Brick-and-Mortar Retail Can’t Risk Missing Out on Virtual Shopping Assistants
Brick-and-mortar retail is getting dissed by millennials, who increasingly prefer to shop online. With millennials representing an estimated $1.4 trillion in purchasing power, brick-and-mortar retailers can’t afford to ignore their needs as e-commerce and subscription services eat into market share. In the words of Vanilla Ice, retailers need to “stop, collaborate and listen,” brick-and-mortar retail “is back with a brand-new invention.”
Artificial intelligence (AI) has been making its way into the physical shopping experience for some time now. Sam's Club jumped on the Amazon Go train and now has select stores with AI-run checkout sections. Sephora’s Color iQ scans customers’ faces and uses AI to determine the perfect makeup combination for their skin.
For many in-store retailers, however, the high expense of AI, combined with limited application, has been an obstacle to adoption. However, a modular conversational agent platform, or virtual shopping assistant, doesn’t require NASA-like funding and a research and development department. A modular agent can be easily developed and help create personalized and seamless interactive experiences for customer support, product searches, and payments, all from a customer’s phone. By focusing on a modular strategy, you can separate out the key building blocks — speech-to-text and natural language processing — and remove, plug in and update different versions of each as your needs dictate.
What’s a Conversational Agent and Why Do I Need One?
Conversational agents are text- or voice-based AI, such as chatbots and virtual assistants. Chatbots facilitate text-based interactions, while virtual assistants, like Alexa, are voice-based. The millennial generation hates talking on the phone, and conversational agents represent an opportunity to engage with a brand minus the social pressures of human interaction. Given that the majority of shoppers prefer to be left alone in-store, conversational agents may be brick-and-mortar retail’s best avenue to in-store customer engagement.
A new development in virtual shopping assistant technology for retail stores allows a chatbot or virtual assistant to be deployed at a kiosk. By utilizing facial recognition technology, retailers can identify customers as they walk in the door, tie them to their online activity, and use a virtual shopping assistant to engage and further refine their profile. Alternatively, virtual shopping assistants can be integrated as a standalone with a mobile or web app, which can potentially eliminate cost as a barrier to entry. While this approach can be used across industries, in-store retail presents unique opportunities to leverage other edge technologies. With the ability to integrate conversational agents with facial recognition technology, for example, retailers can highly tailor the in-store customer experience to each individual.
Customer engagement with a brand now occurs across multiple channels — social, e-commerce, in-store, email, etc. When customers are online, they receive a barrage of nudges — ads, suggestions, reviews — that push them toward products that appeal to them. Physical retailers have struggled to adopt similar techniques, which often results in customers missing out on products they didn’t know existed.
Millennials love their phones. Almost half of all millennials would rather give up shampooing than their phones. And chatbots are on their way to becoming as indispensable as the smartphone; 70 percent of millennials have reported positive experiences with chatbots. Incorporating both into the retail environment can revive the customer experience.
Best Practices for Building a Virtual Shopping Assistant
As adoption becomes widespread, understanding the basic components of a virtual shopping assistant will help retail leaders navigate new technologies and techniques. The most important takeaway for retailers is the importance of "componentizing" your agent platforms so they can be the building blocks for a variety of uses.
What does that mean? If you want to get the most out of your investment, you need to make the right decisions before you begin building your virtual shopping assistant.
- Enable integrations. To start, long-term success means maintaining the ability to integrate with foundational building blocks such as natural language processing, speech-to-text, text-to-speech and software automation technologies. You need to be able to plug in different solutions as they're developed over time to broaden the agent’s application. RESTful APIs, for example, create a sustainable way to develop other use cases for a conversational agent and connect with cloud-based services (or ones you build).
- Design use cases. Conversational agents have the potential to be more than just shopping assistants. From customer support to stylists and the supply chain, the options available will multiply as technology advances. Therefore, it’s important to outline the desired use cases for a model before starting development.
- Start simple. For virtual shopping assistants to converse, they need a content model to pull their language and reactions from, much like human verbal dexterity depends on vocabulary and understanding of context and syntax. Make sure to start with a generic content model as a default and add modular, configurable use case-specific models as you grow. That way your virtual shopping assistant can become smarter over time.
It’s Now or Never
Millennials, Gen X, Gen Z and tech-savvy boomers benefit from a consistent and fluid customer experience. The ability to move from online to in-store shopping without a hitch in the checkout process can dramatically improve brick-and-mortar's viability in the coming years. One way to eliminate hitches is to use virtual shopping assistants. Those that delay adoption risk ending up like the 7,000 stores that closed so far this year.
Not only does retail need to be future-proofed with edge technology, but the technology also needs future-proofing. When building a virtual shopping assistant, develop with a variety of use cases in mind. A platform that can plug and chug the foundational building blocks provides flexibility to choose the most appropriate technology of the moment while adding capabilities over time, including machine vision (facial/object recognition), robotic process automation (RPA) to the backend, even integrating blockchain capabilities or interfacing with hardware components.
In the brave new world of brick-and-mortar retail, you need to run the future to survive the present.
Tipton Loo is vice president of digital edge at ProKarma, a global digital services company that helps organizations build the vision and tools to run the future. He empowers some of the world’s biggest companies to achieve intelligent automation and data-driven decision making through advanced artificial intelligence, machine learning, Internet of Things and analytics solutions. He also heads the Office of Innovation, working on and proving out leading edge technologies.