Artificial Intelligence is dominating conversations across the retail industry. Much of the focus has been on productivity, content generation and automation. While these are valuable applications, the biggest opportunity for retailers may lie elsewhere. AI is giving businesses the ability to better understand their customers, deliver more relevant experiences and increase Customer Lifetime Value without continually increasing marketing spend.
Introduction
There isn’t a retailer today who isn’t thinking about Artificial Intelligence. Every conference includes AI sessions. Every software platform is announcing new AI capabilities. Every week brings another headline predicting how AI will transform commerce.
With so much attention focused on the technology itself, it’s easy to lose sight of the real question: how does AI actually help retailers grow?
For many businesses, the first answer is productivity. AI can write marketing copy, generate product descriptions, summarise customer reviews, create advertising creative and support customer service teams. These capabilities are impressive, and they’re already saving businesses significant amounts of time. But they’re only scratching the surface.
The retailers creating the greatest competitive advantage from AI aren’t simply producing content faster. They’re building stronger customer relationships. Instead of asking AI to create more marketing, they’re asking AI to make their marketing more relevant.
That difference is significant. Because customers don’t necessarily want more communication. They want better communication.
The Next Generation of Retail Isn’t About More Marketing
For years, digital marketing has been driven by scale — more emails, more campaigns, more advertising, more traffic, more customers. The assumption was simple: if businesses communicated more often, they would generate more sales.
Today’s consumers have changed that equation.
The average customer receives hundreds of marketing messages every day. Email inboxes are crowded. Social feeds are saturated. Advertising is everywhere. The challenge facing retailers is no longer how to reach customers. It’s how to remain relevant once they’ve reached them.
This is where AI is beginning to change the conversation. Rather than helping businesses communicate more frequently, AI is helping businesses communicate more intelligently. The difference between those two approaches has a significant impact on customer experience.
Relevance Is Becoming Retail’s Biggest Competitive Advantage
Think about the last promotional email you ignored. It probably wasn’t because the design was poor or because the retailer had a bad product. It was more likely because the message simply wasn’t relevant — perhaps you’d already purchased the item, perhaps the offer didn’t match your interests, or perhaps it arrived at the wrong time.
Customers increasingly judge retailers by how well they understand them. That’s why relevance has become one of the most valuable outcomes AI can deliver.
Instead of broadcasting identical messages to every customer, retailers can increasingly personalise communication based on behaviour, intent and purchasing history. The result isn’t necessarily more marketing. It’s marketing that feels considerably more useful.
AI Learns What Customers Actually Do
Traditional marketing relies heavily on assumptions. Customers who bought Product A might also like Product B. Customers who purchased last Christmas might buy again this year. Customers aged between 30 and 45 may respond well to a particular promotion. Sometimes those assumptions are correct. Sometimes they aren’t.
Artificial Intelligence allows retailers to move beyond assumptions by identifying patterns across thousands or even millions of customer interactions. Rather than relying solely on predefined rules, AI continuously analyses behaviour and notices patterns that would be almost impossible to identify manually — which customers typically reorder after 60 days, which products are frequently purchased together, which customer segments respond best to SMS rather than email, which shoppers are becoming less engaged, and which customers are likely to become high-value purchasers over time.
These are the kinds of signals that customer engagement platforms like Klaviyo are built to capture and act on, connecting purchase history, browsing behaviour and engagement data to create a more complete picture of each customer. Instead of waiting for customers to disappear, businesses can engage them before that happens.
From Segments to Individuals
Most retailers already segment their customers — new customers, VIP customers, loyal customers, inactive customers. These are all valuable approaches. AI allows retailers to go much further.
Rather than assigning customers to broad segments, AI can evaluate each customer’s behaviour individually. Two customers may have purchased exactly the same product. One may be showing signs they’ll purchase again next week. The other may already be disengaging. Traditional segmentation treats them the same. AI recognises they’re completely different.
This creates opportunities for retailers to deliver far more relevant customer journeys. Instead of relying on fixed marketing calendars, communication becomes responsive to customer behaviour. The experience feels less like advertising. More like service.
Customer Engagement Is Becoming Predictive
One of AI’s most significant advantages is its ability to predict future behaviour. Retailers no longer need to wait until a customer has stopped engaging. AI can often identify early indicators — browsing frequency declining, email engagement reducing, purchase intervals increasing, search behaviour changing.
These subtle signals help retailers intervene before customers disappear completely.
Equally, AI can identify opportunities: customers likely to purchase complementary products, customers approaching replenishment timeframes, customers ready for loyalty rewards, customers showing unusually high engagement. Rather than sending generic campaigns to every customer, retailers can focus their attention where it’s likely to have the greatest impact. That’s better for customers and considerably more efficient for marketing teams.
AI Doesn’t Replace Marketers
One of the biggest misconceptions surrounding AI is that it replaces human decision-making. In reality, the most successful retailers are using AI differently. They aren’t replacing marketers. They’re giving marketers better information.
AI can recommend, predict, analyse and prioritise. But it still takes people to decide what experience customers should have, which brand voice is appropriate, when automation should stop and human interaction begin, and how customer relationships should evolve over time.
Technology supports those decisions. It doesn’t make them.
The retailers seeing the strongest results are combining AI with human creativity, customer empathy and strategic thinking. That’s where the real competitive advantage lies.
How Leading Retailers Are Using AI Today
Artificial Intelligence is no longer something retailers are experimenting with in isolated projects. It’s becoming embedded throughout the customer journey — and often, customers don’t even realise AI is involved. They simply experience a website that feels more relevant, an email that arrives at the right time, a product recommendation that genuinely interests them, a reminder just as they’re about to run out of something they’ve purchased before.
These experiences feel natural because they’re based on customer behaviour rather than assumptions. The technology fades into the background. The customer experience improves.
Here are some of the areas where we’re seeing AI create the greatest impact.
AI-Powered Product Recommendations
Product recommendations have existed for years. What has changed is how intelligent those recommendations have become.
Traditionally, retailers relied on fairly simple rules — customers who purchased Product A might also be shown Product B, or a merchandising team would manually decide which products should be promoted together. AI takes a far more sophisticated approach. Rather than relying on static rules, it continually learns from customer behaviour, considering previous purchases, browsing history, products viewed but not purchased, seasonal buying patterns, similar customer behaviour and price sensitivity.
The result is recommendations that evolve as customer behaviour changes. For retailers, this often means higher average order values and stronger repeat purchase rates. For customers, it simply feels like the retailer understands what they’re looking for.
Smarter Customer Journeys
Many retailers still communicate according to a marketing calendar — everyone receives the same campaign on Tuesday, everyone receives the same promotion on Friday. The problem is that customers don’t all follow the same journey. One customer may have made their first purchase yesterday. Another may have been buying from you for five years. Someone else may be browsing regularly without ever completing an order. These customers shouldn’t receive identical communications.
AI allows retailers to create customer journeys that respond to behaviour instead of dates. A customer abandons their cart — AI can determine whether they’re likely to return without intervention or whether a reminder would genuinely help. A customer purchases a skincare product — rather than immediately promoting unrelated products, AI may recommend complementary items or send replenishment reminders based on typical usage patterns. A loyal customer begins engaging less frequently — instead of waiting until they’ve disappeared completely, AI can trigger a re-engagement journey while there’s still an opportunity to rebuild the relationship.
These journeys feel considerably more personal because they’re driven by customer behaviour rather than marketing schedules.
Personalisation At Scale
One of the biggest challenges retailers face is scale. It’s relatively easy to provide a personalised experience for ten customers. It’s almost impossible to do manually for 100,000.
This is where AI changes what’s possible. Retailers can personalise product recommendations, email content, SMS messaging, homepage content, promotional offers, send times and communication frequency — all based on individual customer behaviour rather than broad assumptions.
Klaviyo is built specifically for this kind of scale, allowing retailers to personalise across email, SMS and onsite experiences based on live customer behaviour. Importantly, this isn’t about creating hundreds of different campaigns. It’s about allowing the experience to adapt automatically based on what each customer is doing, so customers receive more relevant communication while marketing teams spend less time manually creating segments.
Predicting Customer Behaviour
Perhaps the most exciting capability AI brings to retail is prediction. Instead of reporting on what has already happened, AI increasingly helps retailers understand what is likely to happen next — which customers are most likely to purchase again, which are becoming disengaged, which may be ready for a premium product, which are likely to respond to SMS rather than email, and which are approaching replenishment timeframes.
These insights allow retailers to become proactive. Rather than waiting for problems to emerge, businesses can act earlier.
That shift from reactive marketing to predictive marketing is one of AI’s greatest strengths. Klaviyo’s predictive analytics tools bring this capability directly into everyday marketing workflows, making it accessible to retailers who don’t have a dedicated data science team.
AI Needs Quality Data
AI is incredibly powerful, but it has one important limitation: it can only work with the information available to it. If customer data is fragmented, incomplete or inaccurate, AI recommendations become less effective.
That’s why leading retailers continue investing heavily in first-party data — purchase history, browsing behaviour, customer preferences, loyalty information, returns and customer service interactions. When this information is connected, AI gains a much richer understanding of every customer. Without quality data, even the most sophisticated AI tools struggle to deliver meaningful outcomes.
Good AI starts with good data. That’s why the most valuable role a platform like Klaviyo plays isn’t just sending communications — it’s unifying customer data from across your commerce stack so AI actually has something meaningful to work with.
Where Platforms Like Klaviyo Fit
As retailers become more focused on Customer Lifetime Value, customer engagement platforms are evolving rapidly. Rather than simply managing email campaigns, platforms such as Klaviyo are increasingly becoming customer intelligence platforms — combining first-party customer data, behavioural insights, automation and AI to help retailers deliver more relevant experiences throughout the customer lifecycle.
Retailers can use AI within Klaviyo to predict which customers are likely to purchase again, identify high-value customer segments, optimise send times, recommend products, trigger personalised customer journeys, improve segmentation and analyse campaign performance.
The objective isn’t simply to automate marketing. It’s to ensure customers receive communication that’s timely, relevant and genuinely useful. When AI, quality customer data and thoughtful customer journey design work together, retailers create experiences that feel less like marketing and more like personalised service.
Technology Is Becoming Easier. Strategy Is Becoming More Important.
One interesting shift we’ve noticed is that the technology itself is becoming increasingly accessible. Capabilities that once required enterprise budgets are now available to mid-market retailers. That’s fantastic news. But it also means technology alone is becoming less of a competitive advantage.
As AI becomes widely available, the businesses that stand out won’t simply be those using AI. They’ll be the retailers that know where to apply it — understanding the customer journey, knowing which moments matter most, and using AI to remove friction rather than create more noise.
That’s where the greatest opportunity lies.
Is Your Business Ready for AI?
The rapid pace of AI innovation has led many retailers to ask the wrong question. Instead of asking “Which AI tools should we implement?”, a better question is “Are we creating the right foundations for AI to deliver value?”
The retailers seeing the strongest results from AI didn’t begin by deploying dozens of AI features. They began by improving the quality of their customer data, simplifying their customer journeys and ensuring their technology platforms worked together. In many cases, AI was the final layer, not the first.
Before investing further in AI, it’s worth asking a few simple questions: Do we have a clear view of each customer across our systems? Is our customer data accurate and up to date? Are we measuring Customer Lifetime Value? Have we mapped our customer journey from first purchase through to repeat purchase? Are we using automation where it genuinely improves the customer experience? Are we collecting first-party customer data responsibly and effectively?
If the answer to several of these questions is “not yet”, that’s where the opportunity lies. AI performs best when it’s built on strong foundations.
The Biggest Opportunity Isn’t Automation
One of the most common misconceptions about AI is that it’s primarily about reducing headcount or replacing marketing teams. We don’t believe that’s where the greatest value lies.
The biggest opportunity is improving decision-making — helping retailers understand customers better, helping marketing teams prioritise the right opportunities, helping businesses communicate more effectively, helping customers find the right products faster, and helping service teams respond with greater context.
In other words, AI should make retail feel more human, not less.
Customers don’t remember whether an email was written by AI. They remember whether it was useful. They don’t remember whether a recommendation came from an algorithm. They remember whether it solved a problem. That’s the standard retailers should aim for.
Looking Ahead
Over the next few years, we expect AI to become embedded throughout almost every part of digital commerce — not as a standalone feature, but as a capability that quietly improves the customer experience.
We’ll see AI helping retailers predict demand more accurately, personalise product discovery, optimise pricing and promotions, improve customer support, reduce churn, increase customer loyalty and build stronger long-term customer relationships.
Eventually, AI will become so common that customers won’t notice it’s there. Just as they no longer think about the technology powering online payments or personalised search, they’ll simply expect retailers to understand them. At that point, AI won’t be a competitive advantage. It will be the standard.
The competitive advantage will belong to the retailers that have invested in the right customer strategy, data and technology to make the most of it.
OSE’s Perspective
At OSE, we’ve partnered with Klaviyo on this article because we see AI as an accelerator rather than a replacement — and Klaviyo is one of the clearest examples of AI being applied to a genuinely meaningful retail problem.
AI doesn’t replace good retail strategy. It amplifies it.
We’ve worked with retailers across Shopify, Adobe Commerce and complex integrated commerce environments, and one thing has become increasingly clear. Businesses that combine strong customer data with thoughtful customer journeys consistently outperform those relying on broad, one-size-fits-all marketing.
That’s why we’re excited about platforms such as Klaviyo. Not because they use AI. Because they combine AI with first-party customer data, automation and personalisation in ways that help retailers build stronger customer relationships.
The technology itself is only one part of the equation. The real value comes from understanding how to apply it to solve meaningful business problems. Whether that’s improving Customer Lifetime Value, increasing repeat purchase rates or creating more relevant customer experiences, successful AI projects always begin with clear commercial objectives.
Technology should support the strategy. Never replace it.
Summary
Retail has always been about relationships. The channels may have changed. The technology has certainly changed. Now AI is changing what’s possible.
But the businesses likely to succeed over the next decade won’t simply be those adopting AI the fastest. They’ll be the ones using it most thoughtfully — the retailers that understand their customers, use data responsibly, communicate with relevance, remove friction from the customer journey and create experiences that customers genuinely value.
Because AI doesn’t change the objective. It simply gives retailers a better way to achieve it.
Want to Know Where AI Can Actually Move the Needle in Your Business?
Most retailers experimenting with AI are starting with content generation and automation. Those have their place. But the bigger opportunity — using AI to predict customer behaviour, reduce churn and increase Customer Lifetime Value — requires something most businesses haven’t fully built yet: a clean, connected view of every customer.
At OSE, we help Australian retailers build the commerce foundations that make AI genuinely useful — connecting your eCommerce platform, ERP and customer engagement tools so platforms like Klaviyo can do what they’re actually capable of.
Whether you’re looking to implement Klaviyo, integrate your commerce stack, or simply understand where your current data gaps are costing you, we’d love to help.
Let’s start the conversation.
Frequently Asked Questions
Productivity applications — writing copy, generating product descriptions, summarising reviews — save time and reduce manual effort. They’re valuable, but they don’t necessarily improve the customer experience. Using AI for customer relationships means applying it to understand purchasing behaviour, predict when customers are likely to churn, personalise communication based on individual actions, and identify the moments where intervention will have the greatest impact. The first makes your team more efficient. The second makes your customers more likely to return.
Predictive marketing means using historical behaviour data to anticipate what a customer is likely to do next, rather than reacting after it happens. In practice, that might mean identifying a customer who is approaching a typical reorder window before they start searching for alternatives, recognising early signs of disengagement before a customer stops buying altogether, or surfacing a complementary product at the moment a customer is most likely to consider it. Klaviyo’s predictive analytics tools make these capabilities available within everyday marketing workflows, without requiring a dedicated data team.
Traditional product recommendations rely on static rules — customers who bought X are shown Y. AI continuously learns from actual behaviour across your entire customer base, factoring in browsing history, products viewed but not purchased, purchase timing, price sensitivity and patterns from customers with similar behaviour. The result is recommendations that evolve in real time rather than being set once and forgotten, and that feel genuinely relevant rather than algorithmic.
No. The retailers seeing the strongest results from AI are using it to give their marketing teams better information, not to replace them. AI can recommend, predict, analyse and prioritise. But decisions about brand voice, customer experience design, when automation should give way to human interaction, and how customer relationships should evolve — those still require people. The competitive advantage comes from combining AI capability with human creativity and strategic thinking, not from choosing one over the other.
Before AI can deliver meaningful value, retailers need a reasonably complete and connected view of each customer across their systems. That means purchase history, browsing behaviour, email and SMS engagement, loyalty activity and customer service interactions should ideally flow into a single profile rather than sitting in separate platforms. Fragmented or incomplete data produces unreliable AI outputs regardless of how sophisticated the tool. For most retailers, the work of connecting systems and cleaning data is the highest-value step they can take before adding AI capability on top.
Klaviyo applies AI across several areas within its platform — predicting which customers are likely to purchase again, identifying customers at risk of churning, optimising email and SMS send times, recommending products based on behavioural patterns, and improving customer segmentation. Crucially, it also acts as a data unification layer, pulling together behaviour, transaction history and engagement data from across a retailer’s commerce stack into a single customer profile. That connected data foundation is what allows the AI features to work effectively. For retailers integrating Klaviyo with an ERP or eCommerce platform, the picture becomes significantly richer.
