亚马逊谷歌搜索引擎推广_就像Google和Amazon一样，为您的企业建立终极搜索

亚马逊谷歌搜索引擎推广

This article was sponsored by Algolia. Thank you for supporting the sponsors who make SitePoint possible.

本文由阿尔及利亚赞助。 感谢您支持使SitePoint成为可能的赞助商。

When companies think about search, they think about Google. They invest heavily in SEO & SEM to drive traffic – meanwhile, their own search experience remains neglected. Default search options on platforms like Shopify and WordPress pale in comparison to Google & Amazon; the problem is, when most people think of improving their own site search, they think about hiring a team of search engineers to create an ultra-personalized, machine-learning, predictive search experience – either invest heavily now or stick with the default search, right? Wrong.

当公司考虑搜索时，就会考虑Google。他们在SEO和SEM上进行了大量投资，以吸引访问量–同时，他们自己的搜索体验仍然被忽略。与Google和Amazon相比，Shopify和WordPress等平台上的默认搜索选项显得苍白；问题是，当大多数人考虑改善自己的网站搜索时，他们考虑雇用一组搜索工程师来创建超个性化，机器学习和预测性的搜索体验-要么立即进行大量投资，要么坚持默认搜索，对？错误。

It’s a bad idea to invest in driving traffic to your site if the customer journey inside your site is not optimal – and if you’re thinking “my search traffic is a low percentage of my site, so why should I worry about it?” then your site search could probably be improved. Remember: in 2016, 93% of all Internet experiences started with search.

如果客户在您网站内的行程不是最佳的，那么投资于增加访问网站的流量是一个坏主意–如果您在考虑“我的搜索量在我的网站中所占的比例很小，那我为什么要为此担心呢？” 那么您的网站搜索可能会得到改善。请记住：2016年，所有互联网体验中有93％来自搜索。

The biggest mistake you can make isn’t thinking “search isn’t important to my customer’s digital experience;” it’s thinking that it takes a team of search engineers to make a great search experience.

您可能会犯的最大错误就是没有想到“搜索对客户的数字体验并不重要；” 它认为需要一组搜索工程师来提供出色的搜索体验。

If there’s one thing you take away from this article, let it be this: in 2017, search isn’t about back-end, it’s about experience. The future of great search experiences is in the hands of UX designers & front-end engineers.

如果您从本文中删除一件事，那就这样吧： 在2017年，搜索与后端无关，而与经验有关。 出色的搜索体验的未来掌握在UX设计师和前端工程师的手中。

Since 2012, Algolia has been working to enable any engineer to build great search experiences on top of our hosted search engine, powering search on thousands of websites & products around the world. During that time, we’ve educated our customers about what is necessary to have a great search experience – there’s more to great search than fancy algorithms or ultra-customization.

自2012年以来，Algolia一直致力于使任何工程师都能在我们托管的搜索引擎之上构建出色的搜索体验，为全球成千上万的网站和产品提供强大的搜索功能。在那段时间里，我们已经向客户教育了获得出色搜索体验的必要条件–出色的搜索比花哨的算法或超定制化还重要。

Search is a very intuitive process. Users don’t analyze a search experience feature-by-feature — in fact, most of your product’s users would likely say that the search bar itself is the feature, and not the various components that make up that search bar — which means that your users intuitively know after the first try whether your search is great or decent. The difference between decent search and great search is in the three pillars of search – Speed, Relevance, and Design.

搜索是一个非常直观的过程。用户不会按功能分析搜索体验-实际上，您产品的大多数用户可能会说搜索栏本身就是功能，而不是组成该搜索栏的各个组件-这意味着您的首次尝试后，用户会直观地知道您的搜索是不错还是不错。体面搜索和出色搜索之间的区别在于搜索的三个Struts–速度，相关性和设计。

毫秒事项 (Milliseconds Matter)

Algolia provides 99% of search results in under 35 milliseconds, anywhere in the world – just ask our customers. Answering the question “How fast is fast enough?” requires a bit of “How” and a bit of “Why,” but let’s start with the latter:

在世界上任何地方，Algolia都可以在35毫秒内提供99％的搜索结果- 只需询问我们的客户即可。回答“多快才足够快？” 需要一点“如何”和一点“为什么”，但让我们从后者开始：

Why Milliseconds Matter:

为何如此重要：

100ms of latency costs Amazon 1% of its Sales
100毫秒的延迟使亚马逊损失了其销售收入的1％
500ms of latency costs Google 10% of its traffic
500毫秒的延迟会花费Google 10％的流量
10 seconds: the attention span of a digital consumer
10秒：数字消费者的注意力跨度

It’s a race against time for you to keep your audience engaged. At any given step in their journey, users will churn if they sense stagnation – especially so with Search, where they have already subconsciously benchmarked your search experience against Google & Amazon.

为了让观众保持参与，这是一场与时间的竞赛。在旅程的任何特定阶段，如果用户感到停滞不前，就会流连忘返-特别是对于Search，他们已经下意识地将您的搜索体验与Google和Amazon进行了基准比较。

You’re either as fast as users expect, and they won’t even notice it, or you’re slower, and they will.

您要么像用户期望的那样快，他们甚至不会注意到它，要么您变慢了，他们就会。

In a conversation, if someone responds to your question quickly, the conversation continues fluidly; if someone stares idly at you long enough for you to ask yourself “what’s taking them so long?” the conversation is broken, and the conversation subject changes from what you were interested in to “why is this taking so long?”

在对话中，如果有人快速回答您的问题，则对话会继续流畅进行； 如果有人无所事事地凝视着你，足以让你问自己“那么长的时间了吗？” 对话中断，对话主题从您感兴趣的内容变为“为什么要花这么长时间？”

The “How” is a bit more operational. There are three things that count when it comes to how fast a search query returns results:

“操作方法”更具操作性。关于搜索查询返回结果的速度，有三点很重要：

The distance the query must travel
查询必须经过的距离
The size of the records that must be queried to determine relevance
确定相关性必须查询的记录大小
The complexity of the algorithm used to determine relevance
用于确定相关性的算法的复杂性

For in-house solutions, the distance of the query to a user depends on where you keep your hosted site servers. There’s no point in having servers all over the world to optimize site load speed, so you’ll want to replicate your search solution across key markets to optimize search speed.

对于内部解决方案，查询到用户的距离取决于您保留托管站点服务器的位置。在世界各地拥有服务器来优化站点加载速度是没有意义的，因此您需要在关键市场上复制搜索解决方案以优化搜索速度。

The blink of an eye is roughly 180 milliseconds

眨眼大约是180毫秒

Creating Instant search – an as-you-type search experience where results appear immediately following the keystroke – requires delivering results faster than the blink of an eye. You should aim for 99% of your queries displaying in under 35ms.

创建即时搜索-一种按需输入的搜索体验，其中在按键后结果立即显示-要求提供结果的时间比眨眼之间要快。您的目标是在35毫秒内显示99％的查询。

For hosted solutions like Algolia, you’ll want to make sure you have a Distributed Search Network (DSN) – a CDN for your search bar – which allows you to replicate your search index across up to 50 servers in every corner of the globe, depending on where your users are coming from.

对于像Algolia这样的托管解决方案，您需要确保拥有分布式搜索网络 (DSN)–搜索栏的CDN –允许您在全球每个角落的多达50台服务器上复制搜索索引，取决于您的用户来自何处。

保持那些记录小 (Keep Those Records Small)

The smaller the record size, the faster it can be passed through the engine. It’s faster for search engines like Algolia to search 1 Million one-paragraph text blocks than 10,000 100-Paragraph text blocks — It can also increase relevancy, pointing to where in a given text the query is matched.

记录大小越小，记录通过引擎的速度就越快。与Algolia这样的搜索引擎相比，搜索1百万个一段落文本块要比10,000个100段文本块要快得多-它也可以提高相关性，指出查询在给定文本中的匹配位置。

Keeping a lean search machine means having a lean search algorithm. Algolia uses a tie-breaking algorithm – a series of simple nested functions which each trigger successively only when there is a tie in the preceding function’s ranking output. That means that if your first function – say, for GeoSearch, distance from the user – returns a unique rank for each result with no ties, that function stops there, quickly and without compromise on relevancy.

保持精益搜索机意味着拥有精益搜索算法。 Algolia使用打破平局的算法-一系列简单的嵌套函数，每个嵌套函数仅在前一个函数的排名输出中出现平局时才连续触发。这意味着，如果您的第一个功能(例如，对于GeoSearch，与用户的距离)为每个结果返回唯一的排名而没有任何联系，则该功能会在此处快速，不影响相关性地停止在那里。

Search engine frameworks like Elastic Search & Solr use floating point score algorithms, which developers write themselves. Those can start out simple enough, but with each iteration and improvement – a little typo-tolerance here, a little synonym handling there – the algorithm gets more bulky & slower, without necessarily being more relevant.

诸如Elastic Search＆Solr之类的搜索引擎框架使用浮点分数算法，开发人员可以自己编写。它们可以很简单地开始，但是随着每次迭代和改进(这里有点打字错误，那里有些同义词处理)，该算法变得更大，更慢，并且不一定更相关。

关联 (Relevance)

Relevance means finding what you’re looking for. Two things go into relevance:

相关性意味着找到您想要的东西。有两件事是相关的：

Textual relevance: How well the query matches the searchable words of a record

文本相关性 ：查询与记录中可搜索词的匹配程度
Business relevance (i.e. your business metrics): number of sales/views/likes, featured objects, price, date…

业务相关性 (即您的业务指标)：销售/视图/喜欢次数，特色对象，价格，日期…

Not all search engines are built the same, and likewise, every search experience will have its own unique balance of textual & business relevance. The most important thing is that the search framework that you use be built to handle these two different types of data points.

并非所有搜索引擎的构建都是相同的，同样，每种搜索体验都将在文本和业务相关性方面拥有自己独特的平衡。最重要的是，构建了用于处理这两种不同类型的数据点的搜索框架。

In addition to ordering by business/vanity metrics that matter most to your users, you’ll want to make sure you handle some of the more semantic challenges:

除了按照对用户最重要的业务/虚荣度指标进行排序以外，您还需要确保处理一些其他语义上的挑战：

Typo-Tolerance: don’t let autocorrect ruin a perfectly good search experience.

错字率 ：请勿让自动校正破坏完美的搜索体验。
Synonyms: British users searching for a “jumper” should find your wonderful collection of “sweaters.”

同义词 ：搜索“跳线”的英国用户应该会找到您的“毛衣”的绝妙收藏。
Long Queries: users searching for “faded blue jeans” shouldn’t come up empty handed just because you only have “faded jeans.”

长查询 ：搜索“褪色的蓝色牛仔裤”的用户不应仅仅因为您只有“褪色的牛仔裤”而空手而归。

Relevance is unique for each search experience, and understanding what your users are searching for, finding & not finding can be more valuable than any tweak or modification to your ranking algorithm.

关联性对于每种搜索体验而言都是唯一的，与对您的排名算法进行任何调整或修改相比，了解用户正在搜索的内容，查找与未查找的内容更有价值。

Algolia provides all users with an analytics dashboard, which, in addition to providing key figures, helps you find queries that come up with no or few results – this can often be the greatest source of frustration for users, and the best place to start when deciding where on your site to focus your energy. Additionally, because Algolia uses a tie-breaking algorithm and not a floating point score, relevancy can be fine-tuned & iterated upon directly inside the dashboard without needing to touch code with every little change.

Algolia为所有用户提供了一个分析仪表板，该仪表板除了提供关键指标外，还可以帮助您找到没有结果或结果很少的查询-这通常可能是使用户感到沮丧的最大原因，也是在以下情况下的最佳起点决定在您的网站上集中精力。此外，由于Algolia使用抢七式算法而不是浮点得分，因此可以直接在仪表板内部微调和迭代相关性，而无需每次更改都无需触摸代码。

设计 (Design)

The UI/UX of your search bar is perhaps the most important pillar, which is often the most neglected – namely because search is often focused around ranking optimization & speed, instead of experience. But what good is it to have lightning fast, relevant search if the user has to press ‘enter’ to get search results each time?

搜索栏的UI / UX可能是最重要的Struts，而它往往是最被忽视的Struts-即因为搜索通常侧重于优化和速度排名，而不是体验。但是，如果用户每次必须按“ enter”键来获得搜索结果，那么进行快速，相关的搜索有什么好处？

Here are a few of our best practices for a great search experience:

以下是我们提供最佳搜索体验的一些最佳做法：

As-you-type search results: every keystroke should be producing results. When combined with great speed, the user feels like the search results are refining themselves with each keystroke.

键入搜索结果 ：每次击键都应产生结果。当以极高的速度结合使用时，用户会感觉到每次按键都使搜索结果更加完善。
Highlight results: Understanding ‘why’ you’re getting the response you’re getting can be just as important as getting the right results themselves. Did the top result only come up because the query appears in a secondary attribute for that record? Display it conditionally and highlight so the user knows what why they’re seeing given results.

突出结果 ：了解“为什么”得到的响应与自己获得正确的结果一样重要。是否仅因为查询出现在该记录的辅助属性中才出现最高结果？有条件地显示它并突出显示，以便用户知道为什么看到给定的结果。
Provide context in results: If you’re using business metrics – popularity, price, availability – in your ranking algorithm, make sure the user sees that by displaying those metrics inside the search results. Think of it as highlighting your ranking formula!

在结果中提供上下文 ：如果您在排名算法中使用业务指标(受欢迎程度，价格，可用性)，请确保用户通过在搜索结果中显示这些指标来看到这些指标。将其视为突出您的排名公式！
Placeholder Text: Let your users know what they can search for by leaving placeholder text inside the search bar before they start typing – i.e: “George Clooney, No Country for Old Men, Drama, 1920s”

占位符文本 ：让您的用户知道要搜索的内容，方法是在开始键入之前在搜索栏中保留占位符文本，例如：“乔治·克鲁尼(George Clooney)，没有老人的国家，戏剧，1920年代”
Multi-Category Search: The more ways the user has to be successful, the higher the chances they’ll find what they’re looking for. Even if you’re just searching through articles in a WordPress blog, allowing users to search by Author, Category, Title & Tag mean that you let the user search how they want, instead of them having to learn how your search works.

多类别搜索 ：用户获得成功的方式越多，找到所需内容的机会就越高。即使您只是在WordPress博客中搜索文章，允许用户按“作者”，“类别”，“标题和标签”进行搜索也意味着您可以让用户搜索所需的内容，而不必让他们学习搜索的工作方式。

Like most creative professions, underneath the hood, design is a series of very concrete steps. The checklist is there for you to have beautiful search, and as you try out your favorite search bars (even SitePoint), keep these design elements in the back of your mind. What is missing? What questions do you have? How could design answer them?

像大多数创意专业一样，在引擎盖下，设计是一系列非常具体的步骤。您可以在清单中进行漂亮的搜索，并在尝试使用自己喜欢的搜索栏(甚至是SitePoint)时，将这些设计元素放在脑海中。什么不见了？你有什么问题？设计如何回答他们？

结论 (Conclusion)

For your end-users, search is instinctual – it works or it doesn’t. For you, search can be easy, if you know what to look for. You don’t have to be a search expert to have a great search experience. At Algolia, we believe the future of search is in great UX/UI, which is why Algolia’s integrations come pre configured with design best practices. The hosted search platform takes care of Speed for you, and makes tweaking relevance something that anyone can do, so that you can focus on building a great app experience.

对于您的最终用户而言，搜索是本能的–它起作用或不起作用。对您来说，如果您知道要查找的内容，搜索将很容易。您不必成为搜索专家即可拥有出色的搜索体验。在Algolia，我们相信搜索的未来在于出色的UX / UI中，这就是为什么Algolia的集成已预先配置了设计最佳实践的原因。托管的搜索平台会为您处理Speed，并调整相关性，任何人都可以做，以便您专注于构建出色的应用程序体验。

No matter how you build search, the bar remains the same. And the pillars that define great search – speed, relevance & design – are not dictated by Algolia, by Google or by any other player. They have been dictated by users, who expect a search experience that just works, whether you’re Google, Amazon, or any other app.

无论您如何构建搜索，栏都保持不变。定义出色搜索的Struts-速度，相关性和设计-并非由Algolia，Google或任何其他参与者决定。它们是由用户决定的，无论您是Google，Amazon还是任何其他应用程序，用户都希望获得有效的搜索体验。

翻译自: https://www.sitepoint.com/three-pillars-of-search/