Six months ago, bustling cities with flourishing businesses and communities across the globe came to an unprecedented mandatory halt. As consumers everywhere adjusted accordingly to their new way of life, so changed their preferences, purchasing decisions — and almost every other daily activity as we know it. As cities begin to reopen, businesses everywhere must adapt to these changes to properly understand and connect with the 2020 consumer. To stay ahead of the competition and fill the gap in productivity and innovation that online workforces now face, many organizations are looking to Artificial Intelligence, and the pandemic continues to shed light on the value it can bring.

六个月前，全球商业和社区蓬勃发展的繁华城市空前停顿。 由于各地的消费者都在适应他们的新生活方式，因此改变了他们的喜好，购买决定以及几乎所有我们知道的日常活动。 随着城市开始重新开放，各地企业都必须适应这些变化，以正确理解并与2020年消费者建立联系。 为了在竞争中保持领先地位并填补在线员工现在面临的生产力和创新差距，许多组织都在寻求人工智能，而这种流行病继续阐明了它可以带来的价值。

Industry experts continually look for innovative ways to capitalize on AI and Machine Learning, specifically to leverage existing and future (consumer) data. Now, with a pandemic that has forced everyone online there has never been more consumer data this easily accessible in history, and the use of AI in marketing is accelerating at a tremendous speed.

行业专家一直在寻找创新方法来利用AI和机器学习，特别是利用现有和未来(消费者)数据。 现在，由于大流行病已迫使所有人上线，历史上从未有如此容易获得的消费者数据，而且AI在营销中的使用正以惊人的速度加速发展。

According to a 2018 study by MemSQL, more than 60% of marketers say that Artificial Intelligence is the most important aspect of their data strategy. So, how does this all work?

根据MemSQL在2018年进行的一项研究，超过60％的营销人员表示人工智能是其数据战略中最重要的方面。 那么，这一切如何运作？

We have narrowed it down to 6 of the most interesting existing use cases for AI in marketing:

我们已将其范围缩小为市场营销中AI最有趣的现有用例中的6个：

1. Recommendation Engines

   推荐引擎

Recommendation engines most likely appear in your day-to-day online activities. This form of Artificial Intelligence predicts what current and potential customers might like, especially when there are a lot of product choices. McKinsey has estimated that 35% of consumer purchases from Amazon originate from product recommendations. Another e-commerce giant, Alibaba Group, utilizes recommendations based on customers past transactions, browsing history, product feedback, bookmarks and other online behavior. This powerful AI tool has proven to have a strong ROI as we see it being used amongst many major brands including Netflix and Youtube.

推荐引擎最有可能出现在您的日常在线活动中。 这种形式的人工智能可以预测当前和潜在客户的需求，尤其是在有很多产品选择的情况下。 麦肯锡估计，从亚马逊购买的消费者中有35％来自产品推荐。 另一个电子商务巨头阿里巴巴集团(Alibaba Group)根据客户过去的交易，浏览历史记录，产品反馈，书签和其他在线行为来利用推荐。 正如我们所看到的，该强大的AI工具已在Netflix和Youtube等许多主要品牌中使用，具有很高的投资回报率。

2. Forecasting

2.预测

Typically, marketers utilize historical data to forecast future purchasing behavior. However, with machine learning assisted forecasting, marketers are able to access up to the minute data for more accurate predictions. While this seems very granular, this type of forecasting allows marketers to get ahead and predict the future of purchasing decisions with far better accuracy.

通常，营销人员利用历史数据来预测未来的购买行为。 但是，借助机器学习辅助的预测，营销人员能够访问最新数据以进行更准确的预测。 尽管这看起来非常精细，但是这种类型的预测使营销人员能够领先一步，并以更高的准确性预测购买决策的未来。

3. Content Generation

3.内容生成

Ah, to be a content marketer in 2020. The content marketing industry is a force to be reckoned with, predicted to be worth over 412 billion by 2021. Given the circumstances we all face with the global pandemic, content creation, digital marketing and everything in between is even more important for a strong marketing strategy. Content creation can be utilized to build brand awareness, connect with existing and future customers and to establish relevance and authority in any space. Artificial Intelligence leveraging text generation or assistance as natural language processing — reading, deciphering, understanding and making sense of the human languages — is becoming more mainstream. The content marketing institute reveals that when comparing content marketing to paid research, content marketing gets 3x the number of leads per dollar spent.

嗯，要成为2020年的内容营销商。内容营销行业是一支不容小force的力量，预计到2021年其价值将超过4120亿美元。考虑到我们所有人都面临着全球大流行，内容创作，数字营销等所有问题，对于强大的营销策略而言，两者之间的关系更为重要。 内容创作可用于建立品牌知名度，与现有和未来的客户建立联系并在任何空间建立相关性和权威性。 人工智能将文本生成或协助作为自然语言处理(阅读，解密，理解和理解人类语言)正在变得越来越主流。 内容营销机构透露，将内容营销与付费研究进行比较时，内容营销的潜在客户数量是每花费1美元获得的潜在客户数量的3倍。

Tools like Wordsmith and Quoll are being used by Forbes and Associated press to write content using templates and fill in the blanks to enter relevant data and keywords. These tools are able to generate written content that reads like it was written by a human. While the content that gets generated is not that of a Harvard level written essay, these tools set the base to produce an article quickly that may have otherwise taken 4 hours to write.

福布斯和美联社正使用Wordsmith和Quoll之类的工具来使用模板编写内容，并填写空白以输入相关数据和关键字。 这些工具能够生成书面内容，其内容类似于人类编写的内容。 虽然生成的内容不是哈佛水平的书面论文的内容，但是这些工具为快速产生一篇文章奠定了基础，否则可能要花4个小时才能写完。

4. Address Churn

4.地址流失

Customers naturally come and go. However, for any business, particularly those that are digital or online, retaining customers is key to long-term success. Acquiring new customers is also 5 to 25 times more expensive than keeping existing customers. What if AI could help to prevent churn by identifying weak customers that are more likely to leave, and address these customers specifically to keep their business?

顾客自然来来往往。 但是，对于任何业务，特别是数字或在线业务，保留客户是长期成功的关键。 获取新客户的费用也比保留现有客户的费用高5至25倍。 如果AI通过识别更有可能离开的弱势客户并专门针对这些客户以保持业务来帮助防止流失，该怎么办？

Online retailer Showroomprive.com uses an ML powered churn prediction algorithm that spots churners with about 77% accuracy. The algorithm allows for Showroomprive to:

在线零售商Showroomprive.com使用ML支持的客户流失预测算法，该算法以约77％的准确度识别客户流失。 该算法允许Showroomprive执行以下操作：

• detect customers that no longer make purchases on the site — depending on the timeframe of previous purchases检测不再在该网站上进行购买的客户-根据先前购买的时间范围
• Refine the targeting of marketing campaigns完善营销活动的定位

This AI powered tool uses predictive analytics to detect the customers that are the most likely to stop buying products on their site.

这个基于AI的工具使用预测分析来检测最有可能停止在其网站上购买产品的客户。

5. RankBrain (Google) and Conversational Search Requests

5. RankBrain (Google)和会话搜索请求

Every marketer understands the value behind solid SEO. Thanks to Artificial Intelligence, there are ways to improve our search results to be more relevant in respect to what information we are truly looking for. RankBrain, created by Google, is a machine learning algorithm that was created to deliver more relevant search results. RankBrain interprets search results and with the power of AI, delivers the best results based on what it interprets from the language input. For example, if one were to input “president” into Google search (while in the US) , Rankbrain could interpret this as a search about our current United States President and will provide information accordingly, rather than producing information about the US government.

每个营销人员都了解扎实的SEO背后的价值。 多亏了人工智能，有很多方法可以改善搜索结果，使其与我们真正寻找的信息更加相关。 由Google创建的RankBrain是一种机器学习算法，旨在提供更相关的搜索结果。 RankBrain解释搜索结果，并借助AI的功能，根据其对语言输入的解释提供最佳结果。 例如，如果一个人(在美国)将“总统”输入到Google搜索中，那么Rankbrain可以将其解释为对我们现任美国总统的搜索，并将相应地提供信息，而不是提供有关美国政府的信息。

6. Chatbots

6.聊天机器人

According to a Facebook host of data, 2 billion messages are sent between people and businesses monthly, and 56% of people would rather message than call customer service — enter Chatbots. A Chatbot is an AI software application that simulates an online conversation with a user in a natural language via text or speech. Chatbots are attracting serious attention as they represent some of the most advanced and promising interactions between humans and machines. Chatbots are used by many businesses for a variety of tasks today and leverage chat mediums such as SMS, website chat windows, and social messaging to respond to messages. There is an argument to be made for Chatbots and predicted use cases include making dinner reservations, answering simple questions and resolving complaints or problems.

根据Facebook的数据来源，人与企业之间每月发送20亿条消息，而56％的人宁愿消息而不是打电话给客户服务-输入Chatbots。 Chatbot是一种AI软件应用程序，它可以通过文本或语音以自然语言模拟与用户的在线对话。 聊天机器人吸引了人们的极大关注，因为它们代表了人机之间最先进，最有希望的互动。 如今，许多企业将聊天机器人用于各种任务，并利用聊天介质(例如SMS，网站聊天窗口和社交消息)来响应消息。 对于聊天机器人，有一个论点，预计的用例包括预订晚餐，回答简单的问题以及解决投诉或问题。

The examples above are just 6 of many that are active today amongst businesses. Artificial Intelligence can also improve hyper-targeted advertising, price optimization and web design. AI in marketing can harness the power of existing and real time data to better predict and understand consumer behavior. It can be used to achieve a better understanding of who you are to your customers, what emotions you trigger and even what topics and emotions generate the most interest in relation to your brand.

上面的示例只是当今在企业中活跃的众多示例中的6个。 人工智能还可以改善超针对性的广告，价格优化和网页设计。 营销中的AI可以利用现有和实时数据的力量来更好地预测和了解消费者行为。 它可用于更好地了解您对客户的身份，触发的情感，甚至是与您的品牌有关的最大话题和情感。

What is so incredible about this transformation is while we allow AI to manage the more granular and never-ending pieces of information, our jobs become different — and easier. We can collaborate with these tools, allowing for better organization, targeting and time-management. Artificial Intelligence is paving the way for incredible innovation in many segments of business, and these improvements in the marketing world are just a small piece of a much greater transformation.

这种转变令人难以置信的是，当我们允许AI管理更细粒度，永无止境的信息时，我们的工作将变得更加轻松。 我们可以与这些工具进行协作，从而实现更好的组织，定位和时间管理。 人工智能为许多业务领域的惊人创新铺平了道路，而营销领域的这些改进只是更大转变中的一小部分。