Transforming retail experiences through the power of AI

Salesforce Canada’s Michelle Grant reveals how AI and machine learning are transforming retail shopping experiences // By Shelby Hautala

Fromsmarter shopping experiences to ethical considerations, a conversation with Michelle Grant, Director, Strategy and Insights, Retail and Consumer Goods at Salesforce Canada, sheds light on the exciting – sometimes challenging –use of data and its effects on consumers. Grant offers insights into the latest innovations, strategies for adaptation, shopping experiences, and how critical it is for retailers to maintain the balance between embracing technology, collecting data, and maintaining consumer privacy.

New era of data strategy

Retailers are actively evolving their data strategies to use the full potential of AI, but are not completely there yet.

Grant says it has been a slow start and that more retailers could be using AI to its full potential, but that they’re beginning to pay more attention to things like collection, cleansing, using more data sources, ensuring accuracy, understanding data, and the ways in which data impacts relationships with consumers.

“Retailers are in a transformative phase where the focus has shifted from just collecting data to truly understanding it,” she says. “With stricter privacy laws and technological advancements, the real challenge and opportunity is in how we collect, clean, and use the data to not just understand our customers better, but also to respect their privacy preferences. It is about building trust through transparency and personalized experiences.”

“Retailers are in a transformative phase where the focus has shifted from just collecting data to truly understanding it,” she says. “With stricter privacy laws and technological advancements, the real challenge and opportunity is in how we collect, clean, and use the data to not just understand our customers better, but also to respect their privacy preferences. It is about building trust through transparency and personalized experiences.”

Due to the evolving privacy policies, such as Apple’s iOS update, which limits tracking across different websites, and Google Chrome’s plans to depreciate cookies; privacy policies now restrict how retailers collect data. As a result, Grant says retailers are refocusing on gathering data through customer interactions, whether it be online, through loyalty programs, or in-store experiences. Retailers can apply data across various functions from predictive analytics and inventory management, to implementing AI-driven personalization in marketing and customer service. Using data from these sources is required in order to tailor marketing strategies, optimizing channels and content, and enhancing the overall consumer experience, but not without challenges.

“Retailers are now navigating a new era of data strategy where the focus is no longer just on collection, but on the intelligent use of data,” she explains. “This shift is driven by the need to adapt to privacy changes, like the iOS update and the move away from cookies – pushing us towards first-party data. It is about leveraging this data to not just understand customer behaviours and preferences, but to do so in a way that respects privacy and enhances their shopping experience.”

Enhancing retail with AI-powered interactions

Grant explains that by collecting customer interactions, history, and by using predictive analytics, retailers can offer a more personalized and efficient level of service, and enhance customer engagement and satisfaction. Before this, however, retailers need to start understanding its collected data to be able to improve its offerings first.

“Retailers have been collecting data since the 1970s, so collecting data is not the problem,” she asserts. “Retailers have a ton of data from their apps, websites, and loyalty programs. All of this data has been built over time. It is important for retailers to start off by taking a step back and assessing what they currently have, and then develop a plan to untie it, clean it, and harmonize it. There is technology out there retailers can use to unite and aggregate all the data into one place and make it actionable, allowing retailers to take the data and improve customer service by creating a more personalized experience.”

Grant emphasizes the fact that the use of data goes hand-in-hand with respecting privacy concerns, ensuring customers trust is never compromised. These data-driven approaches also contribute to operational efficiency, including streamlining services and reducing response times, elevating the overall consumer experience.

“Data is the cornerstone of modern customer service in retail,” she says. “By leveraging insights from every customer interaction, retailers are now able to offer a level of personalization and efficiency that was previously unattainable. This is not just about resolving issues quicker; it is about creating an experience that resonates with customers individually, while respecting privacy. The end goal is always to foster trust and loyalty, and data-driven strategies are key in achieving this.”

Streamlining product feedback with AI: faster, easier, and smarter responses

AI simplifies reviewing consumer feedback and makes it easier for retailers to collect information. Grant says AI can automatically analyze large amounts of data from various feedback channels, such as consumer reviews, social media comments, and through shopping interactions. And it can all be done in real-time, allowing retailers to respond to consumer feedback faster and adjust products if necessary.

“Say there is a production where a product failed, quality was poor, or the colour was off from the online product description,” she suggests. “You can either stop that production on that item that is faulty, or you can change the online description to reflect the product better.”

AI could also offer personalized responses, making each consumer feel heard. It has the potential to be more engaging. And, if there are multiples of the same concern, AI can detect and red flag it. Along with this, machine learning is able to predict future trends and consumer behaviours, predicting issues before they arrive, allowing retailers to adjust accordingly.

Personalizing retail: the impact of AI and machine learning on marketing

In the retail world, AI and machine learning are not just futuristic concepts, but tools retailers use to reshape marketing strategies.

“AI and machine learning have fundamentally changed how we approach marketing,” she says. “These technologies enable us to analyze consumer data deeply, understanding patterns and preferences that were previously unnoticed.”

Going beyond basic demographics and purchases, AI and machine learning dives into subtle behaviours as well, painting a picture of each consumer:

“It’s more than just sending out a marketing email,” she asserts. “Its about ensuring the emails resonate with the recipients on a personal level.”

Algorithms actively tailor content, timing, and communication channels to match each customer’s preferences. Grant says this level of customization increases the effectiveness of marketing campaigns, meaning consumers are receiving relevant and timely messages.

Taking personalization to a new level, Grant says AI can influence product recommendations and orders. AI provides personalized product suggestions from gathered data on consumer behaviours:

“The impact of AI-driven recommendations is significant,” she says. “Not only guiding customers to products they are likely to enjoy, but also increasing their likelihood of purchasing.”

AI and machine learning can also predict demand for products, understand patterns from a consumer to predict what they need in the future, and can help identify fraud.

“We have seen cases such as Amazon, where if consumers are abusing its return policy, you are no longer able to shop with them,” she says. “So, they are using data and analytics to do that amongst returns. And when things are being returned, how do you get it back on the sales floor again if it is sellable? Data and insights will help you do that and will tell you what products are being returned a lot.”

Retailers are also keeping up to date with marketing strategies as machine learning provides relevant and engaging information as it continuously learns and adapts based on interactions, crafting messages with a deep understanding of the individual consumer.

“Every click, every purchase, and every online interaction feeds back into the system, redefining the marketing approach,” she explains. “AI and machine learning are revolutionizing retail marketing by enabling a level of personalization we have never seen before. By analyzing consumer data, these technologies allow us to create marketing strategies that are not just effective, but are deeply personalized. We are now able to send the right message, through the right channels, at the right time to each individual consumer, making every interaction more meaningful and impactful.”

“Don’t Be Creepy”: risks of over-personalization

Grant cautions against taking AI and machine learning tools too far with personalized experiences as it could scare off consumers.

“Personalization in retail must be handled with care,” she warns. “There is a real risk of crossing a line where personalization becomes intrusive. Retailers need to be acutely aware of this balance. It is about understanding your customers without making them feel uncomfortable or watched. When personalization starts to feel invasive, it can quickly turn a positive customer experience into a negative one, leading to a loss of trust and potentially driving customers away.”

While personalization is a growing trend and can be effective, Grant emphasizes retailers must balance it and use broader marketing approaches. This balance, Grant says, revolves around respecting privacy, understanding and following legal boundaries, transparent communication with consumers, and building trust through ethical data practices.

“Retailers must navigate this space carefully,” she says. “We need to use data to enhance our understanding of customer needs without crossing into territory that makes them feel exposed or vulnerable. This is where clear communication about our data practices becomes critical. By being upfront about how we collect and use customer data, and by giving them control over their own information, we not only comply with regulations, but also build a foundation of trust. Ultimately, this trust is what underpins the successful use of personalization in retail. It is about enhancing the customer experience in a way that respects their privacy boundaries.”

Just as retailers need to be careful about over personalization, AI also comes with significant responsibilities, particularly in how consumer data is handled and how ethical considerations are managed.

The ethics of AI in retail: ensuring privacy and building consumer trust

In the digital retail landscape, ethical considerations and consumer privacy needs to come first – presenting both challenges and opportunities for retailers. Retailers must not only collect and use data, but also actively protect it against breaches. Grant says retailers must maintain transparency with consumers, stay ahead of privacy laws, and continuously adapt to new AI developments. Currently, Grant says only 13 per cent of consumers trust companies who are using AI. One potential risk is information linkage.

”With generative AI, you can inadvertently leak consumer data into natural language prompts just by the way you write it, which is a huge concern for retailers and why many of them are nervous about using it,” explains Grant.

As AI and machine learning are continuously evolving, Grant advises retailers to use the technology carefully, avoid mentioning personal information, and collect only essential data. To ensure consumer data is not leaked, Grant suggests that retailers need to be proactive. One suggestion she provides is for retailers to create their own language models and train them for internal data. This would keep prompts within their own servers and guidelines; help them adhere to data privacy and security regulations, and follow rules for data collection, storage, and tracking. Grant says it is highly important for retailers to be cautious, stay ahead of risks, continuously update security measures, and have strategies to deal with a range of cybersecurity risks.

“Understanding it, knowing it, and then actually doing it are all different,” she says. “It is really important for leadership within the industry to understand just how important this is, not just from a legal standpoint, but also from a data and brand standpoint. Consumers don’t want to deal with data breaches, fraud or identity theft.”

To secure consumer trust when it comes to AI, Grant suggests that retailers train and prepare employees concerning its use.

“Training and upskilling employees on the use of technology is beneficial,” she says. “However, understanding exactly what to train for is presenting retailers with a number of challenges that they must overcome.”

Despite the risks associated with the use of AI, Grant says that approxinately 50 per cent of Canadians are willing to give retailers more data for better personalization.

“Consumers are willing to provide information to a retailer as long as they receive value from the brand in return,” she says. “So, I don’t really see too much pushback on the consumer side. I think that the biggest hurdle and obstacle is privacy and keeping the consumer’s trust.”

Looking ahead, AI’s role in personalizing the retail experience is expected to grow: along with machine learning, it will continue to advance, providing even deeper levels of personalization. This means that AI systems will become better at understanding and predicting customer behaviour, enabling retailers to offer even more tailored product recommendations and shopping experiences.

“During the holidays, 17 per cent of all orders were AI influenced through product recommendations,” says Grant. “That has been a huge case for data in the retail world. Product recommendations are a huge aspect of data usage.”

AI and machine learning will also help develop enhanced customer service that is more engaging and interactive for the consumer:

“We foresee AI continuing to transform customer service in retail,” says Grant. “This includes everything from more personalized assistance through chatbots to AI-driven customer support that can anticipate and resolve issues more efficiently. This might involve AI creating hyper-realistic product images or videos, offering virtual try-on experiences, or even gathering personalized product recommendations in real-time.”

Grant suggests that the journey of AI and machine learning in retail is ongoing and will keep offering innovative solutions for the retail landscape.

“The next few years, we will likely see groundbreaking advancements in how AI not only enhances the shopping experience, but redefines it, making it more interactive, personalized, and customer-centric.”

She goes on to offer a glimpse into the future of AI and machine learning, from the ways in which it’s being used to help develop marketing strategies to its potential to personalize customer service and experiences. AI’s footprint in retail is both transformative and expansive.

“The two big departments that we are going to see transformed are marketing and personalization,” says Grant. “Just the ability to scale all that, and test it very quickly, is going to transform how marketers do their jobs. And then the second one is customer service, there is so much better

experiences that can utilize generative AI, such as personalized messages to the consumer.”

The journey of AI within retail, with its impact on data collection, personalization, and customer engagement, suggests a path towards more intuitive and customer focused shopping experiences. As retailers navigate the challenges and opportunities of these technologies, Grant says the focus remains on enhancing customer experiences while maintaining ethical standards and privacy.

“We are just beginning to scratch the surface of what is possible. As we advance, the intersection of AI and retail is set to redefine our shopping experiences in ways we have only begun to imagine. AI could lead to more engaging service, offering more of a visual, interactive, and digital experience that’s powered by AI.”