Today we’re going to talk about the value of qualitative customer data, and how to use it well. To help me discuss this topic, I’d like to welcome Daniel Erickson. Founder & CEO at Viable, an AI analytics tool that enables businesses to instantly access and act on valuable insights from customer feedback.

This article was written by Greg Kihlström for CMSWire. It's likely already too late to pause adoption, but you can still establish an enterprise-wide stance on adoption and best practices for AI in business.

The concept of the autonomous enterprise refers to organizations that leverage advanced technologies, such as artificial intelligence (AI) and automation, to operate more efficiently and effectively.

There are likely many ways that artificial intelligence can benefit your organization, and you likely don’t have time to wait in order to reap the potential benefits.

One of the top trends in customer engagement for 2023, as outlined in Braze’s 2023 Customer Engagement Review, is the challenge of data management for brands

What happens when a disruptive technology is introduced midway through the process of transformation? Unless you’ve got access to a time machine to travel back and forth, you and your team are likely grappling with how to incorporate artificial intelligence like generative AI into your plans.

One crucial aspect that often goes unnoticed or is overlooked in discussions about AI and machine learning is the importance of foundational data infrastructure.

There has already been an impact of AI on content creation and Search Engine Optimization (SEO) and this will continue to grow, particularly with the emergence of Chat GPT and other AI technologies in search engines like Bing and Google.

Last holiday season, and even most of last year, it was hard to escape stories about how the supply chain was causing difficulties for retailers, as well as their customers. This article is based on a recent podcast interview with Peter Pernot-Day at SHEIN.

This article was written by Greg Kihlström for MarketingProfs. Read the full article here.

Most marketing leaders would agree that providing a more personalized customer experience has the potential to drive more purchases, stronger loyalty, and greater customer lifetime value (CLV). But what is the cost of providing those personalized experiences?

This article was written by Greg Kihlström for Fast Company. The website redesign: It is an all-consuming, oft-repeated, difficult-to-measure process that seems to be a requirement for any brand wanting to stay on top of their customer expectations and competitive pressures.

Automation and machine learning have revolutionized the way businesses operate and interact with their customers.

Marketers have a unique relationship to the data within an enterprise, thus data science is increasingly a topic of conversation among their teams.

The last article of the series will look at workflow automation or robotic process automation (RPA), or AI-based tools that enable repetitive tasks to be performed by software rather than humans.

Collecting and analyzing customer interactions is crucial for brands in today's digital age.

Artificial intelligence’s impact on business today, particularly in the marketing world, cannot be ignored. From the unprecedented adoption of ChatGPT to the constant buzz around new AI-based features, we are bombarded with information.

Optimizing customer experience is table stakes these days, as we all know. Doing so consistently, and in a way that balance organizational strategy with competitive pressures, and customer expectations in a consistently improving way can be a challenge, however.

Customer journey analytics is a powerful tool that allows brands to optimize and personalize the customer experience.

This article was written by Greg Kihlström for CMSWire. Uncover the six critical elements of impactful customer journey management & operations to boost your customer experience and foster loyalty

This article was based on a recent podcast interview with Scott Love of Lovelytics. We talk about artificial intelligence and machine learning in the enterprise, where it is today and where it’s currently headed, as well as the role of place in building talented data and technology teams.