h1: The Rise of Generative AI: Revolutionizing Customer-Centricity in Sales and Marketing

h2: How the Generative AI Revolution Will Evolve Over Time

h3: Wave 1: Individual, Ad-Hoc Adoption
h3: Wave 2: Planned, Team-Based Adoption
h3: Wave 3: Transformational, Organization-Wide Adoption

h2: How Three Companies Leveraged AI to Become More Customer-Centric [And How You Can, Too]

h3: 1. Gaming Communities for an Agency
h3: 2. Black Holiday Traditions for Retailers
h3: 3. B2B Machine Learning in Agriculture Startup

h2: How AI Helps Your Team Become More Customer-Centric

h3: 1. AI enables you to become more agile.
h3: 2. AI helps you track changes over time.
h3: 3. AI enables you to adopt a holistic approach.
h3: 4. AI helps you become more future-oriented.

The dominant story of 2023 for salespeople, marketers, and content creators has been the rise of generative AI. ChatGPT, based on OpenAI’s Large Language Model, has quickly gained popularity, with 100 million daily active users within two months of its launch. Despite this, many sales reps, marketers, and businesses have yet to fully embrace generative AI and its potential for enhancing customer-centricity.

Generative AI has the power to level the playing field for businesses, enabling them to listen to their customers at scale, gain actionable insights, and drive growth and profitability. However, the adoption of generative AI needs to be approached strategically, considering people, processes, and organizational goals.

The future of generative AI within sales and marketing functions will evolve in waves. Wave 1 is characterized by individual, ad-hoc adoption focused on saving time. Wave 2 involves planned, team-based adoption aimed at adding value to processes. Wave 3, the transformational wave, requires organization-wide adoption and continuous learning to shape new capabilities and processes.

To demonstrate the power of generative AI in enhancing customer-centricity, three examples are discussed.

In the first case, an ad agency in the gaming industry used generative AI to listen to the experiences and concerns of diverse gaming communities. The insights gained from this study enabled the agency and its clients to understand toxic behavior, identify revenue opportunities, and develop strategies for building inclusive digital communities.

The second example is an agency that aimed to bring fresh insights about Black holiday traditions to retail clients. By using generative AI to analyze open-ended responses, the agency gained valuable insights into the diversity of Black identity and shopping habits. This information helped the retail clients tailor their campaigns and messaging to authentically connect with Black communities.

The third case involves a B2B machine learning startup working with a large tech company. Generative AI was used to understand buyer emotions, hopes, and anxieties about ML/AI-driven products. The startup used the insights gained to shape product design and development priorities, educate buyers, and craft brand awareness messaging targeted at specific industries and market segments.

Generative AI provides several benefits for teams looking