Smarter data management is the key to unlocking AI’s full value for brands. So writes Billy Loizou, APAC Area Vice President, Amperity.
For Australian brands, there’s intense pressure to keep pace with both local and international competition while meeting rising consumer expectations. Customers now expect personalised interactions, experiences and offers as standard.
Many brands are interested in AI and many are experimenting with it. However, most applications remain small-scale or experimental. Amperity research suggests that only 11 per cent of US retailers feel confident about deploying AI at scale across their operations.
In Australia, the use of AI and Gen AI is growing for marketing, ecommerce and digital leaders across all industries, but many are still at an early stage.
According to recent research from Arktic Fox, just 8 per cent of Australian brands have AI for optimisation opportunities and recommendations embedded as part of the way they operate. When it comes to enabling personalisation, just 5 per cent do so.
The data fragmentation problem
Several obstacles prevent retailers from moving faster. Limited technical expertise and high deployment costs create significant barriers. But many retailers globally still struggle to act on customer data effectively.
In Australia, retailers are struggling to maximise the use of their data, with local data suggesting 82 per cent of retail leaders believe they are emerging at best when it comes to activating data to deliver great CX and personalisation. Meanwhile, 84 per cent believe they are emerging at best in building a unified view of the customer.
Clean, accurate data is essential for AI success. Most retailers still have customer information scattered across systems, leaving profiles incomplete. Unfortunately, in Australia, just 58 per cent of retailer leaders are investing their budget in unifying and aggregating data sets to better enable them to leverage and activate it.
Without fixing this fundamental issue, AI risks producing irrelevant or damaging customer experiences.
Businesses must consolidate data from their multiple consumer touchpoints. Otherwise, AI solutions won’t have access to the complete picture. This limits their ability to draw meaningful insights from customer engagements and take effective action.
Building stronger foundations
To succeed with AI, retailers must create solid customer data foundations first. This means deploying platforms that collate various information sources in real-time and present unified 360-degree customer profiles.
AI runs on customer data. Customer data platforms (CDPs) make that data usable at enterprise scale. The advantage is clear: retailers with a CDP are twice as likely to feel confident about understanding and acting on customer behaviour, and three times more likely to deploy AI in customer-facing applications.
These platforms pull information together and make sense of it for AI applications. They tackle major customer data challenges, including the problems created by duplicate profiles.
Solving identity resolution challenges with AI
Duplicate profiles create real problems when retailers engage with consumers across various touchpoints. Duplication happens when people use different identifiers across separate channels, abbreviated names, alternative email addresses, or different contact details.
Australian research suggests that creating a unified customer view is a top investment priority for marketing, digital and eCommerce leaders. Over half of brands are focused on unifying data, with nearly as many investing in activation. In retail, more than half of respondents ranked first-party data strategies and personalisation as key goals.
However, ambition and results don’t match up. Only 14 per cent of brands feel they’re making progress toward a unified customer view. More than half say they’re falling behind on first-party data strategy.
The missing piece is identity resolution. Despite being foundational, only 25 per cent of brands identified it as a key investment area.
This gap creates problems. Unifying customer data requires identity resolution. Without it, personalisation, consent management and omnichannel activation become much harder. Identity resolution helps answer three critical questions about each customer:
1. Who is this customer?
2. What have they signed up for?
3. Where does their data live?
Identity resolution also improves AI application accuracy. When AI personalises interactions, effectiveness improves dramatically when working from complete profiles. It enables cross-channel engagement and prevents customers from receiving conflicting communications.
Early adopters are seeing results
Some brands are finding real success once they tackle data fragmentation head-on. Take UK fashion retailer New Look as an example. When they dug into their customer data, they discovered that nearly a third of their best customers were using more than one email address. That meant 3.4 million profiles were split across multiple records, making it almost impossible to recognise shoppers consistently.
By putting identity resolution in place, New Look was able to bring those records together. Within just one quarter, the brand saw a 50 per cent lift in return on ad spend—saving more than £1 million by targeting the right customers instead of wasting impressions.
A clean data foundation also uncovered something powerful: 71 per cent of their top customers shop across multiple channels. With this insight, New Look could engage up to 24 per cent more high-value customers, fueling smarter, more effective marketing.
Enterprise-wide solutions
With an AI-powered CDP, identity issues can be resolved automatically. However, this remains a low priority for most retailers, only one in five say they’re deploying AI for identity resolution. As retailers look to apply AI more broadly, accurate customer data must become a priority.
The retail sector has reached an inflection point on its path to full AI adoption. The industry is moving from pilot projects and early experimentation to broader deployment and scaled execution. To enable this transition, retailers need enterprise-level data management solutions and CDPs in place first.
The Australian opportunity
A better data foundation will help Aussie retailers move faster, make better decisions and improve their growth potential. Clean consolidated and organised data will enable AI to take on more work, generate better insights and help brands connect more meaningfully with their customers.
Australian retailers who solve their data challenges first will be positioned to win in improving their relationships with customers, especially with AI. The opportunity is significant for brands ready to invest in the right foundations.
If you want to learn more about how retailers are using customer data to close the gap between AI potential and business results, you can see the full 2025 State of AI in Retail Report here.
