15 Ways AI Helps You Conduct Next Gen Digital Experiences at Scale

Artificial intelligence (AI) is transforming marketing, helping professionals become more productive and efficient as well as driving better results. According to Andrew Stephen, the Associate Dean for Research and L’Oréal Professor of Marketing and Head of the Marketing Faculty at the University of Oxford’s Saïd Business School, “The AI revolution in marketing…has been spurred by the influx of affordable and accessible advanced data analytics tools (typically based on machine learning methods), the availability of increasingly rich (albeit still noisy) and extensive datasets, and a growing acceptance among marketers of the potential power of data-driven approaches to marketing decision making.”

With continuous machine learning and deep learning, AI will keep getting smarter, enabling marketers to focus on strategy and results, rather than the mind-numbing minutiae of executing and tracking campaigns across an ever-expanding number of channels. Marketing expert Brian Solis predicts that “over time, machine learning and AI will help modern marketers mature to personalize offerings as customers shop, optimize their journeys and click paths, better predict what they want next, present more personalized recommendations to them, and drive innovation on all fronts.”

Personalized Content is Key

It’s hard to underestimate the importance of content and personalization in helping marketers produce results. In fact, Forrester estimates that content marketing is critical to 70% of marketers, and investments in content and content marketing are up across the board. Forrester predicts that marketers spend 8% of their total budgets on content – exceeding $10 billion in the U.S. alone – and that half of all brands are increasing their investments by 20% or more each year. To maximize those investments, marketers must effectively and efficiently personalize offers and content based on the audience and channel, but as most marketers know, that can quickly become an overwhelming if not impossible task.

That’s because there are so many possible content variations based on the massive amount of data we have collected about our audiences. “All roads lead back to data. Our ability to efficiently collect and process large amounts of data has improved. In fact, last year a report found that 90 percent of the data in the world(i) today has been created in the last two years alone, at 2.5 quintillion bytes of data per day.” The good news is that AI will help manage this increasing complexity and data so you can outperform and differentiate from the competition. For example, AI can help you:

1) Scale your output by making more efficient use of your time and offloading the manual labor.

2) Master complexity by keeping track of everything that is not humanly possible today. At this point, only AI can look at all of the available data—at the same time—and analyze it correctly.

3) Optimize the quality and ROI of content by analyzing results and automatically making adjustments.

15 Ways AI Can Help

As we look across the content lifecycle, there are at least 15 ways that AI helps achieve these goals by automating manual tasks, breaking down data silos to get a clear picture of exactly who your customer is and how to reach them, and analyzing the results of campaigns:

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Let’s look at each of these steps:

Plan & Predict:

  • AI can work in the background to discover and recommend new content such as high-value trending topics and competitive content.
  • Based on all of the data available, AI can help identify much more precise, less idealized personas based on empirical evidence, helping you achieve 1:1 marketing.
  • By analyzing audience preferences, AI can optimize the scheduling and timing of content delivery.

Create:

  • AI can actually write content from data entries, metadata, and other structured information, creating product descriptions, short articles, and other kinds of web copy.
  • Based on what AI knows about the company and its audiences, it can design optimized layouts, basically helping the website design itself.
  • Just by analyzing text, AI can produce video, helping to reduce the costs and labor typically required.

Enrich & Optimize:

  • By taking the human factor out of the equation in content tagging, AI uses semantics to create an accurate taxonomy, appropriate re-use, and related content recommendations.
  • AI can also accurately tag and describe images and graphics, including the alt text that is so helpful to SEO.
  • Speaking of SEO, one of the most manual of marketing disciplines, AI can essentially offload all of the tasks necessary in making a website more search engine friendly.

Target:

  • AI can be used to predict specific content and topics that will resonate with particular users, as well as recommend products based on what it knows about those users.
  • With all of the available data, AI can personalize content specifically targeted to micro-segments, ensuring a relevant and compelling experience.
  • By looking at the results of that targeted content, AI can continuously optimize content for maximum impact to achieve your goals – revenue, AOV, subscribers, conversion rates, upsell rates, dwell time, page views, and more.

Measure:

  • With defined criteria, AI can easily score and manage leads based on where they fall within the buyer journey, their qualification, and propensity to purchase.
  • By aggregating multiple data streams, AI can produce accurate and comprehensive performance reports for any campaign.
  • With that data, AI can also forecast performance, illustrating what is expected to do well, where there may be gaps in results, and recommending specific actions. In time, AI will implement those recommendations automatically to ensure campaigns achieve their goals, without massive human intervention.

AI-Created Content is Compelling and Scales Easily

Let’s look at two specific areas where AI is already optimizing results: content creation and personalization. In regard to content creation, AI is already being used to create well-written and compelling product descriptions compiled from metadata for tens of thousands of products, resulting in a tremendous boost to SEO, user experience, and conversions on the product details page. Imagine having to do that from scratch – it’s simply not possible to do it really well, with perfect grammar and punctuation throughout. But AI can. In fact, even three years ago readers could not distinguish between AI-generated and human-written text(ii) and tools have only gotten better since then, with increasing adoption across all sectors. The Content Marketing Institute reports that machines can create content with simple rule sets and formats such as:

  • Profit and loss summaries
  • Quarterly business reports
  • Hotel descriptions
  • Real-time stock insights
  • Sports game recaps

According to DigiDay UK, The Washington Post published 850 AI-created articles in the past year and Gartner predicts that by 2018, 20% of all business content will be authored by machines.

1:1 AI-Driven Personalization Will Win the Day

With personalization, companies are still figuring out how to obtain a comprehensive and accurate view of their customers on an individual level. “Even though customers are increasingly demanding more personalized engagement, retail brands are still struggling to gain a single view of the customer. Marketing itself is equally disconnected as multi-channel efforts, including email, web, mobile and direct mail lack integration, thereby signifying a lack of customer focus. According to a series of recent studies(iii), only 14% of companies rank themselves as “strong” in achieving a single view of the customer, and less than 10% of top tier retail brands say they’re highly effective at personalization.(iv)”

Given the massive amount of information that is known (as well as unknown) about visitors, it’s extremely difficult to create effective micro-segments manually. But AI can take into account all data sources, including internal, external, and behavioral data, to create an accurate, in-depth picture of your visitor or customer, instead of the chunky, clunky personas of the past. Marvin Chow, VP of Marketing at Google says that “we’re getting closer to a point where campaigns and customer interactions can be made more relevant end-to-end – from planning to creative messaging to media targeting to the retail experience. We will be able to take into account all the signals we have at the customer level, so we can consider not only things like a consumer's color and tone preferences, but also purchase history and contextual relevance. And all of this will be optimized on the fly in real time.”

To support that, vendors are offering data management combined with experience management synchronized across multiple channels to offer audiences the relevant experiences they expect. When driven by AI in the background that’s continuously learning and improving, this becomes a quickly optimized process:

Indeed, when compared to all site visitors, e-Spirit has found that users who engage with AI product recommendations convert 2.3 times more often, with 1.2 times the average order value, adding up to 2.8 times more revenue per user!

From a consumer perspective, AI has already delivered benefits to the user experience. The Economist notes that “the advantages of AI are most visible in firms’ predictions of what users want. Automated recommendations and suggestions are responsible for around three-quarters of what people watch on Netflix, for example, and more than a third of what people buy on Amazon. Facebook, which owns the popular app Instagram, uses machine learning to recognize the content of posts, photos and videos and display relevant ones to users, as well as filter out spam. In the past it ranked posts chronologically, but serving up posts and ads by relevance keeps users more engaged.(v)”

So, how can you take advantage of AI for next gen marketing at scale?

How to Get Started

The first thing you must do in working with AI is to acquire a new mindset. That’s because the shift to AI changes how we work with tools; we must learn to give up control – moving from a pixel-perfect mindset to context-perfect one in which it matters less about what content looks and sounds like and more about the results it produces. In this way, the use of AI moves us from a preview-based mindset to becoming far more KPI-centric.

In a 2017 study of marketing and AI (vi), 29 percent of marketers reported that they believe it’s too difficult to integrate, but that doesn’t need to be the case. The easiest way is to start with ready-made services, lightweight SaaS tools that plug into your existing infrastructure. There are plenty of applications available today that enable all of the 15 ways AI can help marketing that are discussed above (and those are just the tip of the iceberg; more AI-driven apps will surely evolve). These are built on existing AI infrastructure, algorithms, and platforms and services – there’s no need to create them from scratch.

Lastly, think about the role you want AI to play in order to properly embed it within your entire digital experience infrastructure. AI should connect people, technology, and processes so that business users can make the most of their time, budgets, and resources to differentiate content and offerings from competitors in order to achieve their goals, regardless of what they are.

Final Thoughts

So what does all of this mean for marketers today? First of all, it’s clear that we cannot stop the world from becoming more complex, but we can leverage AI and smart DX platforms to master this complexity and reap its benefits -- helping us to become not only more productive, but also to be able to work smarter and outperform the competition.

Offloading work to AI will help people focus on what they’re best at -- strategy, creativity, and agility -- and not worry about repetitive manual tasks that used to overwhelm them from a time standpoint and underwhelm them from a career perspective.

From the viewpoint of the customer, think of AI in online personalization as if your organization had a dedicated account manager for every single client in order to provide them with the best experience possible. You can’t afford to do that with people, but it is completely realistic from an AI perspective. “This is perhaps where AI will have the greatest utility in marketing – in learning user behaviors and needs at a level so granular that each consumer has a completely custom, personalized experience.(vii)” Given that this is the Holy Grail in marketing, what are you waiting for?

We’ve assembled some helpful resources to get you started on the AI journey:

Want to learn more? The FirstSpirit Intelligent Content Engine, a new core component of the FirstSpirit Digital Experience Platform, enables marketers to provide AI-powered, personalized digital experiences via any channel to increase engagement and compel users to action throughout the buyer’s journey, all in one digital experience platform.

Request a demo now

Sources:
(i) https://www.mediapost.com/publications/article/291358/90-of-todays-data-created-in-two-years.html
(ii) Christer Clerwall, Enter the Robot Journalist, 2014.
(iii) https://www.impactbnd.com/blog/the-problems-with-personalization-in-marketing-infographic
(iv) https://www.forbes.com/sites/briansolis/2017/11/30/extreme-personalization-is-the-new-personalization-how-to-use-ai-to-personalize-consumer-engagement/#28c3758b829a
(v) https://www.economist.com/news/business/21732125-tech-giants-are-investing-billions-transformative-technology-google-leads-race
(vi) https://martechtoday.com/report-marketers-like-ai-based-tools-think-already-195107
(vii) Andy Betts, “The CMO’s guide to AI’s marketing impact for 2018,” Martech Today, November 28, 2017.
https://martechtoday.com/cmos-guide-ais-marketing-impact-2018-207350