Podcast Summary: The Agile Brand with Greg Kihlström® - Episode #696: The Network Effect on CX of AI Plus Employees with Jay Pattisall, Forrester

Introduction

In Episode #696 of The Agile Brand with Greg Kihlström®, host Greg Kihlström engages with Jay Pattisall, Vice President and Principal Analyst at Forrester, to delve into the transformative impact of artificial intelligence (AI) on customer experience (CX) and employee productivity. Recorded at the Forrester CX Summit in Nashville, Tennessee, this episode explores the concept of the network effect of AI and its implications for modern businesses striving to enhance customer lifetime value and foster long-term growth.

Guest Introduction: Jay Pattisall’s Role at Forrester

Jay Pattisall opens the discussion by outlining his role at Forrester, emphasizing his focus on marketing services coverage. He explains:

“I sit on a team that serves the B2C marketing executive and my responsibility is to cover marketing services and help brands make the right selection and considerations to take into the right consideration for their partnerships with agencies or systems integration companies or consultancies.”
(03:10)

Jay's extensive background in both agency strategy and planning equips him with a comprehensive understanding of the Martech ecosystem, enabling him to guide both marketers and technology providers effectively.

Insights from the Forrester CX Summit

Greg and Jay exchange appreciations for the ongoing discussions at the summit. Jay highlights key takeaways from his colleagues, emphasizing a customer-centric approach:

“It's not about the actual journey map, it's about the understanding of the customer and being able to serve their needs.”
(04:25)

He further elaborates on the importance of focusing on actionable strategies rather than just theoretical constructs:

“The goal is not about customer obsession but rather the actions that you take to serve your customers needs.”
(05:00)

These insights set the stage for a deeper exploration of how AI can be effectively leveraged to enhance both customer and employee experiences.

The Network Effect of AI in CX and Employee Productivity

Jay introduces the central theme of the episode—the network effect of AI—and its potential to exponentially amplify employee capabilities and enrich customer experiences.

Shift from Cost Efficiency to Productivity and Performance

Jay discusses the prevalent mindset in many organizations that view AI primarily as a tool for cost-cutting and efficiency gains. He challenges this perspective by advocating for a broader view that includes enhancing productivity and improving performance:

“Efficiency is a tremendous focus, but there are other things that can also be delivered in addition to just overall efficiency or cost efficiency or cost reduction.”
(06:02)

He outlines a triad of value that AI can deliver:

1. Efficiency: Automating repetitive tasks to save time and reduce costs.
2. Productivity: Utilizing the time saved to accelerate market time, produce more content, and explore new channels.
3. Performance: Creating more relevant and personalized content that enhances customer engagement and satisfaction.

“We used to look at cheaper, faster, better as pick two because you can't do all three. We're starting to see the opportunity to, with time and with the right maturity, to be able to achieve all three.”
(09:27)

The Triad of Value: Cheaper, Faster, Better

Jay emphasizes that AI enables organizations to transcend the traditional constraint of choosing only two out of cheaper, faster, or better by leveraging the network effect. This allows businesses to achieve comprehensive value by enhancing efficiency, boosting productivity, and improving performance simultaneously.

Case for Executives: Achieving All Three via AI's Network Effect

Addressing the skepticism among executives who are accustomed to traditional paradigms focused on cost-cutting, Jay provides a compelling argument for embracing the network effect of AI:

“It's made through improving and transforming your workflows internally so that your talent and your employees can deliver the value and the brand promise... to scale the brand.”
(10:21)

He explains how AI can facilitate better collaboration and scalability, ultimately leading to increased customer satisfaction and business growth. By tying the return from AI-driven efficiencies back to employee workflow improvements, Jay illustrates a sustainable model for growth:

“Employees create value, value creates happy customers, and more customers.”
(11:00)

Organizational Impacts: Breaking Down Silos and Enhancing Collaboration

Jay explores the organizational changes necessary to fully harness AI's potential. He underscores the importance of dismantling silos that hinder cross-functional collaboration:

“Removing some of the silos... helps improve the overall experience.”
(13:46)

AI acts as a catalyst for connecting disparate teams, fostering a diversity of ideas, and accessing expertise across the organization. This interconnectedness enhances the ability to create more cohesive and innovative customer experiences.

AI Maturity Curve: Efficiency → Productivity → Performance

Jay introduces a maturity curve to help organizations assess their current AI utilization and plan for advancement:

1. Efficiency: Implementing basic AI use cases to automate tasks and reduce costs.
2. Productivity: Leveraging AI to assist in creative processes, such as content creation and competitive analysis, thereby speeding up workflows.
3. Performance: Utilizing AI for personalized marketing and in-depth data analysis to refine strategies and enhance customer engagement.

“If leaders look at the use cases and the value that they're extracting, they'll get a very good sense of where they are in the maturity curve.”
(16:45)

This framework serves as a guide for organizations to transition from mere efficiency gains to achieving significant performance improvements.

Measuring AI’s Impact: Traditional KPIs vs. New Metrics

As AI reshapes customer interactions, traditional performance metrics may no longer suffice. Jay discusses the need for evolving KPIs to better capture the value generated by AI-driven initiatives:

“As the consumer experience changes as a result of AI, then I think the metrics are going to have to start to change.”
(20:14)

He provides examples of emerging metrics, such as shifting from traffic-based metrics in SEO to attention-based metrics, which better reflect the quality of customer engagement in an AI-enhanced landscape.

“We need to shift metrics from the amount of traffic to the amount of attention.”
(21:26)

This shift underscores the necessity for organizations to adapt their measurement strategies in tandem with technological advancements and evolving consumer behaviors.

Future of Marketing Metrics in AI-Driven CX

Jay anticipates that as AI continues to integrate into consumer experiences, new types of interactions—such as conversational agents and personalized shopping assistants—will emerge. This evolution will further necessitate the development of innovative metrics to accurately assess performance and customer satisfaction.

“There could be things that we haven't even thought of yet, but it's contingent upon the advancement of the technology and the change in consumer behavior.”
(21:25)

Staying Agile: Strategies from Jay

In the closing segments, Jay shares personal strategies for maintaining agility in his role:

“I stay busy and I probably take on more work than I should, but I like the constant stimulation and it keeps me on my toes.”
(23:18)

He emphasizes the value of multitasking and cross-project learning as mechanisms to remain adaptable and responsive in a rapidly changing technological landscape.

Conclusion

The episode concludes with Greg thanking Jay Pattisall for his insightful contributions. Listeners are encouraged to follow up through provided links to learn more about Jay and Forrester.

Key Takeaways

1. AI as a Multifaceted Tool: Beyond cost efficiency, AI can significantly enhance productivity and performance, enabling organizations to achieve a triad of value—cheaper, faster, better.
2. Network Effect: AI facilitates a network effect by breaking down organizational silos, fostering collaboration, and connecting diverse teams, which in turn enriches customer experiences.
3. Maturity Assessment: Organizations should evaluate their AI use cases against a maturity curve (efficiency, productivity, performance) to strategically advance their AI capabilities.
4. Evolving Metrics: Traditional KPIs may need to be reevaluated in favor of new metrics that better capture the qualitative aspects of AI-driven customer engagement.
5. Agility in Practice: Maintaining agility requires continuous learning, multitasking, and adaptability to harness the full potential of AI in evolving business environments.

Notable Quotes

• Jay Pattisall on Customer Focus:
  “It's not about the actual journey map, it's about the understanding of the customer and being able to serve their needs.”
  (04:25)

• Jay Pattisall on Triad of Value:
  “We used to look at cheaper, faster, better as pick two because you can't do all three. We're starting to see the opportunity to, with time and with the right maturity, to be able to achieve all three.”
  (09:27)

• Jay Pattisall on Shifting Metrics:
  “We need to shift metrics from the amount of traffic to the amount of attention.”
  (21:26)

This episode serves as a crucial resource for marketing leaders and organizations aiming to leverage AI not just for operational efficiencies but as a strategic asset to drive comprehensive business growth and enhance customer experiences.