6 ways entrepreneurs can use AI in marketing automation to grow faster

As an entrepreneur or small team, you’re trying to connect with your audience, keep up with emerging trends, and drive results—all while managing dozens of channels and feeling the pressure to grow faster without spending more.

Every dollar you spend to acquire a new customer seems to buy less than it did last year. Both ad costs and customer acquisition costs (CACs) keep rising, according to Meta and Klaviyo’s 2025 state of B2C marketing report, respectively.

In this environment, marketers need to start working smarter to hit their goals. And many are already on top of it: our state of B2C marketing report found that AI and machine learning tools are the No. 1 technology investment B2C companies are prioritizing in 2025.

AI in marketing automation takes on the repetitive tasks that can eat up all the time in your day, like campaign creation, audience targeting, and optimization. This gives entrepreneurs and lean teams time back to focus on building their brand and connecting with their customers.

Let’s explore how business owners and marketers are using AI in marketing automation to grow faster and work smarter, not harder.

1. Find and engage highly targeted audiences

In the past, building segments and analyzing audiences to find the best groups for your messaging could take days or even weeks, depending on your tech stack and how much you relied on developers.

Using AI, you can build segments using plain language prompts. Rather than clicking through lots of dropdowns and filters, you can describe the audience you want to reach, and AI creates the segment for you.

Hypothetical AI in marketing automation example: A marketer for a small food and beverage business creates a segment of “holiday entertainers” with the prompt, “Build a segment of past customers who spend a lot during November–December, use gift messages with their purchases, and order in bulk during the holiday season.” Then, the marketer can send this group targeted content and product recommendations, like exclusive pre-holiday deals and bundles.

Real-world AI in marketing automation example: Saranoni, a luxury blanket brand, uses AI to generate zip code-based segments for location-specific messaging. They save 10–30 minutes per segment compared to manually entering parameters.

2. Launch across channels faster with AI-generated content and flows

A blank page can be an entrepreneur or lean team’s worst enemy. You know you need to send that flash sale text, abandoned cart follow-up, or seasonal campaign. But actually finding the time to put it together ends up last on your to-do list.

This is where AI is making a big difference for marketers. According to Klaviyo’s 2024 AI trends report, about a third of marketers say the top benefits of AI are easier idea gathering, better decision-making and planning, increased productivity, and scalability. And 98% report that AI has increased both their performance and productivity at work.

When using AI in marketing automation, you can:

• Get up and running, fast. Use an AI marketing agent to automatically generate on-brand campaigns, key flows, and sign-up forms that are ready to go live.
• Nurture your audiences with ongoing content. An AI marketing agent can also give you weekly inspirational campaign ideas that help you keep up with customers across channels, automatically pulling in the latest industry, competitive, and holiday trends.
• Generate content assets. Use generative AI to create on-brand email subject lines and body content, text messages, and review responses.
• Build automated flows. Use plain language prompts to describe what you want to create and which channels you want to reach your customers on, and watch the flow come together.
• Edit product photography. Use an AI photo editor to repurpose content for different channels, campaigns, audiences, seasons, or styles.

Hypothetical AI in marketing automation example: A skincare brand inputs their website URL into an AI marketing agent, which analyzes product descriptions, founder story, and customer testimonials. In minutes, they’ve got a welcome series educating customers about clean beauty, a newsletter campaign discussing common skin concerns and recommended products to address them, and a sign-up form offering a discount to first-time customers.

Real-world AI in marketing automation example: With one simple sentence, water filter brand Lifestraw created a Recharge subscription confirmation flow. Using AI to build the flow saved the team at least 40 minutes compared to their previous process.

3. Convert more customers with 1:1 personalization at scale

Personalization is now a non-negotiable in marketing. 74% of consumers expect more personalized experiences from brands this year, according to Klaviyo’s future of consumer marketing report.

But personalizing every message manually would be impossible. As your business grows and customer behaviors and preferences change, you need a smart way to keep up.

Our AI trends report found that one-third of marketers consider increased personalization to be one of the key benefits of using AI.

AI in marketing automation helps you personalize at scale by:

• Personalizing product feeds: AI can help you make sure every customer sees products tailored to their interests and purchase history, whether that’s in an email campaign or flow, a product carousel on WhatsApp, their self-serve customer hub, or a conversation with a human or AI customer agent.
• Reaching your customers when they want to hear from you: Use AI to find the best send time for different types of marketing messages so you can get more engagement.
• Automatically sending messages on customers’ preferred channels: Some people love email, while others prefer text messaging or mobile push. AI figures out which channel each customer engages with most, then prioritizes it in sequence.
• Determining the best campaign version for each subscriber: After you create an email or text message campaign, you can run a smart A/B test where AI chooses the variation that’s most likely to resonate with each customer based on initial results, then sends it to them automatically.

Hypothetical AI in marketing automation example: Based on data from a customer’s purchase history, support conversations, and other sources, a pet care brand identifies that a customer has a small senior dog and sends out tailored recommendations for joint supplements and specialized treats.

Real-world AI in marketing automation example: Thirdlove uses AI-powered channel affinity to make sure multi-channel subscribers get abandoned cart messages where they’re most likely to engage. It’s just one way the women’s intimates brand drove substantial growth in revenue from flows.

4. Retain more customers by predicting their next move

According to Chargebee’s 2024 State of Subscriptions and Revenue Growth Report, 86% of marketing leaders agree that customer retention is equally as important as (or even more important than) new customer acquisition.

Rising CACs are forcing brands to rethink their entire marketing strategy. When it costs more to obtain a new customer, the ones you already have become even more valuable.

With predictive analytics, you not only anticipate your customers’ next moves, but also get ahead of their needs. That helps you be more strategic about where you invest your marketing efforts.

Predictive analytics AI in marketing automation can help you focus your efforts and get more bang for your buck by:

• Identifying customers likely to churn: AI helps you see the warning signs before someone leaves, like a lower number of recent orders. This empowers you to be proactive instead of reactive, like sending win-back flows or curated offers to at-risk customers based on past purchasing activity.
• Rewarding customers based on predicted customer lifetime value (LTV): Send customers with high LTV review requests, referral requests, or targeted invitations to join rewards programs based on future spend. Similarly, offer free products, discounts, or lower-cost alternatives to those with low LTV.
• Forecasting how many orders a customer is likely to place: Offer customers predicted to buy two or more products the option to subscribe and save. Or, surprise customers expected to place one or more orders with flash sales, special discounts, or bundles.
• Anticipating when a customer will place their next order: Send a message ahead of each customer’s next predicted purchase date, and include a personalized product feed to help them find the perfect item.

Hypothetical AI in marketing automation example: AI-powered predictive analytics uses historical shopping patterns to identify which of a fashion brand’s customers are likely to churn within 30 days. For high-risk customers, the brand creates personalized styling emails with items similar to previous purchases, exclusive early access to sales in the customer’s preferred categories, or size consultations before they consider leaving.

Real-world AI in marketing automation example: Every Man Jack, a men’s personal care brand, uses predictive analytics to send reorder flows on or before each customer’s unique predicted next order date. They also send targeted campaigns to segments of subscribers with high predicted LTV. In 90 days, the brand generated over 12% of Klaviyo-attributed revenue with predictive analytics segments.

5. Identify areas to improve by benchmarking results against your peers

It’s important to know where you stand in your industry and at your growth stage. But manual benchmarking is time consuming and can be inaccurate.

AI-powered benchmarking compares your results against AI-driven peer groups by looking at businesses of similar size, scope, and market position. Then, you can see business and marketing benchmarks tailored to your industry that refresh monthly.

With AI-powered benchmarks, you can review your business performance and uncover marketing opportunities at a glance, using metrics like:

• Sales performance: Track metrics like average cart size, order count, repeat purchase rate, and order values, as well as the percent of orders returned.
• Email campaigns: Measureopen rates, click rates, placed order rates, bounce rates, spam occurrences, and unsubscribe rates.
• Text message campaigns: Track click rates, placed order rates, conversion rates, and unsubscribe rates.
• Flows: Measure initial engagement metrics (open and click rates), conversion metrics (such as conversion rates and revenue per recipient (RPR)), and health metrics (spam report rate, bounce rate, and unsubscribe rate).
• Sign-up forms: Track submission rates and compare them to industry standards.

Hypothetical AI in marketing automation example: A jewelry brand uses AI benchmarks to compare sign-up form conversion rates against similar-sized jewelry brands. When they find out their form is underperforming, they adjust their messaging, sign-up offer, timing, or placement, driving more new customers to subscribe for updates.

Real-world AI in marketing automation example: Clothing brandBrava Fabrics used AI-powered benchmarks to determine what areas of their email marketing performed well and what areas they could improve. Once they put their data into perspective against their peers, they discovered their lowest-performing metric was their unsubscribe rate. This encouraged them to plan to refine their email marketing strategy to improve ROI.

6. Protect your reputation and keep up with reviews

You work hard to improve your product, your customer service, and your brand. When one unhappy customer leaves a scathing review, suddenly it’s the first thing potential customers see. And you might not even see it until days later because you’re juggling a hundred other things.

The ripple effects of a negative experience go further than you might think. According to our future of consumer marketing report, when consumers have a single negative experience with a brand, most don’t just move on quietly. They contact customer service, leave public feedback, or stop purchasing from that brand altogether.

Each of these actions amplifies the damage. If you’re not on top of customer service and actively monitoring reviews, word of mouth can travel faster than you can say “damage control.”

The problem is, you can’t personally respond to every review within a minute. AI in marketing automation helps you stay on top of your reputation by:

• Auto-generating timely, personalized responses to customer reviews: Quickly respond to both positive and negative feedback on any channel with AI-generated responses that reflect your business’s voice and tone.
• Understanding review sentiment: Get automatic insights that flag changes in what people are saying from month to month, so you can spot and address trends before they become a problem.
• Following up with customers: Trigger cross-channel flows that send automatically when customers leave negative reviews (to make things right) or positive reviews (to thank them).
• Showing the best reviews for each subscriber: Automatically highlight the most relevant reviews in email and text message flows based on customer interests and purchase history.

Hypothetical AI in marketing automation example: A home goods brand uses AI to analyze review themes, identify product issues, and address those issues quickly. When multiple customers mention that the packaging for a specific product is damaged, the brand pauses advertising for that product and customer service performs 1:1 outreach with recent purchasers.

Real-world AI in marketing automation example: In their abandoned cart and win-back flows, natural fragrance brand Happy Wax is A/B testing dynamic review quote blocks, which use AI to select and highlight the review quote most relevant to each customer (for instance: a testimonial about the SKU they just abandoned). So far, both flow versions with review blocks are driving more clicks and revenue per recipient.

Save time and drive better results with K:AI in marketing automation

Whether you’re launching your first store or scaling your small business, AI in marketing automation frees up your time, improves your performance, and helps you grow without adding to the headcount.

The foundation for successful AI marketing is an all-in-one B2C CRM that brings together marketing, service, and analytics, powered by AI and a built-in CDP. With Klaviyo, you get an AI-first CRM that’s not only designed to make your life easier, but also gets smarter every day.

Klaviyo isn’t just another marketing platform with AI layered on top. It’s a full-stack marketing and service engine powered by one of the most robust data infrastructures in the industry.

Under the hood, Klaviyo AI (K:AI) powers built-in agents that use your real-time customer profile data to plan and launch marketing, personalize every send, and resolve customer requests—on one platform, with humans in the loop. Here’s how they work:

• K:AI Marketing Agent: internal-facing AI that helps your team start fast, optimize results, and grow revenue—without prompting and with full control
• K:AI Customer Agent: customer-facing AI that answers questions and completes support tasks in a way that feels human and on brand

Fully integrated with your marketing and service functions, K:AI moves fast with full customer context. Start from scratch, scale what works, and never miss another opportunity for revenue again with K:AI.

When AI handles the nitty-gritty work, you get to focus on the strategic, creative work that actually grows your business.