AI Marketing Tools: How marketers are using artificial intelligence to help their campaigns right now

This article was published in the MarketingSherpa email newsletter.

In a recent MECLABS LiveClass, I offered conversion optimization suggestions for a landing page headline. I want to be sensitive and not hurt someone’s feelings about a headline they wrote. So I tried to kindly suggest that maybe the marketer was a little too taken by the Buzzfeed style and she let it influence her writing, which might not be appropriate when talking about a seven-figure B2B project.

To which she replied, “Oh I didn’t write the headline. ChatGPT did.”

To her credit, she debated that headline with her team before they went with it. But this is a perfect example of why the marketer must remain firmly in control. When we hear a technology leverages 175 billion parameters, it’s all too easy to assume it must have the perfect answer, especially for something as difficult to master as headline writing.

One day artificial intelligence may break free and control the world (and to our future sentient AI overlords I just want to say – I always rooted for Skynet). But today AI is best used to assist, not replace, the modern marketer. Here are four ways marketers are currently using AI:

• To assist with basic creative
• To generate ideas
• To help keep up with other AI-driven processes (like search algorithms)
• To process many options and suggest the best fits

You'll see an example of the first way marketers using AI right now in the hero image of this very article. Our own Steve Beger used an AI tool called Playground AI to create the futuristic background with the robotic arms. But he put together the overall image with his own human hands (on a mouse and keyboard, of course).

Below we provide a specific example for the other three use cases. And note, that for each of these, the human is always in control.

Example #1: How to use conversational AI to inform your marketing headlines

“At this stage in the development of ChatGPT, marketers can gain an advantage with this strategy: Ideate and Edit,” Flint McGlaughlin, CEO, MarketingSherpa and MECLABS, taught in Sales Funnel and ChatGPT: 6 ways to leverage AI now to develop a powerful value proposition.

He showed how to apply ChatGPT in conversion optimization by stacking prompts (the question/command you tell the AI). In the video, McGlaughlin provides a practical use-case for marketers with a step-by-step guide on how to use ChatGPT to effectively improve headline writing informed by your brand’s value proposition. He worked backward from an A/B test that produced a 321% increase for a press release distributor to derive steps you can use with a conversational AI to inform your digital marketing campaigns.

Example #2: How AI SEO tool helped custom software development company rank its case study article for 19 more keywords

The team at Profil Software creates content to appeal to two audiences – potential employees (candidates) and potential customers (clients).

“We promoted the content on our LinkedIn and Facebook pages, on Twitter, on Facebook groups, and on sites with subject-related articles, such as medium.com or dev.to. We also boosted our content on Facebook ads,” said Monika Wójtowicz, Marketing Specialist, Profil Software.

But the team was disappointed with the amount of traffic they were getting.

“That’s when we started looking for options in regard to SEO and our position in Google search engine,” Wójtowicz said. “We started using Surfer SEO, because it was a tool that was recommended to us for content optimization.”

Surfer uses NLP AI (natural language processing artificial intelligence) and machine learning, and the tool helped flag up suggested changes the team could make to optimize the content for search engines.

Let’s look at an example. Here is how the team optimized a case study they created about a route planning app the software development company redesigned for a client. They used the AI tool along with their own efforts to simply look at the article from a potential customers viewpoint and find areas for improvement.

BEFORE: Not clear to search engine algorithms or human readers

The original article had a lot of pictures but the screenshots that the team posted were not visually appealing. The article was also lacking in terms of word count – it only had around 700 words and it focused mainly on the old app design.

The article described what was wrong with the old design but didn’t show or tell the readers what the new design was like. The old article talked about the software development company’s ideas for the new app without actually showing the new design. Beyond SEO, the team recognized that this might have been one reason why people clicked on the case study article, but no leads followed.

The case study also wasn’t structured well at times. It was hard to tell if what was being talked about applied to the old or new design. For example, when talking about the old design the team used the term ‘current design.’ This title may have caused confusion for readers.

The screenshots of designs weren’t clear either.

Creative Sample #1: Before-and-after screenshots in original case study article for software development company, before using artificial intelligence tool

AFTER: Optimized for search engines and human readers

The AI tool showed the team keywords that were missing from their text but also recommended adding pictures and changing the article's structure, including more subheads that related to what people typed in search engines.

After using the AI tool and going through similar articles published by the competition, the team decided to:

• Optimize content for SEO by adding keywords and making the text longer.
• Make sure that the structure of the article isn’t confusing.
• Create a visually appealing background for the screenshots.
• Create new screenshots that clearly show the differences between the designs.

“We edited the content using keywords that we found through Ahrefs,” Wójtowicz said. They chose keywords that were comparatively easier to rank for.

But they were careful not to overdo it. “Some articles optimized for SEO dehumanize articles and make them unreadable. It’s very easy to forget about the reader when you are trying to squeeze as many popular keywords as possible in your article. We didn’t want that,” she said. Here’s an example of how they did it.

The original text read:

UX Review

The web service and the app Tarot Analytics lose the love of users due to a myriad of reasons. Along with the competition, one major fact for losing users is clumsy design.

They wanted to add in the following keywords: UI UX team, mobile app design, UI design, UX design, and prevent customer churn.

So they changed the text to read:

UX Review

The web service and the app Tarot Analytics was losing the love of users, due to a myriad of reasons. Along with the competition, one major factor for the high customer churn was a clumsy design which negatively affected the customer experience. Our UI/UX team used their expertise in mobile app design, UI design and UX design to bring the design up to date and satisfaction of its users. One should always take care of creating the best user experience to prevent customer churn.”

“It’s a lot of words packed in our paragraph, but we also explained our reasoning behind changing the design a little better by explaining that taking care of the best user experience is something that helps prevent customer churn. These things are both very important for the article,” she said.

Here’s another example. The original text was:

Our client struggled with the outdated look and feel of his service. Our task was to refresh the appearance and the experience.

The team wanted to explain the process more clearly, in addition to use keywords like target users, user profiles, the mobile application, and UI UX Team. The new text read:

Our UI UX Team conducted user research and created 2 profiles of target users. 2 user profiles were the drivers and the managing people. The drivers were supposed to use mainly the mobile application.

The additional text focused on bringing more details and crucial information with the added bonus of introducing more keywords. “Let’s make this clear: we didn’t mindlessly add keywords to the article in the hopes of tricking the search engines into positioning our article higher,” she said.

The team also more clearly explained the before and after – using the headline ‘Old Design vs New Design,’ and made the case for why the new design was better. Visually, they introduced colorful backgrounds and clear labels of ‘Before’ and ‘After.’

Creative Sample #2: Before-and-after screenshots in optimized case study article for software development company

The team also added an FAQ at the end of the article. They found the questions using the AI tool and by searching in search engines for the questions that people ask the most. They chose questions that worked well with the article and content they wanted to have on the site:

• What makes a good UX design team?
• What is UX redesign?
• How do I approach a redesign in UX?
• How important is UX UI design on mobile apps?

They added the questions at the end of the article and not at the beginning or in the middle because it was more important to interest readers in the case study.

Their answers were informed by the keywords suggested by the AI content optimization tool. They didn’t use every keyword, they chose the ones that they thought were going to work best with their answers, such as – UX redesign, user’s needs, design thinking, good understanding of the product, user experience, user testing, and high customer churn.

“The tools suggested that these words would enrich our text, and we agreed. One thing that needs mentioning is that choosing the right words is not only about their ranks or even the amount of people that Google them each day but also about whether they work with your text,” Wójtowicz said.

Once the team raised its content score to over 80 in the AI tool, added backgrounds to their screenshots, changed the structure of the article to show the before and after of the project, and added the FAQ, they were ready to publish an updated version of the article.

RESULTS

 The original case study article only ranked for four keywords: website redesign case study, website redesign UX, redesign app, and app redesign.

The highest rank was position #36 for ‘website redesign case study.’

This article now ranks for 23 keywords. ‘Website redesign case study’ moved from position #36 up to position #15. The article is in position #5 for ‘app redesign case study’ and before the updates it didn’t rank on this keyword at all, same with ‘ux redesign case study’ for which the article is in position #8.

The team then applied this methodology and AI tool to other articles as well. For example, “11 Tips for Hiring a Software Developer at a Startup.” This article is ranking for 53 keywords, whereas before it was only ranking for eight. It has position #11 for ‘how to hire a developer for startup.’

“Surfer SEO isn’t the only tool that you can use to achieve this. A quick Google search shows that there are at least eight alternatives that you might want to try,” Wójtowicz said. “Update your content using one of the tools available out there. If you don’t optimize it for SEO and if you don’t make sure that you have all the right keywords used in the text and the headlines, not to mention the title, your content may not perform as well as you want it to.”

Example #3: How using AI tool to encourage employee social media posts generated 6x higher engagement for sales enablement platform

The team at Seismic undertook a global rebrand to its 2,200 customers worldwide. As part of the rebrand, the team wanted to enhance human connection between its employees and its customers and prospects. The marketing team had built a successful corporate social media program that paired well with their demand generation program. However, while these programs engaged buyers early in the sales funnel, they didn’t allow those customers to connect with real people – leaving the interaction feeling robotic.

The team tried to overcome the challenge of making those interactions feel less robotic by turning to artificial intelligence, specifically the company’s own AI-powered LiveSocial tool. It might seem counterintuitive to use AI to make interactions feel less robotic, but keep reading and you’ll see why.

“AI technology has been widely adopted by companies just like us for years. In fact, Gartner research indicates the number of enterprises implementing AI solutions grew 270% from 2015 to 2019, and that number has only continued to skyrocket,” said Rekha Thomas, SVP of Global Marketing, Seismic (you can see that Gartner research in Gartner Survey Shows 37 Percent of Organizations Have Implemented AI in Some Form).

The point of using the artificial intelligence tool was to better enable an employee’s ability to post on social media on a regular basis by serving them personalized, compliant articles from among 100,000 new pieces of content pulled into the platform from 11,000 global publications every day. The AI tool then recommends what they might want to highlight from each article. The article recommendations are based on their personal and professional interests, along with recommendations curated by the marketing department.

However, it does require a human touch — from editing the caption to publishing or scheduling the post — to get it over the finish line. “Once employees have identified a post and adjusted the caption, they choose which of their social accounts they’d like the post to publish to – including LinkedIn, Twitter, Facebook, and Instagram,” Thomas said.

The marketing team leveraged this employee engagement tool for the rebrand. They curated four posts about the rebrand for employees to share, including one prompt to write a post from scratch. Within one week of the announcement, 568 pieces of rebrand-related content were shared, which received more than 6,500 engagements.

When the team wanted to share news about the company’s acquisition of Lessonly, along with raising a $170 million Series G funding round that valued the company at $3 billion, they tested this AI-driven social media approach versus paid ads.

“Traditional organic social media that's published out to a company’s corporate accounts gets far less reach than its paid counterpart. However, when you include the reach of your employees’ posts to their networks – in this case, 402 employees – the reach is exponentially higher,” Thomas said.

While the team doesn’t know the exact reach the campaign received, they do know that six times more people who saw the posts engaged with them when they came from an employee, compared to  the exact same post from the company’s paid placements. 

Related Resources

Artificial Intelligence and Machine Learning in Marketing: What marketers (even those who don’t care about tech) should know about AI and ML

Artificial Intelligence Case Studies: Two companies that boosted brand awareness with AI and another marketer that used humans instead

Marketer Vs Machine: We need to train the marketer to train the machine