We live in an age of personalization and marketers continue to seek ways to connect better with potential customers. As most everyone is aware, significant amounts of data are being collected and that data can be leveraged to better understand consumer behavior and preferences. As a result, cognitive systems (aka artificial intelligence (AI) systems) are some of the most important tools in the kit of modern marketers. Armita Peymandoust (@armita), Vice President of product management for Einstein in Marketing at Salesforce, asserts, “In 2021, companies who tap into the benefits of artificial intelligence can personalize every experience and ultimately drive growth. … Accenture explores this idea and states, ‘75% of CMOs admit past formulas are no match against the new disruptors, able to deliver more relevant customer experiences.’ With the need for relevant customer experiences at an all-time high, artificial intelligence helps companies send messages that understand the needs of their customers and create meaningful moments.”
Because there is so much data to be analyzed, marketing has become very complex as well as continuing to be very competitive. Andrea Leigh (@andreakleigh), Vice President of strategy at Ideoclick, writes, “We are witnessing the rise of retail media networks designed by major retailers to deliver a targeted, personalized experience to shoppers. Walmart, CVS, Amazon and others are putting resources behind this trend, and marketers will need to sharpen their approach by addressing multiple critical factors, including their relevance, keyword targeting, negative targeting, and the shopper’s buying journey to be successful.” This simply can’t be accomplished without the assistance of cognitive technologies. Leigh insists, “Keep ads relevant. At a minimum, the ad should feel like a natural part of the search and browse experience. But ideally, the ad should feel useful and time saving, as though the right product is being presented at the right moment. Highly sophisticated ad platforms like Amazon won’t even let you ‘win’ keywords that are not relevant to your product. Relevancy is literally built into the algorithms.” In other words, you need to fight AI with AI.
The Benefits of Leveraging AI in Marketing
Technology writer Phillip Britt notes, “Companies started using artificial intelligence and machine learning about five to seven years ago, but those early efforts weren’t targeted nearly enough. That is finally starting to change as marketers are turning to the technology to solve very specific issues, like refining their customer retention efforts, targeting competitor’s customers, or creating profiles of their ideal prospects or customers.” Understanding what potential customers want and need is becoming more important as marketplace power is shifting their way. Journalist Elizabeth Crawford (@ECrawfordwrites) notes, “The days of pushing out a refined, tightly controlled marketing message without listening to what consumers want to know are long over, and brands that want to make in the modern world must listen first. … The most significant change in marketing in recent years has been power shift from brands to consumers.” Cognitive technologies can help brands listen (using data) and respond appropriately by leveraging insights mined from data. Marketing expert Uri Kogan (@content_is_all) explains, “Advances in AI (fueled by an annual investment of around $30b from organizations such as Amazon, Google, and Baidu) are now enabling organizations to automate the process of classifying and extracting key attributes and data points from images, audio files, and videos in increasingly sophisticated and intelligent ways. Advances in Natural Language Processing (NLP) and Natural Language Understanding (NLU) enable enterprises to not only automate how content and data are identified and categorized, but it does so in a manner that is more consistent and accurate than manual approaches.” Wilson Raj (@wilsonraj), Global Director of customer intelligence at SAS, suggests several other ways cognitive technologies can help marketers. They are:
- Refine segmentation for better personalization.
- Enable timelier and more relevant customer experiences by recognizing past patterns, current engagements, and predicted behaviors and then surface in-moment offers based on those insights.
- Boost revenue through next-best-action recommendations. Machine learning can help spot patterns or changes in customer behavior more swiftly, enabling marketing to respond in real time by adjusting offers.
Concerning AI, Paul Herman (@paulherman_tw), Vice President of the Product and Solutions Enablement Group at Sprinklr, asserts, “There are real implications and benefits to its use, and marketing will be one of the many disciplines affected the most: 47% of companies agree that those who don’t invest in AI are at risk of being pushed out by competitors, according to Forbes Insights.” He adds, “AI may seem intimidating and enigmatic, but for marketers it really points to one major opportunity: data. AI-powered tools can save time and resources by automating processes and surfacing more data for your brand. Marketers can then use that data to accomplish a range of goals, such as finding influencers, delivering more personalized experiences, and closing the loop between social engagements and online or in-store conversions, ultimately driving business.”
Getting the Most from AI in Sales and Marketing
Andris A. Zoltners, PK Sinha, Sally E. Lorimer, and Arun Shastri, from ZS Associates, note, “Articles have reported sky-high ROI from AI designed to boost field and inside sales force performance. From all the success stories, one might conclude that most sales forces are well on their way to realizing value from AI, and that the going is easy. The truth is that only a small number of sales forces are using AI successfully.” As noted earlier, data is the key to better marketing. Zoltners and his colleagues explain, “AI systems work with vast amounts of data. Some of the data are structured (e.g. demographics, purchase history) and some are unstructured (e.g. words from emails or audio recordings). Assembling the data for a one-time use is difficult enough. Creating the processes needed to continually refresh the data can be daunting, time consuming and expensive. Fortunately, AI can work with incomplete or imperfect data, provided the data are free of systematic bias. In fact, AI can improve the quality of the data, for example, by predicting missing values or identifying possible errors.”
Despite the potential benefits of cognitive technologies for sales and marketing, entrepreneur and journalist Annie Qureshi (@annierqureshi) asserts, “Many marketers are still unclear about the capabilities of AI. … This raises a serious concern about their ability to utilize AI effectively.” She adds, “There are a number of applications of AI in marketing. Marketers need to understand the relevance of this new technology to make the most of it.” She goes to list a few of the common AI applications in marketing:
- Automating email marketing. “Some email marketing platforms use machine learning to optimize delivery and recommend content structures to boost engagement.”
- Streamlining the delivery of advertisements. “Advertising platforms … are using machine learning to better understand the behavior of customers, so they can get ads in front of people that are most likely to convert.”
- Improving advertising content. “Some AI tools are able to recommend changes to content to boost engagement and optimize it for SEO.”
The greatest benefit of cognitive technologies is helping sales and marketing teams get to know consumers better. Cognitive solutions, like the Enterra Shopper Marketing and Consumer Insights Intelligence System™, can help provide the insights brand teams need to improve their performance. The CIO Applications staff insists, “The insights [machine learning] can offer are fantastic. Profile details and behavioral insights mean that one could see each person in their target audience with precision. As one might know, this is known as ‘cognitive.’ Cognitive intelligence includes information such as user persona, cognitive media preferences, interests, and desires.”
Leigh concludes, “Using ad tech is a strategic and increasingly complex piece of the selling puzzle. Ads must be compelling and engaging, certainly. But they also need to be strategically sound, well-placed and differentiated in order to help the buyer in their journey to conversion — no matter where they currently sit in the sales funnel.” The CIO Applications staff adds, “Cognitive advertising makes value to consumers by knowing their though more thoroughly than ever before and [machine learning] and AI are the developments behind it. … Machine learning systems can be used to generate inputs to help advertisers link to their primary target audience more precisely.”
 Armita Peymandoust, “4 Ways AI Will Make You a Better Marketer in 2021,” Adweek, 26 January 2021.
 Andrea Leigh, “Retail Media Strategies Evolve As Ecommerce Surges,” AdExchanger, 29 March 2021.
 Phillip Britt, “Marketing Is Turning to AI for Customer Acquisition,” Destination CRM, 30 March 2021.
 Elizabeth Crawford, “The new marketing playbook acknowledges consumers are in control of brands’ fate,” Food Navigator-USA, 20 November 2017.
 Uri Kogan, “AI Evolves … and Organizations that Manage Digital Content Benefit,” MarTech Series, 24 March 2018.
 Britt, op. cit.
 Paul Herman, “New and Exciting Ways Brands Are Using AI on Social Media,” MarketingProfs, 26 November 2018.
 Andris A. Zoltners, PK Sinha, Sally E. Lorimer, and Arun Shastri, “4 Ways Sales Teams Could Get More Value Out of AI,” Harvard Business Review, 27 February 2019.
 Annie Qureshi, “Marketers Must Demystify AI to Reap Its Benefits,” Datafloq, 27 Feb 2020.
 Editorial Team, “How Machine Learning is Changing the Role of Advertising,” 1 February 2021.