Amazon became the indisputable winner of the retail universe by engineering a self-perpetuating, data-crunching colossus. From diapers and cat food to batteries and books, Amazon has clearly mastered cost and convenience for a massive range of commodity items. Is it really possible that machines — no matter how much data is available — can accurately capture all our wants and desires?
For all those items that aren’t commodities, the bigger purchases that aren’t rote, will we ever give up needing the wisdom of human tastemakers? Will cost and convenience always outweigh service and experience for non-commodity items?
First, it’s important to understand that by employing a strategy of offering greater selection at lower prices, Amazon attracts an ever-increasing, deeply loyal customer base whose trillions of clicks train its personalization machine to become more skilled at predicting each want and desire.
This algorithmic machine improves by generating data with data, guiding almost three fourths of all online purchases in the U.S. Amazon’s platform is fueled by the digital desires of a full one third of US shoppers who want their shopping experiences to be more highly personalized. These modern consumers want retailers to deliver a buying journey that is guided, familiar and fast.
Braced by a vast array of sophisticated algorithms, Amazon can make educated recommendations, and tell its shoppers that people who have bought X also have bought Y, that people who have looked at A have eventually bought C. Its enormous catalog allows for a near-infinite permutation of items, people, intents and actions, a dizzying combination of machine-generated buying advice available at every moment.
The flywheel is a self-propagating juggernaut. It efficiently figures out the best possible way to deliver things quickly at the lowest possible price, increasingly before people even know that they need it.
But it turns out that brand loyalty and tastemaking go hand in (designer) glove as the primary mechanisms to create sustained competitive advantage. iFans buy from Apple directly. Outdoor lovers flock to REI to indulge their enthusiasm for kayaks and snowboards. Bonobos grows 30% annually by directly selling men well-fitting pants.
Each has secured a place in the online retail market. And each has the power to shape trends. Their strengths lie in service and experience, not cost and convenience. They extract high margins from smaller catalogs, narrowly focused on vocal, loyal and affluent buyers.
There are a few common patterns across these companies — they are winners who have thrived despite the proliferation of Amazon- and Walmart-sized low-cost catalogues. They all value the human experience as paramount, a personal touch from actual living people. They see the process of customers evaluating and buying products as intimate, unique endeavors. For instance, Apple hires in-store associates based on tests that gauge their capacity for kindness and empathy.
REI merges online and in-store shopping experiences with experts in segments across their catalogs, while blogging about the subtleties of various kinds of kayaks, and waxing poetic about the joys of paddling the oceans. In-store associates know the peculiarities of waist packs, bivy sacks, and which kind of water filtration tablets are best for which situations.
Bonobos built a massive business almost entirely predicated on soothing the male ego from the disappointment of being born with unflattering bums. It is not possible for Amazon to profitably deliver this type of expert guidance or personal experience at Bezos-scale.
That’s not to say tastemakers are abandoning technology. Rather they are using technology to augment intelligence and enable their employees serve their customers better. This includes delivering more informed and relevant advice about product choices or solving customer issues faster, more personally and with more empathy. They see technology as a way to augment a hyper-personalized customer experience, not replace it.
They also all have adopted business models and technologies that maximize their strengths in service and experience and diminish their weaknesses in cost and convenience. For example, Warby Parker uses an app that enables people to virtually try on frames before they buy.
Stitch Fix gives their customers access to algorithm-empowered personal stylists. Bonobos gives access to their customer service agents via phone, email and video chat. These experts know everything there is to know about getting men’s pants to fit better. It’s no surprise that Bonobos has built an army of engaged, vocal advocates to spread word of their wares.
As Mike Lowndes from Gartner noted, “Sellers that personalize customer experience see greater levels of customer engagement, higher retention, greater repurchase rates, high average basket sizes and increased rates of conversion.”
Tastemakers new and old, from Toms and Healthy Mummy to Apple and Nike, combine a human touch with mastery over sophisticated AI technologies to delight customers with service and experience, allowing them to extract high margins while conceding cost, convenience, and commodification to the ruthlessly efficient low-margin machine that is Amazon.com.
To build a brand with loyal, fanatical customers who keep coming back, do not look to Amazon as an example. It is, for all practical purposes, impossible to compete on cost and convenience without the operational, logistics and pricing power advantages that Amazon enjoys.
Instead, compete on service and experience by putting to work all the brand recognition, industry knowledge, trends and the individual peculiarities of your vertical to build a tremendous long-term advantage. By being uniquely personal, you won’t have to rely on algorithms alone as your only source of strength and strategy.
Prior to joining Lucidworks, Vivek Sriram led product and business development for the search business at Amazon Web Services, where he co-created Amazon Elasticsearch Service and helped grow the search business from inception to large scale. In his 20+ years in software Sriram served in engineering, business development, and product roles at various companies including Lucidworks, Vizu (acquired by Nielsen), Aggregate Knowledge (acquired by Neustar), and SBI Razorfish.