What is AI Marketing: How Are Marketing Teams Using AI - Klaviyo SG
2026-03-10 21:41 Diff
https://www.klaviyo.com/sg/products/ai/what-is-ai-in-marketing

Artificial intelligence (AI) in marketing uses AI-based technologies to analyse data, predict customer behaviour, automate tasks, and personalise brand experiences at scale. And given that marketing and customer service are deeply intertwined, AI can also help you serve customers better and more quickly with deeper customer data analysis and content creation.

AI is how B2C brands can keep up with consumer demand to personalise thousands or even millions of brand interactions. Working with AI is a novel way to accelerate this process, from ideation to execution to optimisation.

What are the benefits of using AI in marketing?

  • AI extracts strategic insights from large datasets. AI excels at analysing customer data to uncover patterns and trends that would be difficult to identify manually. AI tools can sift through millions of data points, predict future customer behaviours, and identify new growth opportunities—all insights that can drive revenue for your business.
  • AI delivers personalisation at scale. According to Klaviyo’s future of consumer marketing report, 74% of consumers expect more personalised experiences from B2C brands. But it’s almost impossible to manually create individualised content for thousands of customers. With AI, you can easily (and quickly) crunch data and tailor your product recommendations, content, and offers to the behaviours and preferences of every customer.
  • AI reaches new customers faster. AI tools can help your brand identify high-value audiences who resemble your best current customers. As a result, you can launch more targeted acquisition efforts. AI can also optimise ad targeting and bidding strategies to reach potential customers with higher conversion potential.
  • AI increases ROI by optimising performance. AI makes it easy to run continuous A/B tests so you’re always optimising your marketing initiatives and increasing the likelihood that every dollar spent results in profitable returns. Whether you want to determine the best time to send emails or automatically select winning campaign versions for each subscriber, you can do all of it with AI.

Marketing teams are using AI to create content, analyse data, and run A/B tests at a scale that was previously impossible. Here are a few specific ways you can make the most of AI to increase revenue with fewer resources:

1. Write emails and SMS messages more quickly

With AI, you can create on-brand content for multiple campaigns in minutes, whether that’s drafting email body copy, subject lines, or SMS messages. When sports apparel brand Proozy, for example, started using Klaviyo’s AI-powered subject line generator and SMS assistant to craft multiple copy options for their messages, they saved 45 minutes per day.

2. Personalise multi-channel campaigns

AI makes it easy to surface more granular customer segments with natural language prompts, so you can improve your targeting efforts. For example, with Klaviyo’s Segments AI, you can describe the groups you want to target and the AI will create them.

From there, you can also use AI to generate multiple message variations for every campaign. This process leads to deeper personalisation based on more specific customer behaviours and preferences.

3. Determine the best send times based on historical data

Oftentimes, email and SMS engagement is a matter of timing, recency, and relevance. AI-powered tools like Smart Send Time optimisation can analyse each subscriber’s engagement patterns and send your messages based on when people are most likely to interact with them.

4. A/B test at scale to find winning combinations

With AI-powered A/B testing, you can run a lot more tests without needing to manually push out the winning variation. AI is better equipped to deal with the volume of tests required to optimise your campaigns, and it’s better at personalising winning results based on customer data.

5. Respond to customer reviews faster

With AI, you can generate brand-appropriate and personalised review responses without templates or manual work. This is critical when you consider that, according to Klaviyo’s future of consumer marketing report, customer reviews and feedback are the most influential factor when shoppers are deciding whether to make a first purchase with a brand.

6. Use predictive analytics to make better decisions

Rather than manually cataloging customer order dates in a spreadsheet and trying to guess the next one, use AI to predict a customer’s next order date. Every Man Jack, a men’s personal care company, uses Klaviyo’s predictive analytics to generate predictions about every subscriber. As a result, the brand is able to set their reorder flow to send around each customer’s unique predicted next order date.

How to track the effectiveness of your AI marketing efforts

Implementing AI is one thing, but measuring its impact is how you prove its value. To truly understand if your AI investments are paying off:

  • Before you start using AI, set benchmarks for key performance indicators (KPIs) such as conversion rates, revenue per recipient, etc. Consider this your pre-AI snapshot of your marketing efforts.
  • Consider using advanced and flexible attribution models to understand how each touchpoint influences customer decisions across channels. This will give you a nuanced, channel-specific snapshot of how AI is working for you.
  • 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 understand 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 systems are only as good as the data they’re trained on. According to Klaviyo’s 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 fragmented customer data spread across multiple platforms. When systems are integrated or, better yet, under one roof, it’s easier for the AI to analyse your data effectively and accurately.
  • Ethical data usage and privacy concerns: AI amplifies data privacy concerns. Even before AI, marketers needed to be compliant with the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), but now they also need to address specific AI risks. Prioritise AI solutions that guarantee data isolation, ensuring your customer data is used solely for your business’s benefit and not to inadvertently train broader models that could inform competitor strategies. Transparency about data use, robust security, and the mitigation of inherent biases in AI outputs are essential for building and maintaining customer trust.
  • Tool integration and implementation: Many smaller B2C marketing teams lack the technical expertise to properly implement and optimise AI tools. Choose a tool built specifically for marketers that integrates with your existing tech stack to ensure adoption.
  • Data retention timespan limitations: Several marketing platforms retain customer data for only 30 days to 18 months. With this limitation, you won’t be able to understand how customer preferences change over time. Consider choosing platforms like Klaviyo that offer unlimited data retention without additional costs.
  • Change management: New AI tools means new processes, which can take time to implement and perfect. Invest in training your team and give them enough time to get used to it, so that AI is enhancing their human roles.

How to get started with AI as a marketer

The right data and marketing automation platform can help you overcome some of the challenges of AI while generating revenue with it a lot more quickly. Klaviyo, the B2C CRM, brings together your marketing, service, and analytics into a single platform, so you can start personalising brand experience at scale.

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