Marigold AI: Building Relationships Powered by AI with a Human Touch, with Iain Short, CPO

Acting as a trusted advisor, Marigold AI enhances personalization at scale, providing actionable insights, predictive analytics, and assistance with workflows. With a focus on responsible AI application, Marigold AI helps brands build better, data-driven connections with their customers without compromising trust. Marigold AI features have long existed in several of our platforms, from content writing and assistance, to product and content recommendations, to machine learning predictions and audience discovery. Now Marigold is bringing the best AI capabilities to more of our platforms under one unified umbrella, Marigold AI, maximizing investment for faster innovation and value to customers, to scale. Moreover, we will continue to innovate on smart capabilities with a conscientious approach around data, compliance, consumer protections, and evolving preferences, continuing a legacy of relationship-centered AI innovation and development.

We interviewed Iain Short, Chief Product Officer of Enterprise here at Marigold, and asked him some questions to get more insight into this significant initiative for Marigold.

How Marigold AI differentiates itself from other AI technology;

Q: How does Marigold AI differentiate itself from other AI-powered marketing platforms, particularly in maintaining trust and brand integrity?

Iain: At Marigold, our platforms and AI-powered offerings are unique due to our intentional and strategic approach to integrating AI and relationship-centric marketing. We started by identifying marketers’ key challenges and assessing how Marigold AI could address these, all while maintaining trust and control. From there, we identified four fundamental ways in which Marigold AI can help marketers build more meaningful customer relationships: by utilizing Marigold AI as a strategic advisor; as a productivity amplifier; as an engagement accelerator; and as a brand advocate.

We also introduced core design and development principles which, at a high-level, drive teams to solve real-world customer use cases where there is a clear role for AI to play. This ensures marketers can maintain oversight and control on AI usage, and consider the impact of AI usage on consumers at every stage of the process.

This approach aligns with our commitment to relationship marketing, which emphasizes building trust and fostering genuine connections between brands and consumers. By thoughtfully controlling our use of AI technology, we aim to enhance rather than undermine these hard-won relationships. Ultimately, our differentiator lies in our ability to harness the power of AI while preserving the human touch that is essential to effective marketing.

Our Four Pillars: How Marigold AI meets marketing challenges;

Q: How do you see Marigold AI taking on the four pillars you mentioned?

Iain: The four pillars were derived from the research we conducted around the challenges marketers face in building relationships with consumers, both today and looking forward:

The Strategic Advisor pillar focuses on leveraging AI and machine learning (ML) to give marketers the insights they’d typically need a team of data analysts to uncover. We’re looking at ways to help marketers understand what’s working, what’s not, and what tactics they should apply to meet their objectives. As Marigold AI evolves, we want our functionality to help you do the heavy lifting, working in the background to surface insights and make helpful recommendations.

When it comes to the Productivity Amplifier pillar, we’re tapping into the power of Marigold AI to boost efficiency and streamline workflows. This goes beyond just helping with content creation and marketing copy – although that’s certainly part of it. We’re looking at ways Marigold AI can assume manual, repetitive tasks that eat up marketers’ time – like creating alternative versions for campaign testing. The goal of investment into productivity amplifier capabilities is to free up marketers to focus on what they do best: building relationships and applying their strategic insights. It’s about working smarter, not harder.

The Engagement Accelerator pillar addresses a critical challenge in today’s multi-channel world. Consumers expect brands to engage them with relevant and consistent experiences wherever they choose to interact, which is no small feat for marketers. We aim to help marketers improve their ability to personalize the customer experience, predicting needs and behavior and adapting content as it learns what works best for each consumer.

Finally, there’s the Brand Advocate pillar, which is really about ensuring that all this AI-powered activity aligns with your brand identity; think of it as a ‘brand guardian’ in your pocket. By training Marigold AI on your brand guidelines and great examples of your copy and messaging, we can generate content that’s on-brand. Furthermore, Marigold AI can help you automatically review existing content and flag anything that might not meet your brand standards. It’s a safeguard that allows you to consistently represent your brand and protect its integrity.

Marigold’s approach to AI policies and ethics:

Q: A study from the Marketing AI Institute found that only 36% of companies said they have an AI ethics policy or responsible AI principles in place.¹ Could you talk more about Marigold’s approach to using AI in marketing, particularly in terms of maintaining trust and ethical practices?

Iain: Our approach to AI in marketing is built on three key principles: being customer-driven, people-centered, and human-controlled. Let me break these down.

First, we’re customer-driven in our approach to Marigold AI. This means we’re being intentional about how we implement AI technologies. We start by looking at the types of problems or opportunities that marketers share. Then, we explore how Marigold AI can help address these challenges, working closely with our customers to understand how our solutions are helping them be successful, in a tangible and effective way. It’s not about applying AI functionality for its own sake, but about using it to solve real problems and creating meaningful opportunities for marketers.

Secondly, we’re committed to being people-centered, essentially constantly focusing on respectful use of AI. We believe that if we want to build better relationships between brands and consumers, we need to use Marigold AI in a way that helps nurture those connections, not manipulate them. Our goal is to maintain the highest trust in the brand-consumer relationship, working closely with early adopters to test solutions and seek feedback with real-world interactions and an ongoing focus on consumer trust.

Lastly, our approach is human-controlled. We ensure that marketers using our system have clear explanations of what we’re doing, what data we’re using, and how Marigold AI is being leveraged. This transparency allows marketers to make informed decisions about what capabilities they’re enabling or disabling. At its core, this principle is about empowering marketers to think about what’s right for their audience.

Marigold AI’s Human-centered approach for brands and consumers

Q: Can you elaborate on how Marigold AI focuses on human-centered connections is helping brands focus more on the consumer?

Iain: There are various ways Marigold AI is helping brands become more consumer-centric, and it’s exciting to see these applications in action. Let me give you some examples from across our product portfolio:

Personalized Recommendations: Getting the right recommendations in front of consumers is crucial. Whether it’s product suggestions, content suggestions, or the next best action or offer, Marigold AI helps marketers tailor these recommendations to individual preferences and behaviors.

Audience Targeting: We know not every message will resonate with an entire audience, so we use features like “smart audience” to help brands identify the right audience for specific messages or offerings. Marigold AI helps pinpoint which subset of your audience is most likely to be interested in a particular message, so that you can target a segment of that audience, rather than the whole audience.

Communication Timing & Cadence: Marigold AI assists in getting the timing and frequency of communications right while keeping personalized preferences top of mind. This is crucial for building better relationships with consumers. By analyzing engagement patterns, Marigold AI can help brands avoid over-communicating, message them when they are most likely to engage, and strike the right balance in their outreach.

Relationship Building:
The key here is that Marigold AI isn’t about blasting messages to your entire audience. Instead, it’s about precision – finding the right audience for each message, ensuring the content will resonate, and delivering it at the optimal time. This approach not only improves the effectiveness of marketing efforts but also enhances the consumer experience.

By leveraging Marigold AI in this way, brands can create more personalized, relevant interactions. This leads to stronger relationships with consumers, as they feel understood and valued rather than flooded with irrelevant content. It’s about using technology to be more human in our approach to marketing, not less.

1. Source: 2024 State of Marketing AI Report, Sponsored by Salesloft and Marketing AI Institute, © 2024 Marketing AI Institute, p 27.)