The Retrofitting of Broadcasting

I returned to my broadcast school for a visit last week. Yes, it was nostalgic, but it was also kind of weird.

Here’s why…

I went to broadcast school in the early 80’s. The program I attended, at the Northern Alberta Institute of Technology, had just built brand new studios, outfitted with the latest equipment. We were the first group of students to get our hands on the stuff. Some of the local TV stations even borrowed our studio to do their own productions. SCTV – with the great John Candy, Catherine O’Hara, Eugene Levy, Rick Moranis and Andrea Martin – was produced just down the road at ITV. It was a heady time to be in TV. I don’t want to brag, but yeah, we were kind of a big deal on campus.

That was then. This was now. I went back for my first visit in 35 years, and nothing had really changed physically. The studios, the radio production suites, the equipment racks, the master control switcher – it was all still there – in all its bulky, behemoth-like glory. They hadn’t even changed the lockers. My old one was still down from Equipment Stores and right across from one of the classrooms.

The disruption of the past four decades was instantly crystallized. None of the students today touched any of that 80’s era technology – well – except for the locker. That was still functional. The rows and rows of switches, rotary pots, faders and other do-dads hadn’t been used in years. The main switching board served as a makeshift desk for a few computer monitors and a keyboard. The radio production suites were used to store old office chairs. The main studio; where we once taped interviews, music videos, multi-camera dramas, sketch comedies and even a staged bar fight? Yep, more storage.

The campus news show was still shot in the corner, but the rest of that once state-of-the-art studio was now a very expensive warehouse. The average iPhone today has more production capability than the sum total of all that analog wizardry. Why use a studio when all you need is a green wall?

I took the tour with my old friend Daryl, who is still in broadcasting. He is the anchor of the local 6 o’clock news. Along the way we ran into a couple of other old schoolmates who were now instructors. And we did what middle-aged guys do. We reminisced about the glory days. We roamed our old domain like dinosaurs ambling towards our own twilight.

When we entered the program, it was the hottest ticket in town. They had 10 potential students vying for every program seat available. Today, on a good year, it’s down to 2 to 1. On a bad year, everyone who applies gets in. The program has struggled to remain relevant in an increasingly digital world and now focuses on those who actually want to work in television news. All the other production we used to do has been moved to a digital production program.

We couldn’t know it at the time, but we were entering broadcasting just when broadcasting had reached the apex of its arc. You still needed bulk to be a broadcaster. An ENG camera (Electronic News Gathering) weighed in at a hefty 60 pounds plus, not including the extra battery belt. Now, all you need a smartphone and a YouTube account. The only thing produced at most local stations is the news. And the days are numbered for even that.

If you are middle aged like I am, your parents depend on TV for their news. For you, it’s an option – one of many places you can get it. You probably watch the 6 o’clock news more out of habit than anything. And your kids never watch it. I know mine don’t. According to the Pew Research Center, only 27% of those 18-29 turn to TV for their news. Half of them get their news online. In my age group, 72% of us still get our news from TV, with 29% of us turning online. The TV news audience is literally aging to death.

My friend Daryl sees the writing on the wall. Everybody in the business does. When I met his co-anchor and told her that I had taken the digital path, she said, “Ah, an industry with a future.”

Perhaps, but then again, I never got my picture on the side of a bus.

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.

We Don’t Need More Athletes and Models – We Do Need More People Who Understand Complexity

Have you seen the Verizon ad?

 

The one that starts with LeBron James walking towards the camera. He tells us “We don’t need more LeBrons” He’s followed in quick succession by other celebrities, including model Adriana Lima, quarterback Drew Brees and soccer star David Villa, all saying we don’t need more of their kind. The ad wraps up by saying what we do need is more people in science and technology to fill the 4 million jobs available. Verizon is pitching in by supporting education in STEM subjects (Science, Technology, Engineering and Math). The world, apparently, needs a lot more engineers.

Fair enough. The world runs on science and technology. But there’s an unintended consequence that comes with that. Technology is making the world a more complex place. And what we really need is more people that understand what complexity means.

By complexity, I don’t mean complicated. Those are two different things. I mean complexity in its classic sense – coming from the Latin “com” – meaning “together” – and “plex” – meaning “woven”. “Woven together” is a pretty good starting point for understanding complexity. It’s a concept that depends on connection, and we are more connected than ever before. Whether we like it or not, with connection comes complexity. And when we’re talking about complexity, we’re talking about a whole new ball game where all traditional bets are off.

There’s another funny thing about complexity. It’s nothing new. The world has always been complex. Biology has long been the domain of complex adaptive systems. This is true of all of the physical sciences. Benoit Mandelbrot found fractal complexity in leaves and the coastline of England. Quantum physics has always been around. It wasn’t invented at the beginning of the last century by Max Plank, Albert Einstein and Niels Bohr. It just took us most of our history as a species to discover it, hiding there beneath the deceptively simple rules of Isaac Newton. Complexity has always been part of nature. We’ve just been ignoring it for a long, long time, believing with all our hearts in a simpler, more comprehensible world.

Humans hate complexity, because complexity brings with it unpredictability and an inherent lack of control. It leads naturally into chaos. We much prefer models with foreseeable outcomes. We have been trying for many years to predict the weather, with very limited success. Why? Because weather is complex and often chaotic. And it’s getting more so, not less.

But the extreme weather we’re seeing more and more of is analogous to many parts of our world. Complexity is rearing its head in more and more places. It lies beneath everything. In the words of the Santa Fe Institute, the self-proclaimed world headquarters for complexity science — “(they) endeavor to understand and unify the underlying, shared patterns in complex physical, biological, social, cultural, technological, and even possible astrobiological worlds”

Which means complexity is everywhere. It impacts everything. And almost none of us understand it. But we’ve got to figure this stuff out, because the stakes are huge.

Let’s take something as important to us as democracy, for instance.

There is nothing especially complex about the idea of democracy. But the model of democracy is a different beast, because it relies on the foundation of our society, which is incredibly complex. Democracy is dependent on unwritten rules, which are in turn dependent on conventions and controls that have been inherent in our society. These are what have been called the “soft guardrails of democracy”. And they are being eroded by our newly connected complexity. A few weeks ago, some of America’s top political scientists got together at Yale University to talk about democracy and almost all of them agreed – democracy is in deep trouble. Yascha Mounk, from Harvard, summed up their collective thoughts succinctly: “If current trends continue for another 20 or 30 years, democracy will be toast.”

So complexity is something we should be learning about. But where to start? And when? Currently, if people do study complexity science, it’s generally at the post-grad level. And that’s just a handful of people, at a few universities. We need to start understanding complexity and it’s implications much sooner. It should be covered in grade school. But there’s no one to teach it, because the majority of teachers have no idea what I’m talking about. In a recent dissertation, a researcher from the University of Pennsylvania asked science teachers in a number of schools in Singapore if they were familiar with complexity. The findings were disheartening, “a large sample of ninety Grades 11 and 12 science teachers in six randomly- selected schools across Singapore revealed as many as 80% of the teachers reported that they did not have prior knowledge or heard of complex systems.” By the way, Singapore is consistently rated best in the world for science education. Here in North America, we trail by a significant margin. If this is a problem there, it’s a bigger problem here.

If you’re old enough to remember the movie the Graduate, there was a scene where “the Graduate” – played by Dustin Hoffman – was wandering around his parent’s cocktail party when he was cornered by a family friend; Mr McGuire. McGuire offered a word of career advice. Literally – one word:

“I just want to say one word to you – just one word. Are you listening? Plastics.”

That was 50 years ago. Today, my word is “complexity.”

Are you listening?

Trust No One, Trust Nothing

In just one day last week looking at the headlines on MediaPost – two different articles mentioned a lack of trust – a lack of trust in contextual ad placement and a lack of trust in audience measurement data. But our industries trust issues go far deeper than just those two instances. Article after article cite an erosion of trust and the spreading of relational fault lines in every aspect of the industry.

The question of the day is “Where did the trust go? The follow up question then becomes, “What do we mean by trust?”

That is a difficult question. Trust is a word with many, many meanings. Over 20 years ago, University of Minnesota business professors D. Harrison McKnight and Norman L. Chervany wrote an extensive review to answer just that question. In it, across the many constructs of trust, they identified four dimensions: benevolence, integrity, competence and predictability. But not all these dimensions are required in all applications of trust.

First of all, there are two broad categories of trust: structural trust – trust in a system – and interpersonal trust – trust in a person. In their analysis, McKnight and Chervany looked at six constructs of trust that can apply in different situations. For the sake of this discussion, let’s focus on two of these:

“System trust: the extent to which one believes that proper impersonal structures are in place to enable one to anticipate a successful future endeavor.”

And…

“Situational Trust – meaning that one has decided to trust without regard to the specific persons involved, because the benefits of trusting in this situation outweigh the possible negative outcomes of trusting.”

What trust that did exist in marketing what an outcome of these two constructs. Both tend to apply to the structure of marketing, not the people in marketing. The headlines I cited earlier both pointed to a breakdown of trust on the system level, not the personal level. Now, let’s look at those four dimensions as they apply to structural trust in marketing. No one has ever accused marketers of being overly benevolent, so let’s set that one aside. Also, I would argue – strenuously – that marketers today – including those at agencies – are more competent than ever before. They have been mostly successful at turning marketing from an arcane guessing game that paraded as art to an empirically backed science. So a lack of competency can’t be blamed for this trust breakdown. That leaves integrity and predictability. I suspect there’s a compound relationship between these two things.

The reason we’re losing structural trust is that marketing is no longer predictable. And this lack of predictability is triggering a suspicion that there has been a corresponding lack of integrity. But the unpredictability of marketing is no one’s fault.

Marketing today is analogous to physics at the turn of the last century. For 200 years the universe had been neatly ruled by Newton’s Laws. Then physicists started discovering things that couldn’t be so neatly explained and the Universe became a place of Uncertainty Principles, Schrödinger’s Cat and Strange Attractors. Everything we thought was predictable in all situations suddenly become part of a much bigger – and more complex – mystery.

Similarly, mass marketing could run by Newton-like laws because we were dealing with mass and weren’t looking too closely. Apply enough force to enough people with enough frequency and you could move the needle in what seemed like a predictable fashion. But today marketing is a vastly different beast. We market one-to-one and those “ones” are all inter-connected, which creates all types of feedback loops and network effects. This creates complexity – so predictability is as dead at the afore-mentioned Schrödinger’s Cat (or is it?)

I don’t think this comes as news to anyone reading this column. We all know we’re being disrupted. I think we’re all beginning to understand the challenges of complexity. So why don’t we just accept it as the new normal and continue to work together? Why are clients feeling personally betrayed by their agencies, market research firms and ad delivery platforms? It’s because our brains aren’t very nuanced when it comes to identifying trust and betrayal. Brains operate by the “when you’re a hammer – everything looks like a nail” principle.

Rationally, we understand the different between interpersonal trust and situational trust, but we have to remember that our rationality is reinforced by emotional rewards and cautions. When we’re in a trusting relationship – or system – our ventrial striatum, medial prefrontal cortex and caudate nucleus all perk happily along, priming our brains with oxytocin and pushing all the right reward buttons. But whether it’s a person or a situation that betrays our trust, the same neural mechanisms fire – the insula and amygdala – creating feelings of frustration, fear, anger and resentment.

Now, none of this is the fault of anyone in marketing. But humans work on cause and effect. If our marketing is not working, it’s easier to assign a human cause. And it’s much easier to feel betrayed by a human than by a system.

 

The Assisted Reality of the New Marketer

Last week, MediaPost’s Laurie Sullivan warned us that the future of analytical number crunchers is not particularly rosy in the world of marketing. With cognitive technologies like IBM’s Watson coming on strong in more and more places, analytic skills are not that hot a commodity any more. Ironically, when it comes to marketing, the majority of companies have not planned to incorporate cognitive technologies in the near future. According to a report from IBM and Oxford Economics, only 24% of the organizations have a plan to incorporate CT in their own operations.

Another study, from Forrester, explored AI Marketing Readiness in Retail and eCommerce sectors. The state of readiness is a little better. In these typically forward thinking sectors, 72% are implementing AI marketing tech in the next year, but only 45% of those companies would consider themselves as excelling in at least 2 out of 3 dimensions of readiness.

If those numbers seem contradictory, we should understand what the difference between cognitive technology and artificial intelligence is. You’ll notice that IBM refers to Watson as “cognitive computing.” As Rob High, IBM’s CTO for Watson put it, “What it’s really about is involvement of a human in the loop,” and he described Watson as “augmented intelligence” rather than artificial intelligence.

That “human in the loop” is a critical difference between the two technologies. Whether we like it or not, machines are inevitable in the world of marketing, so we’d better start thinking about how to play nice with them.

 

I remember first seeing a video from the IBM Amplify summit at a MediaPost event last year. Although the presentation was a little stilted, the promise was intriguing. It showed a marketer musing about a potential campaign and throwing “what ifs” at Watson, who quickly responded with the almost instantly analyzed quantified answers. The premise of the video was to show how smart Watson was. But here’s a “what if” to consider. What if the real key to this was the hypotheticals that the human seemed to be pulling out of the blue? That doesn’t seem that impressive to us – certainly not as impressive as Watson’s corralling and crunching of relevant numbers in the blink of an eye. Musing is what we do. But this is just one example of something called Moravec’s Paradox.

Moravec’s Paradox, as stated by AI pioneer Marvin Minsky, is this: “In general, we’re least aware of what our minds do best. We’re more aware of simple processes that don’t work well than of complex ones that work flawlessly.” In other words, what we find difficult are the tasks that machines are well suited for, and the things we’re not even aware of are the things machines find notoriously hard to do. Things like intuition. And empathy. If we’re looking at the future of the human marketer, we’re probably looking at those two things.

In his book, Humans are Underrated, Geoff Colvin writes,

“Rather than ask what computers can’t do, it’s much more useful to ask what people are compelled to do—those things that a million years of evolution cause us to value and seek from other humans, maybe for a good reason, maybe for no reason, but it’s the way we are.”

We should be ensuring that both humans and machines are doing what they do best, essentially erasing Moravec’s Paradox. Humans focus on intuition and empathy and machines do the heavy lifting on the analyzing and number crunching. The optimal balance – at this point anyway – is a little bit of both.

In Descarte’s Error – neurologist Antonio Damasio showed that without human intuition and emotion – together with the corresponding physical cues he called somatic markers – we could rationalize ourselves into a never-ending spiral without ever coming to a conclusion. We need to be human to function effectively.

Researchers at MIT have even tried to include this into an algorithm. In 1954, Herbert Simon introduced a concept called bounded rationality. It may seem like this puts limits on the cognitive power of humans, but as programmers like to say, bounded rationality is a feature, not a bug. The researchers at MIT found that in an optimization challenge, such as finding the optimal routing strategy for an airline, humans have the advantage of being able to impose some intuitive limits on the number of options considered. For example, a human can say, “Planes should visit each city at the most once,” and thereby dramatically limit the number crunching required. When these intuitive strategies were converted to machine language and introduced into automated algorithms, those algorithms got 10 to 15% smarter.

When it comes right down to it, the essence of marketing is simply a conversation between two people. All the rest: the targeting, the automation, the segmentation, the media strategy – this is all just to add “mass” to marketing. And that’s all the stuff that machines are great at. For us humans, our future seems to rely on our past – and on our ability to connect with other humans.

Is Google Slipping, Or Is It Just Our Imagination?

Recently, I’ve noticed a few articles speculating about whether Google might be slipping:

Last month, the American Customer Satisfaction Index notified us that our confidence in search is on the decline. Google’s score dropped 2% to 82. The culprit was the amount of advertising found on the search results page. To be fair, both Google and search in general have had lower scores. Back in 2015, Google scored a 77%, it’s lowest score ever.

This erosion of customer satisfaction may be leading to a drop in advertising ROI. According to a recent report from Analytic Partners, the return on investment from paid search dropped 27% from 2010 to 2016. Search wasn’t alone. All digital ROI seems to be in decline. Analytic’s VP of Marketing, Joe LaSala, predicts that ROI from digital will continue to decline until it converges with ROI from traditional media.

In April of this year, Forbes ran an article asking the question: “Is Google’s Search Quality Starting to Decline?” Contributors to this decline, according to the article, included the introduction of rich snippets and featured news, including popularity as a ranking factor and ongoing black hat SEO manipulation.

But the biggest factor in the drop of Google’s perceived quality was actually in the perception itself. As the Forbes article’s author, Jayson DeMers, stated;

It’s important to realize just how sophisticated Google is, and how far it’s come from its early stages, as well as the impossibility of having a “perfect” search platform. Humans are flawed creatures, and our actions are what are dictating the shape of search.

Google is almost 20 years old. The domain Google.com was registered on September 15, 1997. Given that 20 years is an eternity in internet years, it’s actually amazing that it’s stood up as well as it has for the past two decades. Whether Google’s naysayers care to admit it or not, that’s due to Google’s almost religious devotion to the quality of their search results. That devotion extends to advertising. The balance between user experience and monetization has always been one that Google has paid a lot of attention too.

But it’s not the presence of ads that has led to this perceived decline of quality. It’s a change in our expectations of what a search experience should be. I would argue that for any given search, using objective measures of result relevance, the results Google shows today are far more relevant than the results they showed in 2008, the year it got it’s highest customer satisfaction score (86%). Since then, Google has made great strides in deciphering user intent and providing a results page that’s a good match for that intent. Sometimes it will get it wrong, but when it gets it right, it puts together a page that’s a huge improvement over the vanilla, one size fits all results page of 2008.

The biggest thing that’s changed in the past 10 years is the context from which we’re launching those searches. In 2008, it was almost always the desktop. But today, chances are we’re searching from a mobile device – or our car – or our home through Amazon Echo. This has changed our expectations of search. We are task focused, rather than “browsing” for information. This creates an entirely different mental framework within which we receive the results. We apply a new yardstick of acceptable relevance. Here, we’re not looking for a list of 20 possible answers – we’re looking for one answer. And it had better be the right one. Context based search must be hyper-relevant.

Compounding this trend is the increasing number of circumstances where search is going “under the hood” – something I’ve been forecasting for a long time now. For example, if you use Siri to launch a search through your CarPlay connected device when you’re driving, the results are actually coming from Bing but they’re stripped of the context of the Bing search results page. Here, the presentation of search results is just one step in a multi-step task flow. It’s important that the result that is on top is the one you’re probably looking for.

Unfortunately for Google – and the other search providers – this expectation stays in place even when the context shifts. When we launch a search from our desktop, we are increasingly intolerant of results that are even a little off base from our intent. Ads become the most easily identified culprit. A results set that would have seemed almost frighteningly prescient even a few years ago now seems sub par. Google has come a long way in the past 20 years but it’s still losing ground to our expectations.