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What is AI in marketing?

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What is AI in marketing?

Artificial intelligence (AI) in marketing means using AI to plan, create, and improve your marketing. Because marketing and customer service are closely connected, it also means AI that answers questions and completes support tasks for your customers.

B2C brands use AI to keep up with demand to personalize thousands or even millions of interactions with customers. Most teams still use AI one task at a time, like a subject line here and a product description there. A marketing agent takes on whole jobs, like building an audience and drafting a campaign, and brings the work to you for approval.

What are the benefits of using AI in marketing?

  • AI finds patterns in large datasets. It analyzes customer data for trends that are hard to spot manually, predicts customer behavior, and recommends growth opportunities.
  • AI delivers personalization at scale. According to Klaviyo's future of consumer marketing report, 74% of consumers expect more personalized experiences from B2C brands. But creating individualized content for thousands of customers by hand isn't realistic. With AI, you can use customer data to tailor product recommendations, content, and offers to each customer's behavior and preferences.
  • AI takes on repeatable work. A marketing agent can build audiences, draft campaigns and flows, and run recurring reports from your brand and customer data, then bring the results to you for approval.
  • AI helps you find and keep customers. It can identify audiences who resemble your top customers and the existing customers most likely to buy again.
  • AI keeps performance under review. A marketing agent can review your campaigns and flows on a schedule and flag what needs attention, so you spend your time on decisions.

How are marketing teams using AI?

Marketing teams use AI across planning, messaging, and customer service. Common uses include:

  • Drafting a marketing plan. A marketing agent can build a plan from a goal plus your brand and customer data, then prepare the campaigns and flows for your review.
  • Drafting messaging across channels. A marketing agent can draft campaigns and flows across email, text, WhatsApp, and push, using your brand and business context, for you to review and approve.
  • Choosing the right channel. AI-powered channel affinity uses historical data to predict which channel each subscriber is most likely to engage on next.
  • Choosing send times. AI can analyze each subscriber's engagement patterns and send your messages when that person is most likely to interact.
  • Responding to reviews and customer questions. AI can draft review replies for you to approve, and a customer service agent can resolve common inquiries, like returns and product questions, and hand off to your team when a conversation needs a person.
  • Predicting customer behavior. Instead of tracking order dates and lifetime value in a spreadsheet, teams use AI to predict a customer's next order date, lifetime value, and churn risk, then send messages accordingly.

How to track the effectiveness of your AI marketing efforts

Measuring impact is how you prove AI's value. To see whether your AI investments are working:

  • Before you start using AI, set benchmarks for key performance indicators (KPIs), such as conversion rate and revenue per recipient. Treat this as your pre-AI snapshot of your marketing efforts.
  • Use advanced, flexible attribution models to see how each touchpoint influences customer decisions across channels. This shows how AI is working for you, channel by channel.
  • Identify which tasks you'll perform with AI, and track how long they take. Track those same tasks after you start using AI to measure your productivity gains.
  • If you're using predictive analytics, run A/B tests to see whether they lead to higher conversions. Use auto monitors to track important metrics and get alerts for dips in performance.

The challenges of using AI in marketing and how to solve them

  • Data quality and integration: AI is only as good as the data behind it. According to Klaviyo's recent AI trends report, 28% of ecommerce marketers are concerned about the trustworthiness of the data AI is based on. Many B2C brands, meanwhile, struggle with customer data fragmented across multiple tools. When that data lives in one place, it's easier for AI to analyze it accurately.
  • Ethical data usage and privacy concerns: AI amplifies data privacy concerns. Even before AI, marketers needed to comply with the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), and now they also need to address specific AI risks. Choose AI tools that keep your customer data isolated, so it's used only for your business and doesn't train broader models that could inform competitors' strategies. Be transparent about how you use data, protect it with strong security, and watch for bias in AI outputs to maintain customer trust.
  • Tool integration and implementation: Many smaller B2C marketing teams lack the technical expertise to implement and optimize AI tools. Choose a tool built for marketers that is easy to use and integrates with your existing tech stack.
  • Data retention: Some marketing platforms limit how long they keep customer data, which makes it hard to see how customer preferences change over time. Choose a platform that keeps your data long enough to track those changes.
  • Change management: New AI tools mean new processes, which take time to set up and refine. Invest in training your team and give them time to get used to the tools, so AI supports their roles.

How to get started with AI as a marketer

Start with one repeatable job, like building an audience or drafting a campaign. Set your benchmarks, let AI prepare the first draft, review it, and compare the result with your pre-AI snapshot. Then add the next job.

Get started with Klaviyo, the agent-first operating system for B2C, and let a marketing agent take on your first job.