Why I Go to a Store

I hate shopping. Let me clarify. I hate the physical experience of shopping. I find no joy in a mall. I avoid department stores like the plague. If I can buy it online, I will.

Except..I don’t, always.

Why is that? I should be the gold standard of e-commerce targets. And most of the time, I am. Except when I’m not. Take home improvement stuff, for instance. I still drive down to my local Home Depot, even though I can order online.

As prognosticators of the online space, we’ve been busy hammering the nails in the coffin of bricks and mortar retail for a while. In a recent story in the Atlantic, E-tail was called the perfect match for the emerging sloth of the first world consumer: “E-commerce is soaring and food-delivery businesses are taking off because human beings are fundamentally lazy and they don’t want to leave the couch to buy stuff.”

That makes sense. But while the smart bets seem to be placed on a consumer stampede heading towards e-tail, Amazon just invested 13.7 billion in buying Whole Foods Market. So if bricks and mortar retail is dead, why the hell did Amazon buy almost 500 more physical stores? That same Atlantic article does a pretty thorough job of answering this question, offering three compelling reasons:

  • To dominate the food delivery market
  • To create an instant fulfillment network
  • To broaden Amazon’s footprint within the consumption habits of affluent Americans

I can buy that. The second point in particular seems to make eminent sense. If I know something is in stock at my local store and I need it right now, I’ll make the trip. And Amazon is currently struggling to deliver the last mile of fulfillment. But I keep going back to my original question: why do I – a man who detests the physical act of shopping – still decide to go to a store more often than I probably want to?

There has been various strategies put forward for the salvation. In a recent post on Mediapost, Mahesh Krishna said Personalization was the answer – use data to tailor an in-store experience. I myself wrote something similar in a previous post about Amazon testing the waters of a bricks and mortar retail environment. But there’s nothing personalized about Home Depot. I’m anonymous til I get to the till. So for me, anyway, that doesn’t seem to explain why.

Experiential shopping is another proffered recipe for the salvation of retail. A recent article from Wharton cited an Italian culinary themed retail success story: “Another experiential success… is Eataly, a chain of Italian marketplaces that combines restaurants, grocery stores and cooking schools. It capitalizes on the appeal of Italian culture and sophistication. ‘It all works together like a little universe,’ she says. ‘There’s a nice synergy there; you can taste the foods in the restaurant … you might then go to the grocery store to buy it so you can make it at home.’

But how much “experience” do I really need in my shopping? The answer is not a lot. As undeniably fantastico as Eataly is, for me it would be a 3 to 4 times a year visit. And let’s face it – the retail niches that suit this over-the-top experiential approach are limited. No, there needs to be a more pragmatic reason why I’ll actually drag my butt away from a screen and down to the local mercantile.

I realized, when I really examined the reasons why I usually go to the store, they all had to do with risk. I go to the store when I’m afraid that stuff could go wrong:

  1. When I’m unsure what I need
  2. When I’m afraid I may have to return what I bought
  3. When I have to ask a question about use of something I want to buy

For me, bricks and mortar shopping is usually nothing more than a risk-mitigation strategy, pure and simple. And I suspect I’m not alone. Apple Stores are often cited as an example of experiential shopping, but I believe the real genius of this retail success story is the Genius Bar. The jigsaw puzzle integration of the All Things Apple universe can be a daunting prospect. Having an actual human to guide you through the process is reassuring, and reassurance is most effective when it’s face-to-face. That’s why I go to a store.

 

Will We Ever Let Robots Shop for Us?

Several years ago, my family and I visited Astoria, Oregon. You’ll find it at the mouth of the Columbia River, where it empties into the Pacific. We happened to take a tour of Astoria and our guide pointed out a warehouse. He told us it was filled with canned salmon, waiting to be labeled and shipped. I asked what brand they were. His answer was “All of them. They all come from the same warehouse. The only thing different is the label.”

Ahh… the power of branding…

Labels can make a huge difference. If you need proof, look no further than the experimental introduction of generic brands in grocery stores. Well, they were generic to begin with, anyway. But over time, the generic “yellow label” was replaced with a plethora of store brands. The quality of what’s inside the box hasn’t changed much, but the packaging has. We do love our brands.

But there’s often no rational reason to do so. Take the aforementioned canned salmon for example. Same fish, no matter what label you may stick on it. Brands are a trick our brain plays on us. We may swear our favorite brand tastes better than it’s competitors, but it’s usually just our brain short circuiting our senses and our sensibility. Neuroscientist Read Montague found this out when he redid the classic Pepsi taste test using a fMRI scanner. The result? When Coke drinkers didn’t know what they were drinking, the majority preferred Pepsi. But the minute the brand was revealed, they again sweared allegiance to Coke. The taste hadn’t changed, but their brains had. As soon as the brain was aware of the brand, some parts of it suddenly started lighting up like a pinball machine.

In previous research we did, we found that the brain instantly responded to favored brains the same way it did to a picture of a friend or a smiling face. Our brains have an instantaneous and subconscious response to brands. And because of that, our brains shouldn’t be trusted with buying decisions. We’d be better off letting a robot do it for us.

And I’m not saying that facetiously.

A recent post on Bloomberg.com looked forward 20 years and predicted how automation would gradually take over ever step of the consumer product supply chain, from manufacturing to shipping to delivery to our door. The post predicts that the factory floor, the warehouse, ocean liners, trucks and delivery drones will all be powered by Artificial intelligence and robotic labor. The first set of human hands that might touch a product would be those of the buyer. But maybe we’re automating the wrong side of the consumer transaction. The thing human hands shouldn’t be touching is the buy button. We suck at it.

We have taken some steps in the right direction. Itamar Simonson and Emanuel Rosen predicted a death of branding in their book Absolute Value:

“In the past the marketing function “protected” the organization in some cases. When things like positioning, branding, or persuasion worked effectively, a mediocre company with a good marketing arm (and deep pockets for advertising) could get by. Now, as consumers are becoming less influenced by quality proxies, and as more consumers base their decisions on their likely experience with a product, this is changing.”

But our brand love dies hard. If our brain can literally rewire the evidence from our own senses – how can we possibly make rational buying decisions? True, as Simonson and Rosen point out, we do tend to favor objective information when it’s available, but at the end of the day, our buying decisions still rely on an instrument that has proven itself unreliable in making optimal decisions under the influence of brand messaging.

If we’re prepared to let robots steer ships, drive trucks and run factories, why won’t we let them shop for us? Existing shopping bots stop well short of actually making the purchase. We’ll put our lives in the hands of A.I. in a myriad of ways, but we won’t hand our credit card over. Why is that?

It seems ironic to me. If there were any area where machines can beat humans, it would be in making purchases. They’re much better at filtering based on objective criteria, they can stay on top of all prices everywhere and they can instantly aggregate data from all similar types of purchases. Most importantly, machines can’t be tricked by branding or marketing. They can complete the Absolute Value loop Simonson and Rosen talk about in their book.

Of course, there’s just one little problem with all that. It essentially ends the entire marketing and advertising industry.

Ooops.

To Buy or Not to Buy: The Touchy Subject of Mobile ECommerce

A recent report from Akamai indicates that users have little patience when it comes to making purchases on a mobile device. Here are just a few of the stats:

  • While almost half of all consumers browse via their phones, only 1 in 5 complete transactions on mobile
  • Optimal load times for peak conversions ranged from 1.8 to 2.7 seconds across device types
  • Just a 100-millisecond delay in load time hurt conversion rates by up to 7%
  • Bounce rates were highest among mobile shoppers and lowest among those using tablets

But there may be more behind this than just slow load times. We also have to consider what modes we’re in when we’re interacting with our mobile device.

In 2010, Microsoft did a fascinating research project that looked at how user behaviors varied from desktop to tablet to smart phone. The research was headed by Jacquelyn Krones, who was a Search Product Manager at the time. Search was the primary activity examined, but there was a larger behavioral context that was explored. While the study is 7 years old, I think the core findings are still relevant. The researchers found that we tend to have three large buckets of behaviors: missions, explorations and excavations. Missions were focused tasks that were usually looking for a specific piece of information – i.e. looking for an address or phone number. Explorations where more open ended and less focused on a given destination – i.e. seeing if there was any thing you wanted to do this Friday night. Excavations typically involved multiple tasks within an overarching master task – i.e. researching an article. In an interview with me, Krones outlined their findings:

“There’s clearly a different profile of these activities on the different platforms. On desktops and laptops, people do all three of the activities – they conduct missions and excavations and explorations.

“On their phones we expected to see lots of missions – usually when you use your mobile phone and you’re conducting a search, whatever you’re doing in terms of searching is less important than what’s going on with you in the real world – you’re trying to get somewhere, you’re having a discussion with somebody and you want to look something up quick or you’re trying to make a decision about where to go for dinner.

“But we were surprised to find that people are using their mobile phones for exploration. But once we saw the context, it made sense – people have a low tolerance for boredom. Their phone is actually pretty entertaining, much more entertaining than just looking at the head in front of you while you’re waiting in line. You can go check a sports score, read a story, or look at some viral video and have a more engaged experience.

“On tablets, we found that people are pretty much only using them for exploration today. I had expected to see more missions on tablets, and I think that that will happen in the future, but today people perceive their mobile phone as always with them, very personal, always on, and incredibly efficient for getting information when they’re in mission mode.”

Another study, coming out The University of British Columbia Okanagan, also saw a significant difference in behavioral modality when it came to interacting with touch screens. Assistant Professor Ying Zhu was the principal author:

“The playful and fun nature of the touchscreen enhances consumers’ favour of hedonic products; while the logical and functional nature of a desktop endorses the consumers’ preference for utilitarian products,” explains Zhu.

“Zhu’s study also found that participants using touchscreen technology scored significantly higher on experiential thinking than those using desktop computers. However, those on desktops scored significantly higher on rational thinking.”

I think what we have here is an example of thinking: fast and slow. I suspect we’re compartmentalizing our activities, subconsciously setting some aside for completion on the desktop. I would suspect utilitarian type purchasing would fall into this category. I know that’s certainly true in my case. As Dr. Zhu noted, we have a very right brain relationship with touchscreens, while desktops tend to bring out our left-brain. I have always been amazed at how our brains subconsciously prime us based on anticipating an operating environment. Chances are, we don’t even realize how much our behaviors change when we move from a smart phone to a tablet to a desktop. But I’d be willing to place a significant wager that it’s this subconscious techno-priming that’s causing some of these behavioural divides between devices.

Slow load times are never a good thing, on any device, but while they certainly don’t help with conversions, they may not be the only culprit sitting between a user and a purchase. The device itself could also be to blame.

Shopping is Dead. Long Live Shopping!

Last week, a delivery truck pulled up in my driveway. As the rear door rolled up, I saw the truck was full of Amazon parcels, including one for me. Between the four of us that live in our house, we have at least one online purchase delivered each week. When compared to the total retail spending we do, perhaps that’s not all that significant, but it’s a heck of a lot more than we used to spend.

We are a microcosm of a much bigger behavioral trend. A recent Mediapost article by Jack Loechner reported that online retail grew by 15.6 percent last year and represents 11.7 percent of total retail sales. An IRI report shows similar trends in consumer packaged goods. In 2015, ecommerce represented just 1.5% of all consumer packaged good sales, but they project that to climb to 10% in 2022. In fueling that increase, Amazon is not only leading the pack, but also dominating it to an awe-inspiring extent. Between 2010 and last year, Amazon’s sales in North America quintupled from $16 billion to $80 billion. Hence all those packages in the back of the afore-mentioned truck.

Now, maybe all this still represents “small potatoes” in the total world of retail, but I think we’re getting close to an inflection point. We are fundamentally changing how we think of shopping, and once we let that demon out of the box (or bubble wrapped envelope) there is no stuffing it back.

In the nascent days of online shopping, way back in 2001, an academic study looked at the experience of shopping online. The authors, Childers, Carr, Peck and Carson, divided the experience into two aspects: hedonic and utilitarian. I’ll deal with both in that order.

First of all, the hedonic side of shopping – the touchy, feely joy of buying stuff. It’s mainly the hedonic aspects that purportedly hold up the shaky foundations of all those bricks and mortar stores. And I wonder – is that a generational thing? People of my generation and older still seem to like a little retail therapy now and again. But for my daughters, the act of physically shopping is generally a pain in the ass. If they can get what they want online, they’ll do so in the click of an OneClick button. They’ll visit a mall only if they have to.

In an article early this year in The Atlantic, Derek Thompson detailed the decimation of traditional retail. Mall visits declined 50 percent between 2010 and 2013, according to the real-estate research firm Cushman and Wakefield, and they’ve kept falling every year since. Retailers are declaring bankruptcy at alarming rates. Thompson points the finger at online shopping, but adds a little more context. Maybe the reason bricks and mortar retail is bleeding so badly is that it represents an experience that is no longer appealing. A quote from that article raises an interesting point:

“ ‘What experience will reliably deliver the most popular Instagram post?’—really drive the behavior of people ages 13 and up. This is a big deal for malls, says Barbara Byrne Denham, a senior economist at Reis, a real-estate analytics firm”

Malls were designed to provide an experience – to the point of ludicrous overkill in mega-malls like Canada’s West Edmonton Mall or Minnesota’s Mall of America. But increasingly, those aren’t the experiences we’re looking for. We’re still hedonistic, but our hedonism has developed different tastes. Things like travel and dining out with friends are booming, especially with younger generations. As Denham points out, our social barometers are not determined so much but what we have as by what we’re doing and whom we’re doing it with. Social proof of such things is just one quick post away.

Now let’s deal with the utilitarian aspects of shopping. According to a recent Harris Poll, the three most popular categories for online shopping are:

  1. Clothing and Shoes
  2. Beauty and Personal Care Products
  3. Food Items

Personally, when I look at the things I’ve recently ordered online, they include:

  • A barbecue
  • Storage shelves
  • Water filters for my refrigerator
  • A pair of sports headphones
  • Cycling accessories

I ordered these things online because (respectively):

  • They were heavy and I didn’t want the hassle of dragging them home from the store; and/or,
  • They probably wouldn’t have what I was looking for at any stores in my area.

But even if we look beyond these two very good reasons to buy online, “etail” is just that much easier. It’s generally cheaper, faster and more convenient. We have a long, long tail of things to look for, the advantage of objective reviews to help filter our buying and an average shopping trip duration of just a few minutes – start to finish – as opposed to a few hours or half a day. Finally, we don’t have to contend with assholes in the parking lot.

Online already wins on almost every aspect and the delta of “surprise and delight” is just going to keep getting bigger. Mobile devices untether buying from the desktop, so we can do it any place, any time. Voice commands can save our tender fingertips from unnecessary typing and clicking. Storefronts continue to get better as online retailers run bushels of UX tests to continually tweak the buying journey.

But what’s that you say? “There are just some things that you have to see and touch before you buy?” Perhaps, although I personally remain unconvinced about the need for tactile feedback when shopping. People are buying cars online and if ever there was a candidate for hedonism, it’s an automobile. But let’s say you’re right. I already wrote about how Amazon is changing the bricks and mortar retail game. But Derek Thompson casts his crystal ball gazing even further in the future when he speculates on what autonomous vehicles might do for retail:

“Once autonomous vehicles are cheap, safe, and plentiful, retail and logistics companies could buy up millions, seeing that cars can be stores and streets are the ultimate real estate. In fact, self-driving cars could make shopping space nearly obsolete in some areas.”

Maybe you should buy some shares in Amazon, if you haven’t already. P.S. You can buy them online.

 

The Cathedral and Bazaar Cycle of Mar -Tech Innovation

Each year my friend Scott Brinker sits down to update his marketing technology landscape and each year he is amazed by the explosion of vendors he has to fit on a single slide. Last year’s version clocked in at 3874 Mar Tech solutions – almost twice as many as 2015. He started in 2011 with about 150 and it has effectively doubled with each iteration. While everyone has expected eventual consolidation this hasn’t happened to date.

marketing_technology_landscape_2016_3000px

Scott’s Marketing Technology Landscape – 2016

Why?

For a possible answer, we can look at a fascinating study conducted by a UCLA team looking at the fossil record of cars. Since 1896, there is a reliable record of the introduction of new automobile makes and models. In essence, this creates a “fossil” record, similar to biology, where we can look at the evolution of a technology over an extended time period. In this case, the researchers were looking to isolate the factors that led to the greatest introduction of new models and the discontinuation of old models. When many new models were being introduced, the evolution of the automotive technology accelerated. The researchers wanted to see if this pace of evolution was tied to strength of the economy, changes in oil prices or the number of other cards on the market. What they found was that competition in the marketplace played a bigger role in the variety of car models than either economic growth or oil prices.

However, these periods of rapid innovation didn’t last forever. Inevitably, there was a period of consolidation, where the major manufacturers focused on a few models to increase profitability. It’s a lot more profitable to produce a popular model with relatively few changes over a long period of time.

Once again, we have an oscillation or wave happening.

What is interesting about this is that these periods of rapid innovation always come from an open market with many competitors – exactly what is happening in marketing technology right now. That is because open markets always drive more innovation than can be achieved within hierarchal organizations. As Eric Raymond showed in his brilliant essay on the open source movement – The Cathedral and the Bazaar – the evolutionary forces of a distributed open market (or “Bazaar”) always trump vertical integration (“Cathedrals”) when it comes to spinning off fresh ideas.

In their book “Creative Destruction,” authors Richard Foster and Sarah Kaplan show that organizations (cathedrals) tend to favor incremental innovation with occasional forays into substantial innovation. But markets (bazaars) unleash transformational innovation. The unpredictability and risk increases by a factor of ten as you go from one version of innovation to the other, but so do the rewards. Innovation in markets grow on a logarithmic scale. It’s why some players – like Tesla and Google – have espoused the open-source “Bazaar” approach in areas like sustainable transportation and artificial intelligence where rapid innovation is essential.

There is another critical factor at play here as well. The market/bazaar, being ruthless, quickly culls the competitors down to those that have the best market potential. This explosion of innovation and the subsequent winnowing need a brutally competitive market environment – a rugged landscape in evolutionary terms. Organizations/Cathedrals are reluctant to pull the plug on losers as they fall victim to the sunk cost fallacy and loss aversion. Markets/bazaars operate like nature – “red in tooth and claw” – with a brutal efficiency in dispatching the less fit.

After this explosion of innovation and the subsequent purge, there is a period of consolidation where the biggest players benefit. Let’s call this the Cathedral phase. Here, operational efficiency takes over, looking for greater profitability. Here, market tested innovation is acquired by the largest organizations and systematically incorporated into a replicable template that allows for scalability. Here, the Cathedral model does what it excels at, maximizing profits. Of course, there is a trade off. Innovation withers and dies in this environment, leading to eventual stagnation, which triggers the need for break out innovation all over again.

Will marketing technology follow the Cathedral/Bazaar pattern? In his last landscape, Scott mentioned that rather than coalescing around an “a small oligopoly of platform providers competing for that starring role” the Mar-Tech ecosystem seems to be embedding plug and play compatibility allowing for a longer “Bazaar” phase. Perhaps, with the elimination of market friction, we’re getting to a point where profitability can be uncoupled from the need for scale. I guess we’ll have to wait and see how many mar-tech vendors end up on the 2017 version of Scott’s slide.

 

 

 

 

The Rise of the Audience Marketplace

Far be it from me to let a theme go before it has been thoroughly beaten to the ground. This column has hosted a lot of speculation on the future of advertising and media buying and today, I’ll continue in that theme.

First, let’s return to a column I wrote almost a month ago about the future of advertising. This was a spin-off on a column penned by Gary Milner – The End of Advertising as We Know It. In it, Gary made a prediction: “I see the rise of a global media hub, like a stock exchange, which will become responsible for transacting all digital programmatic buys.”

Gary talked about the possible reversal of fragmentation of markets by channel and geographic area due to the potential centralization of digital media purchasing. But I see it a little differently than Gary. I don’t see the creation of a media hub – or, at least – that wouldn’t be the end goal. Media would simply be the means to the end. I do see the creation of an audience market based on available data. Actually, even an audience would only be the means to an end. Ultimately, we’re buying one thing – attention. Then it’s our job to create engagement.

The Advertising Research Foundation has been struggling with measuring engagement for a long time now. But it’s because they were trying to measure engagement on a channel-by-channel basis and that’s just not how the world works anymore. Take search, for example. Search is highly effective at advertising, but it’s not engaging. It’s a connecting medium. It enables engagement, but it doesn’t deliver it.

We talk multi-channel a lot, but we talk about it like the holy grail. The grail in this cause is an audience that is likely to give us their attention and once they do that – is likely to become engaged with our message. The multi-channel path to this audience is really inconsequential. We only talk about multi-channel now because we’re stopping short of the real goal, connecting with that audience. What advertising needs to do is give us accurate indicators of those two likelihoods: how likely are they to give us their attention and what is their potential proclivity towards our offer. The future of advertising is in assembling audiences – no matter what the channel – that are at a point where they are interested in the message we have to deliver.

This is where the digitization of media becomes interesting. It’s not because it’s aggregating into a single potential buying point – it’s because it’s allowing us to parallel a single prospect along a path of persuasion, getting important feedback data along the way. In this definition, audience isn’t a static snapshot in time. It becomes an evolving, iterative entity. We have always looked at advertising on an exposure-by-exposure basis. But if we start thinking about persuading an audience that paradigm needs to be shifted. We have to think about having the right conversation, regardless of the channel that happens to be in use at the time.

Our concept of media happens to carry a lot of baggage. In our minds, media is inextricably linked to channel. So when we think media, we are really thinking channels. And, if we believe Marshall McLuhan, the medium dictates the message. But while media has undergone intense fragmentation they’ve also become much more measurable and – thereby – more accountable. We know more than ever about who lies on the other side of a digital medium thanks to an ever increasing amount of shared data. That data is what will drive the advertising marketplace of the future. It’s not about media – it’s about audience.

In the market I envision, you would specify your audience requirements. The criteria used would not be so much our typical segmentations – demography or geography for example. These have always just been proxies for what we really care about; their beliefs about our product and predicted buying behaviors. I believe that thanks to ever increasing amounts of data we’re going to make great strides in understanding the psychology of consumerism. These  will be foundational in the audience marketplace of the future. Predictive marketing will become more and more accurate and allow for increasingly precise targeting on a number of behavioral criteria.

Individual channels will become as irrelevant as the manufacturer that supplies the shock absorbers and tie rods in your new BMW. They will simply be grist for the mill in the audience marketplace. Mar-tech and ever smarter algorithms will do the channel selection and media buying in the background. All you’ll care about is the audience you’re targeting, the recommended creative (again, based on the mar-tech running in the background) and the resulting behaviors. Once your audience has been targeted and engaged, the predicted path of persuasion is continually updated and new channels are engaged as required. You won’t care what channels they are – you’ll simply monitor the progression of persuasion.

 

Is Amazon Creating a Personalized Store?

There was a brief Amazon-related flurry of speculation last week. Apparently, according to a podcast posted by Wharton, Amazon is planning on opening 300 to 400 bricks and mortar stores.

That’s right. Stores – actual buildings – with stuff in them.

What’s more, this has been “on the books” at Amazon for a while. Amazon CEO Jeff Bezos was asked by Charlie Rose in 2012 if they would every open physical stores. Bezos replied, ““We would love to, but only if we can have a truly differentiated idea,” he said. “We want to do something that is uniquely Amazon. We haven’t found it yet, but if we can find that idea … we would love to open physical stores.”

With that background, the speculation makes sense. If Amazon is pulling the trigger, they must have “found the idea.” So what might that idea be?

Amazon does have a test store in their own backyard of Seattle. What they have chosen to do there, in a footprint about the tenth of the size of the former Barnes and Noble store that was there, is present a “highly curated” store that caters to “local interests.”

Most of the speculation about the new Amazon experiment in “back-to-the-future” retail centers around potential new supply chain management technology or payment methods. But there was one quote from Amanda Nicholson, professor of retail practice at Syracuse University’s Whitman School of Management, that caught my attention; “she said that space represents ‘a test’ to see if Amazon can create ‘a new kind of experience’ using data analytics about customers’ preferences.”

This becomes interesting if we spend some time thinking about the purchase journey we typically take. What Amazon had done online brilliantly is remove friction from two steps in that journey: filtering options and conducting the actual transaction. For certain kinds of purchases, this is all we need. If we’re buying a product that doesn’t rely on tactile feedback, like a digital file or a book, Amazon has connected all the dots required to take us from awareness to purchase.

But that certainly doesn’t represent all potential purchases. That could be the reason that online purchases only represent 9% of all retail. There are many products that require an “experience” between the filtering of options available to us and the actual purchase. These things still require the human “touch” – literally. Up to now, Amazon has remained emotionally distant from these types of purchases. But perhaps a new type of retail location could change that.

Let me give you an example. If you’re a cyclist (like me) you probably have a favorite bike shop. Bike stores are not simply retail outlets. They are temples of bike worship. Bike shops are usually an independent business run by people who love to talk about their favorite rides, the latest bikes or pretty much anything to do with cycling. Going to a bike store is an experience.

But Trek, one of the largest bike manufacturers in the world, also recognized the efficiency of the online model. In 2015, they announced the introduction of Trek Connect, their attempt to find a happy middle ground between practical efficiency and emotional experience. Through Trek Connect, you can configure and order your bike online, but pick it up and have it serviced at your local bike shop.

However, what Amazon may be proposing is not simply about the tactile requirements of certain types of purchases. What if Amazon could create a personalized real world shopping experience?

Right now, there is a gap between our online research and filtering activity and our real world experiential activity. Typically, we shortlist our candidates, gather required information, often in the form of a page printed off from a website, and head down to the nearest retail location. There, the hand off typically leaves a lot to be desired. We have to navigate a store layout that was certainly not designed with our immediate needs in mind. We have to explain what we want to a floor clerk who seems to have at least a thousand other things they’d rather be doing. And we are not guaranteed that what we’re looking for will even be in stock.

But what if Amazon could make the transition seamless? What if they could pick up all the signals from our online activity and create a physical “experiential bubble” for us when we visited the nearest Amazon retail outlet?

Let me go back to my bike purchasing analogy in way of an example. Let’s say I need a new bike because I’m taking up triathlons. Amazon knows this because my online activity has flagged me as an aspiring triathlete. They know where I live and they have a rich data set on my other interests, which includes my favored travel destinations. Amazon could take this data and, under the pretext of my picking up my bike, create a personalized in store experience for me, including a rich selection of potential add-on sales. With Amazon’s inventory and fulfillment prowess, it would be possible to merchandise a store especially for me.

I have no idea if this is what Amazon has “in store” for the future, but the possibility is tantalizing.

It may even make me like shopping.