The pace and scope of technological advancement is growing faster and wider than ever. It’s not just components and infrastructure – emerging technologies are transforming the human experience, penetrating every aspect of our lives. From biometric authentication to genetically personalized medicine; from in-home automation to virtual reality-based shopping; from connected cars to 3-D printed products, such a kaleidoscope of technologies introduces new interfaces, new capabilities, new forms of value for end users and businesses alike.
Opportunity 1: More Context
IoT sensors, such as those in mobile, smart home devices, and in-store beacons, offer data streams that capture physical context (e.g. location, temperature, movement, dwell time, etc.). AI can combine these sensor feeds for incredibly nuanced intelligence, such as the ability to distinguish between if someone is running to catch the bus versus running for a jog.
Computer vision, a technique employed in cameras and IoT devices, enables machines to recognize objects (fixed and moving) and perceive information about the real world, in real-time. For brands, this unlocks new experiences such as a virtual or augmented clothes fitting; in-store layout optimization; emotion and facial recognition and beyond.
Machine and deep learning, in which computers identify, learn, and predict patterns and outcomes, offer brands a mechanism for data mining at scale, critical for understanding behavioral context. Such techniques can analyze massive amounts of data and identify unseen patterns, while retaining nuanced learnings necessary for personalization.
A great example of this is from sports retailer, Under Armor, which uses these techniques in its app Record. The app not only tracks and analyzes workouts, sleep, and nutrition, but mines other third-party apps and data sources to analyze, learn from, and deliver personal nutrition, coaching, and training advice. Recommendations tap into IBM Watson’s modeling of other similar health/fitness profiles, as well as nutritional databases, psychological, and behavioral data, learning individual and aggregate ‘wisdom’ over time.[JG1]
Opportunity 2: Brand Extension
Thanks to advancements in natural language processing and machine learning, innovative brands are looking to new technologies like chatbots, virtual avatars, robotics, in-car experiences, and voice-based agents to scale 1:1 engagement. Bot agents help brands manage support more efficiently, handling simple, repetitive inquires and triaging more complex or sensitive issues to human agents. They can also span multiple channels, meaning brands can offer less tedious support experiences allowing customers to pick up on one channel (e.g. phone) where they left off on another (e.g. Facebook Messenger). Brands thus increase their own visibility across partners and better meet customers where they [already] are by writing a skill or bot on existing platforms like Amazon’s Alexa products or WhatsApp.
A host of new interface technologies like AR, VR, voice, gesture, touch, and other biometrics are also reshaping how we interact with technology. Shifting interface away from purely screen-based inputs doesn’t just open up new market share for brands— e.g. elderly, disabled, or less technically savvy— it offers new modalities for brands to offer value. In its quest for an ever more seamless delivery process, Domino’s Pizza now lets customers order from the couch (via voice) through Amazon Echo, a skill which can automatically personalize the pizza based on machine learning.
AI also offers brands opportunities to extend the value they provide, serving as trusted educators and partners. Real-time context and interface-appropriate engagement mean companies can offer resources at just the right time, rather than merely pushing sales and advertising. Google’s Assistant product, a virtual agent designed to learn from each individuals’ interactions across Google products, mobile data, and profile, is an effort to offer a personalized AIs for each of their billion+ users. The agent extends across all Google products (hardware and software) and also integrates with devices such as Bose headphones, LG smart watches, and GE appliances.
Opportunity 3: Societal Benefit
Technologies also spell potential in areas like environmental sustainability. Some farmers are using computer vision for precision agriculture to minimize application of chemicals and increase yield and reduce run-off. Deep learning is being applied to improve energy allocation, power consumption, and cooling efficiencies for data centers, offering benefit to IT infrastructure costs and the planet at large. Advancements in additive manufacturing and 3-D printing also promise significant cost savings associated with design prototyping or shipping products across the globe that can be printed locally.
Safety and Responsibility
From advancements in cybersecurity like predictive threat detection, or fraud prevention driven by blockchain, to medical breakthroughs using biotechnology, the opportunities for societal benefit run wide. For brands, emerging technologies represent an opportunity for extending social responsibility programs beyond just storytelling and donations, and into their infrastructure. Such authenticity we know is an important factor for Generation Z consumers, who brands are itching to court.
Opportunity 4: Faster Innovation
Marantz is a manufacturer of connected speakers and audio equipment which uses product data to inform design, functionality, CX, marketing, sales, and partnership innovation. They know where the product resides, how often it’s turned on and off, and what music is played from which streaming services. These data have already informed simple tweaks to product features, UX, and marketing, such as the introduction of a waterproof speaker line and a forthcoming rugged speaker. The company uses data for proactive customer service, as well as for cross- and upsell campaigns to great effect. They’re even considering productizing B2B streaming data to music streaming companies.
The next generation of this comes when products learn from each other, gaining shared intelligence across all interactions. Tesla, the well-known connected car manufacturer doesn’t just offer cars with autonomous features, it has designed a fleet of interconnected cars that actually learn from each other—one car’s “experience” trains the rest of the fleet. Telsa also shares certain data with the U.S. Department of Transportation and other automakers to advance the broader autonomous vehicle industry.
For brands, this introduces a new paradigm in which products can more rapidly appreciate (not depreciate) over time through constantly evolving feedback loops between users and products, and even across products themselves.
Data is now Brand-Consumer Currency
Through this lens, data generated with each touchpoint should inform how, where, and why to improve every aspect of both CX and business operations. From a business standpoint, data informs more effective marketing, sales and channel strategies, partnerships, inventory and supply chain efficiencies, security and product innovation. Companies receive an added benefit in that informed customer engagement helps train algorithms.
Customers receive better, safer, more efficient and contextually relevant products and experiences that improve over time. Certain technologies such as blockchain and cryptocurrencies take this concept further, potentially providing secure mechanisms for end users to tokenize, even monetize their interactions. Realizing data as currency means brands of the future won’t just be customer-facing, they will be altogether customer-driven.
To learn more about Jessica and how Kaleido Insights helps brands, visit www.kaleidoinsights.com. You can also access Kaleido Insights’ latest research report, Three Macrotrends Impacting the Journey to 2030, which dives into longer-term implications of the technologies, impacts, and brand opportunities outlined in this article.