Amazon Alexa: A lesson in product failure.
Build better products by learning from Amazon Alexa's mistakes.
If you’ve ever asked Amazon’s Alexa for help and heard a clumsy response - or watched it recommend the same product you just bought - you know that even the biggest brands can stumble. (Sorry, Mr. Bezos)
Despite Amazon’s global reach and seemingly endless resources, Alexa’s slow evolution proves one thing: simply piling on features doesn’t guarantee a product will meet changing user expectations.
Let's look at the numbers shaping the Amazon landscape to understand the weight of these challenges related to Alexa.
The data: Amazon and Alexa by the numbers
Market Muscle: Amazon averages $1.29 billion in daily sales and holds about 39.6% of the US e-commerce market. Over 310 million users worldwide rely on Amazon, and 92% of online shoppers have purchased from it.
Customer Behavior: Although 63% of shoppers start their search on Amazon and Prime members spend more frequently, the platform’s recommendations can feel hollow. Buy an Instant Pot once, and it insists on showing you the same pot again and again. (Including the link so you can experience this real-time)
Alexa Adoption & Usage: More than 71 million Americans use Alexa, which is available on 60,000 devices connected to 100 million products.
The failures: where Alexa fell short
Early on, developers built countless Alexa “skills” to enrich the experience - but most felt like low-quality demos, not real solutions. Conversational clunkiness forced users to repeat skill names endlessly.
Voice recognition often missed the mark, faltering with accents or less common speech patterns. This persistent misalignment left Alexa feeling less like an adaptive assistant and more like a stubborn device stuck in its ways.
Meanwhile, the world moved on. ChatGPT and similar technologies showed us that AI can learn fast, respond naturally, and adapt to user input. Suddenly, Alexa’s inability to grow felt even more glaring.
If Amazon rolled out a new AI upgrade now, would anyone be wowed - or would we just shrug at another late attempt to catch up?
How to keep your product relevant
Amazon’s missteps with Alexa are a cautionary tale, but they also offer valuable lessons for anyone building products.
So, how can you ensure your work stays relevant, adaptive, and aligned with what users need?
Stay Connected to Customers:
Don’t just watch your metrics - reach out, listen, and observe. Gather feedback in forums, user testing sessions, and direct conversations. These insights can show you where your product feels stale before your customers leave.Adopt New Tech Mindfully:
Adding the latest buzzworthy technology doesn’t matter unless it improves the user’s life. Ask if a new feature solves a real problem. If it doesn’t, skip it.On the flip side, If the industry standard is having the bar set by technology - such as conversational experiences driven by AI - you should learn how to integrate the features into your product in natural and helpful ways.
Use Data to Improve, Not Just Sell:
Raw data means nothing if it doesn’t lead to meaningful recommendations or improvements. If a customer buys an Instant Pot, offer recipes, compatible utensils, or cooking classes - something that shows you understand their needs, not just what’s in their cart.Additionally, if they have made it clear they are no longer impulsively looking at these items - move on from presenting them and show them what is more recent. Consider bringing them back up at a later date.
A few additional things to think about to be better than Amazon.
Scaling features blindly without revisiting their usefulness.
Relying on brand power to keep customers around. Today’s users will abandon outdated experiences.
Designing rigid, awkward interactions that make people work too hard to get what they need.
Final thoughts
Alexa’s story reminds us that no product can ride its initial success forever. True relevance comes from staying curious about your customers, evolving alongside them, and using data in genuinely helpful ways.
Adopt new technology if it fits, refine features when they lag, and keep asking what users actually want right now. Do this consistently, and you will not only keep pace with their expectations but also stay one step ahead.
Until next week,
