The CMO’s guide to AI-powered marketing

Understanding trends in AI marketing

For as long as marketers have honed their craft, they’ve understood that the organizations that know their customers and most effectively provide a personalized experience are the ones that can drive engagement, acquisition, and lifelong loyalty. In fact, research shows that a well-executed, hyper-personalized marketing strategy can deliver 8x the return on investment (ROI) and lift sales by 10% or more.¹

Although marketers have relied on AI for some time now (maybe without even realizing it), the generative AI revolution is creating lots of excitement, numerous questions, and some trepidation about what new use cases could mean for marketing. For many organizations, it can still be very difficult to power a customer-centric and hyper-personalized AI marketing strategy that effectively links back to and connects with its customers.

To understand why, we surveyed a diverse group of marketing and IT leaders throughout the world to:

• Identify the use cases that marketers prioritize but struggle to execute
• Understand the common challenges that marketers experience with generative AI use case execution
• Define what marketers truly mean by “personalization” and “bringing their customer experiences to life”

When exploring the major challenges that organizations run into when implementing or using artificial intelligence/machine learning (AI/ML) to support their marketing use cases, our research uncovered an impactful collection of barriers.

What are the major challenges or barriers that your organization experiences when implementing and using AI/ML to support marketing and advertising use cases?

Marketing benefits from a unified data ecosystem combined with AI

Providing a superior customer experience is increasingly important for organizations, especially in today’s crowded marketplace. However, to meet or even exceed their customers’ needs, organizations should adopt a unified data ecosystem that integrates with their existing data systems, as well as harnesses the power of AI to create authentic customer experiences. This unified data ecosystem serves as the infrastructure that helps organizations take advantage of AI. In addition to positioning your organization to be successful with AI, you may realize the following benefits:

Make everyone an analyst
This concept of “everyone is an analyst” introduces a new way to work by making data and marketing analytics capabilities more accessible to all interested stakeholders. Essentially, it can empower an understanding of data at a superficial level by enabling marketers and other business users with the ability to create actionable insights through conversation. In turn, this can make insights commonplace and reduce the time needed for organizations to transform their vast amounts of data into insights and decisions.

Democratize storytelling
As part of our research, we discovered that 42% of marketers believe that generative AI use cases have the potential to significantly impact their marketing processes and are actively exploring its capabilities. For example, content guidelines and policies can be effective tools for marketers but are sometimes difficult to design and deploy. Content strategists can utilize generative AI to brainstorm and develop the content pillars that incorporate their organization’s mission, vision, and brand values. Additionally, generative AI can be an effective tool to enforce the brand guidelines that ensure an organization’s voice is consistent in content and community engagements across numerous platforms and channels.

How to create a unified data ecosystem and enable AI-powered marketing

Find an implementation approach that works for everyone
Perhaps the best place to start this journey is with the teams and individuals who will be responsible for the design, implementation, use, and support of the new data and AI capabilities. The objective here is to bring the marketing, business, and IT teams together to align on a data and AI implementation that fits with the organization’s culture, values, and growth strategy.

Build a data cloud
Ultimately, organizations can work with a data cloud provider to help design and drive use case testing that can quickly prove value without needing a new, full-scale enterprise system implemented. From that point, organizations can help build an appropriate business case, assess the output, and evolve.

Download the full paper to read in detail about all the strategies for unifying your data to supercharge your marketing efforts.

Endnotes

¹ Deloitte. “Connecting with meaning: Hyper-personalizing the customer experience using data, analytics, and AI.”