1. Conversational AI across shopping and support
Shopping used to be linear: research a product, browse a catalogue, compare prices, make a purchase. Now, it’s a dynamic conversation between consumers and brands—one that extends across the entire journey, from discovery to post-purchase support.
AI agents can help shoppers get fast, accurate, and personalised answers that lead to better decisions. Notably, PwC found that 54% of companies using AI agents have improved the customer experience.
With AI agents for both shopping assistance and customer support, brands use context to transform moments of friction into moments of loyalty.
AI-powered shopping: the new digital sales associate
Conversational commerce is the latest consumer expectation. People are turning to AI like ChatGPT and Perplexity for product recommendations. Meanwhile, retail giants are responding with their own AI shopping assistants. Amazon’s Rufus and Walmart’s Sparky are designed to guide, suggest, and eventually handle transactions directly.
According to Klaviyo’s AI shopping index, 81% of consumers have used AI tools to shop or research products in the last three months, and 75% of consumers have abandoned a purchase because they couldn’t get a quick enough answer.
This shift means brands need to rethink how they show up in the shopping journey. It’s not enough to publish a static product catalogue. FAQs, reviews, product details, and user-generated content all need to be structured for discoverability by AI agents and large language models (LLMs).
And the stakes are high: 65% of consumers in the survey research behind Klaviyo’s AI shopping index expect AI shopping assistants to be a normal part of their brand experience by 2026. 60% of those who’ve already used one in the past 6 months have even switched retailers because another site offered an AI-powered assistant.
In other words, if your brand isn’t “AI-ready”, you risk being invisible where consumers are increasingly making decisions. To keep customers loyal, keep your product catalogue up to date and provide an AI shopping assistant.
Trained on your brand’s own data, an AI shopping assistant can:
- Surface relevant products based on someone’s browsing or purchase history.
- Explain features and sizing.
- Check stock and delivery details.
- Recover abandoned baskets.
- Guide customers through checkout.
Because it’s trained on your catalogue, content, and customer data, an AI shopping assistant delivers fast, accurate, and on-brand responses that help shoppers find what they need.
The rise of contextual, AI-powered customer support
AI isn’t only transforming shopping. It’s also changing how customers get help after their purchase.
Microsoft research found that 90% of consumers expect self-service options as a standard part of support. And nearly 4 in 10 consumers surveyed expect a response within 4 hours after reaching out to a brand about a negative experience, according to Klaviyo’s 2025 future of consumer marketing report.
AI customer agents are helping to meet those expectations by providing faster resolutions with instant answers, day or night. According to IBM research, AI can resolve 80% of routine customer queries, freeing human teams to focus on complex, high-value interactions.
With AI-powered customer service, you can automate helping customers with common issues such as:
- Checking order status
- Processing returns
- Updating subscriptions
When the AI is trained on your storefront and customer database, it not only makes these kinds of routine customer interactions feel more personal, it also feeds information back into customer profiles and preserves full context in case a human agent needs to get involved with a problem.
When home fragrance brand Happy Wax implemented an AI customer agent, they saw a dramatic reduction in support tickets. And over 90 days, 50% of the conversations handled by the AI agent were fully resolved without human involvement.
AI for CX tip: Look for an AI agent that acts as both a shopping assistant and a customer service agent in one.
2. AI-powered personalisation and product recommendations
Consumers don’t just want to understand your products. They want to understand how your products work for them.
In Klaviyo’s 2025 BFCM forecast, personalised recommendations and gift suggestions ranked among the top five factors that make someone likely to purchase. Personalisation isn’t just a “nice to have” — it’s a key differentiator in winning first purchases and repeat loyalty.
Yet many brands still struggle to personalise beyond the basics. AI helps close that gap, turning data into dynamic experiences that evolve with every interaction.
Our BFCM forecast also found that more than half of consumers plan to use AI for holiday shopping, primarily to discover products, find gift ideas, and get fit/sizing recommendations. And 38% said they’d rather have an AI remember their past preferences than explain them to a sales assistant.
With an AI-first CRM that enables personalisation at scale, you can:
- Enrich customer profiles by pulling details from support conversations and browsing behaviour, then using that data to trigger personalised text message and email flows.
- Describe an audience group, using any piece of data from any source, and let AI create dynamic segments that adapt automatically as customer behaviour changes.
- Power product discovery with AI-driven product recommendations embedded in AI shopping assistants, flows, or personalised “For You” pages in self-serve customer hubs.
Consider intimate apparel brand Thirdlove. They’ve built individualised “For You” pages in their self-service customer hub that highlight personalised product recommendations, display purchase history, and allow customers to save favourites. Experiences like these keep customers engaged—and keep them coming back.
3. Predictive analytics for proactive engagement
According to Chargebee’s State of Subscriptions and Revenue Growth, 86% of marketing leaders believe that customer retention is just as important as, or more important than, acquisition. That means efforts to keep current customers happy go a long way towards increasing revenue.
Traditional customer experience strategies are reactive: brands wait for customers to act, then respond. AI flips that script by predicting what customers will do next, so you can engage them before they ever reach out. It moves you from reacting to anticipating, predicting customer needs with rich context that drives efficiency and creates exceptional customer satisfaction.
In particular, AI-powered predictive analytics empowers brands to:
- Forecast the time between orders so customers receive perfectly timed replenishment reminders.
- Calculate lifetime value and average order value so you can focus resources where they matter most.
- Identify at-risk customers so you can deliver tailored retention offers.
- Create segments based on predicted behaviour, such as high spenders, gift buyers, or seasonal shoppers.
Willow Tree Boutique, for example, uses predictive analytics to target big spenders with luxury items. Similarly, oral care brand Smile Brilliant uses predictive analytics to send automated reorder reminders when someone is likely to run out of a product.
4. AI for cross-channel support experiences
Today’s shoppers don’t think in terms of “channels”. They move fluidly. They’re discovering a product on Instagram, checking reviews on a desktop, completing a purchase on mobile, and reaching out for support via WhatsApp.
Klaviyo’s 2025 BFCM forecast revealed that 77% of omnichannel shoppers use three to four channels when they shop, and more than one in five use five or more.
Meanwhile, Gartner found that 88% of service journeys start with self-service, but end up spanning multiple channels. The key to satisfaction: 93% of consumers report higher CSAT scores when those transitions are seamless.
Meanwhile, the line between marketing and customer service is fading. In Klaviyo’s 2025 State of B2C Marketing report, 75% of marketers said customer service now takes up at least 10% of their job. Teams need shared data and context to deliver consistently excellent experiences across every touchpoint.
Enter: the AI-powered helpdesk.
An AI-powered helpdesk acts as your central nervous system for customer interactions, breaking down the silos that traditionally separate email, text messaging, chat, and social DMs. Instead of fragmenting each touchpoint into a different system, a modern helpdesk consolidates them into a single, real-time customer profile.
That continuity is key: when a shopper starts a chat about sizing, follows up with an email about shipping, and later reaches out via Instagram, the system recognises it’s the same person and keeps track of all the conversation threads in a single view.
But consolidation is only the foundation. A truly AI-powered helpdesk layers intelligence on top of that centralisation, helping service teams make sure every touchpoint feels consistent, personalised, and efficient with:
Real-time context
An AI helpdesk enriches every interaction with real-time context from past orders, browsing behaviour, loyalty programme status, and marketing activity. That way, neither your AI agents nor your human agents are ever starting from scratch. Instead, they have a complete snapshot of the customer’s history at their fingertips, ready to personalise the interaction.
Smart ticket prioritisation
In an AI helpdesk, intelligence extends to triage and resolution. AI can detect the intent and urgency behind a customer’s message, automatically resolve routine issues such as order tracking or subscription updates, and route more complex or high-value cases to the right human agent.
For service teams, that means spending less time on repetitive tickets, and more time on interactions that require empathy and creativity. For customers, it means faster answers and less frustration.
Smooth handovers
When humans need to step in, the handover should feel effortless. An AI helpdesk can escalate with the full context intact, so customers never have to repeat themselves. It can also suggest the next best response or pre-drafted replies that agents can send or adapt on the spot.
Over time, the AI learns from these interactions, improving its accuracy and aligning more closely with your brand’s voice.
Create better customer experiences with Klaviyo
The common thread running through all these shifts is clear: customers expect every interaction to be easier, faster, and more personal, without compromising trust. Meeting that expectation can be the difference between customers who remain loyal and those who move on to competitors.
The good news is that delivering seamless, AI-powered customer experiences doesn’t require stitching together an endless stack of disconnected tools. With Klaviyo, the B2C CRM, you can:
- Centralise customer data into unified profiles that reflect every interaction, from browsing behaviour to purchase history.
- Use K:AI Customer Agent to resolve customer questions instantly, reduce friction, and keep shoppers engaged.
- Rely on Klaviyo Helpdesk for complete cross-channel customer context, driving growth through intelligent sales opportunities.
- Personalise engagement across channels—email, text message, web chat, WhatsApp, and social—so customers feel seen and important, wherever they are.
- Scale predictive analytics and proactive support to anticipate needs, prevent churn, and strengthen long-term loyalty.
The future of customer loyalty will belong to brands that strike the right balance between using data-driven intelligence to deliver speed and precision, and maintaining the human authenticity that builds trust. AI isn’t replacing human connection; it’s enabling it at scale.
Now is the moment to embrace that shift. With Klaviyo, you can transform every stage of the customer journey into a seamless, personalised experience that fuels efficiency, deepens relationships, and drives growth.
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