As new AI tools continue to launch in the marketplace, opportunities arise for marketing and PR to collaborate on data sharing, analytics, gauging public sentiment, brand awareness efforts, and more. Here are three ways marketing and PR can work together on integrated, AI-driven strategies, according to a piece in PRNEWS.

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New AI-enabled products for brands continue to enter the marketplace. On Wednesday, Salesforce unveiled a series of new features that incorporate generative AI technology into its marketing and commerce clouds. An article in AdExchanger looks at how marketers can leverage the tools to improve campaign creation, segmentation, measurement and personalization.

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CM sister pub Event Marketer conducted a survey of AI in events during the month of March, and 86 percent of respondents said they were not using AI intentionally right now. However, 75 percent do believe that AI will change the course of events. Explore these insights and others in EM‘s latest Pulse Survey.

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The marketing industry and culture at large is adjusting to the sudden influx of large language model generative AI tools, such as ChapGPT, that could potentially alter the way we work, perform and do business. But whether those changes are perceived as positive or negative depends on who you ask.

For a group of more than 1,400 leaders in technology, academics and AI research, who signed an open letter on March 22 that called for a pause in AI development until better safety standards and oversight are in place, artificial intelligence can pose “profound risks to society and humanity.”

We’re talking more than college essay writing, of course. Warnings about unhinged AI experimentation have long been echoed by some of the letter’s more well-known signatories, including Elon Musk. But what of AI’s practical applications, and those for marketing purposes in particular?

Peter Prodromou, president of AI-focused marketing agency Boathouse Group, takes a more moderate point of view and supports practical uses for AI while simultaneously developing guidelines to follow, according to an AdExchanger podcast. He dishes on the difference between AI and machine learning, AI’s applications for social learning, and tips for avoiding companies that are merely attempting to capitalize on the trend.

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For the past two and a half years, Levi’s has been integrating artificial intelligence applications into the brand’s data strategy by investing in targeting consumers with relevant marketing messages. The focus is threefold: targeted email messages; the online experience across its app and website; and the buying experience. AdExchanger spoke with Levi’s AI chief Katia Walsh about applying AI to marketing processes, transforming the 170-year-old company into a digitally-advanced brand, combating bias in algorithms, and more.

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The Weather Company has access to a trove of first-party data, which gives it a distinct targeting advantage in a post-cookie world. But it’s also investing in AI technology—through IBM Watson Advertising—to create quality content; focusing on a subscription model; and deprioritizing revenue gained from short-term advertising within its apps in order to create a richer experience for consumers. Here’s a look at the strategy behind the brand’s recent decision to reduce its in-app ad footprint by 42 percent, according to a piece in AdExchanger, plus how the company is using AI to improve its subscription offering.

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Olay is holding its own AI functions accountable in a new initiative to combat hidden bias in beauty algorithms. Following is what the brand’s #DecodetheBias campaign entails and how its effort to unearth bias in data sets supports more inclusive coding practices, according to an article in AdExchanger.

Olay’s campaign, which coincides with National Coding Week, has the goal of sending at least 1,000 women of color to code camp through a partnership with Black Girls CODE. The idea is to change who is doing the coding—and therefore influence beauty algorithms that Olay has revealed are perpetuating monolithic beauty standards. The campaign includes national TV spots and print ads and also encourages other brands to examine bias within their own data sets.

The brand analyzed its own technology, a web-based tool that relies on selfies to recommend skin care products, to uncover bias—and, importantly, rectify it. After partnering with ORCAA, an organization that audits algorithm risk, the company found that its Olay Skin Advisor tool was less precise depending on age and less accurate for people with darker skin tones.

A key part of the campaign is supporting a more diverse talent pool within businesses. Because “as more women and women of color become coders,” Headley told AdExchanger, “we’ll get better code and more inclusive code.”

For more detail on Olay’s #DecodetheBias campaign, read on in AdExchanger.

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“We had to quickly pivot to provide support in forms beyond product,” explains Pam Griffin, Associate Director, Cleaning Division for the Clorox Co. “My focus was on providing resources to consumers in a time of heightened anxiety, especially when misinformation was prevalent, and reaching consumers in environments where we could offer meaningful and reliable information in lieu of available product.”

By summer 2020, Clorox decided to experiment with artificial intelligence, in particular IBM Watson Advertising Conversations. Implementing the tool required collaboration not just with functional groups within Clorox but also with its PR and media agencies (Ketchum and OMD, respectively) and, of course, IBM. Griffin and team developed a list of nearly 100 anticipated consumer questions. Using machine learning and natural language processing (NLP), the technology was able to not only answer the questions but also understand user intent so that its recommendations were tailored specifically to the consumer.

Executional work began in late September, and the chatbot went live on December 21. It was incorporated into ads running on the Weather Channel’s website and targeted paid media. Clorox also placed the chatbot in a pop-up on its own website’s COVID resources hub—the first brand outside of IBM itself to integrate the tool into its site. To reach consumers offline, Clorox featured a QR code directing people to the site’s chatbot in its January 2021 national free-standing inserts.

As well as inviting consumers to ask questions, the media assets offered a menu of topics that visitors could explore. Common questions focused on product availability, cleaning advice, which Clorox products kill COVID-19 and tips for caregivers and essential workers.

“We were pleasantly surprised to find that we didn’t encounter a significant number of queries that fell outside the scope of what we built,” Griffin notes. “We did make minor content adjustments midstream to ensure we had the most up-to-date product information as our brands continued to receive EPA claim approval for killing the COVID-19 virus, and we will be making more significant updates to the chatbot in the coming quarter to incorporate content that will pivot our focus to helping address anxiety and confusion associated with being outside the home and on the go as the country begins to reopen at scale.”

In terms of effectiveness, Clorox’s AI implementation has exceeded IBM’s activation and engagement benchmarks, according to Griffin. The average user went three “conversations” deep per visit, and 63 percent of those surveyed said they were satisfied or very satisfied with their experience. “That’s kind of remarkable when you remember that in many cases we were talking to consumers who could not access product, and who you might therefore expect to be dissatisfied,” Griffin adds. IBM considered the program to be so successful that it honored Griffin as one of its Women Leaders in AI for 2021.

Griffin offers two pieces of advice for those considering adding AI and chatbots to their marketing arsenal. First, “it’s really important to put in the initial work and engage your functional experts to make sure the content you develop is as thorough, accurate and useful as it possibly can be and that you are in compliance with all legal and data-related regulations.” Second, be sure to think not only as a marketer but also as a consumer when crafting the user experience. “Many of our best ideas came from taking a moment to consider our own perspective, concerns and needs living through these unprecedented times.”

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Typically, there are three different stages or types of an email campaign: the initial campaign, which may include product recommendations in the form of wish lists; last-minute deals that leverage FOMO to help sell a product; and the post-purchase campaign that offers thank yous and further discounts. Through analyzing your data with AI, marketers can tailor campaigns to customers depending on each stage.

AI software can assist with personalizing email messages. Using the data from past campaigns and predictive analytics, marketers can use AI to create the smallest possible segments. Machine learning software allows personalization of discounts and optimization of emails overall, from the content, offers and even the copy, ultimately increasing conversion rates.

Determining the subject lines that work best in an email campaign is another use of AI technology. Analyze your past email marketing campaigns to determine optimal subject lines, from the number of words to the choice of specific phrases. For more ways in which AI can assist marketers’ email campaigns, including retargeting, read on in Multichannel Merchant.

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AI Personalization

AI-powered recommendations, writes Jan Soerensen, General Manager, North America at Nosto, will become more transparent to consumers by providing clearer explanations for why certain products are suggested to shoppers. For instance, the consumer might be told that the item is in their size or it has a similar color to a previous purchase. Such explanations will serve to make AI recommendations less intimidating and ultimately more successful.

Image Recognition

Shoppers will soon be able to search for products within images and videos, and online personalization engines will be able to recognize specific colors and patterns. While this “shop the look” capability exists now to some degree, the capability will gain more traction, particularly in verticals like fashion and interiors.

Psychographic Personalization

Demographics that are commonly used in ecommerce personalization include age, gender, geography and online behavior. But new types of personalization, such as personality types (i.e. trusting, confident, adventurous) could be applied to the user experience in the future and inform product recommendations.

For more ways in which personalization could evolve in 2021, including recognizing long-term consumption habits and pinpointing the most profitable visitor segments to target, read more in Multichannel Merchant.

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