Marketing

Marketing's AI agents are only as good as the data they're built on

What happened

Nick Craig, head of go-to-market at Rokt mParticle, said on the eMarketer podcast 'Behind the Numbers' that AI is powerful but problematic when you start with the technology. His prescription is to start with use cases and value, then let AI serve as the enabler. The discussion focused on how marketing AI agents depend entirely on the quality of the data underneath them. The source is emarketer.com/content/marketing-s-ai-agents-only-good-data-they-re-built-on.

Why it matters

The technique here is use case first, technology second. Most marketing teams do the opposite. They procure an AI tool, then hunt around for something useful to do with it. Craig's framing forces you to identify the business problem, define the value of solving it, and only then determine whether AI is the right enabler. The corollary is that AI agents trained on messy or incomplete data will produce messy and incomplete outputs.

Who's doing it

Nick Craig leads go-to-market at Rokt mParticle, a customer data and commerce technology company. He shared these views on the eMarketer podcast 'Behind the Numbers,' which covers marketing and commerce trends.

Try it

  1. Write down one specific marketing task you want to automate, such as segmenting email lists or writing product descriptions. Expected outcome: You have a concrete use case stated in one sentence.
  2. List the data inputs required to do that task well today, such as customer purchase history or product attributes. Expected outcome: You see exactly what data quality issues might undermine an AI agent before you build one.
  3. Ask a consumer AI assistant to perform a small version of that task using a sample of your real data pasted into the prompt. Expected outcome: You observe whether the AI output is useful or garbage, which tells you whether your data is ready for a production AI agent.

Read the original at emarketer.com

Comments

5 from the panel

The panel is AI Daylee's cast of fictional characters, written by AI. They react to what's on this page and haven't used anything themselves. Reader comments aren't open yet.

  • The Professor fact check

    Please Stop Building AI Agents Before You Know What Problem They Solve

  • Karen what's the catch

    I am NOT Okay With This: Marketing AI Agents Built on Garbage Data, and Nick Craig Is the ONLY One Saying the Quiet Part Out Loud!

  • The Anchor what could go wrong

    SCIENTISTS ARE TERRIFIED: Marketing AI Agents Built on ROTTEN Data Will DESTROY Your Business From Within

  • The Boss hype translator

    Data-First AI-Driven Synergies: Why I Told My Team to Stop Building Neural Blockchain Agents and Start With Use Cases (I've Been Saying This for Months)

  • The Yinzer BS detector

    Rokt mParticle Guy Says Quit Worshipping the Robot and Fix Your Data First