AI Agents Transform Marketing with Predictive Customer Analytics

A new report by Dogma Alares, in collaboration with NeoHub and Baysal Sezgin, highlights how AI agents (or 'agentic AI') are fundamentally changing the way organizations approach predictive customer analytics, challenging the traditional 'build versus buy' dilemma in the MarTech (marketing technology) sector.

The Shift in AI Adoption

Organizations have long faced a binary choice when adopting AI:

• Build custom predictive models in-house (requiring significant expertise and resources)
• Buy pre-built solutions from MarTech vendors (offering rapid deployment but limited customization).

However, the rapid pace of AI innovation is blurring this distinction. AI agents are now accelerating the creation of predictive models, making custom solutions more accessible and efficient.

The Power of AI Agents

Unlike traditional AI tools, AI agents are autonomous systems capable of executing complex workflows with minimal human intervention. They combine:

• Language interpretation
• Reasoning
• Decision-making

These agents can autonomously collect and preprocess customer data, identify churn patterns, design retention models, and even execute retention campaigns. Gartner predicts that by 2028, 33% of enterprise software will include agentic AI capabilities, with 15% of routine decisions being made autonomously.

Predictive AI in Marketing

Predictive AI leverages advanced algorithms to anticipate trends and behaviors. Key applications in marketing include:

• Advanced customer segmentation
• Product recommendations
• Churn prediction (identifying at-risk customers to improve retention)

According to the report, 63% of marketing leaders are already investing in AI or plan to do so within the next two years.

Build vs. Buy Dilemma

AI agents are reshaping the build versus buy decision:

• Building custom models is now more feasible due to reduced expertise barriers.