In part 1 of this blog, we talked about how a large, American clothing department store chain Ness works with – we’re calling it “Top Brand” – is using digital platforms and data to create customer delight for its patrons. Top Brand has established the foundation – the ability to gather data, automate interactions and maintain an omni-channel omni-presence – for the next revolution in retail technology.
In part two, we’re exploring what retailers like Top Brand can expect in the coming decade and how to prepare for it so they can stay ahead of the curve.
Immersive Digital Experiences Will Proliferate
The coming revolution in retail technology may be closer than some think. In just the next couple of years, we’ll see technology continue to evolve at a rapid pace, and it will have a major impact on the retail industry.
Devices like augmented and virtual reality (AR/VR), voice assistants and smart watches are precursors of what’s to come, but their implementation has only just begun. It won’t be long before handheld devices are no longer necessary. All tech will be wearable, voice-driven and all-encompassing. This will make for deeply engaging, natural and instinctive digital experiences that will change the way customers shop.
Voice-activated wearables will become increasingly more conversational, allowing for customers to ask virtual agents anything, anytime, anywhere in natural language. The ubiquitous Amazon Alexa already allows customers to ask for package tracking and can make purchases on request. With natural language understanding, spoken commands can become more complex and virtual agents will have all the data needed to process those requests accurately to provide a more seamless customer service experience.
We can also expect AR/VR technology to develop rapidly and provide a host of new capabilities for retailers. With VR, stores like Top Brand can digitally recreate an immersive brick-and-mortar shopping experience. Customers can view an interactive, moveable, personalized 3D model that demonstrates what the product looks like in use, including how it fits their body and their style. If my daughter were browsing for a new pair of sneakers with VR capability, she could see what those shoes would like on her, specifically, not on a generic model. She could even view how they look when running or jumping.
In response to customer expectations, retailers are already experimenting with similar technology for new customer/product interactions. For example, some retailers are using 2D models, but that only shows how a product looks, not how it fits in motion, as 3D models can.
Cloud-Based Data Analytics Are A Necessity
Innovations in retail tech will be powered by, and produce, lots of data. To accommodate this influx, retailers will need to rethink the way they store their data. Traditional, onsite data lakes would need to be massive. Companies would have to pay for hardware, as well as the overhead to house all of it, making the cost an infeasible option to manage and maintain. The solution lies in cloud-based data warehouses that save money on hardware costs and wasted space while providing scalable, unlimited storage to meet the company’s growing requirements.
Forward-thinkers like Top Brand have started migrating their data storage to cloud-based data services like AWS RedShift or Snowflake. With these services, companies buy the space they need for an analysis, and then relinquish that space once the analysis is complete; a vastly more scalable option, both up and down, than on-premise storage.
Preparing Data for the Road Ahead
To prepare for the coming retail tech revolution, Top Brand and other retailers will need a thorough understanding of their data. They will need to ask themselves several questions: How much data do they have? Where does it currently live? Is it already structured, or does it need to be prepared before feeding it to an algorithm? Fortunately, machine learning can be trained to analyze and aggregate a company’s data. SimplifAI, a new Ness offering, provides an end-to-end, scalable, enterprise-ready artificial intelligence platform that leverages best-in-class open-source technologies to enable just this sort of ML capability.
Data scientists will need to keep in mind that the data needs to work for the customer first and foremost. Understanding customers’ needs and expectations and factoring that into their AI/ML solutions will be critical to developing processes that work to that end. Ness is using ML to scan millions of Top Brand’s customer interactions to build an automation-readable set of frequently asked questions and their answers. This solution will deflect hundreds of thousands of emails a year to an automated solution that can save Top Brand about $1.4M per year.
Retailers with the right data infrastructure, transformation processes and analysis methods will be able to capitalize on the power of their data like never before. This will result in improved productivity and increased revenue. Additionally, emerging technologies like AR/VR and voice-activated automated assistants will provide them with the opportunity to engage the customer in new and unique ways, ultimately leading to more brand loyalty among shoppers. Customer expectations are changing and growing as rapidly as the technology that fuels them. Top Brand understands that it needs to be on the forefront of adopting these new capabilities and other retailers will need to follow suit or risk losing market share.