Why Should You Care About Deep Learning?

People and patterns and predictions, oh my.

For marketers, a simple way to think about deep learning is that it’s ultimately about presenting customers with exactly what they want, whether or not they know yet that they want it. That could mean an experience, a bit of information, an ad, or a suggestion for a specific product. But what is deep learning?Deep learning is a subset of artificial intelligence (AI) derived from the science of neural networks. And neural networks are simply an attempt to mimic the way scientists think our own brains process and make sense of the world. Basically, a neural network self optimizes its performance on a desired task based on exposure to structure and unstructured data.

I spy with my AI…

For example, let’s imagine we’re creating a deep learning based image recognition system designed to spot a product––a specifically branded can of soda—in photos posted on social media because we’d like to give a shout out, through our own social accounts, to the poster for their brand loyalty.The first thing we would need to do is train the deep learning neural network using a number of verified positive and negative sources—e.g., photos containing said soda can, pre-tagged as a hit as well as photos with no can correspondingly tagged as a non-hit. Next, the system would be fed untagged positive and negative photos. The digital patterns in those photos would be compared to whatever digital patterns emerged from reviewing the initial guided positive and negative inputs.If the system recognizes what it has determined is the pattern for, “branded can,” it marks that photo as a positive hit. At this stage, the system will require human feedback to determine whether that positive hit was, in fact, positive and whether other photos were falsely tagged as hits or non-hits. Each iteration, every data point, refines the neural network to better identify its proper target. And with data sets that span the internet, you can imagine how refined those algorithms can get.But here’s the interesting part. Humans generally can’t read or understand those algorithms. We don’t know what the criteria the network is using, per se. We only know it’s getting better (or worse) at identifying the branded can. And there are plenty of times the technology fails completely, not to mention offensively.

Sidebar:

How this “portrait” was made:

1. generate random polygons
2. feed them into a deep learning, neural net face detector
3. mutate to increase recognition confidence until the neural net is reasonably sure it is “seeing” a face

A synthetic portrait “recognized” among random overlaid polygons by deep learning AI at here, here and here, deep learning AI will likely become increasingly pervasive in marketing and advertising. If you want a far more detailed and thorough primer on the topic, Stanford university has placed online an amazing guide to deep learning.    

Looking For a Path to Growth? Change Your Perspective.

Whether simply beginning to map out long-term product or technology roadmaps, examining areas of exploration or innovation, analyzing channel strategy or simply wanting more from existing customers, every company would be well served by asking

What are my customers really buying?

The first big mistake most companies make is believing their customers are buying a thing—a specific product or service. Meaning, your basic widget manufacturer thinks they are satisfying a consumer's desire to own a widget. That frame of mind works well enough in most cases. You can survey the market fairly efficiently and determine the total current market for widgets. You can do a bit of google searching and know how many other widget manufacturers are out there. And finally, you can do a bit of math and quickly determine getting more or less of your reasonably fair share of the market. The problem with that perspective is that it tends to limit the range of growth ideas to those defined by their widgetness. Better widgets. Bigger widgets. Cheaper widgets.

Harvard Business School Clayton Christensen views consumer transactions from a different perspective. In his book, Competing Against Luck, Christensen posits products are not purchased, but rather “hired” by the customer to do a specific job. And if a company can unravel the relationship, it gives them more and better avenues along which to innovate—creating better candidates for the available job.

One example he cites in his classes at HBS is that of a milkshake company that hired Christensen and his team to help boost sales. Through a series of post-purchase interviews with customers at the milkshake purveyor’s retail outlets, Christensen was able to determine that for most buyers, the job the milkshake was hired for wasn't sustenance or even pleasure, per se, but rather a distraction during a long commute home. That the physical challenge of pulling a thick shake through a straw was the perfect distraction to help make the long drive more tolerable.

The company used that insight to create a new line of shakes, both thicker to last longer, and more entertaining through the addition of fruit chunks and other bits to deliver additional joy and keep drivers more “shake engaged.” Changing perspective and understanding what their customers were really buying—entertainment and distraction—opened new avenues for product innovation and growth.

Does my business really have to work this way?

The second big mistake many make is assuming the way you’re currently doing business is the right way and that the logical path to follow leads to doing more of it. As soon as you resign yourself to a specific channel strategy, technology platform, distribution model, et al, you close yourself off to potential opportunities and open opportunities for new market entrants.

Case in point: Casper mattresses. Prior to Casper, the mattress retail experience adhered to a few fairly strict experience guidelines. First, the buyer had to be able to try out the mattress in a retail showroom before purchase—usually under the watchful eye of sales associate. A mattress was too large a purchase to make blindly. Adding to that risk was guideline number two—retailers would do just about anything not to have to take returns on mattresses. And three, selling mattresses direct, online, wouldn’t be financially viable, due to the shipping costs.

In 2014, Casper turned literally every aspect of the purchasing process upside down. The mattresses ship to a customer’s doorstep in a highly compressed in a box of only 19 x 19 x 41 inches—keeping shipping reasonable. Customers are free to sleep on the mattress in their own home for 100 nights. If they return it, Casper picks it up and donates the mattress to a local charity. Truly a disruptive entrant. An article from Fortune nicely encapsulates the dangers of the incumbent being too wedded to their model:

At first, big mattress companies dismissed the “bed-in-a-box” trend as a niche phenomenon, hardly worth acknowledging; but that was before the startups grabbed 9% of U.S. market share. In August 2016, Sealy launched Cocoon by Sealy, a bed-in-a-box brand boasting minimalist fonts, an uncluttered scrolling webpage, and a price point half that of Casper’s. “It’s been a delayed reaction, but now they all have bed-in-a-box products,” says Seth Basham, senior vice president of equity research at Wedbush Securities. As for Casper, Basham adds: “They’ve already got a foothold. Now it’s a matter of how big they’ll grow.”

In what way are you failing customers?

Sometimes the toughest act for a company, or an entire industry, is to take a honest look in the mirror and document the flaws, warts and all. That means really taking the time to understand the end-to-end customer experience and cataloguing every point of friction, pain or frustration. Then looking at those points and asking, “If these flaws, no matter how insignificant they may seem, were critical enough to put me out of business tomorrow, how would I, and to what effort would I put forth, to solve it?” History has shown US market entrants who address issues that companies imagined were trivial can radically alter the competitive landscape. Sometimes that thing can be as small as an emoji.

Starting in 2010, Domino’s Pizza started looking in the mirror and being honest about what it saw, or rather, tasted. It admitted that its pizza was, shall we say, “less than tasty.” So, their first action was to admit it. To themselves and to the world, through their advertising. The second, was obviously to reformulate. Setting aside whether you subjectively agree that the outcome of that reformulation was an improvement, objectively the market began to take notice.

Continuing the examination, Domino’s started to look at every aspect of the ordering experience, leading ultimately to what I would say is the most frictionless ordering experience in their industry, the emoji order. Once you are in their system, your mobile number registered, the only thing between you and a fresh hot delivered pizza is one texted pizza emoji.

Was ordering a pizza via phone, the web, or a mobile app really a “fail”? Easy enough, right? Maybe. But given the number of pizzas ordered by those under the influence of any number of chemical substances every year, something as simple as an emoji just might substantially increase their chances of a completing that order successfully. And it’s a pretty entertaining experience for everyone else, too.

And addressing those seemingly minor, “fails,” has had a major positive impact on their stock price.

Ultimately, try to think like a customer… from another planet.

It’s never easy to see past our experiences or biases. But when a company can be deliberate about the process of self-examination and inquiry, and take on the perspective of an objective observer, opportunities reveal themselves.

Three Proven Paths to Disruptive Innovation

[embed]https://soundcloud.com/magnani_brilliant/3-three-proven-paths-to-disruptive-innovation[/embed]

Justin and Justin discuss the myth of overnight success, the three proven paths to disruptive innovation, and how half the Fortune 500 companies listed in 2000 have been replaced by market disruptors. And, as a bonus, they give their subjective opinion of Domino’s pizza.

The Great Nokia Time Travel Experiment (How I Learned to Shake My Notifications Habit)

In the middle of 2017, I found myself reading quite a bit of the current research on the effects of heavy smartphone usage on cognitive function. You can see an overview of what I found here. In short, the persistent drip of dopamine our brain releases when we get rewarded with repeated notifications can negatively affect our ability to concentrate as well as diminish our ability to transfer short-term memory into long-term memory. Cool, right?Coincidentally, as I was reading all of this research, my iPhone battery was, as they say, giving up the ghost. Knowing I would at some point have to part with my iPhone for some 24- to 48-hour period for repairs anyway, I decided it was, with the help of the newly relaunched Nokia 3310 3G, time to attempt to return to a simpler era.

Instant weight loss

I went online and put down my hard-earned $59.99 (plus tax and shipping) on a new, previous blog about wearables, I have a limit on the number of “things” i will commit to carrying. Specifically, I have a limit of four NEED to remember when I leave the house: Wallet. Keys. Glasses. Cell phone. If I add a fifth, I’ll likely forget one of them at home. So, no iPod. Suddenly, the calculus of the value of this newfound calm has changed. It was time to reopen negotiations with the old iPhone—newly repaired and returned from its battery transplant surgery at the hands of an Apple Store tech.

The grand compromise

While using the Nokia—more specifically—my experience with Gmail, I realized that even this old school handset could provide unending distraction if properly (improperly?) set up to do so. The afflictions resulting from iPhone use are not inherent in its glass touch screen, but rather from the default preponderance of notifications. The next step. Return to the iPhone, with all notifications off.

I cannot recommend it enough

Not the Nokia, sorry. Texting with T9 is still an awful way to communicate. But an iPhone with notifications turned off is a definite life improvement. Eventually I found I needed calendar reminders and text notifications (without previews). But that's it. Facebook, Instagram and LinkedIn are not mission critical. Maybe not even enjoyable when they get full reign over your attentions.Of course, I will keep the Nokia as a pending threat to my kids if their smartphone usage gets out of hand.

Why Your Brand is Only a Guest in the House of Reddit: A Lesson on the Sanctity of the Upvote

The house that diversity built.

Around since 2005, Reddit is a social platform most marketers have heard of, but many tell us they’re not exactly sure what it is and how it should fit into their overall communications program. So, what is it? Reddit is a social content aggregator that allows anonymous users to post content—photos, links, thoughts—to relevant “subreddits” where other users can “upvote” or “downvote” the content, and the subsequent conversation thread contained within.Currently, Reddit has over 540 million monthly visitors, ranking as the #4 most visited website in U.S. and #6 in the world. It’s had a storied evolution from science and programming content (along with the expected content that has been the foundation of the social internet) to a broader range of content that has gone on to help drive the tastemakers and content curators of this generation—it’s likely if you shared something on Facebook and Twitter, it was originally posted on Reddit. The evolutionary spark that ultimately drove the emergence of the Reddit we see today was failure of Digg.com. In 2009, the popular content aggregator Digg launched a major UI update that incited a user rebellion. And those users ultimately flocked to Reddit—forever altering and diversifying  the type and the quality of the content on the site. The spike in users, and the subsequent influx of mainstream content subreddits, also delivered an impressive “hive mind” of like-minded users. Collectively, by sheer scale, they brought the site into the mainstream but not necessarily the limelight. They were the center of a diaspora of content and ideas, even if most people ultimately consumed those ideas and content on outside social platforms, like Facebook or Twitter.

The temptation for brands was inevitable.

Since the great Digg migration of 2009, advertisers have coveted and courted the Reddit user base, repeatedly trying to break into the platform. The best of them authentically joining the conversation. The most doomed of them trying to manipulate the community.Brands that have succeeded don’t push the brand, they react honestly to community sentiment, solve problems and respond to issues.See: here, here and here.Brands that have failed try to game the system, create fake supporters, tell users they are “wrong,” or generally treat community members as pawns in their marketing schemes.See: here, here and most impressively here.

And the bots are why we can’t have nice things.

What fuels Reddit is the upvote. What gets voted up is supposed to be the real result of natural confirming clicks of the community. But a number of brands and marketers, along with an army of bots, has been trying to change what “real” means. Joining the community, manipulating the process and creating a critical mass of votes to try and push something front and center.Vote buying startups, astroturfing, and, of course, the Russians are beginning to erode confidence in the veracity and authenticity of the vote and, by proxy, the community itself.

Strategies for approaching the platform.

If brands want to interact in this space, a proper strategy might be first, to watch, listen and explore. You could start here. Look around and ask if there is already a stage where your brand or service might resonate or already is resonating.For example if you provide a service, listen in subreddits for complaints, and resolve those complaints publically and transparently—much like how Twitter has become for a more reliable customer service experience.Posting funny images of your brand, product or service rarely resonates and will more likely seen as pandering. A more reactive and helpful approach to the platform garners more positive sentiment and provides more value to the users.And, always, before entering the house, remember, you’re only a guest.

How to Improve Your Odds of Successfully Innovating? Hint: It’s a Numbers Game.

How many of Edison’s 1,000+ inventions can you name?

There is the electric light bulb, the phonograph, the motion picture camera... and more. And that’s the point. For every notable invention Edison patented, there were dozens more along the lines of his entire post on the value of failure in the innovation process. One way to think about it is to look at a very rough rule of thumb used by many venture capitalists. Among all of the investments they make, they expect:

• One third of investments fail outright
• One third of investments break even
• One third of investments generate 10X returns

If they can stick to that schedule, failures and all, they are generally making better than average returns on the portfolio overall. Granted, it’s not a sound strategy for any normal investor looking for someplace safe to slowly grow their money over time, but it’s perfect if your investments are collectively high risk/high reward endeavors. And if your innovation program doesn’t fit that description, you’re probably not actually innovating.

So, how can you improve your odds?

Reading all of this discussion of failure and risk, one might assume innovation programs are a drawn out roll of the dice. There are, however, proven ways to increase your chances of success, besides simply having the tenacity to ride out the failed iterations along the way.

1. Define your area of focus Try to determine what aspect of your industry or category offers the greatest opportunity for disruptive innovation. Is it in product cost? Performance? Service model? We have another article covering a few approaches to this issue here.
2. Focus your teamCreate a dedicated innovation group. Make sure they’re charged not only with creating new innovation projects, but also shepherding them—both the successes and the failures—through to completion.
3. Know your end userThis may be the most important safeguard of success. Great innovation is about solving for real human needs and challenges. When component bells and whistles drop in price, should you add more bells and whistles or create a cheaper bell and whistle delivery system? Unless you know what truly matters to your existing and potential users, you have no reasonable way to determine which path offers the greatest chance for success.

In other words. Everyone rolls the dice. But smart innovators take the time to figure out where to shave off a corner here and there to make the numbers come up in their favor more often.

Why Persona Development Should Be A Part Of Every Customer Experience Design

As strategic marketers and UX strategists, we understand the importance of persona development, yet many still have a difficult time selling in this important step within their organizations. When discussing the persona development process with clients, I tend to receive the same questions at the outset of every project. So, I thought it might benefit our readers to tackle the basic answers to many of those questions in this post. Here it goes.

We have segmentation. Why do we need personas?

Customer segmentation enables marketers to understand the similarities in customer groups—whether it be demographic or behavioral commonalities—to uncover which customers have the most growth potential, ultimately leading to understanding which customers need the most attention.On the other hand, personas provide a more personalized “character”—one based upon robust qualitative and sometimes quantitative research methodologies. These personas become the center of a user-centric story. The fictional hero, if you will, of a story that organizations can use as a roadmap for envisioning and evaluating what will be a truly motivating customer experience. Real end-users aren’t available throughout the strategic development and design process. However, a persona, through their story, gives them a voice by proxy that can be referred to throughout the experience design process enabling more strategic decision making.

Why should we invest in customer insights to develop personas?

While personas are fictional characters, they are characters developed as a composite of real end-users and insights uncovered during secondary and primary qualitative or quantitative research. Investing in a customer research initiative to develop personas ensures your personas are based in reality. Providing a true representation of the goals, motivations, nuance and behaviors of end-users to your project team minimizes any unconscious bias or assumed perceptions within the team or organization.

What’s the ROI of persona research?

Simply put, the ROI is time—and therefore money. Personas ensure project teams are grounded in an understanding of the user whose problem they’re solving. They’re better able to avoid rabbit holes and making assumptions by developing solutions based on where their end users currently are—resulting in more efficient problem solving and often, less rework.

Finally, if your organization likes concrete numbers, here’s a big one.

Forrester reports a web redesign using personas can provide a return of up to four times over a site design not using personas.1 I believe the same, if not greater, return can be expected using personas to develop any customer experience solution.

1. https://www.forrester.com/report/The+ROI+Of+Personas/-/E-RES55359

How to Manage the Human Element of Enterprise Activation

People are not cogs

In an earlier post, we offered five ways to activate the enterprise. It covered approaches on what you need to do, but it didn’t address the key factor in whether those activities would ultimately succeed: people. Initiating change in any organization is never purely academic. Organizations are a collection of people. And people are beholden to self-interest and influenced by emotion. That’s not a bug, it’s a feature. Done with care, you can harness the power of that self-interest and emotion, and transform uncertainty surrounding any major change into commitment and passion, your chance of a successful activation increase exponentially. And, you’ll have created an accelerated path to success.

Start at the top

Enterprise activation is, at its heart, a change management issue. And in most companies, unless you build consensus among senior management prior to asking for commitment from employees, managing change across multiple departments or business units can be akin to herding cats. If employees sense that their managers and leaders aren’t fully committed, or if they sense the change ultimately, “won’t take,” they may never actually undertake the behaviors asked of them.

Think of the early stages of consensus building among senior leadership as the beta test for activation across the enterprise as a whole. If there is resistance or hesitation at the top, it will only accelerate or amplify when the activation is rolled out to the rest of the organization.

Communicate the context

Activation is rarely embraced quickly or positively when delivered as an edict. Employees need and deserve context. Far too often, companies send out new-sheriff-in-town style memos outlining what is changing with little background on why, what the implications are and how those changes fit into the long-term vision for success. One approach might be to follow a simple narrative outline that covers:

1. What factors (external or internal) prompted the need or desire for change
2. How leadership arrived at the approach to address that need
3. What the impending change looks like and the time frame within which they will be implemented
4. What the expected positive outcomes of those changes are
5. What mechanisms for providing feedback or asking questions are available and how inquiries or suggestions will be considered by management

Enhance communications with metaphors, analogies, examples and stories

Stories are one of the most powerful tools for engaging any audience. And the more complicated the plan being presented, the more powerful a strategically wielded anecdote, metaphor or analogy can be. Metaphors and analogies can help people begin to understand and evaluate the implications any proposed change in a framework abstracted from its direct impact on their position in the firm. In other words, stories are a highly relatable way to express what the changes mean, not simply what the changes are.

Address any elephants in the room directly

An “elephant,” in most enterprise settings, would be any aspect of the impending activation plan that will affect what employees earn or the amount of time it takes them to earn it. Even if that means something as seemingly ”fun” as a kickoff party planned for what would normally be a non-work Saturday. Or, if it means something more dramatic, like people would have revised job descriptions. In any case, it pays to anticipate those impacts and address them upfront.

Repeat, repeat, repeat (and vary the medium of communication)

It’s one thing for an idea to be heard. It’s quite another for an idea to be understood. That’s certainly not a new concept for anyone charged with marketing or communications, but all too often companies expect that once a program has been communicated, everyone should consider themselves “informed.” But garnering change from any population, corporate or otherwise, requires repetition. A rule of thumb long held in media and advertising is that the minimum level of impressions needed to become top of mind, let alone trusted, is five. The dynamic holds for internal campaigns as well. Further, since we are all getting much better at tuning out intrusive messaging, it helps to provide those impressions over a variety of media.

Simply think of your own experience. Imagine you’ve seen the same email header twice. The third time it arrives atop an incoming message, you’ll likely not even notice it’s there. But if the third impression arrives on a mug, emblazoned with the theme line for your internal activation campaign—third hit noticed. Follow that with a mention of support for the program in the CEO’s monthly town hall address. Noticed. What about creating a rap song performed by upper management? No. Never do that. But you get the idea. The more and different ways you can reinforce the program with employees, the smoother and faster the adoption.

Ultimately, speak to the enterprise like you would want to be spoken to individually

Regardless of what industry you’re in, or the size of the company, human nature remains constant. Every employee or stakeholder wants first to know what’s in it for them and what about their day-to-day work life will change and what it all means. So, for any enterprise activation program to be successful, you have to address those issues.

Three Proven Paths to Disruptive Innovation

Disruption isn’t magic

The popular mythology is that nobody sees disruption coming. Disruptive businesses, like unicorns, appear as if by magic, to upend the status quo. And the disruptors are mad wizards who somehow see the future no one else could have. But the truth is, most disruptors follow a very linear thought process and those companies being disrupted are more victims of their current successes than they are caught off guard.

Even the best companies are vulnerable

More than half of the companies listed in the Fortune 500 in 2000 have since been removed—dethroned by a more technologically savvy disruptor. And, it is predicted, that between now and 2025, half again will have succumb to a similar fate.In his seminal work, “The Innovator's’ Dilemma.” Harvard professor Clayton Christensen lays out the basic development trajectory of disruptive innovation and provides a myriad of logical reasons why successful companies fail to act when smaller, even less-well-funded, disruptors enter the scene.

It’s an excellent text with innumerable examples that most will read with exquisite hindsight and shake their heads at what seem today to have been myopic management decisions. But how do you know you’re not following the same path today in your own industry—great at the game you’re playing, but not realizing the game itself is about to change?

1. Launch tomorrow’s market offering, today

Is your target segment a growing or shrinking demographic? Are there macroeconomic trends that will have any major impact on the size of your current markets? Are there any shifting  generational or social norms that could affect perceptions of your brand or your offering?Choosing which trends might materially affect your markets one day is an art form, to be sure. But the idea here is to scour secondary research sources and glean from that data the most relevant bits to help model a snapshot of your market at some specific point in the future—two years, five years—when you believe those trends will converge to a tipping point for the current market.

For a relevant example, we can look at the hospitality industry. In it, there are any number of examples of companies using this type of analysis to shift their offering to meet future demand. Case in point, while Generation X may currently represent the largest segment of business travelers, many of the leading hoteliers have focused their innovation teams on changing their room and common space designs to address the impending market dominance of Millennial business travelers.

Watch a Gen-X-aged business traveller enter a recently renovated room at a Marriott and you’ll likely see them looking all around the room for a desk that isn’t there. Watch a Millennial business traveller enter the same room and they’ll sit on the bed and pull out their laptop without a second glance for a desk they’d likely never use anyway. Common areas are being similarly transformed. Where once hotels created separate lobby, work and dining areas with nationally recognized eateries, current renovations are delivering integrated common rooms and unique culinary options derived from local influences.

2. Expose your industry’s deepest darkest secret

In most industries, there’s some fact about the standard business model that no one really wants to talk about because, though it may be inconvenient for the customer, it drives significant revenue. Take for example the insurance industry. Everyone in the industry would tell you that it is, by necessity, a relationship business. To get insured properly, you need a guy or gal in the business who knows the business, because every customer is unique, getting the best premium is math intensive, and the process is too arcane for the issuance of a policy to happen any other way.On top of that, once you were insured, having a claim processed and (hopefully) paid was often a weeks-long undertaking.

Customer complaints about that extended time span were met with explanations that processing a claim required multiple checks and balances and a great deal of necessary paperwork.Though, as proven by industry upstart Lemonade, it is likely more accurate to say the deepest darkest secret of the insurance industry was that most customers fall into common risk profiles, adding obfuscation and complexity in how premiums are calculated reduces price comparison opportunities, and that claim delays were more about earning a greater amount of interest on cash reserves than it was about extensive investigations.

Lemonade began providing renters and home insurance for urban dwellers through an A.I. fueled mobile app, in a process that takes less than two minutes. And claims processing and payment? Three minutes. Further, instead of paying annually, Lemonade customers can “subscribe” to their coverage on a monthly basis.The innovation here doesn’t appear to have stemmed from a single a-ha moment. It seems the product of a systematic, cumulative uncovering of all of the ways the insurance industry intentionally complicates the offering to protect existing revenue streams.

3. Create a future where your industry’s greatest strength is a weakness

This has demonstrably been the most fruitful path to success for disruptive businesses in the past decade. Just look at Alibaba, Uber or AirBnB. Prior to Alibaba, retailers professed their strength by touting the depth and scale of their inventory. Nothing could compare to, “everything, in stock!” Alibaba became the largest retailer in the world expressly by creating a business model where they carry no inventory. Love them or hate them, the same approach was quite successfully taken by Uber.

They have grown to be the world’s largest taxi company, expanding rapidly in more than 80 countries and they own no taxis. AirBnb? The fastest growing hotelier in the world because they explicitly own no property. Ironically, the most current example of this might be Amazon’s recent push to open physical storefronts—differentiating themselves from increasing online retail competition by creating enhanced opportunities for more personal interactions as well as faster local deliveries.

Innovators understand that if you can envision a way to threaten the value of an industry’s greatest asset, the industry will instinctively apply resources to protect that asset, temporarily giving the innovator plenty of runway upon which to gather momentum.

Pick a path. Now act like, or fund, a startup

Technology, machine learning and automation is lowering barriers to entry in every industry. Emerging generations expect better solutions. Disruption is imminent. If you’re charged with improving the long-term competitiveness of your business you have two main choices. Disrupt, or be disrupted. The point here, is that it doesn’t take a massive spark of genius to spot the next disruptive opportunity. It only takes commitment to taking the path.

4 Ways Artificial Intelligence Can Improve Your User Experience

Intro

News flash… the digital space is ever evolving. No place is this more apparent than the onslaught of artificial intelligence implementations that are quickly (and subtly) injecting themselves into our everyday lives. When Siri was introduced on the iPhone back in 2011, AI was looked at as a curiosity. But as these services have become more common (I’m looking at you Alexa and Google Assistant), and our interactions with them more comfortable, businesses are looking at the benefits of these tools in smoothing customer interactions. If you haven’t already done so, now is the time to consider four areas where AI implementations can improve user experience.

Search

Some of the earliest implementations of AI were applied to search, and this makes a lot of sense. Search, even in its simplest incarnations, is an algorithmic exercise. In basic keyword search, for example, when I type the word “dog”, an algorithm stores that string (a collection of characters), evaluates the available dataset for the same string, and returns results that contain the string, in this instance, “dog.” As search has matured over the decades, more and more parameters have been combined with that basic keyword approach to the point where a Google search is evaluating a single word against over 200 parameters.

Search is the most obvious place to use AI to augment your current digital offerings both internally and externally. Brand-name services such as Watson from IBM, offer capabilities that can augment your pre-existing keyword search with additional components such as natural language recognition and semantic relationships that can make entering search criteria simpler and the returned results more relevant.

Chat

When Facebook rolled out chatbot functionality to its messaging services a couple years ago, the ground shifted beneath the customer service industry. Although chat-based AI hasn’t completely replaced a responsive human customer service representative, the implementations of these experiences are expanding. Most likely, you’re already interacting with digital virtual assistants if you’re engaging in chat with a major telecom service such as Comcast or AT&T. (In fact, I was just texting with “Samuel” from AT&T this week).

Chatbots can be used in two valuable ways: assisting potential new customers in converting to a purchase, or helping existing customers with problems that may arise when they're using a good or service. Even the exercise in developing the personality of the bot, the script it will use and the services it will address can help your company get to a better understanding of the questions and concerns your new and existing customers may experience with your products and your brand.

One caveat regarding chat: the successful implementation of chatbots also means being structured in such a way that the assistance the bot provides is backed up by great real-world service. If your bot is appropriately funneling leads to your sales team, it means nothing if those leads aren't acted upon by a representative from your firm.

Organization

Companies small, medium and large are constantly struggling with the proper organization and classification of their content. In fact, errant content tagging is often one of the more common issues we hear about when we're onboarding new clients. Returning the proper content when called is crucial to delivering a quality user experience.

Content classification issues often fall into three categories: none, all and legacy. “Nones” are companies that have never had a need to segment their content, so it's not labeled at all. “All's" are just the opposite - their content is often over-tagged so every piece of content is returned on every piece. “Legacy” companies have content that has been around a while and have migrated systems a couple of times. Their content is tagged, but it's loaded with outdated tags that are now irrelevant to the new aim of the business.

Regardless of which category your business falls into, there is good news: services exist and are emerging in the marketplace that capitalize on machine learning to help you better organize existing and new pools of content - for video, images and text. Machine learning is exactly what it sounds like: using a small pool of starter criteria, you train a program to accurately read and identify content. The program will get better at identifying the inputs over time and will begin to return better and better results.

Sorting thousands or articles and images is a daunting task for humans that is far better for machines. Companies like Clarifai use neural networks to make it easier for companies to automatically classify and tag custom libraries of imagery and video. AWS offers a variety of tools to recognize, evaluate and categorize a wide array of content, from the spoken word to long-form text.

Authoring

When the Associated Press announced in early 2015 that they were beginning to use bots to author some categories of articles, it rocked the world of journalism and confirmed the worst nightmares of countless publishers had come true… the robots were here. In the ensuing three years since that announcement, more and more work has been done in the field of content authoring, across a wide array of media—writing, music, and painting are a few examples.

Content authoring is in some ways a more complex endeavor than the other three categories listed on this page, but it only takes a little imagination to see a world in which certain types of media are generated, deployed, measured and reported on by machines, which then evolve those pieces over time to create more and more targeted variants. In fact, our own Justin Daab pointed to the evolving perception of “creative” work last summer.

It’s time to embrace AI

The tech has matured to the point where it’s time to be thinking seriously about incorporating AI in your digital ecosystem. Adding just one or two of the features mentioned above can greatly improve the user experience of the products and services you offer. More importantly, it puts you and your teammates in the mindset of thinking more broadly about what’s possible, and sets you up for a future where these features aren’t simply add-ons… they’re table-stakes.

3 Ways 2018 Will Change UX Design Forever

The simplest metaphor for the next wave of UX design is air.It’s invisible. It’s everywhere. It conforms to whatever space in which it resides. With the emergence and adoption of natural language/voice interfaces, expanded IOT offerings and machine learning/AI, UX design is poised to adopt those same qualities in 2018.

Invisibility

With the advent of the Amazon Echo, Google Home, and to a lesser extent Siri, the past year finally saw mass adoption of voice-based interfaces. Powered by cloud-based natural language processing, semantic search and a pinch of machine learning, more than 30 million of these devices found residence in American homes in the fourth quarter of 2017.What could be simpler than an invisible interface? Well, for consumers, maybe, but not necessarily for content providers or UX designers. Moving from a presentation of information to a fluid conversation requires an entirely new mode of thinking, not to mention tagging and syndicating.Thankfully, to get our collective heads fully engaged in the movement, Amazon has an easy to follow guide to creating an Alexa-friendly voice-based UX, so does Google, with their guide, “Extending the Google Assistant,” which includes a Design Principles and Methodology for conversation design.

Ubiquity

Uncovering information on the internet used to be attached to what we like to call destination behaviors—finding something required having some destination in mind: a URL typed into a browser address bar or a specific app launched on a mobile device. But with voice assistance, you command the information to be delivered to you. It doesn’t matter if you are sitting on the couch, chopping carrots in the kitchen, or singing in the shower. Ultimately, thanks to your smart speaker, you’re commanding information to make you its destination, pulling answers literally out of thin air.It’s part of a larger trend of the breakdown of separation between data and the environment. Information is becoming an overlay to our everyday experience. Today, it’s a kitchen conversation with a helpful but disembodied Alexa as you slice through a newfound recipe.

Tomorrow, it will be a semi-transparent layer of meta-data superimposed over every object in your view through a pair of AR glasses. As UX designers, we will all need to understand that we will less frequently be creating a self-contained experience than crafting an enhancement to more layered, contextually driven data presentations occurring whenever, wherever users happen to be. Which means how we present those layers need to conform to the moment of delivery. Which brings us to wave number three...

Conformability

Legend has it, that in or around 2002, Jeff Bezos wrote a memo that famously commanded all development within Amazon be built as a service layer API that could be called upon by any other service or process within the company datasphere. For example, if HR wanted a new tool to search the database of employees, that tool would primarily be a fully developed API that could accept requests and return data usable by any other tool that may, at some point in the future, also need access to employee information. In other words, they made it possible for any data source, and the rules to access that data, to be conformable to any future need.UX designers need to begin to think of journeys as conformable. It’s not enough to assume a user will enter or complete a purchasing journey on some form of responsive web experience. They may be buying through an Amazon Echo or Google Home.

Or, they may be telling their voice-assistant driven AR goggles that they want to buy the same pants as a person in their view is wearing, while finding out what other colors are available in that style. The experience you design for that customer is the conversation your ecommerce system is having with the cloud-based virtual assistant that is acting as concierge at that moment.We need to increase the amount of data abstraction (service layers, APIs, etc.) that we build into our data models and systems today, to prepare, like Jeff Bezos did a decade ago, for any new modes of interaction that may be heading our way.

We’re all taking the road never traveled.

In a world without sign posts, it’s seems expedient to claim we cannot design for a future we can’t fully or clearly see. But the truth is, if we can once again channel the spirit of Jeff Bezos, you may not be able to plan for a single future, but you can better position yourself for all possible futures. As we all undertake our digital transformation, brand experience, customer experience and enterprise activation projects this year, there’s nothing preventing baking in the foundations of tomorrow’s interfaces, or lack thereof, today.

Math for Marketers: How to Evaluate Growth Opportunities

In the more than 30 years this agency has existed, we’ve never had a client come to us and reveal that they had unlimited time and unlimited funds to apply to their growth challenges. When developing a strategic roadmap, each and every one had to weigh the opportunities and opportunity costs of every decision and prioritize those efforts and investments that will yield the greatest net returns to the business.As one undergoes the strategic planning process, understanding what potential opportunity may result from any strategic priority will undoubtedly require a mix of assumption and intuition, and, more importantly, basic quantitative analysis. In this post, we wanted to outline a couple of basic but powerful formulas and processes to assist in some of the most common areas of inquiry: market sizing and budget prioritization. In other words, “how big is the opportunity, overall?” and, “How should budget dollars be allocated to ensure maximum average returns?”

Part 1—How to calculate potential market size.

Estimating the size of any new market is a mixture of art (the assumptions are you are making) and science (the hard evidence you have to quantify the validity of each assumption). Now, there are plenty of folks willing to stake their reputations and their businesses on a purely art-based approach—you could say relying on emotional confidence versus statistical confidence—but the following formulas deliver far more reliable results if you backup your input variables with actual research data. So, what are the variables that go into your formula?

Total population (P): This simply corresponds to the total population in your trading area. That could be local, regional, national or global.N = Total Geographical Population

Percentage of Target Customers (PTC): The percentage of the total population that fits the target segments most likely to be an active customer.

Average Transaction Quantity (Q): The average quantity purchased by a single user at a time.

Frequency of purchase (F): How many times the product or service is purchased in the most relevant period of time (annually/quarterly, etc.).

Price of Product (P): What the expected revenue generated is per transaction.

Market Size (MS) Formula = (get ready, this is the math part) MS = P * PTC * F * P

An example: Since the advent of bike share programs around the country, articles keep popping up about the need for single-use or limited-use helmets. So, let’s say you’ve just invented a new recyclable engineered paper bicycle helmet for bike share usage. And you want to launch it in a test market, like Chicago. In 2017, Divvy claimed more than 37,000 members, so in this example, we can use that for P.

P=37,000

But all 37,000 will not be in the market for our new helmet. How many will be? This is where it would behoove you do some actual quantitative research (the science) among Divvy members to determine levels of need and interest. Let's say we conducted a quantitative online survey with a representative sample (300) Divvy members that indicated 50% of them already own their own traditional bike helmets. Of the remaining 50%, half again of those will never wear a helmet. So, we are left with 25% of the original population that do not own a helmet and are not opposed to it. But only half of those (the remaining 12.5%) said they would be interested in purchasing your helmet. So, in the end:

PTC=.125 (or 12.5%)

Each consumer would generally only purchase one helmet at a time, so:

Q=1

But the helmets only last about 4 weeks before the paper breaks down and most Divvy members only bike 3.5 months out of the year. Discounting for the fact that most people will not be diligent about replacing the helmets in a timely fashion, let's put the frequency of purchase at 2.5 per year.

F=2.5

And, finally, you've designed the helmet to sell for about $10, so:

P=10

So, let’s plug those into the formula!MS = P * PTC * F * P

Market size (MS) = 37,000 * .125 * 1 * 2.5 * 10

Or…

MS= $115,625

After going through those calculations, you realize there’s a reason the idea of single-use helmets comes up every year, yet no one is developing single-use helmets.

Part 2— How to prioritize marketing budgets for growth.

Every marketer faces similar challenges when it comes to budget prioritization. It always comes down to determining against which products or services do you spend what portion of the budget. And always, the calculus centers on ultimately realizing the greatest returns for every dollar spent. Surprisingly, even though this is an ongoing concern, many marketers rely more on gut intuition than quantitative reasoning.To add a little more quantitative reasoning into the mix, we’ll introduce you to another simple calculation (courtesy of McKinsey & Co), called the customer growth index (CGI). It’s an interesting way to understand the correlation between initial consideration and growth potential.

Simply put, to arrive at the CGI, you take the percent of time your brand is a member of your customers’ initial consideration set, then divide that by that your brand’s current market share, and finally, multiply that result by 100 to create an index. The closer to 100, the greater the brand’s ability to keep up with the pace of growth in the market as a whole.

CGI= %consideration * %marketshare * 100

McKinsey uses this for looking at overall brand, but we think it can be a useful tool if you know that same inputs with in each of your product categories. Let’s say Nike was evaluating marketing budget allocations for shoes, apparel and tech wearables. By calculating the Nike CGI for each product category, they would have a better indication of the brand health in each, and which are more or less likely to experience growth for each marketing dollar applied. It’s not the end all determination of which categories should get what budgets, but it’s a strong signal of momentum that should be taken into consideration.

Lasting success is calculated.

Marketing is always a blend of art and science. No matter what the size the market opportunity or propensity for growth, we all need to deliver memorable, motivational experiences for our customers. In the end, these formulas can help simply provide an additional objective sense of perspective in the planning process.

Five Ways to Activate the Enterprise in 2018

It’s not surprising that for many marketers, enterprise activation can be a nebulous term. And frankly, the idea potentially encompasses so many functions across a company—from operations to customers service to fulfillment, that even deciding which activation points to focus on can be a daunting task. Regardless of the specifics, what does the general term mean anyway? Enterprise activation is about creating a shared vision for success then aligning and coordinating the internal departments, resources and processes needed to deliver exceptional brand, user or customer experiences.

Whew. Encompassing, indeed. And to complicate things further, choosing and prioritizing the messages and tactics needed to pull that off can differ wildly, company to company. But no matter what the size or type of enterprise you’re seeking to activate, here’s a list of five basic activation areas every company should undertake.

1. Craft a vision statement

A vision statement is an essential tool for promoting understanding throughout any organization. The most successful of those should define an aspirational state of what the enterprise would like to achieve or accomplish and provide a clear guide for evaluating business choices today, as well as evaluating and prioritizing future plans of action.

An example: Amazon’s vision statement: “Our vision is to be earth's most customer-centric company; to build a place where people can come to find and discover anything they might want to buy online.” Its bold language leaves them focused on their purpose, yet open to innovative arrangements like affiliate marketing and contract fulfillment, and unique lines of business like Amazon Web Services (AWS). And, undoubtedly, it seems to be working for them.

2. Prioritize an enterprise-wide goal

If you have a viable vision statement, now you need to define a measurable goal that stakeholders throughout the business can focus on to guide their individual efforts. Whether it’s a customer related goal (increased awareness levels, positive net promoter score, improved conversions, etc.), a specific business goal (revenue targets, improved operating margin, broad market share, etc.), or operational (zero waste to landfill, 100% renewable energy usage, etc.), the act of choosing “the big one” for the enterprise to rally around can be instrumental in activating the enterprise. There is always opportunity to be found in getting everyone in the company to pull on the same rope. But you’ll improve greatly your chances of making it happen when you define what the rope looks like.

3. Define and measure your KPIs

To extend our rope metaphor, your key performance indicators (KPIs) tell everyone just how far they’ve moved whatever goal is on the business end of that rope. It’s not always possible to choose a KPI that is a direct measure of progress against the goal. But there is always some viable proxy. For example, if you don’t have a budget to conduct formal pre/post campaign awareness studies, you could examine your web analytics for any changes in the frequency of unique visitors. The main point is that you choose a KPI that is sufficiently available and transparent to be communicated throughout the company in as close to real time as possible, so that stakeholders throughout the enterprise feel their actions are directly influential to its movement and can use the measure of it to evaluate their effective progress against the enterprise-wide goal.

4. Cross-departmental process evaluation

Potentially the most resource-intensive and complex points in this post, cross-departmental process evaluation is about cataloging and auditing those company processes that have the greatest impact on your chosen goals and KPIs. The purpose is to uncover where there may be processes that are bottlenecks to reduce, or accelerative behaviors that should be promoted throughout the enterprise. An example would be if your main goal is to increase revenues, and the KPI for measuring progress is converted web leads. Upon examining the cross-departmental processes, you find the web site is delivering an adequate level of form fills and warm leads, but processes or systems for distribution of and follow up on those leads within the sales department is inordinately delayed. That makes it very clear you should focus remedial efforts on shortening the time between lead acquisition and first follow-up to improve efficiencies and maximize conversions.

5. Employee communications & campaigns

At the foundation of activation is understanding. You’ve crafted a vision statement and defined all the variables that go into achieving and measuring the impact of them. But enterprise activation is never as simple as a “build it and they will come” kind of program. Activating any enterprise requires communications. In practice, that may manifest as something as simple as a t-shirt or mug with the vision statement silkscreened on it, or as complex as creating digital signage in the company elevators, or coding a bespoke social network for use inside the company. There’s no simple, best-practices solution for employee communications and campaigns. How much of an effort this is correlates directly with the scale and global footprint of the enterprise.

Go forth and activate

If branding and marketing is about talking the talk, enterprise activation is about making sure the business is truly walking the walk.

How to Develop an Innovation Strategy

The myth in popular culture is that innovation is the byproduct of a random spark of inspiration. Lightning strikes. Someone has a eureka moment. The world is forever changed. Sounds quite easy, if mostly unachievable by mere mortals.The truth is that innovation is more often the result of a resolute commitment of time and resources—and a solid innovation process. Committing the resources is simply a matter of availability and will. Creating a strategy can be more complicated. There are, however, some basic questions that every company should ask and answer to begin solidifying a viable innovation strategy that the entire company can rally around.

What would change the value equation of our industry and our customers?

This is an intentionally broad question, but it is at the root of any successful innovation strategy. For a business, innovation isn’t about change for change’s sake, it’s about taking steps today to secure the greatest share of revenues and profits in the future. And the first step gaining a glimpse of what that future looks like is to imagine what the market would look like if you, through your product development efforts, could radically alter the cost structures for the business or its customers, or both. What would the market look like if you could radically alter the product lifespan? What if you radically changed the scale of your solution? Delivery times?It’s not that you need to answer exactly how you will accomplish this, for now. But rather, you need to decide, as a company, what of those changes could have the greatest impact on the landscape of your industry. Further, whatever you choose to focus on needs to be something you believe is at least somewhat achievable with the application of time and resources.

How could our business model be disrupted?

One of the best ways to start answering this question is to look at your own and the market leader’s greatest strengths and start to ask how a new entrant might turn that into a weakness. 10 years ago, few would have predicted that the world’s largest taxi company (Uber) would own no taxis, or that the world’s largest retailer (Alibaba) would hold no inventory, or that the world’s fastest growing hotelier wouldn’t own or manage a single room (Airbnb). But those companies looked at the market leader’s greatest strength and made it a weakness.

What parts of today’s business are we willing to sacrifice for tomorrow’s innovation?

In his seminal work, “The Innovator’s Dilemma”, Harvard Business School professor, Clayton Christensen, outlines the ways highly successful companies end up ceding markets to disruptors they could have easily stopped in their tracks had the company been willing to suffer through the opportunity costs of innovation. The point being, sometimes you innovate and sometimes you have innovation thrust upon you. And it pays to understand in advance how the business could function, thrive or survive with various lines of business or product lines removed.

What capital are we willing to invest/risk?

It should come as no surprise, but innovation is rarely inexpensive. In fact, it’s usually costly, even comparatively wasteful by normal business investment standards. Where investments in the day-to-day operations are expected to produce standard linear returns, investments in innovation should be thought of more like a venture capital model—most of them will return nothing, but the home run ideas deliver 10X returns. It’s not math most companies are used to or comfortable with. But failures are as much or more a part of fruitful innovation programs as the successes. A great example of this mentality is Apple. It is widely reported that Apple kills off far more of its R&D projects than it ever sends to market. And that willingness to experiment has obviously served them well.

If it ain’t broke, why fix it?

It’s tempting to think that wildly successful businesses are somehow immune to radical disruption, but none truly are. Traditional relationship businesses could be easily overwhelmed by conversational AI. Delivery, distribution and logistics are in the crosshairs of self-driving vehicles. Accounting, auditing and title insurance businesses could suddenly find themselves anachronistic leftovers by blockchain technology. Just as traditional media planning and strategy has succumbed to programmatic models, even formerly technology-resistant creative professions will find themselves pressured by bots that can literally start running the infinite monkey’s algorithm until they hit upon the marketing equivalent of Shakespeare. This is not a gloom and doom prophecy. It’s the call of opportunity resulting from new disruptive technologies. We just have to keep open minds.

5 Things Every CMO Should Understand About AR Experience Design

As we’ve watched the slow uptake in VR adoption, it would be simple to dismiss AR as having similar challenges ahead. But as we mentioned in a past article, the installed base AR-capable hardware has already reached a critical mass of users the moment iOS 11 was released. Every mobile handset from the iPhone 6s up is capable run apps based on Apple’s ARKit. Google has followed suit with its similarly capable ARCore for Android devices. So, any marketer looking to dip a toe into the AR waters already has billions of active, waiting AR-ready consumers, worldwide. But as with any burgeoning technology, creating a truly valuable and engaging customer experience that forwards your business goals requires maintaining perspective in what really makes its use successful. Here are a few things to consider, so that we all avoid launching the next “stache.”

1) It’s about experiences, not technology

Every potential project should be evaluated in terms of how it enhances the customer experience and/or strengthens the relationship with the customer. This idea seems basic, but when new technology appears, even veteran marketers looking for any possible competitive advantage, can get swept up in the fervor of novelty at the expense of strategy. Great brands have proven, time and time again, that being first is far less valuable than being thoughtfully great.

2) It’s about time

A well implemented AR experience can offer incredible time savings for consumers. IKEA has given us a beautiful example of this. The IKEA Place app lets consumers virtually place any piece of IKEA furniture right in their own home. They can position it, rotate it and swap it out for something else in moments. No more trodding to the store for a better view, or carting something back to the store because it didn’t feel right in the space once it was in the home.Images: ©IKEA

3) It’s about measurement

Permanently emblazoned on our office walls is the phrase, “It ain’t creative unless it sells.” A great AR experience should be created and considered in terms of whether it will result in a measureable impact on whatever KPIs are driving the success of your product, brand or business. Will it drive sales? Will it drive users to connect with more content? Will it increase users’ advocacy and sharing of your brand? Will it reinforce your competitive position in the marketplace? Do you have the infrastructure and personnel in place to review and analyze the data generated? Even the most basic of AR projects require substantial resources to achieve, so make sure you have the measurement analytics tools and processes in place to understand if you are maximizing your return on investment. Both Apple and Google provide in-app analytics tools that can aid in understanding user behaviors. So, what should you measure?Primary measurements may cover basic use and engagement:Installs – how many times your app is installed?

Opens – is it being used after the first install? How, when and where is it being activated?

Purchases – are purchases being made with the app or does it push visits to a transaction outside of the app itself?

Content Views – are users exploring deeply within the content provided?

Shares or Invites – if you are providing means of sharing or connecting with social media accounts, how often is that feature activated?

Custom Events –  are specific behaviors that drive revenue or leads being accounted for?

Complementary measurements may track connections to the rest of your digital ecosystem:

Google analytics - are you properly attributing and tracking online sessions for users who originate from the app?

Leads generated - how many app users translate into active leads?

Social Mentions and Shares - whether through the app or organically, how often, by whom and with whom is the app mentioned or shared?

4) It’s about human nature

Technology evolves at an increasingly rapid pace. Human nature, however, does not. When creating or evaluating any potential AR experience, ask what basic human need it addresses (or leverages).

Does the experience foster or improve a sense of community or belonging - either within your specific target segment or the greater population?

Does the experience confer status upon the user - perhaps through either gamification, social rankings, early-adopter or exclusivity-based bragging rights?

Does its use instill confidence - either through confirmation or positive feedback?Ultimately, AR experiences have the ability to connect with customers on a level that supports at least a few tiers of Maslow’s hierarchy of needs as well as your business needs. And those marketers who can deliver on that potential will always outcompete their more traditional competitors.

5) It’s never been easier to innovate

Historically, as digital technologies and media have emerged, the tools used to create the content have lagged. In the case of AR, however, elegant development tools like ARKit and ARCore that take care of the bulk of the mathematical heavy lifting and foundational coding have made it easier than ever to close the gap between innovation and execution.

In short: the dog already needs to dance really well

Unlike those early years of the Web where people were entertained for hours by blue text links and static webcam images of a Cambridge University coffee pot, thanks to early successes like Pokemon Go and SnapChat filters, consumers’ expectations of AR are already quite high. Marketers need to understand that AR experiences exist as integrated parts of their consumers’ lives, not aside from it.