The Current, delivered daily.
Brands’ primary goal is to sell products, but that’s not the only way they differentiate themselves.
The experience a consumer has with a brand can be just as important when it comes to standing out and influencing the decision to buy, especially when people have to choose between similar products. That experience can also have a big role in determining whether people will buy from a brand again, helping the brand to live beyond an individual product’s consumption in a consumer's mind.
As commerce becomes more digital, the experiences that can be offered to consumers is evolving rapidly. Digital channels for selling and marketing are only expanding, and the way a customer experiences a brand matters at each point. Meanwhile, technology is advancing to create new ways of communicating with customers and serving them that feel less rigid, and fit into their lives. According to customer experience-focused software company Zendesk’s 2023 CX Trends Report, 61% of customers are excited about experiences that are natural, convenient and fluid.
Within brands and retailers, Zendesk said it’s all pushing toward two trends: A bigger role for CX, or customer experience, and more investment in creating immersive experiences for consumers.
At the NRF Big Show 2023, The Current spoke with Zendesk CTO Adrian McDermott about three components of immersive CX that were highlighted in the report. Here’s a look:
Given all of the attention and wonder that was inspired by the release of generative tools such as the chatbot ChatGPT and image-generating DALL-E-2, AI is at or near the top of any conversation about technology to start 2023.
While AI is not new, the outpouring underscores how quickly AI is evolving, and the readiness of consumers to use it. In ecommerce, AI is familiar in the form of chatbots. They are often deployed in customer service to triage and answer questions. Business leaders have harnessed the technology for years, and see it advancing, as well. According to Zendesk’s survey, about three-in-five leaders say AI and bots have become more natural and human-like, while also improving performance. Looking ahead, 57% of leaders expect AI and bots to replace some human agents in the next few years.
But even as the ability to harness tools like large language models to perform human-like tasks gains promise, it must be adopted and become part of an organization’s operations before it can reach customers. According to Zendesk, 64% of leaders say they believe their organization is lagging in the use of AI and bots, even as the same percentage say expansion is an important priority.
At the same time, consumers are gaining higher expectations of AI. When it works, there is recognition that it can be a tool to improve their lives. The arrival of new features like ChatGPT serves to highlight not just how quickly the technology is advancing, but also how AI is capable of more as it gets better.
This means they will look to the places where they interact with AI to do more. Chatbots currently triage and answer questions. Could they also provide something that consumers weren’t considering when they started a chat?
“People are looking for high quality, AI-based interactions, and accepting of those. So the shift is from, this is a way for me to save money, to, this is a way for me to innovate on experience,” McDermott said.
For the companies building technology and the brands and retailers using it, the question is: What will you build with it next?
Text messages. Chats. Voice commands. Messaging is becoming the center of our digital lives.
“Whether it's Facebook Messenger, it's embedded messaging in your application, it's WhatsApp or it’s Google Business messaging, the messaging window has become the new browser window,” McDermott said.
Those can quickly become places of business, as well. While chatbots are already familiar, these spaces are not just for customer service. In messages, retailers could add product carousels, coupons or delivery tracking. These are some of the uses of Zendesk Sunshine, which is a product that normalizes the APIs of different messaging platforms into a software development kit that brands can use to create experiences for customers.
Yet not all businesses are built for this shift at this time. According to Zendesk’s survey, about half of leaders said their agents are able to access conversations and respond across all support channels in one place. Additionally, 61% said they are not built for conversational experiences at this time.
But there is interest. About two-thirds of leaders surveyed are rethinking the entire customer journey to build a more fluid experience that is available to assist a customer “in any way they need at any time,” Zendesk said.
Meeting customers where they are is always a good bet. More and more, they’re messaging, and they’re willing to carry out more of their lives in the chat. Brands can provide the tools to do so.
Increasingly, the convergence of data, conversations and machine learning tools that help to match preferences with customers are enabling shopping experiences to be more tailored to the individual.
That’s the promise of personalization, and business leaders see how it can drive growth. According to Zendesk’s survey, 77% of leaders say personalization increases customer retention, while 59% say it reduces customer acquisition costs.
The data that in part powers personalization plays a unique role in commerce. Customers provide key data like their address and size to make a purchase. That’s purely for utility. But they also want better experiences. The data can be harnessed to provide them.
Instead of tracking numbers and rote lists of options, brands can leverage personalization tools to use real names in communication and provide recommendations for products.
The access methods may change. With the decentralization offered by web3, identity data may be stored in a digital wallet, and order data may only be available for a few weeks via an ephemeral key. Looking out ahead, McDermott sees “consumers controlling both what you could know about them, and how long you can know it.”
But the insights that are gleaned from the data in aggregate can live on, with consumers benefiting from experiences that are made for them. With further development and investment, they will only continue to grow better over time.
Trending in Shopper Experience
Shelf checking, online window shopping and product recommendations are the focus areas.
The NRF Big Show arrives in New York on Jan. 14, and that means companies will be rolling out their latest technologies and partnerships to start off 2023 strong.
Google is getting a head start. Just ahead of the event, the company’s cloud division shared details on four new AI-powered releases for retailers on Friday. The technologies are designed to advance in-store shelf checking, as well as ecommerce browsing and recommendations.
The launches show how Google Cloud is expanding a suite of products for others. This is distinct from Google Shopping through the search giant’s own site, which has also gotten plenty of upgrades over the last year.
"Upheavals over the last few years have reshaped the retail landscape and the tools retailers need to be more efficient, more compelling to their customers, and less exposed to future shocks," said Carrie Tharp, VP of retail and consumer at Google Cloud, in a statement. "Despite uncertainty, the retail industry has enormous opportunity. The leaders of tomorrow will be those who address today's most pressing in-store and online challenges with the newest technology tools, such as artificial intelligence and machine learning."
For those looking to see how AI will play a role in commerce, Google’s technologies offer a few use cases, from store operations to personalized online shopping.
The technologies include:
A shelf-checking solution
This aims to ensure that shelves in stores don’t become low or empty. Built on Google’s Vertex AI Vision, this uses Google’s database of people, places and things to help recognize products. It uses two AI models: a product recognizer and tag recognizer.
The goal is to solve a particular problem: “how to identify products of all types, at scale, based solely on the visual and text features of a product, and then translate that data into actionable insights.”
The AI tool can identify products based on images taken from a variety of different angles. Currently in preview, the product allows retailers to retain their imagery and data.
An online window shopping tool
This feature is designed for browsing and product discovery.
Here’s how it works: Shoppers choose a category, such as “women’s jackets.” Then machine learning selects optimal ordering of products in the results. The system, which is powered by Discovery AI, learns the ideal order on each page, and improves over time with more data.
The feature can be used on browsing, brand and landing pages.
Typically, products are ordered based on best-selling items, or human-written rules. The AI tool essentially self-curates a selection. For retailers, the potential benefits are more revenue per visit and team time saved.
Personalized search and browsing results
This is designed to show customers products that align with their tastes and interests.
AI is employed to analyze a customer’s behavior on an ecommerce site, such as their clicks, cart, purchases and more. This helps to determine shopper tastes and interests, and AI then moves up products that match them in results.
Google said the results are based solely on an interaction on a specific retailer’s site through an account or first-party cookie, and not linked with Google more widely.
Upgrades to Recommendations AI
This is designed to help retailers arrange and coordinate recommendation panels that appear on ecommerce sites. New capabilities include:
- Page-level optimization to help an ecommerce site dynamically decide what product recommendation panels to show shoppers.
- Revenue optimization uses machine learning that helps to identify recommendations that will increase revenue per user session.
- A third tool, built with DeepMind, uses machine learning to analyze product categories, item prices, and customer clicks and conversions. It finds recommendations that balance customer satisfaction and revenue lift.
- Buy-it-again, which provides recommendations for repeat purchases based on a shopper’s history.