{"id":8531,"date":"2021-10-22T12:56:43","date_gmt":"2021-10-22T12:56:43","guid":{"rendered":"http:\/\/TheNextWeb=1370774"},"modified":"2021-10-22T12:56:43","modified_gmt":"2021-10-22T12:56:43","slug":"mailchimp-wants-to-optimize-your-email-campaigns-using-ai-heres-how","status":"publish","type":"post","link":"https:\/\/www.londonchiropracter.com\/?p=8531","title":{"rendered":"Mailchimp wants to optimize your email campaigns using AI \u2014 here\u2019s how"},"content":{"rendered":"\n<p>Earlier this month, Mailchimp released Content Optimizer, a new product that uses artificial intelligence to help improve the performance of email marketing campaigns.<\/p>\n<p>Thanks to its vast trove of data, Mailchimp is in a unique position to discover common patterns of successful marketing campaigns. Content Optimizer taps into that data and uses machine learning models and business rules to predict the quality of email campaigns and provide suggestions on how to improve content, layout, and imagery.<\/p>\n<p>This is not Mailchimp\u2019s first foray into using AI for content marketing, but it might be its most impactful effort in the field. Leading the effort to develop Content Optimizer is John Wolf, Product Manager of Smart Content at Mailchimp. Wolf was the founder of Inspector 6, a startup acquired by Mailchimp in 2020. The technology and experience that Inspector 6 brought to Mailchimp played an important role in the development of Content Optimizer.<\/p>\n<p>In an interview with TechTalks, Wolf provided some behind-the-scenes details on the vision and development process of Content Optimizer and shared insights on how AI is changing the future of content marketing.<\/p>\n<h2>The vision for AI-powered content marketing<\/h2>\n<p><figure class=\"post-image post-mediaBleed aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370776 js-lazy\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email.jpeg\" alt=\"email\" width=\"696\" height=\"392\" sizes=\"(max-width: 696px) 100vw, 696px\" data-srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email-280x158.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email-240x135.jpeg 240w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email-479x270.jpeg 479w\"><noscript><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370776\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email.jpeg\" alt=\"email\" width=\"696\" height=\"392\" srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email-280x158.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email-240x135.jpeg 240w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/email-479x270.jpeg 479w\"><\/noscript><\/figure>\n<\/p>\n<p>Like many products, the idea for Content Optimizer started with someone feeling the pain. Wolf spotted the need for AI-powered content marketing before founding Inspector 6, when he was Chief Marketing Officer at Intradiem, a software development company.<\/p>\n<p>Like all companies, Intradiem needed great marketing content. But the process was difficult, and measuring quality and success was very subjective.<\/p>\n<p>\u201cThe creative process was completely dominated by opinions with little data. It was very manual, very labor-intensive, lots of cycles to get the creative right, and I was thinking there just has to be another way,\u201d Wolf said.<\/p>\n<p>At the time, machine learning was starting to find real business applications in many sectors. So, Wolf started to think about using ML to optimize the creative process for content marketing.<\/p>\n<p>\u201cThe idea was, what if we could use machine learning to understand marketing content? If a software can understand what story marketing content is telling and how it\u2019s telling it, it can then correlate features with marketing outcomes and start to standardize and add data to much of the creative process and replace those opinions with data,\u201d Wolf said.<\/p>\n<p>In 2017, Wolf founded Inspector 6 with the vision of developing AI-powered content marketing. Inspector 6 became an AI platform that analyzes marketing content to deliver insights and recommendations for improvement.<\/p>\n<h2>Meeting data challenges<\/h2>\n<p>Like all <a href=\"https:\/\/bdtechtalks.com\/2021\/04\/19\/applied-machine-learning-challenges\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">applied machine learning applications<\/a>, marketing content optimization hinges on having large amounts of quality data. Accordingly, Inspector 6\u2019s platform was successful in some areas and met challenges in others.<\/p>\n<figure class=\"post-image post-mediaBleed aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-1370777 js-lazy\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf.jpeg\" alt=\"John Wolf, product manager of smart content at Mailchimp and founder of Inspector 6\" width=\"420\" height=\"420\" sizes=\"(max-width: 420px) 100vw, 420px\" data-srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf.jpeg 420w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-210x210.jpeg 210w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-135x135.jpeg 135w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-96x96.jpeg 96w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-270x270.jpeg 270w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-192x192.jpeg 192w\"><figcaption><a href=\"https:\/\/thenextweb.com\/news\/mailchimp-optimize-email-campaigns-ai-syndication#\" data-url=\"https:\/\/twitter.com\/intent\/tweet?url=https%3A%2F%2Feditorial.thenextweb.com%2Fneural%2F2021%2F10%2F22%2Fmailchimp-optimize-email-campaigns-ai-syndication%2F&amp;via=thenextweb&amp;related=thenextweb&amp;text=Check out this picture on: John Wolf, product manager of smart content at Mailchimp and founder of Inspector 6\" data-title=\"Share John Wolf, product manager of smart content at Mailchimp and founder of Inspector 6 on Twitter\" data-width=\"685\" data-height=\"500\" class=\"post-image-share popitup\" title=\"Share John Wolf, product manager of smart content at Mailchimp and founder of Inspector 6 on Twitter\"><i class=\"icon icon--inline icon--twitter--dark\"><\/i><\/a>John Wolf, product manager of smart content at Mailchimp and founder of Inspector 6<\/figcaption><noscript><img decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-1370777\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf.jpeg\" alt=\"John Wolf, product manager of smart content at Mailchimp and founder of Inspector 6\" width=\"420\" height=\"420\" srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf.jpeg 420w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-210x210.jpeg 210w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-135x135.jpeg 135w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-96x96.jpeg 96w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-270x270.jpeg 270w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/John-Wolf-192x192.jpeg 192w\"><\/noscript><\/figure>\n<p>\u201cOur largest customer was a very big multi-national consumer packaged goods company with 500 brands in 200 countries, and I thought they would have plenty of data to power my predictive models. And I found that it wasn\u2019t necessarily true,\u201d Wolf said. Providing value for small businesses was more difficult since they had even more limited data for training machine learning models.<\/p>\n<p>Before Mailchimp acquired Inspector 6, the two companies entered a partnership. Mailchimp delivers hundreds of billions of emails per year, and through the partnership, the Inspector 6 team got to experience the advantage of training its models on the huge volume of marketing data that Mailchimp has.<\/p>\n<p>\u201cThe amount of data and the breadth of data, everything from marketing content that is selling products and services to content marketing and newsletters and everything in-between, some very high-performing and some just as importantly low-performing\u2014having that depth and breadth of data becomes the key component to delivering a solution like this,\u201d Wolf said.<\/p>\n<p>Recommendations also require context. An analyst would have to know the goal, business vertical, audience, and other information about a marketing campaign before providing feedback on its efficiency. Likewise, machine learning models require context. Fortunately for Mailchimp, the variety and number of customers it has provided ample data to train machine learning models that can perform well across different contexts.<\/p>\n<p>\u201cYou take Mailchimp\u2019s data with 360 billion emails a year that become our training set for this, but then you\u2019d have to slice it by context to really be able to solve this problem,\u201d Wolf said. \u201cSo basically, the 360 billion emails start to become a collection of many individual training sets that are context-specific.\u201d<\/p>\n<h2>Transitioning to Mailchimp<\/h2>\n<p><figure class=\"post-image post-mediaBleed aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370778 js-lazy\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer.jpeg\" alt=\"Mailchimp\" width=\"696\" height=\"392\" sizes=\"(max-width: 696px) 100vw, 696px\" data-srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-280x158.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-240x135.jpeg 240w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-479x270.jpeg 479w\"><noscript><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370778\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer.jpeg\" alt=\"Mailchimp\" width=\"696\" height=\"392\" srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-280x158.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-240x135.jpeg 240w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-479x270.jpeg 479w\"><\/noscript><\/figure>\n<\/p>\n<p>The partnership between Mailchimp and Inspector 6 eventually turned into an acquisition proposal, which became a win-win situation for both companies.<\/p>\n<p>Mailchimp\u2019s data and infrastructure gave the Inspector 6 team the opportunity to expand its application to a wider base of customers<\/p>\n<p>\u201cHaving gone through the experience of knowing how much data my predictive models were going to require and how much data Mailchimp had, I thought it could be really interesting to now solve this problem that I\u2019m solving mostly for a handful of large multinationals for millions or tens of millions of small businesses, which is more aligned with my passions,\u201d Wolf said.<\/p>\n<p>On the other hand, Mailchimp got to boost its AI efforts by acquiring a tried-and-tested backend technology stack for predicting marketing campaign outcomes and a team of engineers who were focused on the intersection of marketing, computer science, and data science.<\/p>\n<p>\u201cMailchimp has experience in all of those areas, but to have a focus on solving this problem at that intersection is what Mailchimp was most interested in acquiring from a talent standpoint,\u201d Wolf said.<\/p>\n<p>Inspector 6 had architected its technology as individual microservices on Amazon Web Services. The system ingests a marketing asset, and the individual microservices independently do their job to analyze it.<\/p>\n<p>Mailchimp, on the other hand, uses the Google Cloud Platform. So, the services had to be transferred from one cloud platform to another. Fortunately, before the acquisition, Mailchimp had undergone a massive project to port all their data into Google BigQuery, a cloud-based data warehouse that makes it easy to manage large stores of information and use them in data analysis and machine learning pipelines. Mailchimp also uses other GCP products such as Dataflow, a streaming analytics service that creates dynamic views of real-time and stored data in very efficient ways.<\/p>\n<p>This made it much easier to integrate Inspector 6\u2019s services into Mailchimp\u2019s cloud infrastructure.<\/p>\n<p>\u201cFrom a technology standpoint, we went from one collection of microservices to another, and that worked pretty well,\u201d Wolf said.<\/p>\n<p>Inspector 6\u2019s microservices are an enabling technology. They are integrated into the backend of Mailchimp\u2019s system and offered through frontend products. The services started with providing reporting services to Mailchimp but gradually developed into becoming a generator of content insights through frontend product groups. And Wolf\u2019s vision of AI-powered optimization of marketing campaigns, which kicked off Inspector 6, eventually became Mailchimp\u2019s Content Optimizer.<\/p>\n<h2>Machine learning and business rules<\/h2>\n<p><figure class=\"post-image post-mediaBleed aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370779 js-lazy\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1.jpeg\" alt=\"Mailchimp\" width=\"696\" height=\"392\" sizes=\"(max-width: 696px) 100vw, 696px\" data-srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1-280x158.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1-240x135.jpeg 240w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1-479x270.jpeg 479w\"><noscript><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370779\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1.jpeg\" alt=\"Mailchimp\" width=\"696\" height=\"392\" srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1-280x158.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1-240x135.jpeg 240w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-dashboard-1-479x270.jpeg 479w\"><\/noscript><\/figure>\n<\/p>\n<p>Content Optimizer provides scorecards that reflect the overall content quality of marketing emails and the number of best practices in each analysis category, like skimmability and layout. All users can access the content scorecard. Premium users also get actionable recommendations to improve their content.<\/p>\n<p>\u201cOur north star in solving this problem is improving campaign performance. If we improve campaign performance across our user base by just 10 percent, that will create 190 million incremental online visits to our customers\u2019 businesses,\u201d Wolf said.<\/p>\n<p>Naturally, <a href=\"https:\/\/bdtechtalks.com\/2017\/08\/28\/artificial-intelligence-machine-learning-deep-learning\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">machine learning<\/a> is a key component of Content Optimizer. Behind the scenes, a pipeline of ML models goes to work to parse and analyze different parts of the marketing email and to predict its outcome.<\/p>\n<p>The first batch of models extract the features of different elements of the content such as the tone of writing, the messaging, the layout of the marketing content, and the images used to tell the story.<\/p>\n<p>These features become the input of the next series of machine learning models, which try to predict the outcome and quality of the marketing campaign. In some areas, Content Optimizer combines ML predictions with <a href=\"https:\/\/bdtechtalks.com\/2019\/11\/18\/what-is-symbolic-artificial-intelligence\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">symbolic AI<\/a> to provide recommendations that are more robust and understandable.<\/p>\n<p>\u201cBeyond machine learning, sometimes we use a <a href=\"https:\/\/bdtechtalks.com\/2020\/03\/04\/gary-marcus-hybrid-ai\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">hybrid of machine learning models and business rules<\/a> to detect things,\u201d Wolf said. \u201cSometimes we found that business rules are actually easier to maintain, easier to develop, and in some cases more accurate than machine learning.\u201d<\/p>\n<p>For example, a \u201ccall to action\u201d is a key component of any marketing asset. Most successful call-to-action sentences start with a verb of a certain form. That business rule performs very well, the Content Optimizer team found. So, in this case, they use ML libraries to detect parts of speech in CTA text and feed the parsed data to a rule-based system that evaluates its quality based on static rules.<\/p>\n<h2>Human oversight<\/h2>\n<p><figure class=\"post-image post-mediaBleed aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370781 js-lazy\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen.jpeg\" alt=\"Glasses screen\" width=\"696\" height=\"392\" sizes=\"(max-width: 696px) 100vw, 696px\" data-srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen-280x158.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen-240x135.jpeg 240w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen-479x270.jpeg 479w\"><noscript><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370781\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen.jpeg\" alt=\"Glasses screen\" width=\"696\" height=\"392\" srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen-280x158.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen-240x135.jpeg 240w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/glasses-screen-479x270.jpeg 479w\"><\/noscript><\/figure>\n<\/p>\n<p>While the machine learning models provide valuable insights, they can\u2019t work autonomously yet. For the moment, Mailchimp uses human operators to make sure the output provided by Content Optimizer makes sense and would be in line with recommendations a creative director would make.<\/p>\n<p>\u201cWe go through a traditional predictive modeling exercise, but then there\u2019s a manual vetting process,\u201d Wolf said. \u201cThat creates inefficiency in the process, but we feel it\u2019s necessary at this point.\u201d<\/p>\n<p>There is some controversy around putting human operators behind AI systems. Sometimes, it\u2019s called the \u201c<a href=\"https:\/\/bdtechtalks.com\/2018\/07\/23\/artificial-intelligence-wizard-of-oz\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Wizard of Oz technique<\/a>\u201d or pseudo-AI. But in our conversation, Wolf was very transparent about it, and he believes that it will be an important factor in the success of the product. Moreover, the company is not outsourcing the task and is carrying it out entirely through internal resources.<\/p>\n<p>\u201cIn the early days of applied AI, I think the risk of losing credibility with our users by making a recommendation that is just out of bounds and doesn\u2019t make sense is too great that we want to be incredibly careful and sensitive,\u201d Wolf said.<\/p>\n<p>As the Content Optimizer gathers more data and feedback, the team will gradually finetune the machine learning models and figure out how to make them less reliant on human assistance.<\/p>\n<p>\u201cIt takes time. It adds a labor-intensive element. But it\u2019s an area we\u2019re willing to put people against,\u201d Wolf said.<\/p>\n<p>It\u2019s not guaranteed that the task will be fully automated. But at the end of the day, a machine learning product is, like all products, a tool to solve problems with better outcomes, at greater speeds, and at lower costs. If Content Optimizer helps Mailchimp improve the campaign performance of its clients in a statistically significant and cost-efficient way, then it is a successful product regardless of how much human effort it requires. A notable example in this regard is AdWords, Google\u2019s online advertising platform and its greatest source of revenue. AdWords uses a combination of AI and human evaluation to make sure ads are relevant and compliant with the company\u2019s policies.<\/p>\n<h2>Learning from users<\/h2>\n<p><figure class=\"post-image post-mediaBleed aligncenter\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370782 js-lazy\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1.jpeg\" alt=\"Mailchimp\" width=\"696\" height=\"254\" sizes=\"(max-width: 696px) 100vw, 696px\" data-srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1-280x102.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1-270x99.jpeg 270w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1-540x197.jpeg 540w\"><noscript><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-1370782\" src=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1.jpeg\" alt=\"Mailchimp\" width=\"696\" height=\"254\" srcset=\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1.jpeg 696w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1-280x102.jpeg 280w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1-270x99.jpeg 270w, https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2021\/10\/mailchimp-content-optimizer-1-540x197.jpeg 540w\"><\/noscript><\/figure>\n<\/p>\n<p>One of the key parts of the product management process is learning from users. After launching a product, your hypotheses will be put to test. You\u2019ll usually find pain points that you had overestimated or overlooked and interesting use cases that you had not thought about.<\/p>\n<p>For example, the Content Optimizer showed that in general, Mailchimp users did a better job at typography than the product team had initially estimated. They also found that many marketers struggle with writing simple and concise language.<\/p>\n<p>\u201cIt\u2019s almost like the collective system is the creative director for 14 million active users and you need to be the creative director for them,\u201d Wolf said. \u201cSometimes they\u2019ll surprise you with what they\u2019re great at and what they\u2019re still struggling with.\u201d<\/p>\n<p>One of the positive outcomes of the Content Optimizer, according to Wolf, is that marketers have already become comfortable with using the product.<\/p>\n<p>\u201cWhen you put a new product on the market, you expect a lot of questions about \u2018What is this?\u2019 and \u2018How is it done?\u2019\u201d he said. But when people are using Content Optimizer, their conversations are more about marketing and less about the product, he says, which has been a nice surprise.<\/p>\n<p>\u201cIf they go straight to the marketing conversation and what they\u2019re going to do differently in the future, that\u2019s the exact goal. They\u2019ve taken the product and understood it really well,\u201d Wolf said.<\/p>\n<h2>The future of AI-powered content marketing<\/h2>\n<p>According to Wolf, his team will keep on expanding Content Optimizer to provide a wider variety of recommendations in tone, messaging, brand consistency, imagery, and other areas. The product will also expand from email marketing to other channels such as web pages and social media. The touchpoints will also increase in the future. For the moment, Content Optimizer is a reporting tool, but the team plans to also make it available as a real-time recommendation system that operates while users are editing their content.<\/p>\n<p>Wolf is also interested in getting into computer-generated content in the future.<\/p>\n<p>\u201cEven the most sophisticated marketers in the world would love to spend less time generating content,\u201d he says. \u201cEveryone is familiar with cutting-edge copywriting generative models like <a href=\"https:\/\/bdtechtalks.com\/2020\/08\/17\/openai-gpt-3-commercial-ai\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">GPT-3<\/a>. Those are great. But how do you make sure they\u2019re on-brand, on-message, and they\u2019re optimized in the same way that we\u2019re optimizing human-generated content.\u201d<\/p>\n<p>Generative models <a href=\"https:\/\/bdtechtalks.com\/2020\/09\/14\/guardian-gpt-3-article-ai-fake-news\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">struggle with consistency and coherence<\/a> when used in isolation. But Wolf believes that the combination of the Content Optimizer pipeline and generative models like GPT-3 can create immense value for marketers.<\/p>\n<p>\u201cOur customers spend 28 million hours a year writing copy alone, not even designing and sourcing images. We think with some technologies in the generative space, we can decrease that by 80 percent. That\u2019s 22 million hours we can save our customers,\u201d he said. \u201cThat to me is just staggering and it\u2019s one of the things I found most compelling about selling my business to Mailchimp, just to be able to create value at that scale. We\u2019re really excited about what the future holds and we\u2019re really just getting going.\u201d<\/p>\n<p><i><span>This article was originally published by Ben Dickson on&nbsp;<\/span><\/i><i><span>TechTalks<\/span><\/i><i><span>, a publication that examines trends in technology, how they affect the way we live and do business, and the problems they solve. But we also discuss the evil side of technology, the darker implications of new tech, and what we need to look out for. You can read the original article<\/span>here.<\/i><\/p>\n<p> <a href=\"https:\/\/thenextweb.com\/news\/mailchimp-optimize-email-campaigns-ai-syndication\">Source<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Earlier this month, Mailchimp released Content Optimizer, a new product that uses artificial intelligence to help improve the performance of email marketing campaigns. Thanks to its vast trove of data, Mailchimp is&#8230;<\/p>\n","protected":false},"author":1,"featured_media":8532,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=\/wp\/v2\/posts\/8531"}],"collection":[{"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=8531"}],"version-history":[{"count":0,"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=\/wp\/v2\/posts\/8531\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=\/wp\/v2\/media\/8532"}],"wp:attachment":[{"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8531"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8531"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.londonchiropracter.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8531"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}