I’ve been fiddling with the idea that tech enabled products will empower experiences for both enterprise and consumer. People will use tech enabled products to enhance their lives, rather than have tech be their lives.
Whether it be employees using AI to search and categorize unstructured data for insights regarding a customer inquiry, or something as simple as ordering a Sweetgreen salad, the world is moving towards tech enabled empowerment. The above examples illustrate how tech enables consumers to execute ordinarily mundane tasks, quickly and efficiently allowing them to spend time on high value activities.
It’s not all about speed when it comes to the future of consumer tech. There’s value in data-driven products. An already tested hypothesis, but some of the biggest winners of today have taken data to create a unique end product for users. Stitch Fix, Rockets of Awesome, and other retailers like MM.Lafleur have already incorporated data science into their core platform – something previously thought to be too farfetched when pitched to investors.
Between data and efficiency, experience can’t be compromised. Every transaction, purchase and service must be unique, drawing consumers back for repeat sales. Having a sleek and sexy design is a good start, but to truly reach the coveted Unicorn status, startups must create an experience-enabled [whatever] that draws a competitive moat in and of itself. Airbnb is a marketplace driven by experience. Spin classes were around long before SoulCycle, yet they created an addictively immersive experience.
In today’s digital age, marketplaces have been commoditized with D2C retailers, pop-up poké stops are on every street corner of NYC, and just about every app has built in recommendations claiming ‘AI’. Competitive marketplaces fuel innovation and the biggest winners of consumer tech will be those that have fully integrated and innovated upon today’s top business models.
The next generation of category defining consumer tech will come from Data + Efficiency + Experience = ?
Data to understand. Efficiency to execute. Experience to make it real.
Here’s what they might be: