Omnichannel customer engagement platform, SAP Emarsys has evolved a lot as a business – starting out with a core focus on email marketing and then expanding to omnichannel marketing to incorporate more channels such as SMS and social media, as well as expanding the type of data it collects beyond customer contact information.

Retailbiz recently spoke to SAP Emarsys senior vice president of revenue and general manager for APAC, Daniel Hagos about key retail trends including AI and data privacy, as well as the evolving loyalty landscape.

“Our core ethos has always been how we can make it easier for marketers to send more personalised and relevant messaging because that’s what customers want,” Hagos said.

“Artificial Intelligence (AI) is not a new term – it’s a very old term but there’s been a lot of different iterations of it. It started as a personalisation tool in the early 2000s for retailers like Amazon and eBay because of their wide and complex product catalogues that were constantly changing.

“Back then, our core business was one-to-one personalised messaging but now, although personalisation is still there, AI is being used for send-time optimisation to share messages at the right time and on the right channel. This automation helps eliminate manual and repetitive tasks and makes the decision-making process easier.

“The more recent stage of AI is generative AI. For us as a business, we still come back to our core ethos of making it easier for marketers and improving day-to-day efficiencies. How can we automate repetitive tasks that are done on a frequent basis? How can we create personalisation at scale?”

Emarsys sees marketers being able to interact with a marketing assistant or chat tool for tasks such as finding the best performing campaigns within a certain time period or discovering the highest conversion among best selling products and then running A/B testing.

“It’s about bringing what’s discussed in a meeting or written on a whiteboard and communicating that using AI so it can be done automatically and instinctively. Fundamentally, we’re making the life of a marketer easier, while improving efficiency, creativity and automation,” Hagos said.

Data privacy

There’s many conversations happening about data and data privacy when it comes to AI, but Hagos believes there’s an interesting contradiction.

“Our research shows that consumers want more relevant and personalised experiences but are hesitant about how their data is used and shared,” he said.

“But for a platform like Spotify, for example, to send personalised music recommendations, you need to listen to music and allow the data to be sent so it can understand listening preferences. I think we need to be careful about how data is being used and stored, and which businesses you’re spending with, because there’s been a lot of data breaches and we need to be sensitive to that.

“Fundamentally, for AI or any sort of personalisation tool to work, it needs data. If we want relevant experiences and want AI to be useful, as both consumers and businesses, data is king. There’s this motion that we like AI but privacy is pulling us back, so we need to have transparent conversations about data privacy and security processes. It’s not a hot topic – it’s a critical one.”

Beyond personalisation, Hagos believes there’s a complex data conversation that needs to happen to ensure data is connected between physical stores and online channels for a smoother customer experience.

“The perception of online and offline has completely changed, largely driven by Covid when people weren’t able to shop in stores and online needed to be leveraged a lot more. I believe that blend was necessary and something that was sped up. It forced retailers to manage and evaluate the unique benefits of both channels and connect them more seamlessly to improve the customer experience,” he said.

“We’re also seeing retailers increase their use of technology in store to deliver different ways of interacting with the brand. A few years ago, technology was quite gimmicky and rigid but now it’s been integrated more seamlessly through technology such as QR codes.”

Changing loyalty landscape

Against a challenging economic backdrop, Hagos has observed a greater focus on return on investment (ROI) and the impact on a business.

“This means there’s more accountability when organisations invest in technology as they want to ensure their teams are using it,” he said.

“Looking at it from a consumer point of view, there’s been multiple shifts. On one hand, there’s been a lot of discounting with research suggesting that consumers are more cost conscious, but on the other hand, businesses need to be more loyalty focused and find ways to create a better experience by adding more value. Instead of reducing prices, finding ways to give more while maintaining prices, through offers such as gift with purchase promotions.

“Overall, I don’t think everyone is jumping to discounts as much as one might think. There’s a lot of brands that continue to hold value, like Apple, because they have such powerful brand loyalty. But we are working with mid-tier brands and retailers and helping them find ways to improve the customer experience through enhanced and relevant marketing content.”

Emarsys has built a predictive segmentation tool, which leverages AI, to predict what a customer is likely to do next. “Before sending a campaign, the platform will advise whether to send a discount or not. If someone adds an item to their cart but doesn’t convert right away, it doesn’t mean they won’t purchase the item later – they might’ve just gone on their lunch break or not had their credit card on hand. The tool is based on our understanding of the customer and how likely they are to convert; with or without a discount.”

Interestingly, Emarsys data shows that some customers don’t respond well to discounts – they want to pay full price and don’t want to purchase something because it’s on sale, especially when it comes to big-ticket items. “We’re telling our clients, don’t just hit the button and give away discounts because you’re just giving margin away when you might not need to.”

A collaborative approach to product innovation

Hagos expects task automation to continue to expand in terms of AI capabilities, but outside of AI, Emarsys has been focusing on mobile and building a mobile wallet platform, which launched earlier this year with City Beach as the pilot client.

“We run a customer advisory board every year. A lot of our innovations and products are built and based on conversations with our clients. For example, we worked with Cue Clothing on a pilot project that we built for them, and it ended up being rolled out globally. Looking at our future roadmap, it will be based on our own vision and objectives, but also influenced and driven by our customer discussions.”