Exploring the Era of AI: Navigating the Authenticity and Automation Paradox

Would you be inclined to trust an artificial intelligence (AI) that is designed to act and communicate in human-like ways?

Turns out, as AI systems become more advanced and human-like, people are having a tougher time differentiating between authentic human behavior and that manufactured by a machine. When done wrong, it could create distrust in AI systems, but when done right AI can offer unparalleled business benefits such as increased creativity and productivity. That’s the paradox: the more AIs become human-like, the less authentic they may seem, and the retail sector needs to leverage such technologies mindfully and in ways that create positive brand impact.

After all, brand recognition and authenticity drive customer loyalty. Customers look for brands that subscribe to their needs, and in many cases, their values. Therefore, brands must work hard to align messaging and brand values with products to foster customer trust and earn their loyalty. As AI becomes more autonomous, the risks are becoming more apparent for brands relying on deep-learning algorithms in place of human-generated content without due diligence.

This quest for authenticity in an increasingly automated world, combined with the rise of generative AI, challenges retail marketing leaders to redefine what authenticity means to their brand. Should authenticity be human-created or simply requires the illusion that a campaign or program was created by humans?

The authenticity imperative for retail

The brands people buy in stores, online, and the packaged goods they consume daily represent the core values and beliefs that influence all facets of their lives. Whether it’s the apparel they wear, the furniture that graces their homes, or the food they consume, consumers view brands as extensions of themselves. In this context, retail brands are not just products and services; they are a reflection of who we are and what we believe. Therefore, the importance of brand authenticity cannot be over-emphasized. It is the very foundation upon which enduring and meaningful customer relationships are established.

While it may be intuitive for humans to connect and empathize with others, AI can’t (at least not yet). As humans, we can usually sense what’s authentic and what’s not. The danger presented by unbridled AI in marketing is that brands can lose long-standing relationships. It could diminish the empathy and credibility they have built up over time by accidentally spreading misinformation, over-personalizing messages, and potentially introducing algorithmic bias.

As customers demand more corporate responsibility from retail brands on topics such as sustainability, ethics, diversity, and climate change, authenticity has become critical for companies, particularly those in this space. Authentic brands are those that present their identity, values, and purpose across all digital touchpoints. These brands are consistent and genuine in their communication and messaging strategy, which helps build trust and loyalty with their customers.

The rise of generative AI and automation

Generative AI and automation technologies are particularly useful to marketers looking for fresh and innovative ways to engage with their target audience, scale campaign efforts, or save on development time for creative concepts. They leverage deep-learning algorithms to spur new ideas for unique content and jumpstart creativity. This allows businesses to create and test different variations of content (including images) across an array of channels, and then to assess which ones perform best. The result is high-quality, engaging, and contextually relevant imagery and copy for blog posts, social media updates, and email campaigns.

Majid Al Futtaim Holding, a Braze and Amazon Web Services (AWS) customer, is a great example of automation being leveraged to support migration and campaign efforts. The team was able to migrate all of Majid Al Futtaim’s different brands and communications to a new customer engagement platform on Braze—something that’s particularly challenging with such a large organization.

Moving to Braze made it easier to support the strong personalization, automation, and ongoing innovation that makes sustainable engagement possible. They were able to accelerate the launch of over one hundred automated campaigns by the end of 2022. They executed over one thousand unique communications on Braze during their first year using the platform. They also successfully sent communications to over 5.5 million recipients with strong open and click rates.

“The new email design system has grown and flourished, allowing us to reduce the amount spent per setup of campaigns while maintaining the excellence in our look and feel.”

Sereen Hindawi
Senior Manager, Customer Engagement at Majid Al Futtaim

AWS for Retail: Helping businesses innovate with generative AI

With enterprise-grade security and privacy, a choice of leading foundation models, a data-first approach, and the most performant, low-cost infrastructure, organizations trust AWS to deliver everything they need to accelerate generative AI powered innovation. And, with AWS, customers can access leading foundation models, customize with their own data, and use the leading security, access control, and features they trust from AWS.

From startups to enterprises, organizations of all sizes are experimenting with generative AI. Everyone wants to capitalize on generative AI and translate the momentum from experimentation to practical innovations with measurable outcomes.

So, what do organizations need to bring generative AI into the enterprise, and make it real?

When AWS has talked to customers, they tell us they need security and privacy, the ability to scale, and price-performance. Most importantly, customers want solutions that are relevant to their business. AWS is putting generative AI at the fingertips of every business, so organizations of all sizes can build new generative AI applications that enhance employee productivity, transform customer experiences, and open up new business opportunities.

Responsible AI, security, and privacy

AWS offers access to foundation models (FMs) with responsible AI in mind at each stage of development. Throughout design, development, deployment, and operations we consider a range of factors. Here are some examples:

Privacy, such as protecting personal information and customer prompts.
Accuracy, such as verifying how closely a summary matches the underlying document or whether a biography is factually correct.
Fairness, such as determining whether outputs treat demographic groups similarly.
Appropriate use, such as filtering out user requests for legal advice, medical diagnoses, or illegal activities, toxicity, for example, hate speech, profanity, and insults.
Ownership, such as Intellectual property and copyright considerations.

At AWS, we know that generative AI technology (and how it is used) is evolving, posing new challenges that will require additional attention and mitigation. With academic, industry, and government partners, we are committed to the continued development of generative AI in a responsible way.

Maximizing value through an effective data strategy and technology ecosystem

In this exciting era of AI innovation, modern growth strategies must have a robust approach to first-party data collection and management to accelerate customer engagement efforts. Not to forget, brands must also have a technology ecosystem that’s built for purpose and able to support such strategies. For example, the collaboration and integration capabilities among Braze, AWS, and Snowflake (another tenured and industry-experienced AWS Retail Competency Partner), have successfully supported retail and digital commerce brands in addressing these challenges and capitalizing on AI technology.

In close collaboration with Snowflake and AWS, Braze excels when it comes to supporting cross-channel engagement and transformative strategies that leverage real-time personalization to shape customer journeys and deliver valuable insights for marketers. Delivering timely and relevant messaging is a common goal for most brands. This joint effort equips Braze with the necessary data orchestration capabilities to fulfill this demand, serving as a crucial advantage in an environment of rising acquisition costs and more budget-conscious consumers.

You can see this powerful combination in action with Petz, which focuses on marketing to customers who’ve abandoned their carts and those who need that extra nudge for repeat purchases. Petz consolidates data from various sources in Snowflake, but in order to capitalize on their customer 360 view, Petz needed an easy way to activate against this data with the ability to experiment across various channels.

By leveraging Braze Canvas, Petz created intuitive customer journeys and could segment, orchestrate, personalize, and test messaging experiences. With Petz focusing on customers with abandoned carts, they could craft specialized messaging designed to persuade customers to complete purchases, as well as repeat purchases of certain items—increasing product sales by 300%. Using Braze Canvas allowed Petz to experiment with different channels including email, Facebook, and even WhatsApp (using webhooks) and analyze the effectiveness of each.

The AWS, Braze, and Snowflake advantage

As a leading cloud service provider (CSP), AWS enables brands and AWS Partners such as Snowflake and Braze to store, analyze, and process data in the public cloud. Many retailers choose Snowflake to store both operational and customer data in the data cloud. Together, AWS and Snowflake enable brands to access customer data from various sources, as well as move customer data within the organization. This breaks down data silos and empowers teams to collaborate around customer insights once data is consolidated, which Braze helps activate through messaging.

Braze is built on AWS, and architected to support continuous data streaming, allowing retail and ecommerce brands to facilitate interactive, responsive, and personalized conversations across channels and digital platforms. Because Braze easily integrates with AWS, and an array of different best-in-class technologies like Snowflake, brands in the space can easily build and optimize a purpose-built engagement approach. With Braze and AWS at the core, brands can amplify the impact of their customer engagements and leverage generative AI — both to support more timely campaign creation and to forge deeper efficiencies within their customer engagement program.

Braze is also powered by Snowflake, making it possible for marketers to activate first-party data, stored in the Snowflake Data Cloud, across a full range of customer messaging channels. Modern marketing is powered by data; therefore, Braze and Snowflake enable brands to access data at the speed of business. From audience segmentation to behavior-triggered outreach, brands rely on data agility using native Braze and Snowflake bi-directional data sharing to create timely, relevant, and personalized messages.

Brands can also query the metadata associated with those activations to glean insights and optimize later activations. This creates an activation/optimization flywheel between Braze and Snowflake which amplifies the impact of direct customer messaging. The Braze and Snowflake partnership supports:

A customer-centric approach: Brands can employ a robust first-party data strategy, continually learning from their customers, to create engaging cross-channel customer experiences, while saving time through automating journey creation and orchestration, routine copywriting tasks, content refinement, and image creation, among other efficiencies.
Enhanced personalization: Brands can harness first-party data collected from Braze, Snowflake, and AWS, to deliver highly personalized and responsive user journeys that will significantly enhance customer satisfaction, conversion rates, and long-term loyalty. They can also take advantage of Braze Liquid personalization and in-the-moment dynamic content personalization using Braze Connected Content. Braze also integrates with Amazon Personalize (on AWS), which uses machine learning algorithms similar to those leveraged on Amazon.com to serve up tailored recommendations for individual users—across websites, apps, short message service (SMS), and email.
Automating with accuracy and transparency in mind: Brands can communicate with their customers accurately and with authenticity. Real-time data integration enables them to make data accessible across teams, driving collaboration and timely insights. For example, brands dedicated to ethical practices can communicate raw material shortages disrupting the supply chain to sustainably-minded consumers.
Operational efficiency and streamlined collaboration: With Braze, Snowflake, and AWS, brands can improve operational efficiency and unlock new opportunities for targeted customer engagement. They can automate their “always-on” campaigns, freeing up time for the creative innovations they’ve been dreaming to achieve.
Preserving the human element: Brand authenticity relies on the human element. With Braze, Snowflake, and AWS, brands can channel efforts into creative endeavors and relationship-building by using AI and automation. It can reduce time on routine tasks, freeing up teams to concentrate on innovative ways to support brand authenticity and foster long-term customer loyalty.

Conclusion

Together, Braze, Snowflake, and AWS empower retail brands to navigate the authenticity paradox by leveraging AI, advanced automation, and data analytics to achieve higher productivity and effectiveness.

As the retail landscape continues to evolve, the synergy between technology and human elements exemplified by collaborative relationships will be key to future success. Navigating this balance is the way forward for retail brands to thrive and adapt in the ever-changing landscape, all while preserving the authenticity that is at the heart of their success.

Learn more about AWS Partners, or contact an AWS Representative to see how we can help accelerate your business.

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