Retailers Unlock the Power of AI Through a Composable Tech Stack

With advancements in artificial intelligence (AI) and the emergence of composable tech stacks, marketers now have more power to create unique, data-driven experiences for every single customer. This evolution can help fuel deeper personalization, allowing brands to use the full potential of data to connect meaningfully with their users. It also can help free up time and resources for overworked marketers, allowing them to easily automate and optimize 1:1 customer journeys at scale.

Despite the promise of these innovations, many marketers have yet to fully embrace the potential of a best-of-breed tech stack. By investing in a flexible, modular system composed of specialized tools, retailers can enhance customer engagement and streamline operations. This approach not only allows brands to meet the unique needs of their customers but also positions them to thrive in a dynamic, highly competitive market.

When it comes to embracing a composable tech stack, marketers can’t afford to wait. After all, the majority of teams in the ANZ region (99%) are struggling with achieving more creative and strategic customer engagement, according to The State of Customer Engagement in Australia and New Zealand, a data report based on insights from over 200 VP+ marketing executives in the Australian and New Zealand markets.

Improve the shopper experience with a composable tech stack

Across channels, consumers are constantly receiving marketing messages, whether it’s from their favorite brand or an online store they ordered from once five years ago. There are 8.1 billion emails sent per day in Australia alone. It’s clear that sending outreach to customers is effective—for example, email subscribers have 9.6X longer user lifetimes compared to customers who receive no outreach at all—but not all outreach is equal.

Customers are looking for personalized experiences that add real value to their lives, whether it’s a message that makes them laugh or one that solves a persistent pain point. And brands that figure out how to do that successfully have a lot to gain. According to Deloitte Digital, nearly 3 in 4 consumers are more likely to purchase from brands that deliver personalized experiences. They also spend 37% more with those brands.

Furthermore, Deloitte Digital explains that “Personalization isn’t about understanding your average customer. It’s about knowing the customers who hold significance for your brand, deciphering what matters to them and delivering the right depth of personalization based on their unique preferences and behaviors.” And in order to do that, you need the right tech stack that will allow you to quickly understand and act on your data sources.

While many brands are still struggling to get a clear view of their customers and achieve the data agility needed to make that happen, there’s good news to keep in mind. Composable tech stacks can empower retailers to scale and adapt to the evolving wants and needs of their customers. This flexibility not only helps reduce marketing costs but also enables teams to work smarter and ignite their creativity.

According to Deloitte Digital, the shift toward composable architectures has been further driven by the evolution of traditional ecosystem vendors, which have become increasingly complex due to a mix of many technologies and acquisitions gained over time. The once-powerful network effect is now being challenged by the cost and capability advantages of modular, best-of-breed systems that give greater flexibility and agility.

Deloitte Digital and Braze are working with retailers to align their customer engagement goals with the right enabling technology. Leading Australian retailer, David Jones, has embraced composability in connection with their marketing stack and they are realizing multiple benefits like:

• Removing complexity with traditional ecosystem models that have multi-platform product sets, significantly reducing implementation effort.
• Dramatically accelerating speed-to-value with numerous examples of rapid integration of major multi-brand organizations.
• Removing vendor lock-in and reducing total cost of ownership.
• Improving usability for marketers, with the ability to create segments in real time, build rich customer journeys, and deliver multivariate testing, removing the requirements for SQL specialists, development resources, and other specialists that historically caused delays and increased cost.
• Owning a single, centralized persistent source of data on cloud-native extensible platform.

According to Ellie Ward, Head of Loyalty at David Jones, "Braze has allowed us to optimize our ecosystem with best-of-breed solutions, ensuring that we leverage the most advanced and effective technologies available. This has driven innovation and efficiency, enabling seamless access and insights for all teams. The platform has allowed us to launch campaigns faster than ever before while significantly reducing development efforts."

Using AI to personalize the retail customer journey

Composable tech stacks empower retailers to enhance their customer engagement strategies by providing the flexibility, agility, and scalability needed to collect, analyze, and act on data effectively. Once brands unlock the power of a composable tech stack, they can start taking advantage of more advanced capabilities—like AI.

By leveraging advanced AI capabilities, brands can create personalized experiences that resonate with individual customers, ultimately driving loyalty and increasing sales. Here are some of the key benefits of taking this approach:

1. Experiment and personalize with more creative campaigns—at scale

We all know that one-size-fits-all campaigns are less effective than tailored outreach. Yet there’s a reason companies churn out generic messaging and creative assets—because 1:1 personalization has been hard to scale. That is why we are so excited about the prospect of Project Catalyst, an initiative our teams are working on and plan to launch in H1 of next year.

With Project Catalyst, marketers set clear guidelines for journeys, content, items, and incentives while defining their target audience and goals. The AI agent then creates numerous variations for each aspect of the experience—such as subject lines, message tone, available offers, channel mix, and optimal timing. This approach helps ensure each consumer receives a personalized and unique experience tailored to their preferences.

2. Ensure smarter segmentation

With AI-powered solutions like Predictive Events, brands can now identify which of their customers are at risk of churn in the future or which customers are most likely to take a specific action. For instance, they could identify users who are most likely to purchase items from a new apparel line, create targeted segments based on these potential behaviors, and send more relevant campaigns designed to encourage these particular segments of users to take a specific action, whether that’s to complete a transaction for the first time or the first time in a long time, use a promo code, or add items to their cart.

3. Generate product recommendations that are tailored to the individual

Thanks to advanced deep learning technologies that keep track of what items customers have expressed interest in previously, it’s possible to predict the products that customers are most likely to be interested in in the future. With AI recommendation capabilities, savvy marketers are deploying dynamic, tailored suggestions that adapt in response to individual user behavior.

For example, AI Item Recommendations take advantage of customer event and interaction data to predict which products your customers are most likely to be interested in next, based on their past interactions. By seamlessly integrating these individually-personalized recommendations into your campaign, you can help customers discover the products they truly want or need, driving better results for your brand.

4. Deliver completely customized experiences

Identifying the customer path that’s mostly likely to lead to conversion can be challenging, but with journey optimization powered by AI, teams can automatically tailor the copy, images, timing, channel, promotions, and more for each customer experience throughout their lifecycle.

Personalized Paths takes testing and personalization to a new level—often many levels. It can optimize every step of the customer journey, ensuring that individuals receive the message copy, creative, and offers they are most likely to engage with at any stage in their lifecycle, and receive them on the channels they prefer. This feature allows marketers to set up sophisticated experiments in Braze Canvas to evaluate the effectiveness of different versions of a customer journey. By leveraging AI analytics, it identifies the path most likely to result in conversion for each user, based on their unique behaviors and preferences.

The future of retail marketing technology implementation

While many companies are still in the early stages of adopting AI, those that have embraced a creative, data-driven approach to customer engagement are already reaping the rewards. Our research indicates that top-performing brands, which are more likely to leverage AI in their marketing strategies, experience higher levels of customer engagement, increased purchases per user, and improved retention rates.

Looking ahead to the next five to ten years, we can expect a significant shift in the industry. The majority of brands will likely harness AI and machine learning tools to deliver personalized 1:1 messaging, streamlining workflows for marketers and transforming the customer experience. The future is bright for those ready to innovate and adapt.

Want to learn how you can harness the power of AI for your marketing efforts? Download our AI Customer Engagement Playbook.

Forward Looking Statements

This blog post contains “forward-looking statements” within the meaning of the “safe harbor” provisions of the Private Securities Litigation Reform Act of 1995, including but not limited to, statements regarding the performance of and expected benefits from Braze and its features and products. These forward-looking statements are based on the current assumptions, expectations and beliefs of Braze, and are subject to substantial risks, uncertainties and changes in circumstances that may cause actual results, performance or achievements to be materially different from any future results, performance or achievements expressed or implied by the forward-looking statements. Further information on potential factors that could affect Braze results are included in the Braze Quarterly Report on Form 10-Q for the fiscal quarter ended October 31, 2024, filed with the U.S. Securities and Exchange Commission on December 10, 2024, and the other public filings of Braze with the U.S. Securities and Exchange Commission. The forward-looking statements included in this blog post represent the views of Braze only as of the date of this blog post, and Braze assumes no obligation, and does not intend to update these forward-looking statements, except as required by law.