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A.I. Content Intelligence Could Mean 90% Creativity/10% Perspiration

The advertising maven Dave Trott once professed “Creativity may well be the last legal unfair competitive advantage we can take to run over the competition.” These are important words to keep in mind because it is getting harder and harder for brands to differentiate themselves from the competition. The marketing process has always been expensive and highly laborious. Anything that reduces cost and increases automation should help free up talent, which will help them focus on the most important thing in marketing today — creativity.

Today, content creation and marketing automation software are becoming ubiquitous. A tool like Canva provides designers with cheap software to create head-turning collateral. Mailchimp is a free marketing automation platform. Open-source CRM solutions abound and there are plenty of social platforms that are easy to use and offer companies wide exposure for minimal investment. In an environment where everyone has access to cheap tools, creativity is one of the only things that can make a brand stand out.

Snowed Under by Personalization

Personalization marketing has created an almost insatiable demand for content that is needed to fill the multitude of channels used by today’s sophisticated consumers. In its article The Magic of AI in a content-driven world. Using AI to create content faster, the Adobe Enterprise Content Team argues that we’re currently in the midst of a content explosion. “Consumers expect to have personalized, relevant experiences at all times, in all places, and on all platforms,” says the Adobe Enterprise Content Team. This is, of course, an extremely difficult thing to pull off. Marketing professionals are feeling the heat because the demands of marketing in real-time, on multiple channels and devices, are increasing exponentially.

An Adobe/IDC survey revealed 85% of marketing professionals felt burdened by the demand of creating assets and delivering more marketing campaigns than they had to do just a few short years ago. They were also under pressure to deliver these campaigns at a faster pace than in the past. In fact, over two-thirds of respondents said they had to create ten times more content to support the growing number of channels their personalization marketing required. This growing demand is increasing in complexity and the costs associated with them are rising as well. However, there might be help on the horizon and that might be with the help of AI.

Today, designers can spend hours searching for just the right image to use in a particular marketing piece, and that doesn’t count the time required to manipulate and crop the image, set it in the perfect layout, attach the best headline, and then publish it to a website, a social channel, or even attach it to an email that will be sent directly to the client. Serving the right content to the right person at the right time on the right channel takes an enormous amount of time. Of course, the cost for all this work adds up too, as does the cost of the photo and/or video shoots required to create all this content.

AI and machine learning can provide marketers with more efficient ways to find, tag, use, and reuse their digital assets. Tagging an organization’s content has a secondary benefit as well — by defining assets on the granular level, personalization marketing is simplified. If a marketer can figure out why a customer is responding to a piece of collateral by breaking the content down into its granular components, it should make future marketing to that customer much more effective. This is what Adobe is now doing with its Sensei product.

Content Intelligence

According to the Adobe Sensei Team, AI can help businesses create more relevant content as well as build more engaging experiences across a customer’s buying journey at the speed today’s customers expect. Adobe’s State of Creativity in Business 2017 survey found that 40 percent of creatives are already using AI in photo and design retouching. On the creative side, AI can automate tedious tasks like labeling sets of digital content. It can identify and organize assets or adjust and refine content for specific channels, contends the Adobe Sensei Team.

On the audience level, AI can help organizations “better understand which audiences respond to which content,” says Adobe. AI can also reveal how often people prefer to receive emails, so organizations can deliver the experiences their customers want while fully respecting their preferences and privacy, contend the Sensei Team.

Since AI technology gets smarter and smarter with use, it also can play a valuable role in automating the content creation process. AI can help marketers choose the best image from amongst thousands, ensuring the best visual attributes are utilized. NLP can read text to identify emotional sentiment in images and/or text as well.

In his article Machine Learning and AI: If Only My Computer Had a Brain Wired for Business, Michael Klein claims AI can help brands understand the focal — or sellable — point of hero images, and then “auto-crop them for best performance based on an understanding of millions of assets with similar meta-data.” AI not only enhances creativity but also enables a level of responsiveness and efficiency that hasn’t been available for marketers up until now, contends Klein.

In today’s incredibly fast-paced marketing environment, designers don’t have the time to tag the thousands upon thousands of images housed in their libraries. Even if they did, manual labor like this isn’t always the best use of an employee’s time. According to IDC, one-third of marketing assets go unused or underutilized because there isn’t enough manpower to properly tag and archive the images. To address this issue, Adobe created “Auto Tag”, an Adobe Sensei capability that automatically tags images with keywords. “The Auto Tag service is used to power the Smart Tags features in Adobe Experience Manager, Photo Search in Adobe Lightroom, and Visual Search in Adobe Stock,” explains the Adobe Sensei Team.

Because Adobe itself has massive amounts of content and data assets, from high-resolution images to high-definition video, the Adobe Sensei technology is built upon decades of image libraries and can learn to automatically identify what’s in a photo. It’s not just what the object in the photo is, but also the concept of the image, including context, quality, and style, say the Adobe Sensei Team. Sensei’s auto-phrasing service can reveal how each tag scores for prominence. This helps the technology build simple sentences or captions that more accurately describe an image or a video, states the Adobe Sensei Team.

Using the Sensei framework, marketers can train AI and machine learning models to create auto tags unique to their industry. Manually tagging images with descriptive and contextual metadata is the kind of job in which machines excel. “AI-powered smart tags automatically provide consistent, content-based metadata in seconds,” claims the Adobe Enterprise Content team. This process can save an organization hours of manual labor time. As Adobe’s Senior Product Marketing Manager Elliot Sedegah trenchantly puts it, “Computers will not complain about having to add metadata, they will not try to avoid it and they will work just as hard on the hundred-thousandth image as on the first.”

Identifying brand characteristics like the company insignia or designs could help marketers adhere to specific brand standards. If a company runs a social media feed through Adobe Sensei, the system will tag places where a brand is pictured, even if there is no mention of the brand. This allows companies to see which products and/or services are trending and how wide their social media reach is.

According to Adobe’s Indelible content, incredible experiences, marketers want to build once and deliver everywhere, with content automatically adjusting to fit whatever channel it is being surfaced through. Machine learning can do this. For example, Adobe’s smart summarization tool can customize a blog containing almost any kind of content and turn it into a useful news clip or as the main body of an email.

At the recent Adobe Summit, Adobe released a sneak peek of its Catchy Content solution that “analyzes images and text in real-time to identify the attributes that most resonate with customers: colors, content, reading level, and more.” In his Forrester article about the event, Adobe “Catchy Content” Shows How Content Intelligence Powers Personalization, Nick Barber states Adobe believes catchy content lets marketers recognize the types of content that a particular audience favors. From this information, marketers can then deliver better customer experiences. Barber sees the solution working in three steps:

  1. Data is gathered on the types of content that engage the customer, including everything from product copy, images, and/or videos, including the meaning of the messages.
  2. The attributes of the content are recognized, understood, and logged.
  3. Relevant content is then matched up with the marketing content, including the segment, persona, or individual that brands are looking to target.

Barber contends this is an important milestone for personalization because it shows content intelligence is just as important as customer data, that personalization isn’t all about selling products, and this process paves the way for content automation.


Most marketers would agree that implementing content at scale is exceptionally difficult. When brands successfully consolidate their assets into a content hub or digital asset management (DAM) solution, they also create a single source of the truth across an entire organization, says Barber. Only then will they be able to match content with experiences, he adds.

When a brand knows a certain image is performing well, it can surface other similar images to its customers, states Barber. “When it knows that the tone or sentiment of copy resonates with a type of buyer, it could match up variants of that copy with different segments. Does this mean content creators are out of jobs? No, of course not. But it means that the mundane task of creating content variants or filling in metadata could be done by a bot, while higher-level creative work can be done by humans,” says Barber.

Circling back to creativity, Thomas Edison’s once stated success was 10% inspiration and 90% perspiration. AI might just upend that ratio, removing much of the mundane work humans once did — and always hated doing — leaving them with the much more rewarding tasks of inspiration and creativity. I think we’d all take that ratio, no matter how unfair it might seem to those we’re leaning on to do the grunt work.



Product AI is a magazine that covers AI product/project management, AI business cases and reference architectures. We invite product experts and solution architects to share their knowledge here.

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Andrew W. Pearson

Andrew Pearson is the MD of Intelligencia, a software consulting company. Speaker, author, columnist, Pearson writes about IT issues like AI, CI, and analytics.