也没有功用

任由提供或不提供此成效,顾客满足度都不会有更换,客商根本不留意;

我们翻译了卡诺的葡萄牙语原稿。大家与顾客体验总结学家JeffSauro探讨了差别计算深入分析的相对优势,那一个总结剖判是品质管理中央(Center for Quality Management)公布的。净结果是全然有信心在大家的章程中央银行使这种措施。

Anti-feature Features 反向成效

顾客根本都尚未此意义,提供后客商满足度反而会下降。

情势运用问卷提问的章程募集数据,最后通过数量整合得出三个效应的多个周密:好听周到Satisfaction Coefficient 不称心周到 Dissatisfaction Coefficient。假定满足全面超越不令人满足周密,该作用值得做。

以下是原作内容 Let's Go:

在我们谈谈实行一项卡诺商量以前,理解卡诺的比方是很要紧的。他从理论上感到,大家对特色存在八种区别的情感反应,从不喜欢到欢腾慰勉。与1983年的还要代人分裂,他感觉客商忠诚度与对产品特征的心绪反应“概况”相关——二者恰如其分的同心协力,个中囊括令客户开心,和给予他们在经验在此之前都不知底自个儿想要的那三个特征。

The Kano Analysis

接下来,他开展了一项900人的商量,用来注解这个心理反应类型的存在,何况能够可信地质测量量。

A Better Way Discover What Users Really Want From Your Product

by Brian O'Neill

You’re on the design team for Crunchrr, a new app that helps users discover cereals they’ll love. Users can:

- Create a profile and connect with others

- Discover cereals based on their preferences

- Rate and review cereals

Crunchrr is in the hands of some early adopters who are loving its core features. Things are going great. That is, until the requests start rolling in.

Annelise from marketing says: “Crunchrr needs a map view so users can see where each cereal is made. People are really interested in where their food comes from nowadays, so this is really a must! Besides, every app has a map view.” Kevin from sales was at a meeting with a potential advertiser who asks: “Where’s the chatbot? You can’tnothave a chatbot. Conversational UI is the future!”

One of your early adopters pings you to suggest: “There should be a button so I can email the cereal maker to request a gluten-free version.” Another one says: “Maybe there could be something like Shazam for cereal. That way, if I’m in a restaurant I can take a picture of what the person at the next table is eating and it’ll show me what that cereal is.”

The next thing you know, your backlog is a gaggle of suggestions, requests, and demands. It seems that everyone has brilliant idea that justhasto go into the next release.

This can’t be avoided. Everyone has an opinion and given the opportunity, they’ll express it. And people easily fall into a “more is better” mentality. More features equals a better product, and the more of each feature, the better.

The obvious problem is that you can’t deliver on every request. Not only that, but all ideas aren’t created equal, and users are often at a loss as to how to articulate what they really want and need. On the other hand, internal stakeholders tend to view features in the narrow context of their own interests. How do you stop the madness?

“The most important thing that a team can do to help their design is to say no to almost any idea for a feature”

— Jared Spool

You need a way to predict user satisfaction that lets you prioritize feature releases and even re-evaluate existing features. And you need hard data to support your decisions about what goes into Crunchrr and when. That’s where theKano Modelcomes in.

二、卡诺的七种心情反应类型

The Kano Model

In 1984 professor Noriaki Kano presented a model that predicts how satisfied people will be with a product based on its features. Since then, the Kano Model has become a standard design tool because of how effectively it can make typically invisible ideas about quality visible. The core principle of the model is that satisfaction can be plotted along five distinct curves.[1]

卡诺将二种心理反应可视化为图中的曲线,当中,y轴是情感反应,x轴是特色的成熟程度。激情反应的强度由特征怎样尽量表现和其早熟程度驱动。

Curve 1: Desired Features

Remember when I said more isn’t always better? Well,sometimesit is it is. More storage space or battery life is better. Faster download speeds? Better. These are all examples of where the user will usually express greater satisfaction in direct proportion to how much of the feature they get.

With desired features, satisfaction is directly proportional to feature implementation

In the case of Crunchrr, desired features could be:

- Speed and responsiveness

- Number of users to connect with

- Suggestions based on stated preferences and past browsing behavior

- Options for quickly zeroing in on a kind of cereal (sorting, filtering, etc.)

- Size of cereal selection

魔力属性

Curve 2: Required Features

Required features are the ones users expect and take for granted.

With required features satisfaction levels off once the basic need has been met

Users are dissatisfied when a required feature is not present and satisfied when it is. But that satisfaction levels off after a certain point. This makes sense when you think about it. If a wheel doesn’t roll, it will cause dissatisfaction. If it does roll, it will cause satisfaction. But it’s hard to get anyone excited about a wheel that rollsreally, reallywell. In the case of Crunchrr, as with most other apps, this could mean things like:

- Reliable uptime

- Search

- Ability to create a profile

- Easy log in/out

当魔力属性显示时,会慰勉知足和欢欣,但万一该属性不饱含在内,客户并不会以为到不满。魔力属性是始料比不上的,消除以前未满意急需的。发掘这个品种的本性,最佳的议程是透过生成性商量。这个属性是发生关于产品正面口碑的第一。

Curve 3: Delightful Features

Delightful features are the ones that make an app fun to use and give it a personality. They’re the features you love, but don’t expect. It could be as simple as when the login form appears to shake its head when you enter the wrong credentials. Or it could be the tone of the writing or a fun mascot character or some unique interaction.

Users are satisfied with delightful features, but are not dissatisfied when they are absent

As you can see from the graph, users express increased satisfaction with delightful features. But there’s no dissatisfaction when they’re not present. Also, as with required features, there’s a limit to just how delighted a user can be. After a certain point, there are diminishing returns. ­

Annelise’s map view is probably an example of a delighter because it’s little more than eye candy, and it certainly isn’t solving any of the currently defined business needs for Crunchrr.

Delightful features are an important part of the user experience, and shouldn’t be ignored. Butthey come with a shelf life, in part because they’re so easily imitated. For a while, the swiping interaction was a big part of Tinder’s unique identity. Now, Tinder is justone of many appswhere users can swipe left or right. In other words, over time, delightful features go on to become desired or even required features.

图片 1

Curve 4: Indifferent Features

These are features the user simply doesn’t care about either way. Whether they’re implemented fully or not at all, they won’t change users’ opinions about the app, or change how they use it.

Neutral features don’t affect satisfaction one way or another

一维属性

Curve 5: Anti-features

Anti-features are the features that users actively dislike. (Remember Clippy?) And the more these features are implemented, the greater the dissatisfaction. Anti-features are like the mirror opposite of desired features.

Anti-features are the ones that frustrate or annoy users. Dissatisfaction is directly proportional to implementation

这么些属性突显的结果是看中,而要是不表现,就能够导致不满。属性的老到程度和心思反应之间呈线性关系,首要针对于如易用性、花费、娱乐市场总值和安全性那样的成品特征。

Putting it All Together

Looking at all of these features together not only provides a clear pictorial representation of how features will be perceived, but also helps you figure out strategic direction.

The complete Kano Model diagram

Desired Features:Resources should be invested heavily in these features, because they are key to user adoption and retention, as well as competitive advantage

Required Features:Resources should be invested heavily in these features, but only until basic needs have been met.

Delightful Features:It’s fine to invest resources here, but not at the expense of desired and required features. However, delightful features are often key differentiators that can build loyalty and buzz.

Indifferent Features and Anti-features:Resources should be invested only in identifying these so as not to waste cycles on building and implementing them.

By now I hope you’re sold on the Kano Model. Then the next question is: How do you find out which features belong to each category? That’s where the Kano Analysis comes in.

图片 2

The Kano Analysis

To find out which features belong where, we need to ask our users. But remember, users are not usually great at identifying or expressing what they really want and need. The Kano Analysis accounts for this by asking questions in pairs: afunctional questionfollowed by adysfunctional question. Let’s go back to Annelise’s suggestion of a map view for Crunchrr. We could ask a question pair about this feature like this:

If Crunchrr let you see on a map where a brand of cereal is made, how would you feel?

If Crunchrr did not let you see on a map where a brand of cereal is made, how would you feel?

For both functional and dysfunctional questions, users must choose one of the following answers:

- I like it that way

- I expect it that way

- I am neutral about it

- I can live with it that way

- I dislike it that way

You would prepare an entire questionnaire in this style for each of the features in your backlog. Each user’s answers can then be analyzed by plotting its outcome in the following table.

The analysis table tells you where a user would place a feature in the Kano Model based on how the functional and dysfunctional responses compare

It should be clear that if a user likes it when the feature is present and dislikes it when it’s not, then that is a desired feature. The designation ofquestionablehappens when the answers apparently contradict each other. (This is often the result of the user not understanding the question.)

Great. We’re almost done. The final piece is to aggregate all of the survey responses to find the overall results for each feature. (Alternatively, you could break this down even further and aggregate responses based on personas.)

必备属性

Coefficients

After you’ve aggregated all of the responses, you’ll calculate the satisfaction and dissatisfaction coefficients. The satisfaction coefficient is a number between 0 and 1: the closer to 1, the stronger the influence on satisfaction. The dissatisfaction coefficient is a number between 0 and -1: the closer the closer to -1, the stronger the influence on dissatisfaction. We calculate the coefficients with these formulas:

Let’s say that the aggregated responses for the map view breaks down like this:

Desired: 5%

Required: 12%

Delightful: 4%

Indifferent: 23%

Anti-feature: 31%

Questionable: 25%

That would give you these results:

Satisfaction: (4 + 5) / (4 + 5 + 12 + 23) =0.2045

Dissatisfaction: (5 + 12) / (4 + 5 + 12 + 23) * (-1) = -0.3864

As you can see, the map view feature is having a significantly stronger influence on dissatisfaction than on satisfaction. This clearly indicates that we should leave it out of Crunchrr. Sorry, Annelise! (Actually, if you saw these results in the real world, you wouldn’t even need to calculate the coefficients. Seeing 31% anti-feature and 25% questionable is enough to tell you not to include this feature. I used these exaggerated figures to highlight the differences produced in the coefficients.)

Other times, the coefficients will show little difference in influence. Cases like those will require a judgement call or re-testing.

那个属性是客户愿意产品全部的。通过美化和提高必备属性得到激情收益是有限度的。

In Closing

A Kano Analysis is cheap and easy to perform and provides clear vision into what users actually want and expect from your product. It also provides hard data, which breaks everyone out of the trap of biased or shortsighted thinking. There’s no need to argue and debate with internal stakeholders about which features are in or out. The numbers don’t lie!

Brian O’Neill @brianeoneill is a designer in the San Francisco Bay Area, currently at NVIDIA.

[1]These curves go by many different names, depending on the source. I picked these names arbitrarily. In the end, it doesn’t matter what they’re called.

图片 3

不主要性质

顾客对不根本的本性是动摇不决的,他们平昔不保养它们含有与否。那几个属性的投资收益率极低。

图片 4

无需的天性

蕴含不供给的性质会否认魔力属性和一维属性的积极影响。

图片 5

三、发生变动

卡诺从理论上测算了开销者对知足度的感知会趁机时间的推迟而转换。前几日激情愉悦的性质将随着年华的延期,变为具有客户的梦想和要求。种种心思反应中,魅力属性曲线摇身一产生为了不能缺少的曲线。另外,“最棒”的概念是延绵不断调换的,进而影响给定特征落在x轴的哪个地点。

图片 6

四、衡量客商反馈

卡诺考察难题——各类属性多少个难点

咱俩期盼在我们的花色中尝试卡诺的主张。基础相当粗略:解释或显示三个性情,询问顾客若是该属性存在,他们怎会以为如何;然后再问,若无提供这么些本性,大概未有完全呈现,他们会认为怎么。那样一对主动/衰颓难点与曲线图上八个例外的点绝对应,知道这八个点能力所能达到分明,对于一个加以的习性,顾客正在经历哪一类激情反应。

下边列出的反射并不意在提供一个简练的依附激情反应评级的量表,而是要创设一种期望的感到到。

本身欢娱它

笔者期望它

自家的势态是中性的

本身得以忍受它

本身不爱好它

卡诺评估表

对四个难点中的每多个的答复让你能辨识反应的规模,对此卡诺提供了三个评估表。

上边包车型地铁比喻中,卓越显示的那一行表示对于第叁个,积极难点的回复。出色体现的那一列象征对第四个,失落难点的对答。行与列的交叉点满含了那特天性的分类项目,在那个事例中,为魅力属性。

图片 7

五、剖析卡诺数据

定量深入分析引起与顾客开展职能庞大的发话。那些讲话充裕利用定性研究结果,以询问那个数字的背后的“为啥”。

从卡诺结果中领取人物剧中人物特点

不是各类人都对两样属性的影响同样。尽管不是二个十分的大的出人意料,在这么些差异中搜寻格局会发生一蹴而就的观点。首先,大家在或然的情形下,通过辨认分裂的人选剧中人物开头分析卡诺数据。然后咱们把数量归到人物剧中人物分组的各类子聚焦。那使大家能够为各类人物剧中人物建设构造反应资料。我们商量了针对性各类属性,区别人物角色之间的比不上影响。

笔者们在几项商讨中窥见,顾客对该软件核心属性的反应是决断她属于哪个人物角色组立见分晓的查看方法。比如,在一项研商中,大家看出对多少个骨干部家属性的如下反应。

图片 8

早期采用者(小风螺宝石红)是亟需以此软件的大家。

那么些客商须要和期待的是一维属性和须求属性。因为我们认为她们是在不久的今后最有异常的大希望购买该软件的人,所以把这么些人内定为“开始时期选拔者”人物角色。

最后选用者(藤黄色)是感觉该软件的中坚特征“具备魅力并且越过预期的”大家。

咱俩只要,纵然这些部落对该软件感兴趣,但将会推迟购买,直到概念更为主流。

不选用者(紫灰色)是对软件的骨干特征不感兴趣,而且在可预感的前景不会使用该软件的民众。

通过人物剧中人物筛选出的结果发生可操作的洞见

当大家利用那三人物角色筛选其他的风味时,大家注意到分裂部落对部分风味的感应存在差异。这种量化的数据抓住了顾客的集中力,并说服他们重新评估部分专门的学业,蕴含最先选拔者组不希罕的特点。

上边的数据展示了,中期选取者人物剧中人物组不感兴趣,何况会鼓劲其伤心影响的四个特色。由于刚开始阶段接纳者组是保险产品在上龙时选取度的要害,客户决定不再追求那些组不爱好的风味。

图片 9

看见大的布局——比较种种特征

要应对我们最先关于要包涵如何特色的主题材料,我们营造了能够对顾客对富有特征的影响进行比较和排序的可视化图表。为了达成这一职务,我们利用前边聊到的CQM于1991年第1回报道的主意。来自三个主要新英格兰集团的,想要一齐钻探的COO和高等管理职员们于一九八七年确立了CQM——进行最初进的管制举行,以加快品质立异。在对卡诺方法的告知中,他们聚焦了各样施行者的阅历和拓宽。

在报告的有余主意中,我们引入以下三种。

先是种格局是互补卡诺问卷本人。除了各样特征询问的那三个难点,客户还被供给注解那一个个性的入眼程度怎么着。那些排序是9点李克特量表,从“根本不根本”到“特别关键”。华盛顿圣路易斯分校大学的JohnHauser建议的这种额外度量,有利于将集中力聚集在卡诺切磋的最根本结果。

其次种方式是对卡诺结果进行总结剖析,允许在不一致的特色之间的结果开展相比。这种措施是BillDuMouchel提出的,它同意总计规范差,进而得以窥见什么分化是鲜明的。

当把那个特征正是二个一体化时,我们读到的方法中一向不三个可见提供一种令人信服的可视化来把握卡诺结果。因而,大家尝试并安插了如下的DuMouchel分析的可视化。

图片 10

这种聚成堆的排序呈现了一组特征,大概不顺心的在左边手,或者满意的在左手。那几个顺序呈现,排在最上边的特色,如果未有被含有在成品中,就有最大的或许会孳生不安适。多数风味在CQM剖析中显现满足和在卡诺结果中显现欢腾的恐怕性是近似的。与客户的对话包罗权衡,如复杂性和相关性。这种措施的结果会贯通于决策中。

六、做出决定

聪明的钱应该投身一维属性和魔力属性上

至于卡诺的曲线图,可以激起满足和欢愉的七个分类是魅力属性和一维属性。想想当今市道上最成功的那八个产品,它们经过重申那一个类其余质量来成功。

苹果通过投资于取悦客户的特色,而俘获顾客的芳心。举个例子,台式机计算机的电源线具备磁性连接,能够轻松断开,以免卫损坏设备,那纯属不是多个不可能不怀有的特征。另外,苹果多量入股了优雅设计和易用性方面的一维属性。

标题是,大家如何察觉那些改动游戏法规的特征?

入股于生成性研讨

“魅力”特征是日常顾客不清楚去要求的。当这么些特征出现在市镇上,引起震惊,竞争对手会不慢地抄袭。今日买好客户的特征会成为明日她俩所供给和期待的。但什么察觉这几个引领前卫的风味呢?

简言之:研究。

卡诺模型当中三个最令人开心的用处是永葆与客商就生成性研讨在成品成功进程中所扮演的尤为重要剧中人物进行对话。在生成性钻探中,大家就地观望顾客与技艺拓宽互动。我们见证未被满意的供给,那便是创办不一样,取悦顾客的空子。

只在客户愿意的这一个特征的布署性上投资会限制赢得客户芳心的力量。

抓完成有特征的投资收益率

大家从读书卡诺最早钻探的出版物翻译个中得知,卡诺伊始评释无法轻巧地通过压实花费者曾经上马期望的存活特征,来获取并保证顾客的忠诚度。卡诺曲线图不仅仅表达了干吗那是当真,它们也得以用于评估立异现存特征的投资报酬率(在客户满足度方面)。

叁个当下的特征作为一个点存在于在这之中一幅反应图中。增添特色的老到程度使这些点随着曲线而移动。心情反应的成形在于此特征落在哪贰个反应图上。譬如,加强必需必备的表征,会由此缓解客商的不合意程度来回报,但不断立异的投资收益率会显明地稳步回退。

问询三个特点作为三个点落在七个图表中的哪叁个,能够剖析投资收益率,以精雕细刻此特征。

揭秘净推荐值

常用的净推荐值是贝恩集团的 FredReichheld制订的一种客商忠诚度的心地标准。它是指推荐某第一行当品的顾客平平均数量减去劝阻别的人使用这么些产品的顾客平平均数量。尽管在与竞品相比较时,净推荐值对预测某第一行当品或劳动是或不是中标是低价的,但其自个儿和这种度量方法并从未提供关于如何革新产品的引导。卡诺结果为明白各种特征对净推荐值的贡献提供了一种方法。为何那是真的?客商会推荐激发兴奋和适意的成品。用户会劝阻其余潜在客户使用激发不好听的制品。精晓特征怎么着推动高兴和不满的那些感受,能让产品组长做出明智的挑选,以增添其净推荐值。

七、使用卡诺模型你须求驾驭怎么样

要测量检验多少名客商

笔者们的商量中归纳了少至12名客商和多达24名顾客的事例。指标是要包罗丰硕的客商以感知到全体计算学意义的相信差距。完毕这一对象所需的客商的数目取决于七个关键因素:

切磋中人群的二种性

你筹算衡量的差异的精细程度

即便卡诺研究供给的参加者比周围的简约可用性测量试验多,简易的可用性测量检验从5或6名参预者中提供意见,但我们早就分明举行田间处理考查和剖析数据的方式,以担保以最低的工本产出高素质的见解。与富有的研商措施一样,须要参与者的数据决议于要测量的出入的独具匠心程度。大的出入须要比较少的客户。依照你的研讨指标,你或然想看看区别人物剧中人物组之间的结果,也许你可能唯有对衡量八个加以的人工早产感兴趣。

进展一项卡诺切磋

与客商和别的身处UX社区的民众的成都百货上千讲话中,我们以为钻探难题是怎么被实行的很关键。最佳的结果来自让客户体验这几个特色(带有场景的线框图也能起成效),并当即摄像他们的影响。把特色从利用景况中抽出出来的文字表明或图解发生相持不那么明确的结果。

当卡诺切磋科学完结时,它可以以一种直观的艺术产生相关总计置信水平的结果。最好实行的清单包蕴:

选聘专门的职业,以保障客户真正代表了最后指标客户,也许依据顾客对产品根性子情的反馈,将结果分入分化的人物脚色组。

推行总结解析,所以决定是依照刚毅差距置信水平的。

为客商提供体验(实际不是简约地读书)产品性格的有意义的机会。

感受叁个加以的性状后立马衡量客户的反应。

八、意义构建的Haoqing

在projekt202,大家接受设计然究,以提供有含义的实施方案。大家不断完善和扩展我们的钻探工具。大家开展卡诺商量的秘籍在询问相关定性数据的细微差异上提供了显而易见优势。

大家切磋和考试了卡诺方法和数据,直到它有含义,并形成了强有力的画面来更加好的垂询我们的顾客。不时感觉就像七个考古考查,回到叁个措施最先的视野和专门的工作知识,而该措施已经因为在采纳中错失严俊性而遗失了影响力。大家修改的卡诺方法的版本已经成为贰个保障的工具,能够扶助解答大家客商有关在何地投资他们的陈设性和开采财富的韬略难题,进而影响他们的做到和下线。

看见客商因探究而欢愉总是值得的。当研讨成果产出了中标的制品和一等的客户体验时,它就更值得了。

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