AI in MarTech: 50 Expert Insights on How AI is Transforming DAM & MarTech (and How to Use it)

How AI is Transforming DAM & MarTech

In recent years, the marketing world has been all abuzz with plenty of new high-tech prospects, most notably machine learning (ML) and artificial intelligence (AI). Firms often use these terms to appeal to customers, yet Gartner reveals that only 30% of companies worldwide are expected to use AI in their sales processes by 2020. That means there’s an opportunity on the horizon for marketers savvy enough to grab it. AI’s potential touches every facet of the marketing and sales cycle, supporting marketing and sales efforts at every stage of the buyer’s journey and beyond, from powering digital asset management (DAM) solutions with facial recognition and auto-tagging to bolstering content marketing and enabling marketers to scale 1:1 personalization with customized, targeted recommendations that keep your customers coming back for more.

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To help you get started on the implementation of AI technologies into your DAM program and your marketing plans as a whole, we’ve compiled a list of 50 insights on how AI is transforming martech, as well as useful tips and tricks to help you effectively integrate AI in your initiatives.

Benefits of AI for MarTech & Digital Asset Management

1. AI helps companies maintain a competitive edge. “Both publishers and consumer brands such as The Wall Street Journal, Pandora, La Redoute, and TopFan use an AI-powered approach to improve their conversion rates and differentiate from competition, as Boomtrain reports.

“Pandora, for instance, brings together human curators and machine learning algorithms to suggest new songs listeners might like. Music listening services give us many good examples of competitive advantage achieved by delivering the best user experience. If you’re working with large quantities of content, algorithms can help to surface the most relevant ones for each individual user.” – Karola Karlson, 8 Ways Intelligent Marketers Use Artificial Intelligence, Content Marketing Institute; Twitter: @CMIContent

2. Speech recognition can extract searchable text from audio and video assets. “MerlinOne was a pioneer in this realm as perhaps the first DAM provider to employ AI-powered speech recognition to extract searchable text from audio and video assets. That was an early toe-dip in the AI pond.”

“MerlinX utilizes AI in its Automated Metadata Enhancement (AME) feature where it extracts and analyzes identifiable features within an image to then be able to auto tag metadata.” –Chris Carr, How AI can enhance the utility of DAM, MerlinOne; Twitter: @MerlinOne_Inc

3. AI bolsters automation. “Beyond traditional industrial automation and advanced robots, new generations of more capable autonomous systems are appearing in environments ranging from autonomous vehicles on roads to automated check-outs in grocery stores. Much of this progress has been driven by improvements in systems and components, including mechanics, sensors and software. AI has made especially large strides in recent years, as machine-learning algorithms have become more sophisticated and made use of huge increases in computing power and of the exponential growth in data available to train them. Spectacular breakthroughs are making headlines, many involving beyond-human capabilities in computer vision, natural language processing, and complex games such as Go.”– James Manyika and Kevin Sneader, AI, automation, and the future of work: Ten things to solve for, McKinsey & Company; Twitter: @McKinsey

4. AI supercharges asset-tagging and tracking. “A new and emerging breed of AI platforms for media analysis, when paired with leading-edge media asset management tools, offers great potential for transforming media workflows and making it easier than ever for operations to access, manage, and archive tremendous volumes of content. Through powerful tools such as speech-to-text and automatic language translation, AI engines bring new power to the MAM task of logging and tagging content—with the ability to tag assets automatically based on attributes such as people, places, things, and even sentiment.” – Dave Clark, CEO of Square Box Systems, Transforming Media Asset Management with Artificial Intelligence, TV Technology; Twitter: @TVTechnology

5. Content recommendations are automated. “Publishers are also implementing AI-powered content recommendation widgets that can identify related content to surface to readers, and even personalise those recommendations based on readers’ browsing habits. We recently introduced a feature like this on Econsultancy: our ‘Recommended’ sidebar is powered by a tool called IDIO, which learns our readers’ interests as they browse and uses this to suggest articles that they might be interested in reading.” – Rebecca Sentance, 15 Examples of Artificial Intelligence in Marketing, Econsultancy; Twitter: @Econsultancy

6. AI technology gathers precious predictive data. “‘The impact of machine learning in our marketing strategy is substantial,’ Pattabhiram said. ‘Because we now have the ability to better understand our buyer based on real data, we are able to develop a stronger relationship and open dialogue with sales. We can focus on being more creative in our work while leveraging knowledge gathered by our technology to point us in the right direction, so we don’t waste time on projects that are destined to fail before they begin. It enables all of us to be true data-driven marketers.'” – Chandar Pattabhiram, Chief Marketing Officer at Coupa, as told to Dom Nicastro, 6 Ways Marketers Are Embracing Artificial Intelligence (AI),; Twitter: @cmswire

7. The technologies help marketers find the best keywords. “Image, video and audio content can only be found if it has been properly tagged. Nowadays, every Digital Asset Management system has tagging capabilities. The most sophisticated DAM systems even use artificial intelligence (AI) and image recognition to automatically find the right keywords for your image. This really saves you time and hassle!” – Andreas Dangl, Business Unit Executive Cloud Services at Fabasoft, The 25 Top Benefits of Digital Asset Management, Fabasoft; Twitter: @Fabasoft

8. AI can improve accuracy. “Marketers spend countless hours attempting to gain some insight into their target audience, as they know consumer insights are the key to more strategic marketing campaigns.

“In the past, the availability of quality data was lacking and fueled mostly by demographics. Now, we’re entering an era of robust AI data analytics, that open the doors for marketers to fully understand their audience on a deeper level.

“Of course, like most things in life, AI isn’t 100 percent foolproof. However, AI predictive analytics aim to make the most accurate predictions by analyzing past and present customer behavior patterns. Using the data gathered, marketers can incorporate insights into their marketing efforts to create an optimized and targeted campaign.” – Philip Kushmaro, How AI is reshaping marketing, CIO; Twitter: @CIOonline

9. AI powers predictive capabilities. “You worked hard to bring in new business from your rivals and your best customers are constantly under attack from your competitors. Understanding those customers, their value to you and if they are likely to leave you would be very useful, right. Imagine then if you could also predict when this could happen and what kind of strategies would prevent them leaving you.

“Artificial intelligence can take all your company’s data and through machine learning quickly identify those pieces of data that matter to you. It will then help you build sales and marketing strategies to retain the customers. The best bit is because it is predictive you will know what the result will be in advance.” – Glen Westlake, 5 Key Benefits of Artificial Intelligence in Marketing, Digital Doughnut; Twitter: @Digitaldoughnut

10. It is supported by a secure, cloud-based system. “Cloud-based digital asset management software provides anytime, anywhere access to all of your digital content. Have secured 24/7 access to all of your business-critical files from any web device—whether you’re at your desk, working from home, or at a coffee shop halfway around the world.” – Maciej Duraj, Contributor at Forbes, Digital Asset Management and Custom Link Branding Services Worth Checking Out, Forbes; Twitter: @Forbes

Best Practices for Implementing AI in DAM

11. With AI, you can find what you’re looking for faster than ever before. “As advanced technology solutions grow smarter, it’s important to remember that audiences are becoming smarter as well. Thanks to social media and rapid-fire search engines (thanks Google!), people find what they are looking for faster than ever before. AI and big data solutions can actually analyze these search patterns and help marketers identify key areas where they should focus their efforts.” – Lindsay Tjepkema, What Is Artificial Intelligence Marketing & Why Is It So Powerful?, Emarsys; Twitter: @Emarsys

12. AI improves lead nurturing. “When it comes to gathering and analyzing customer information, we mortals are no match for the pace and efficiency of computers. AI-based programs are capable of processing user data at lightning speed and can be hyper-responsive to customer needs.

“Automating the data collection process can help simplify the lead-nurturing process for businesses, while AI can set the course for future marketing strategies.

“Capturing information: AI provides marketers with the valuable information they need to close a sale. It tells us when someone has visited their site, which pages they visited and how much time they spent perusing products.

“Marketing teams are using this data to drive sales, and if statistics are any indication, it’s working. AI could lead to an economic boost of $14 trillion in additional gross value added (GVA) by 2035, according to Accenture research.” – John Oechsle, Five ways to take your marketing automation further with AI, ClickZ; Twitter: @ClickZ

13. Research and understand its capabilities. “AI is built to perform narrow, specific tasks at superhuman levels. So, your marketing technology stack will likely expand, which obviously creates complexity if you don’t plan ahead. Success with AI requires an understanding of what it is and what it’s capable of doing (and not doing), as well as experimentation, patience and a strategic vision.” – Paul Roetzer, CEO of PR 20/20, 9 Ways to Become a Marketing Artificial Intelligence Pioneer, Marketing Artificial Intelligence Institute; Twitter: @MktgAi

14. When tagging, use contextual hints. “It is important to note that these systems do not generate narrative text, rather they used predefined or controlled lists of values and try to choose what appears to be the most appropriate based on some mechanically applied selection rules.  Usually there are thousands of possibilities, so a scoring algorithm will get applied to rank them.  This is all fairly straightforward database engineering stuff and you can see it applied to on-line shopping websites where they present some alternatives based on the behaviour of other users.  The options I tend to get offered when I use these sites are a bit hit and miss and are often more of a distraction than a help (with some exceptions).  While I can ignore unsuitable suggestions on a shopping website, they could become more of an issue on a DAM system where less diligent users accept the defaults without bothering to verify their suitability.

“This technique depends on having a decent-sized repository of assets already (or at the very least some source data structured in a format that can be used).  In addition, users need to be already finding suitable material and ideally cataloguing it appropriately also.  This kind of feature rewards the metadata-virtuous who have already been following best practices and policing the accuracy and validity of their metadata, but it makes things markedly worse for those DAM systems where the cataloguing has become a bit of a free for all and gone unchecked for many years. This is an issue which seems to keep coming up with any evaluation of these automated methods.” – Artificial Intelligence and Metadata Cataloguing: Advice for Digital Asset Managers, DAM News; Twitter: @DAMNEWS

15. Weigh keyword accuracy and terminology. “The approach that most of the API providers seem to be taking is to teach their systems to recognise as many subjects as possible and provide the same function to all clients (so if client A and client B both pass exactly the same image to the API they will see exactly the same results). This seems like a reasonable approach, but it leads directly to the two key problems (accuracy and different terminology) as they clearly don’t know enough yet to be sufficiently accurate for all clients’ images and client B might not want to see the same results as client A.

“Is it the best approach anyway? Given that most, if not all, of the APIs use neural networks, which are inspired by how we think the human mind works, let’s consider how a human would add keywords to a large set of an organisation’s images.” – Martin Wilson at Bright Interactive, AI in DAM: The Challenges and Opportunities, DAM News; Twitter: @DAMNEWS

16. Take time to learn from the experts. “When listening to actual data scientists talking about how all this stuff works, you quickly realize the freshness of this science. It is all so new that they will invariably refer to a canonical paper written in the past three months. If you are determined to dive in and learn ML from top to bottom, you have made a career decision, and not picked up a hobby. Things are moving so fast that you should not dwell on the specifics, but on the concepts.” – Jim Sterne, How to Get Started with Machine Learning and AI for Marketing, Conversion XL; Twitter: @conversionxl

17. Get familiar with AI. “Take the time to become familiar with what modern AI can do. The TechCode Accelerator offers its startups a wide array of resources through its partnerships with organizations such as Stanford University and corporations in the AI space. You should also take advantage of the wealth of online information and resources available to familiarize yourself with the basic concepts of AI. Tang recommends some of the remote workshops and online courses offered by organizations such as Udacity as easy ways to get started with AI and to increase your knowledge of areas such as ML and predictive analytics within your organization.” – Rob Marvin and Brian T. Horowitz, 10 Steps to Adopting Artificial Intelligence in Your Business, PC Mag; Twitter: @PCMag

18. Get to know the ‘lightbox’ functionalities. “Most Content DAM systems include some kind of collections or ‘lightbox’ functionality where users can assemble arbitrary selections of assets.  In recent years, these have become quite a lot more sophisticated and I have seen DAM solutions where these tools form the basis of a brand guidelines (or similar features for different use-cases).  As with asset usage, where users are entering text in the notes sections of a lightbox or collections feature, this too can be analysed.  A further higher-level feature is to try to analyse what assets get collected together by users.  If a reasonable number of users are storing two assets in the same collection, but the metadata used to describe them has no or few common features and they are being found via separate searches, this suggests a potential opportunity to cross-fertilise metadata from one asset to another.” – Ralph Windsor, DAM News Editor, Combining AI with Digital Asset Supply Chain Management Techniques, DAM News; Twitter: @damnews

19. Take advantage of all retail and shopping capabilities. “Retail is also full of great innovation examples powered by the evolution of AI. Online shopping has transformed the process of filtering online catalogues; where you used to have traditional check boxes and exact search terms, now you have an intuitive, automatic determination of the color, size and even style of the clothing to suit the user.” – Ariel Long, Using AI for Better Digital Asset Management (DAM), Digital Doughnut; Twitter: @Digitaldoughnut

20. Put a strong emphasis on training. “Everyone who will be touching the DAM solution — from sales and marketing to finance and HR — should be trained on how to use it. Provide in-depth, comprehensive training for the system admins who will be naming and adding new files, organizing assets, setting expiration dates, capturing metadata, and more. You’ll have to define your naming conventions, folder hierarchies, and required metadata fields in advance of this training.

“Regular system users, on the other hand, only need to know how to find files, access the DAM from mobile devices, distribute files to clients and customers, and create collections for ease of collaboration. Also consider assigning one or more individuals from your group to act as a ‘Digital Asset Manager’ or ‘Librarian,’ who will be tasked with consistently cataloguing and updating information in the database. This can help prevent key information from being omitted or misspelled — errors that can make it difficult to locate important assets in the future.” –Joe Staples, Chief Marketing Officer at Motivosity, 5 Tips for Making the Most of Digital Asset Management, Martech Advisor; Twitter: @MarTechAdvisor

How AI is Transforming MarTech

21. Heightened intelligence will make for a more transparent marketplace. “Automated data analysis does reduce the need for every brand, agency and platform to maintain their own data science department. However, as machines get smarter, the firms that employ this technology will need to be more educated on the types of AI and how they work.

“According to the Harvard Business Review, many companies have been fiscally burned because they pursued the wrong type of AI for the project at hand. To avoid this, we’ll see marketers actively advancing in their understanding of AI methodologies, such as regressions, decision trees and neural networks. Further, marketers will gain a more nuanced understanding of how these methodologies align with business requirements including compliance, transparency, cost, goals and timing.” – David Dowhan, Founder and CEO at TruSignal, 3 Ways Marketing AI Will Advance in 2019, Marketing Land; Twitter: @Marketingland

22. AI will drive innovation. “AI is ideal for looking at multi-dimensional relationships and offering up insights that humans can’t obtain on their own. Yet, right now, it would appear that we’re still very early in the AI revolution (thought coming fast) and AI has yet to reshape most businesses. The way to make an impact, according to most experts, is to ‘start small.’

“Ultimately, AI is going to reinvent how we invent. As marketers, our role in informing future innovations in our organizations depends on our ability to drive consumer insights from the data.” – Jeremy Epstein, CEO at NeverStop Marketing, How Blockchain, AI, and Martech Intersect, Medium; Twitter: @jer979

23. It bolsters responsive paid search ad strategies. “As a digital marketer, chances are you’ve run your share of A/B tests to determine the paid search headlines and descriptions that drive the most clicks or calls. You’ve endured the lengthy cycle of running ads side-by-side, comparing results, tweaking the ads, running them again, and so on, until you discovered that perfect combination. Currently in the beta phase, Google’s Responsive Search Ads are designed to eliminate time-consuming A/B testing. Rather than running different headline and description combinations in various ad sets, Google allows you to run a series of headlines and descriptions in one constantly evolving search ad.

“To set up the ad, simply enter up to 15 headlines and four descriptions—AdWords will automatically show different combinations depending on the search query. Over time, Google will test various headline and description combinations and calculate which perform best. The multiple headline and description options allow your ads to compete in more auctions and match more queries, broadening the base of potential customers you can reach. Additionally, Google will optimize your message for various device widths, enhancing the experience for customers on mobile, tablet, and desktop.” – Louise Thompson, Public Relations and Content Manager at DialogTech, How AI is Transforming the Martech Landscape, G2 Crowd; Twitter: @g2dotcom

24. It provides powerful tools that communicate with customers. “Though marketers still haven’t fully tapped into their full power just yet, chatbots are a good example of how AI is beginning to take hold in martech – particularly in ecommerce. The power to both predict and proactively deliver information to customers before they even realize what they’re looking for is a significant feature, and one that keeps consumers top-of-mind.” – Lou Jordano, AI Powered Everything: The Second Marketing Revolution, Chief Marketer; Twitter: @chief_marketer

25. AI creates highly-personalized experiences for users. “Machines can use customers’ browsing patterns to learn about their interests and shopping habits, and by the time they reach your website, the AI has put together an idea of what they are most interested in seeing. This can include best-fit offers and content, as well as personalized push notifications alerting users to sales.” – Shalaka Nalawade, Former Editor at Martech Advisor, Blurring Lines: AI is Blurring the Lines Between Martech and Adtech, Martech Advisor; Twitter: @MarTechAdvisor

MerlinOne brings unprecedented AI to DAM

26. AI takes the guesswork out of strategizing. “Artificial Intelligence helps to reach the right audience at the right time, on the right channel and with the right message. It helps companies and brands to have a more targeted approach and focus their marketing budget and efforts in the right direction. Other useful benefits of AI in marketing include better sales forecasting, targeted advertising, and finding the best audience based on their buying behavior, demography, interests, and focus.” – Bijoy K.B., Associate Marketing at Lemnisk, The Role of Artificial Intelligence in Martech and its Applications in the BFSI Sector, Lemnisk; Twitter: @LemniskCo

27. It reduces human error and eliminates bias. “Marketing strategies easily stray into the woods when human bias distorts data and drives bad insights. For example, advertising is still widely a boys’ club, but should all ad creative be left to male judgment? AI can intervene before bias runs amok.

“Just as AI data and behavior analysis will inspire more holistic audience targeting, in 2019 it will help brands develop target appropriate campaigns. By reducing marketing risks, AI will drive marketing investment. As much as Andy Markowitz, Mastercard’s svp of managed services, likes the idea of marketing that is free of bad insights, he has some words of caution. ‘AI will start to alleviate some human error-caused risk, but don’t expect it to inoculate marketers against all bad assumptions.'” – Ben Plomion, CMO of Computer Vision and Digital Innovation at GumGum, 5 Ways Artificial Intelligence Will Continue to Shape Marketing, Adweek; Twitter: @Adweek

28. The appearance of AI is helping to break apart martech silos. “According to marketing technologist, Scott Brinker, the number of public APIs has grown from 186 in 2005 to 15,799 in 2017. Seeing as APIs pretty much exist to promote integration between one platform and another, this should be creating greater efficiency. But, unless your chosen marketing technology has all the right functions integrated, you’ll still be seeing multiple reports from each platform.

“The data may flow between platforms, but you’re still not seeing the big picture. AI and companies are eliminating the need for multiple platforms, offering integrated marketing solutions that work for your company. You no longer have to bend your marketing strategy around someone else’s technology stack. Capabilities like machine learning mean that previously inaccessible data is tracked, analyzed and made useful.” – Artificial Intelligence is Breaking Down Martech Silos, SAM.AI; Twitter: @samdotai

29. AI supports hyper-targeted programs and campaigns. “First, marketers should not think about ‘how can I get started with AI?’ any more than they should say, how do I get started with Python or Java? AI is merely a means to an end. Marketers need to start by asking themselves what challenges they need to solve. Once they’ve identified those challenges, they need to evaluate the best, most effective way to solve them. For things like intent-based insights, hyper-targeted programs, personalized experiences on the web, and others, AI will be the quickest path to success.” – Barb Mosher Zinck, Survey Says that Marketers are Excited About the Potential of AI – But Where Does it Have Impact?, Diginomica; Twitter: @diginomica

30. The future of AI in martech is endless. “Attainable use cases for AI martech include content intelligence, budget allocation intelligence, and ‘things that require a lot of data and a lot of time,’ such as advertising strategy and execution, Roetzer said. He projects that in the next 3 – 5 years, there will be ‘ways to do things so much more intelligently, that as a marketer, you can’t fathom going back to setting up your own workflows.’” – Amy Koski, interviewing Paul Roetzer, CEO at PR 20/20, Assessing the Intelligence of AI Marketing Tech, Aberdeen; Twitter: @abderdeengroup


31. AI enables better, faster decision-making. “AI systems, particularly those that rely on deep learning, excel at quickly analyzing mountains of big data. Learning algorithms recognize patterns and identify relationships with limited or no supervision. When marketing intelligence is gathered more quickly, marketers can then make media-buying and content-placement choices more quickly too. With predictive abilities, deep learning simplifies campaign optimization, giving marketers a competitive edge.” – Kerri Hale, Leveraging the Power of AI in Marketing, Now and In the Future, Towards Data Science; Twitter: @TDataScience

32. Adtech and martech tools are merging together with the help of AI. “‘The hottest martech trend of 2019 is going to be the merging of adtech and martech. Advertising is becoming more one-to-one by using first-party data, which has historically been the ‘bright line’ between advertising and marketing,’ said Len Ostroff, Senior Vice President, Strategic Partnerships and Alliances at Criteo. By combining adtech and martech data resources, marketers can better understand what customers are looking for and how to improve their brand experience.” – Len Ostroff, Senior Vice President, Strategic Partnerships and Alliances at Criteo as told to Katrina Cameron, 5 Martech and AdTech Trends to Watch in 2019, RampUp; Twitter: @rampup

33. The intelligent agents help to boost efficiency. “Marketers work with martech vendors to use AI’s optimization capabilities to improve marketing efficiency and continuously lift marketing performance over the long term. But success depends on marketers’ ability to clearly define use cases, determine how to improve their marketing performance, and evaluate which AI-powered marketing solutions best match the use cases.” – Xiaofeng Wang, Senior Analyst at Forrester, Nine AI Marketing Use Cases That Have the Potential to Deliver Business Value, Forrester; Twitter: @forrester

34. AI solves clear-cut–and not so clear-cut–problems. “There is no such thing as ‘general’ intelligence. On an abstract level, we know this for a fact via the ‘no free lunch’ theorem — stating that no problem-solving algorithm can outperform random chance across all possible problems. If intelligence is a problem-solving algorithm, then it can only be understood with respect to a specific problem. In a more concrete way, we can observe this empirically in that all intelligent systems we know are highly specialized. The intelligence of the AIs we build today is hyper-specialized in extremely narrow tasks — like playing Go, or classifying images into 10,000 known categories. The intelligence of an octopus is specialized in the problem of being an octopus. The intelligence of a human is specialized in the problem of being human.” – Francois Chollet, The Implausibility of Intelligence Explosion, Medium

35. Creating sensitive algorithms is just getting simpler. “With machine learning, instead of giving the computer lots of rules to follow, we’re programming it to learn everything it can about a person and select the experience most likely to appeal to that person. And for machine-learning personalization to be most effective, marketers should be able to build their own ‘recipes’ that tell the computer what types of information to consider when determining someone’s digital experience. A customizable recipe begins with the selection of one or more pre-programmed base algorithms. These algorithms can be simple, such as displaying items that are trending or recently published, or they can be more advanced, like collaborative filtering or decision trees.” – Kag Katumba, Marketing Executive at Smart Insights, Digital Marketing Trends in 2019, Smart Insights; Twitter: @smartinsights

36. The technology allows for the automatic analyzing of customers’ interests. “You now will have the ability at an individual level to take that promise that we’ve had as marketers for God knows, 20-plus years, of real, one-to-one marketing, and actually be able to use signals to determine what is the propensity of a particular individual to purchase a product based on the attributes of that product, the channel that they’re in [and] the sequence of how they’ve been engaged.” – Jason Heller, Partner, Global Lead, Digital Marketing Operations and Technology at McKinsey & Company, AI Powers Personalized Marketing, Channel Futures; Twitter: @ChannelFutures

37. It can make backend operations more efficient. “We often hear about how AI will take jobs, but it generally makes more sense to view AI as a technology that takes tasks. And many of these tasks are on the backend – logistics operations such as basic accounting, scheduling, and other forms of day-to-day organization. Considering the fact that small businesses have a limited number of employees, the transfer of time-consuming tasks like these to AI is crucial to help them use their human capital efficiently.

“In a December 2017 article for Minutehack, the co-founder of inniAccounts, James Poyser, explains that his small business has made ‘significant strides to automate some elements of bookkeeping’ with the help of AI. When AI is used for backend operations, it’s also less of an encroachment on employees. Poyser is sensitive to this fact: ‘If people see AI as a threat to their job, which it isn’t in our case, then it’s game over.’

“On the other hand, most employees welcome technology that can get rid of monotonous tasks and free them up to do more meaningful work. As the respondents to our survey acknowledge, AI increasingly does just that.” – Rebekah Iliff, 5 Ways Small Businesses Can Benefit From the A.I. Revolution Right Now, Inc.; Twitter: @Inc

38. AI frees up marketers to focus on more creative tasks. “So here’s the big question: Where does artificial intelligence leave the marketer? Technology has already reshaped blue-collar industries, eliminating the need for jobs. Won’t automated systems threaten to destroy traditional marketing roles as well?

“AI proponents concede that technology will replace some roles, but they believe AI has the potential to create just as many new jobs. Plus, they argue, software could free up marketers to focus on creative, strategic work rather than day-to-day processes.” – Dillon Baker, Marketing’s Artificial Intelligence Revolution is Here, Contently; Twitter: @contently

39. AI can connect dots that humans can’t. “‘For marketing, one of AI’s strengths is its ability to connect the dots within volumes of data in ways that human analysis is unlikely to discover without a team of data scientists,’ Husson writes. ‘Marketers must supply AI-powered systems with accurate, updated, diverse, clean, and complete data. Then AI can iteratively search for insights so CMOs can take advantage of immediate benefits like personalization, insight detection, dynamic content optimization, and marketing automation.'” – Forrester VP and principal analyst Thomas Husson, as quoted by David Kaplan, How CMOs Are Getting Past the Hype About AI by Finding the Practical Use Cases,; Twitter: @geomarketing

How to Apply AI to Every Stage of the Customer Journey

40. Use consistency as a tool. “It’s all about in-the-moment personalization. Marketers are swamped with tons of data with almost no actionable insights. But, data alone won’t lead you anywhere. With artificial intelligence, marketers can get deep and powerful insights to identify key moments in the customer journey to automatically send the right message to the right person on the right channel, making the customer most likely to convert.” – Nandini Rathi, CMO at Betaout, 4 Ways You Can Use AI to Enhance Every Step of the Customer Journey, Entrepreneur Asia Pacific; Twitter: @entrepreneurapj

41. Provide your customers convenience with virtual voice assistants. “With the induction of ML, we get immense opportunities from Natural language processing (NLP). NLP has facilitated voice search, providing the best outcomes based on location and earlier search history. It’s now easy to tap into this technology to enhance CX.” – Oleksii Kharkovyna, AI & ML Revolution to Scale Customer Experience, Towards Data Science; Twitter: @tdatascience

42. For streamlined customer recommendations, combine implicit data with explicit data. “While the quality of recommendations has improved over the years, it’s still lacking since it only uses implicit data such as purchase history or viewed products. For more intelligent and relevant product recommendations, you must combine implicit data with explicit data. Explicit data is shared by the customer and helps businesses understand their real needs, brands they love, colors, styles and more.” – Michelle Deery, The 6 Stages in the Evolution of AI and Customer Experience,; Twitter: @_GuidedSelling

43. Rely on today’s automated powers in attribution. “‘Most marketers really use reporting, not true attribution,’ says Matt Scharf, Integrated Marketing Analytics at Adobe. ‘Attribution AI gives our marketing initiatives much more value by showing how much revenue each marketing channel contributes to each sale. This allows us to shift the conversation away from marketing as a cost center towards marketing as a valuable sales driver.’

“The result is a much more meaningful view of what works and what doesn’t. For instance, marketers might find that a small paid search campaign promoting Adobe Premiere Pro effectively nudges people toward purchase, even as they’re just beginning to research video editing software. Or they may discover that a high-volume monthly email push doesn’t significantly contribute to subscriptions—and in fact turns customers off. That kind of insight is invaluable to a marketing team committed to constantly refining the experiences they deliver.” – Matt Scharf, Integrated Marketing Analytics at Adobe, as told to Paige Pace, The Future is Now–How AI Enhances Customer Experience Management at Adobe, Adobe Blog; Twitter: @Adobe

44. Harness the power of AI with informed predictions. ” To deliver on the magic of AI, you must leverage predictive models to deeply understand consumer behavior. In reality, machine learning is really using statistics to predict outcomes, and statistics is one of the most powerful ways to interpret the world around you. From weather forecasts to medicine to insurance, predictions are critical to understanding behavior and anticipating the future. Marketers using AI-driven, self-adapting predictive models will find a new superpower in being able to anticipate customer behavior in the context of your products, your taxonomy and your engagement touch points.” – Konrad Feldman, Founder and CEO of Quantcast, How AI Can Make Your Customer Journey Magical, Ad Age; Twitter: @adage

45. Integrate AI with existing tools to provide more value to customers. “Being able to succeed in today’s marketing landscape relies upon being able to achieve intelligent journey orchestration. Brands need to be able to deliver the right message, to the right individual, at exactly the right time, using high-quality customer data.

“AI technology is an incredibly valuable tool for any and all marketers looking to achieve true 1:1 personalisation at scale. By making sense of huge amounts of data, and converting this into actionable insights, businesses can dig even deeper into the specific behaviours and interests of their customers, which in turn allows them to start crafting hyper-specific messages that resonate. It’s a significant step forward in being able to craft the perfectly personalised customer journey.” – Sonja Kroll, Can AI Crack the Perfectly Personalized Customer Journey, DTC Daily

46. Use AI to leverage research phases. “During the initial phase of the buyer’s journey, brands must find ways to captivate potential customers, make them aware of their need, and provide the information they are looking for to push them towards a purchase. To grab their attention, most online companies focus on keyword optimization and SEO strategies to boost their website’s ranking for initial searches.

“There are two smart approaches for e-commerce businesses to take so AI can make the most of their SEO strategies. AI can analyze keyword data extremely fast and even make conclusions – thanks to deep learning methods that would never be possible with manual research. Furthermore, AI can even use predictive analysis to figure out what your customers’ next move may be (such as their next search question) and map intent with real-time stream processing for more relevant results.” – Manish Dudharejia, President and Founder at E2M Solutions Inc, How E-Commerce Brands Can Include AI Into Every Step of the Customer Journey, Datafloq; Twitter: @datafloq

47. Use AI to help create accurate buyer personas. “To create the best customer experience, you have to first understand your customers – who they are, their motivations and concerns. If your organization wants to deeply understand customers and empathize with them, you need access to in-depth intel.

“There are two ways you could do this –

  1. Profile the types of customers your customer service team deals with every day. There’s no better way than this to understand customer’s needs.
  2. Once you have enough information, you can create buyer personas. The most effective buyer personas represent real people, human beings, so you can account for emotional or psychological elements that can hugely impact your customer experience.” – Amritpal Dhangal, Top 14 Ways to Create a Great Customer Experience Strategy in 2019 [Updated], Acquire; Twitter: @acquire_io

48. Consider these important questions before implementing an AI solution. “Over 85% of B2B marketing spend is solely focused on the acquisition stage of the buyer’s journey. Especially if you are in a SaaS technology business, you have to look more closely at two key metrics that will contribute greatly to the overall health of the organization over the long haul:

  1. How are you driving higher lifetime value within your customer base?
  2. Are you creating enough advocates for your brand?” – Chandar Pattabhiram, Using AI to Increase Effectiveness in the Buyer Journey, FlipMyFunnel; Twitter: @FlipMyFunnel

49. Make use of customer data to bolster retention efforts. “This is where you recognize that members of your audience are at risk of leaving, determine why they are losing interest, and either keep them from wandering off the trail or make it easy for them to come back in the future. Data can help you notice when engagement dips and tools like exit surveys can provide insights for future outreach.” CUSTOMER JOURNEYS: How to Keep Customers Connected and Coming Back, Salesforce; Twitter: @salesforce

50. Customer insights should be used to inform both the present and the future. “In the past, marketers were often blind to the customer’s journey. When might a customer purchase, and why then? These key questions matter for speculation and “gut” thinking. Now, we have data about every step of the customer journey. We can leverage that data to understand our customers and develop actionable insights that inform what we do. Data, the “oil” fueling AI and ML, simply gives us more visibility into the entire customer experience. In the end, AI allows us to market at scales not humanly possible before.” – Chuck Leddy, Contributing Writer at Zylotech, 4 Ways AI and Machine Learning Enhance the Customer Experience, Customer Data & Analytics Blog; Twitter: @zylotweet

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