Products

EMARKETER delivers leading-edge research to clients in a variety of forms, including full-length reports and data visualizations to equip you with actionable takeaways for better business decisions.
Reports
In-depth analysis, benchmarks and shorter spotlights on digital trends.
Learn More
Forecasts
Interactive projections with 10k+ metrics on market trends, & consumer behavior.
Learn More
Charts
Proprietary data and over 3,000 third-party sources about the most important topics.
Learn More
Industry KPIs
Industry benchmarks for the most important KPIs in digital marketing, advertising, retail and ecommerce.
Learn More
Briefings
Client-only email newsletters with analysis and takeaways from the daily news.
Learn More
Analyst Access Program
Exclusive time with the thought leaders who craft our research.
Learn More

About EMARKETER

Our goal at EMARKETER is to unlock digital opportunities for our clients with the world’s most trusted forecasts, analysis, and benchmarks. Spanning five core coverage areas and dozens of industries, our research on digital transformation is exhaustive.
Our Story
Learn more about our mission and how EMARKETER came to be.
Learn More
Methodology
Rigorous proprietary data vetting strips biases and produces superior insights.
Learn More
Our People
Take a look into our corporate culture and view our open roles.
Join the Team
Contact Us
Speak to a member of our team to learn more about EMARKETER.
Contact Us
Newsroom
See our latest press releases, news articles or download our press kit.
Learn More
Advertising & Sponsorship Opportunities
Reach an engaged audience of decision-makers.
Learn More
Events
Browse our upcoming and past events, recent podcasts, and other featured resources.
Learn More
Podcasts
Tune in to eMarketer's daily, weekly, and monthly podcasts.
Learn More

The Daily: How generative AI can humanize messaging, LinkedIn bets on trust, and ChatGPT's personalizing content

On today's episode, we discuss real-world examples of how generative AI can humanize messaging, increase engagement, and turn customers into brand advocates. "In Other News," we talk about why LinkedIn is betting on trust and some promising use cases for generative AI in content marketing. Tune in to the discussion with our analyst Kelsey Voss.

Subscribe to the “Behind the Numbers” podcast on Apple Podcasts, Spotify, Pandora, Stitcher, Podbean or wherever you listen to podcasts. Follow us on Instagram

Episode Transcript:

Marcus Johnson:

The new analyst access program from Insider Intelligence provides clients with exclusive access to a team of thought leaders who create our research. The one-on-one sessions would be tailored to your unique retail and e-commerce business, providing a deeper understanding of the most relevant and timely research that affect your growth goals. Visit insiderintelligence.com/analyst access to find out how you can book your interactive presentations on retail media networks, CBGs and more.

Kelsey Voss:

It can immediately mitigate for CX customer experience with personalized solutions, again, personalized. And it can encourage customers to provide positive reviews and also share user generated content.

Marcus Johnson:

Hey gang, it's Tuesday, June 20th. I hope you all had nice long weekends. Kelsey and listeners, welcome to the Behind the Numbers Daily, an eMarketer podcast. I'm Marcus, may not sound like it. This is my new voice that you're probably stuck with for a while, but I'm definitely still here. And today I am joined by one of our principal analysts spaced out of Seattle, it's Kelsey Voss.

Kelsey Voss:

Hello.

Marcus Johnson:

Hey, Kelsey, welcome to the show. Welcome back, I should say.

Kelsey Voss:

Thank you.

Marcus Johnson:

Today's fact, how many animals are there on the planet? Would you like to guess? Kelsey's like, no.

Kelsey Voss:

All animals?

Marcus Johnson:

All species of animals.

Kelsey Voss:

That's phenomenal number. I don't know. I imagine it's quite [inaudible 00:01:38].

Marcus Johnson:

No one knows, yeah. Well, this is actually the kind of crux of today's fact, is that actually yeah, no one really knows. So as of now, there are around 1.2 million species of animal that have been identified and described so far. Most of them are insects, but 1.2 million. However, scientists have estimated that there is a total of nearly 9 million animal species living on earth. So put another way, scientists think that there are nearly 8 million species yet to be discovered. Put another another way, for every one animal on the planet scientists think there are another eight yet to be discovered. It's terrifying. So you might be thinking, well, where the hell are they? Well, according to the Federal University of Paraiba in Brazil and also Yale University in the US, tropical environments in countries like Brazil, Indonesia, Madagascar, and Columbia are most likely to harbor the most undiscovered species. And then also in the water, scientists estimate that over 90% of ocean species have yet to be classified, over 90%. And that over 80% of our ocean is unmapped, unobserved and unexplored.

Kelsey Voss:

Fascinating.

Marcus Johnson:

Yeah, it's terrific. If you're looking to hide somewhere, the ocean is a good place to start.

Kelsey Voss:

The mafia would agree with you.

Marcus Johnson:

Yeah, that's very true. That gets brought up a lot on this show. I feel like Stephanie's bringing it up every other episode, shout out the mafia, can't to stop watching so much Sopranos. Anyway, today's real topic, The Power of Generative AI in the Buyer's Journey. So in today's episode, first in the lead we'll cover generative AI in the buyer's journey. Then, for another news, we'll discuss why LinkedIn is betting on trust and the use cases for AI in content marketing. But Kelsey, we're starting with generative AI in the buyer's journey. Something you've just finished writing about, talking about how marketers are elevating customer experience using artificial intelligence. And so first question is, what is exciting US marketers the most about generative AI?

Kelsey Voss:

Gen AI can be such a powerful tool for marketers. I'd say marketers are excited that it can speed up market research on prospects that can help create and scale content faster. And it can be used as a springboard to brainstorm ideas for future campaigns. I would also say that a top benefit of gen AI for content creation is the increased performance. And this was per a BACO AI survey from March 2023. Increased performance outweighed cost efficiencies. So it's really about how gen AI can support and enhance and improve the work that marketers do with their content and campaigns.

Marcus Johnson:

Yeah. You mentioned some really interesting ways or reasons that US marketers are excited about gen AI, which you very nicely abbreviated. I keep saying generative AI, which is exhausting at best. So gen AI is what we'll use from now on. But what I found most fascinating, you had some research from Sitecore in the chart that was asking what excites US marketers the most. And what was most interesting to me about that survey was that marketers appeared to be very excited about multiple benefits of gen AI. Each response, and there were I think six of them, got over 50%. And so it seems like there's not just one thing that people are overwhelmingly excited about. There's multiple items here that marketers are getting pretty stoked about. In the report you write that gen AI can help businesses boost brand awareness. And then you go on to suggest that it's possible for gen AI, for generative AI to humanize messaging. How that seems counterintuitive, how so?

Kelsey Voss:

Yes, it does. Yes, it absolutely can. Yes, it can write, copy content that is sometimes better than human generated content. And an example of this is Chase Bank, and they've been doing this for a while. They look at a vocabulary database filled with over a million words that trigger emotional appeal in consumers, and then they use gen AI. It's actually from Persado, which is a company that uses gen AI to write marketing creative. They use that gen AI to humanize their messaging. For instance, a traditional human generated ad for the bank read, access cash from the equity in your home. The AI generated version which didn't have the subjectiveness of the marketer read, it's true, you can unlock cash from the equity in your home and it performed better.

Marcus Johnson:

And it's interesting because they sound similar, but it's not until you look at both those statements side by side and break them down. The second half of both of those different marketing messages from the bank are equity in your home. Both of them are the same. But it's the beginning which is so interesting. So the beginning of the one written by a human was access cash, and the other one written by the AI generated version is started with, it's true, to suggest the kind of true or false element that this thing is true that they're about to tell you. And then the you can, was quite empowering, something that you can do. And then unlock, that visualization of you being able to unlock and gain access to something. And yeah, I think if you put both those statements in front of me, I probably would've said that one was written by a human and not the other one, which is quite terrifying.

Kelsey Voss:

Yes.

Marcus Johnson:

So how does... You talk about how generative AI can also increase engagement, not just humanized messaging, but increase engagement as well. How so?

Kelsey Voss:

Well, first I would say dehumanizing messaging aspect of it, it's not always the case. So again, you would want some human oversight there to make sure that the messaging is on point and makes sense with the brand.

Marcus Johnson:

Yeah, absolutely.

Kelsey Voss:

You can't just let it free and go. But as far as engagement, Gen AI can increase engagement in a number of ways. It can provide product information and relevant product reviews based on buyer preferences and behaviors. It can repurpose content into different formats that may be more appealing to certain buyers. It can create more customized email copy and it can help write personalized chatbot responses that are specific to that buyer in their tone of voice. For example, Sephora has a virtual artist chatbot that applies natural language processing to understand customers questions and then provide personalized makeup recommendations. The chatbot also uses a different type of AI to analyze a buyer's facial features that will help with this recommendation

Marcus Johnson:

And this, so I was looking up some research from Bolt and they were looking at what beauty technologies would help US beauty consumers feel more confident purchasing products digitally. This was from May of this year. And personalized content, which is what you said Sephora's virtual artist does very well, providing personalized makeup recommendations. Personalized content and product recommendations was the number one technology that Americans felt would help them the most when buying beauty products by 37% and customizing foundation color, things like that. Shade matching was 27%, and then virtual product try-on, foundation try-on with a camera was behind that in 19% as well. So it seems like a technology that people absolutely want and can help them make those decisions.

Kelsey Voss:

Yes.

Marcus Johnson:

Further down the report, you talk about how artificial intelligence can turn customers into brand advocates. How so?

Kelsey Voss:

There are multiple ways. For instance, gen AI can offer referral incentives and reward customers who are likely to recommend their brand. It can immediately mitigate poor CX customer experience with personalized solutions, again, personalized. And it can encourage customers to provide positive reviews and also share user generated content. And one of the best and most, I would say famous examples of this encouragement is from Coca-Cola. They launched an AI platform with DALL-E 2 and GPT-4 for a create real magic contest, in which artists can generate original works using Coke brand assets for the chance to be featured on Coke's digital billboards in Times Square and Piccadilly Circus, which is pretty cool.

Marcus Johnson:

Yeah, that is pretty cool. Yeah, giving people a chance to be featured in pretty most prominent positions arguably, particularly for outdoor advertising in New York and London is a heck of a draw. So I thought this a really good example of how to turn those customers into brand advocates using AI. What are two ways that marketers and CX leaders can capitalize on generative AI? You have a bunch in your report at the end, but could you give me and the listeners two ways that marketers and CX leaders can capitalize on gen AI?

Kelsey Voss:

I would say overall first that marketers and CX leaders need to be able to change and adapt as the technology keeps evolving quite rapidly. So they should, I would say, smartly lean into innovation and experimentation with Gen AI. What I mean is, they should invest in training so employees can develop AI skills and knowledge, including effective prompts and context and data analysis techniques. But they should also keep business objectives in mind and not get too distracted by all the fun they can have with Gen AI, for instance they should continue to monitor and measure how Gen AI applications perform. And always to make sure design experiences that meet the needs of their customers.

Marcus Johnson:

That was the one that I pulled out as well, the investing in training and not just letting or assuming that your employees are going to run off and start experimenting with this by themselves. But having some kind of a well-thought-out initiative and strategy in terms of understanding this technology as a company, and helping to disseminate that information to your employees through specific training programs I thought was very smart. And then your point about considering ethical implications, I thought was incredibly poignant. Monitoring the regulatory landscape as well because using this technology could certain... And we've already seen it in a handful of instances, and the thing's been around for generative AI at least, particularly mainstream generative AI has only been around for six odd months, but they could certainly backfire particularly with regards to brand safety,

Kelsey Voss:

Right. Yes, it absolutely can.

Marcus Johnson:

That's what we've got time for, for the leads. It's time of course, for the halftime report. So Kelsey, what to you is most worth repeating from the first half?

Kelsey Voss:

I think we keep coming back to personalization and that's where gen AI can really help and support marketers. And generative AI, I should say, is not replacing marketers. It's helping them do their jobs better, increasing their performance. But the personalization aspect of it, I think is it permeates throughout a lot of what the marketers are doing. By using gen AI, they can create content that resonates very specifically with buyers and customers. They can deliver very specific personalized recommendations. They can offer hyper personalized content through chatbots. But overall delivering that personalized experience that can exceed customer expectations is what's really helping marketers.

Marcus Johnson:

Yeah, I think it's a brilliant takeaway. It's a word that popped up in your report quite a lot in a number of different sections. And I think that just supports what you are saying in terms of the importance of personalization, particularly with using generative AI, what it can do for marketers. Kelsey's full report is called The Power of Generative AI in the Buyer's Journey, how marketers are elevating customer experience. There's a link in the show notes, and of course you can head to insiderintelligence.com to read it there as well. Now, that's what we've got time for for the first half-time. For the second half of the show today in other news. LinkedIn bets on trust and what are some promising use cases for Gen AI in content marketing

Story one, LinkedIn is betting on trust. The professional social network recently rolled out new features to bolster its verification processes aimed at instilling increased confidence among job seekers, about the authenticity of companies and job postings on the platform. So our director of briefings, Jeremy Goldman, he notes that these upgrades follow LinkedIn's recent introduction of free verification badges to validate users' identities and employment through a partnership with CLEAR. That company you might have seen at the airport before. But Kelsey, the most interesting sentence in Jeremy's article about LinkedIn betting on trust is what and why?

Kelsey Voss:

I think the most interesting sentence is the very last one which is, this move by LinkedIn could also set a precedent for other social platforms and encourage them to take more proactive steps towards enhancing user trust and safety. Meaning in an era of eroding trust from many previously trusted institutions, social media side, LinkedIn can lead the way. And particularly with the growing use of AI generated fake profiles on all networks, LinkedIn's success at this could influence how other social platforms tackle their own issues with user trust.

Marcus Johnson:

Yeah. Story two, Kelsey, you recently wrote a piece noting that nearly six in 10 marketers worldwide already used AI tools to optimize existing content to improve things like search or copy. According to a 2022 ERA survey, in the piece you outlined four promising use cases for gen AI in content marketing to repurpose content to personalized content, to create high ranking content and to test content. Which of these use cases to you is most interesting at this most and why?

Kelsey Voss:

Let's go back to personalization. So I believe the use case to highlight here is to personalize content. I say that AI tools can track buyer and customer behavior, segment audiences and help distribute personalized content. So some of that AI is not generative AI, but the personalized content aspect is the gen AI part. So you can personalize that content in the tone of voice of the buyer. And to match their preferences to be specific and customized to certain locations at specific time and different languages. So hyper-personalization is the best use case.

Marcus Johnson:

Yeah, terrific points. That's all we've got time for today's episode. Thank you, Kelsey, so much for hanging out today.

Kelsey Voss:

Thank you.

Marcus Johnson:

My pleasure. And of course, thank you to Victoria who edits the show, James, who copy edits it, and Stuart who runs the team. Thanks to everyone listening in. We'll see you tomorrow for the Behind the Numbers, Re-Imagining Retail show, an eMarketer podcast where host Sarah Lebow will be speaking with analysts Andrew Lipsman and Max Wills, all about the latest developments with retail media networks.