How global marketers are using AI to solve their pain points- 9th Edition

Welcome back to the 9th edition!

Happy Sunday....

It's an honor to have each of you along for the ride.

With each edition, we've delved deeper into the transformative power of AI across various sectors of business operations, from sales to customer service.

As a seasoned marketing professional with over a decade of experience, I've witnessed firsthand the remarkable evolution of technology within our industry.

From the rise of social media to the advent of data analytics, the landscape continues to shift, presenting both challenges and opportunities.

Throughout my journey, I've remained dedicated to staying at the forefront of these advancements, eagerly absorbing knowledge through webinars, certifications, and hands-on experience.

And now, I'm thrilled to share with you the insights I've gathered on how marketers are leveraging AI to tackle the challenges they face in today's dynamic environment.

So, let's kick back, relax, and delve into this captivating realm where creativity intersects with cutting-edge technology.

Do you know how are marketers currently implementing AI to solve challenges they’re facing?

What can AI do for your marketing campaign?

In data-driven marketing, the near limitless media channels demand an almost insatiable amount of content. Marketers are stretched to the limits of their output, and many smart marketing teams are turning to AI for help with the time-consuming, mind bending and overwhelming task of serving relentless marketing channels.

Whether the struggle is to generate copy, target the right audience or measure results, AI can be the smart, fast and cheap assistant you’ve been looking for.

Here are several examples of teams that not only improved their marketing campaigns with AI, but built tools to help them repeat their efforts.

1. Bayer

Bayer’s Australia team wanted to do more than respond to market trends. They wanted to predict the future and get in front of those trends, according to a case study.

“We wanted the work to become less reactive and more proactive, so we could predict and anticipate how to best reach the right consumer with the right content at the right time,” says Eric Gregoire, SVP and global head of digital and media, Bayer.

To accomplish this, the team combined Google trends data with weather and climate information and fed that into a forecasting model that they built with Google cloud machine learning (ML) technology. The model predicted when a 50% surge in flu cases would happen across the country.

The marketing team used this knowledge to adapt their marketing strategy to get the most effective and engaging copy in front of the right people at the right time. The strategy worked better than they ever dreamed it would.

Results

• 85% increase in click-through rates year over year
• Reduced cost per click by 33% over previous year
• Saw a 2.6x increase in website traffic over long run

You can check out the detailed article here

2. Sage Publishing

Sage Publishing is a global textbook publisher that creates educational materials in the native languages of its audience. The company’s marketing team was responsible for developing copy for more than 100 new textbooks each year. This was time-consuming and expensive, according to a case study.

“We needed an interface that could not only power content creation at scale, but be incredibly organized and allow our teams to work together and share content,” says Shellie Johnson, senior director of global marketing operations, Sage.

They turned to Jasper, a marketing-specific AI toolkit. The team used Jasper to simplify and speed content creation. By inputting a book’s title, author and preface, the tool was able to draft book descriptions in seconds.

This allowed the company to bring translations in house, which allowed it to quickly expand the reach of its products into new regions. It also nearly eliminated the team’s need for copywriters on certain vehicles, such as jackets and catalogs. Instead, the team focused on improving content and raising the quality bar for their campaigns and content. The team was happier working on more meaningful tasks and the quality and quantity of their output improved.

Results

• Reduced time spent on content drafting by 99%
• Reduced the company’s marketing spend by 50%
• Increased the speed of creating textbook descriptions by 99%

You can check out the detailed article here

3. Buzz Radar

A good social and influencer marketing campaign can yield big results. But creating them involves crunching a lot of data and spending a tidy fortune. Buzz Radar wanted to make the process easier for marketing teams, especially those who are not data specialists, according to a case study.

“I was working at a marketing agency that pioneered social media marketing for international brands,” says Patrick Charlton, CEO and co-founder, Buzz Radar. “For every client, it was the same story: we would have a team of a dozen analysts working hard all week to analyze the ROI of a social campaign and produce detailed reports. But when we presented the data to our clients, they didn’t really have time to absorb more than an executive summary.”

He left the agency to form Buzz Radar and build out a platform called the Cognitive Command Center. He used IBM Watson technologies as a backbone. The platform includes digital marketing, monitoring, analytics and visualization and provides trends and insights in real-time.

“By providing instant insight into return on investment, we give our clients the data they need to optimize their campaigns in-flight.”

Results

• Millions of dollars saved for clients maximized their ROI in digital media campaigns
• Enabled agency to outperform larger, more established competitors
• Helped eliminate employee attrition by letting developers focus on interesting problems

You can check out the detailed article here

4. Epsilon Abacus

Epsilon’s Abacus team helps brands reach the right consumers with the right product. When customers want to run a campaign, the company can build a modeled list of customers who might be interested in their product, catalog or sale. This is a complicated process, according to a case study.

“In the environment of increasing privacy regulations, the tools Epsilon employs need to provide transparent list selection,” says Andrea Thornton, VP of analytics, Epsilon Abacus.

Epsilon Abacus wanted to use machine learning to improve its list accuracy and stay ahead in a rapidly evolving marketing niche. It turned to H20.ai to develop a machine learning system, called Accelerate, to do the heavy data crunching faster.

The model removed inaccurate targets, added relevant consumers and delivered improved lists to the team’s data scientists, who combed it before offering it to clients. As a result, Epsilon Abacus was able to improve response rates and revenue for its customers.

Results

• Improved list response rates by 3%-5%
• Increased direct mail response rate for one large client by 1.10%
• Found, on average, 15,000 highly relevant customers for every marketing campaign

You can check out the detailed article here

5. Typeface

Many small brands turn to Typeface as a content management solution. The company wanted to boost its offering by making it easier for those brands to compete with the big marketing budgets of larger competitors, according to a case study.

Typeface used Microsoft Azure, OpenAI Service and Azure machine learning to build tools and templates that can create brand-specific images and content in seconds. Typeface’s template engine ingested a client’s brand look and feel and quickly generated images and content that are consistent with it. The tools allowed Typeface customers to quickly turn a few assets, a defined brand look and voice and some ideas into large amounts of content that they can use across all channels.

“Because of the capabilities of Azure OpenAI Service and the overall Azure platform, we were able to go from a vision to a solution incredibly fast,” says Vishal Sood, head of product, Typeface.

The templates saved customers time and money, kept their intellectual property safe and allowed them to generate the high-volume content necessary to market across various social media channels.

Results

• Made it possible for small companies and startups to compete with major names in their market
• Generated 10x content for a client with a small team
• Transformed ideas into on-brand copy and images in seconds

You can check out the detailed article here

What's stopping you from implementing AI?

Consider this: 70% of marketers consider it easy or somewhat easy to measure the success of marketing automation, so give it a go.

In the worst case, you‘ve run an experiment (and isn’t that what marketing is all about?), and in the best case, you've got the data to support the success of your AI endeavors. Getting buy-in from your team or stakeholders will be easier when they know AI drives marketing objectives.

Plus, with the top tips from marketing leaders, you’ll start with the best possible insights to make AI and marketing an absolute success.

See you in my next edition!

Rubia