After long anticipation and a whole year of delay, Amazon Go was finally launched to the general public with much fanfare three weeks ago. Well, that is if you call opening one small store on the ground floor of your giant corporate building – a “launch”.
The move has reignited the debate about what impact the new technology will have on 2.3M cashiers in the U.S., whose jobs might be eliminated, and on the retail industry as a whole.
But the real question runs deeper. It’s very clear that operating an Amazon Go store comes at a major cost. If all the cost saving is the paychecks of a few cashiers, but the price to pay is installing and maintaining a very large number of advanced sensors – not to mention the initial price of developing the technology – the bottom line is clearly not a profitable one.
Furthermore, if all Amazon wants is to remove the need for cashiers, self-checkout has existed for quite some time and is likely much cheaper to install. Walmart took care to announce that it expanded its “scan and go” app in advance of the Amazon Go launch – yet another alternative. Why is it so critical for Amazon to eliminate the explicit checkout step altogether?
Is it all perhaps just a publicity stunt? Amazon is not known for pulling such stunts; when it launches something big, it’s usually to truly make a strategic move in that direction.
To better understand Amazon’s motivations, we need to go back to how we, the target audience, have been looking at this story, and in particular – the user data story.
If no cashier or RFID readers scan your (virtual) shopping bag, it inherently means that Amazon should have a different way to know what you put in it. Using cameras means it will need even more than that – it will need to know which item you picked up and only looked at, and which item you did decide to purchase eventually.
So, Amazon Go means Amazon should be watching every move you make in the store. In fact, it means Amazon must watch everything you do, or else the whole concept will not work. This requirement that we accept so naturally, this seemingly so obvious conclusion… this is the heart of Amazon’s strategy.
Just think about it: You walk into an Amazon store; your body and face are being scanned and tracked to the point that you can be perfectly recognized; your every move is being tracked and monitored, and all are mapped to a personally identifiable profile tied to your credit card, managed by a powerful private corporation. In any other context, this would trigger a firestorm of privacy and security charges, but for Amazon Go – well, that’s what it takes to deliver on its promise, isn’t it?
What does Amazon gain from this data?
What’s fascinating to notice is that this data enables the transfer of an entire stack of technologies and methodology from online to offline, from the app or site to the brick-and-mortar, which is a dramatic gain. Think about the parallels to what we already came to expect from online – browse sessions, recommendations, abandoned cart flows… That item you were considering? Amazon now knows you considered it. Data scientists all over the retail world would love to put their hands on such physical, in-store behavioral data.
For now, the technology may be limited to groceries as a first step. But we could expect Amazon to work to expand it – rather than to more locations – to further verticals. Just think of the personalized recommendations and subscription services such a technology could drive in high-end wine stores, as one example.
One indication that may show Amazon is truly after the data rather than the stores themselves will be if Amazon licenses Go to other retailers or small players. This will immediately position it as a data broker. In any case, retailers have yet another good reason to keep a close look on Amazon’s disruptive moves.
Amazon is promoting voice shopping as part of its deals for Prime Day next week. Shoppers will get $10 credit just for making their first voice purchase from a list of “Alexa Deals“, items that are already greatly discounted. That’s a major incentive just to push consumers into something that should actually be a great benefit – effortless, simple, zero-click shopping. Why does Amazon have to go through so much trouble to get shoppers to use something that’s supposedly so helpful?
To understand the answer, it’s worthwhile to first understand how valuable voice shopping is for Amazon. In all demos and videos for the various Alexa devices, voice shopping is positioned as the perfect tool for spontaneous, instant ordering purchases, such as “Alexa, I need toilet paper / diapers / milk / dog food / …” That easily explains why you would need to be an Amazon Prime subscriber in order to use voice shopping, and getting Prime to every household is a cornerstone to Amazon’s business strategy.
In addition, Alexa orders are fulfilled by 1-click payment, yet another highly valuable Amazon tool. Amazon also guarantees free returns for Alexa purchases, just in case you’re concerned about getting your order wrong. Now, combine all of these together and you can see how voice shopping is built to create a habit, of shopping as a frictionless, casual activity. That is probably also why the current offer does not apply for voice shopping from within Amazon’s app, as the long process of launching it and reaching the voice search in it ruins the spontaneity.
And yet – shoppers are not convinced. In last year’s Prime Day, a similar promotion offered by Amazon drove on average one voice order per second. This may sound like a lot, but ~85K orders are still a tiny fraction of the total ~50M orders consumers placed on Amazon that day. This year Amazon raised the incentive even further, which indicates there is still much convincing to do. Why is that?
For starters, Amazon’s Alexa devices were never built to be shopping-only. Usage survey reports consistently show that most users prefer to use the Alexa assistant to ask questions, play music, and even to set timers, much more than to shop. This does not mean that Amazon has done a bad job, quite the contrary. Voice shopping may not be that much of a habit initially, and getting used to voice-controlling other useful skills helps build habit and trust. Problem is, when you focus on non-shopping, you also get judged by it. That’s how Amazon gets headlines such as “Google Assistant is light-years ahead of Amazon’s Alexa“, with popular benchmarks measuring it by search, question answering and conversational AI, fields where Google has historically invested more than Amazon by orders of magnitude. The upcoming HomePod by Apple is expected to even further complicate Amazon’s stand, with Apple growing to control the slot of a sophisticated, music-focused, high-end smart home device.
The “How it works” page for the Prime Day Alexa deals hints at other issues customers have with shopping in particular. Explanations aim to reassure that no unintended purchases take place (triggered by your kids, or even your TV), and that if your imperfect voice interaction got you the wrong product, returns are free for all Alexa purchases. These may sound like solved issues, but keep in mind the negative (and often unjustified) coverage around unintended purchases has sent countless Echo owners to set a passcode on ordering, which is actually a major setback for the frictionless zero-click purchasing Amazon is after.
But most importantly, voice-only search interfaces have not yet advanced to support interactions that are more complex than a simple context-less pattern recognition. It’s no accident that the most common purchase flows Alexa supports are around re-ordering, where the item is a known item and no search actually takes place. This means that using Alexa for shopping may work well only for those simple pantry shopping, assuming you already made such purchases in the past. Google, on the other hand, is better positioned than Amazon in this respect, having more sophisticated conversational infrastructure. It even enables external developers to build powerful and context-aware Google Assistant apps using tools such as api.ai (for a quick comparison on these developer platforms, see here).
So what might Amazon be doing to make voice shopping more successful?
Re-ordering items is the perfect beginner use-case, being the equivalent of “known item” searches. Amazon may work on expanding the scope of such cases, identifying additional recurring purchase types that can be optimized. These play well with other recent moves by Amazon, such as around grocery shopping and fulfillment.
Shopping lists are a relatively popular Alexa feature (as well as on Google Home), but based on owner testimonials it seems that most users use these for offline shopping. Amazon is likely working to identify more opportunities for driving online purchases from these lists.
Voice interface has focused mainly on a single result, yielding a “I’m Feeling Lucky” interaction. Using data from non-voice interactions, Amazon could build a more interactive script, one that could guide users through more complex decisions. An interesting case study for this has been eBay with its “ShopBot” chatbot, though transitioning to voice-only control still remains a UX challenge.
And finally – it’s worth noting that in the absence of an item in the purchase history (or if the user declines it), Alexa recommends products from what Amazon calls “Amazon’s Choice“, which are “highly rated, well-priced products” as quoted from this help page. This feature is in fact a powerful business tool, pushing vendors to compete for this lucrative slot. In the more distant future, users may trust Alexa to the point of just taking its word for it and assuming this is the best product for them. That will place a huge lever in Amazon’s hands in its relationship with brands and vendors, and it’s very likely that other retailers as well as brands will fight for a similar control, raising the stakes even more on voice search interfaces.
Prismatic is shutting down its app.
I’ve been fascinated by algorithmic approaches to information overload for quite some time now. It seemed like one of those places where the Web changed everything, and now we need technology to kick in and make our lives so much easier.
Prismatic was one of the more promising attempts to that I’ve seen, and I’ve been a user ever since its launch back in 2012. Every time I opened it, it never failed to find me real gems, especially given the tiny setup it required when I first signed up. Prismatic included explicit feedback controls, but it seemed to excel in using my implicit feedback, which is not trivial at all for a mobile product.
Flipboard is likely the best alternative out there right now, and its excellent onboarding experience helped me get started quickly with a detailed list of topics to follow. With reasonable ad-powered revenue, which Prismatic seemed to shun for whatever reason, it is also less likely to shut down anytime soon. Prismatic still does a much better job than Flipboard in surfacing high-quality, long-tail, non-mainstream sources; let’s hope Flipboard continues improving to get there.
It seems, though, that news personalization is not such a strong selling point. Recently, Apple moved from a pure personalized play for its Apple News app to also add curated top stories, as its view counts disappointed publishers. In my own experience, even the supposed personalized feed was mostly made up of 3-4 mainstream sources anyway. Let’s hope that this is not where information overload is leading us back to. Democratizing news and getting a balanced and diverse range of opinions and sources is a huge social step forward, that the Web and Social Media have given us. Let’s not go backwards.
IBM made some news a couple of days ago announcing consumers can now use Watson to find the season’s best gifts. A quick browse through the app, which is actually just a wrapper around a small dedicated website, shows nothing of the ordinary – Apple Watch, Televisions, Star Wars, Headphones, Legos… not much supercomputing needed. No wonder coverage turned sour after an initial hype, so what was IBM thinking?
Rewind the buzz machines one week back. Google stunned tech media, announcing it is open sourcing its core AI framework, TensorFlow. The splashes were high: “massive potential“, “Machine Learning breakthrough“, “game changer“… but after a few days, the critics were out, Quorans talking about the library’s slowness, and even Google-fanboy researchers wondering – what exactly is TensorFlow useful for?
So what is the nature of all these recent PR-like moves?
There is one high-profit business shared by all of these companies: Cloud Computing. Amazon leads the pack in revenue, and uses the cash flow from cloud business to offset losses on its aggressive ecommerce pricing, but also Microsoft and Google are assumed to come next with growing cloud business. Google even goes as far as predicting cloud revenue to surpass ads revenue in five years. It is the gold rush era for the industry.
So the next time you hear some uber-smart announcement from one of these companies that feels like too much hot air, don’t look for too much strategy; instead, just look up to the cloud.