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Social Media Engagement: 2017’s Surprising Best And Worst Performers

Michael Brenner

Spoiler alert: Facebook is not the most engaging social media channel! Despite its sheer numbers of active users and maturity, this social media network may no longer be the top platform to focus on for your social media marketing strategies.

You can probably guess which platform ranks as the most potent channel for engagement. Since its inception as a photo-sharing app in 2010, Instagram has risen to become one of the largest social media networks with well over 500 million active monthly users.

According to a new report, Instagram isn’t just growing. It may be the most powerful social media channel available to businesses on the internet.

There are a few other surprises, such as Twitter’s waning significance and LinkedIn’s strength in certain industries.

Are you focusing your efforts on the right social media channels for your brand? Even more crucial, as we marketers strive to work smarter with the shift towards agile methods, are we wasting our time on others?

How social media sites add up – new digital marketing analysis report

This year’s official analysis of the digital marketing industry by TrackMaven – a comprehensive look at more than 700 leading businesses across 13 industries, found that Instagram isn’t simply the most engaging. This network crushes the other social media platforms when it comes to social media engagement in every industry except real estate.

Image source: trackmaven.com

And the least engaging? Of Facebook, Twitter, Instagram, LinkedIn, and Pinterest, our old friend Twitter inspires the least engagement across the board. As with the Instagram phenomena, where the site was wildly engaging when compared to other networks, the report found that Twitter looks pallid next to all of its brighter, more engaging social network colleagues.

Again, with one exception. Construction equipment – which received, on average, 21.26 interactions per post per 1,000 followers. When it comes to the world of dump trucks, cranes and plow trucks, marketers get about the same amount of engagement across channels.

What’s even more surprising is that Facebook isn’t getting that much engagement, at least not enough to warrant its popularity among marketers. Still, today:

  • 55% of marketers say Facebook is their most important platform for marketing – with the second in line being LinkedIn, favored by 18% of marketers
  • 67% of marketers plan on increasing their activity on Facebook in 2017

Are we way off when it comes to our social media strategies? Should we be working on filling our photography skills gap for our brand’s Instagram account?

Industry does matter

Before you sign up for an evening photography class, what industry you are marketing for does make a difference. For example, in the healthcare industry, as well as in food services and accommodations, Facebook is still incredibly useful for engagement.

This makes sense – Facebook is great for restaurants and hotels who need a channel to regularly post updates, specials, and news about their location that locals would be interested in. Facebook also comes with the ability to let customers check in, often in exchange for deals.

This is like getting people to wear your brand’s t-shirt. They become a walking ad for your business and feel pretty good about it because they get something out of the deal as well.

Appealing to all demographics, including older adults, Facebook is ideal for health awareness campaigns and posting announcements about health classes, services, and general health tips. Also, this is an industry that tends to be very community-driven, just like your local pizzeria and coffee shop, which meshes with Facebook’s local business appeal.

Anne Arundel’s Medical Center has been a fantastic example of an engaging Facebook presence since their Facebook contest to raise awareness for men’s health in 2015, encouraging users to share their best “stachie” (mustache) photos. The company also does a great job tackling local issues that people are interested in, like addiction recovery and infant health. This type of marketing really fits with Facebook and wouldn’t work as well with a platform like Instagram.

Image source: Facebook

Real estate, on the other hand, gets the most engagement with LinkedIn – the network known to appeal the most to professionals. This industry also does well with the visual sites, Pinterest and Instagram, which offer agents the chance to showcase their properties.

For higher education, which is marketing towards a younger audience, Instagram is a powerful engagement channel. Instagram is known to be extremely popular with millennials. In 2016, just under 60% of internet users between the ages of 18 and 29 were on Instagram – only 8% of users aged 65 and over had accounts.

Perhaps this has something to do with the popularity of Instagram with consumer goods companies. The power of Instagram for the finance and insurance industry may be a shock to marketers. This idea may sum up industry sentiment:

“Instagram probably isn’t going to move the needle for the majority of financial institutions. It could be a gigantic waste of time for many banks and credit unions.”

Well, it’s moving the needle. The visual, personal feel of Instagram appears to have an impact on customers. Financial services company, US Bank is a great Instagram example. It uses the platform to tell the story of their brand values, through regular posts about community involvement using #communitypossible.

 

 

Image source: Instagram

Engagement does matter

Social media engagement isn’t everything. You may have great activity on your brand’s social media channels, but this isn’t necessarily going to directly translate into sales. What it will do is bring more attention to your brand and help to build loyalty and trust. 53% of Americans who follow brands are likely to be loyal to them. It also helps to make your brand feel more human, which eases those conversion rates. People are more interested in doing business with other humans.

And it will drive traffic to your website.

Image source: socialbakers.com

Research done by Social Bakers found a direct correlation between activity in response to social media posts and website page views.

Getting the most out of your engagement

There’s a lot more to marketing than social media engagement, but marketers should really take a look at how they are using social media to engage in order to get the most out of their efforts. Is it worth spending as much time and resources on Facebook and Twitter?

Are you measuring how your engagement changes on each site over time? A good question to ask – and to test: Would you be better off automating more of your interactions with the channels that aren’t getting much engagement?

Or have you already put your eggs in the Instagram basket – if so, are you using this site well to tell your brand’s story? Are you getting the intense response from your audience that your competitors are getting?

The most important insight to take from this report is that social media marketing perhaps is changing faster than we assumed. Sure, digital marketing is a rapidly evolving field, but social…this is an arena where there is so much freedom and flexibility.

With so many new entrants changing the game every few months or so, perhaps there will never be hard-and-fast rules. There’s no best single social network, or most popular, or most effective. It’s just what works, for you, right now. Thank goodness for Fridays and agile marketing.

What do you think? Do you agree with the data?

For more social media marketing strategies, see How To Master Social Media Marketing In 2017.

Image Source: Unsplash.com

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About Michael Brenner

Michael Brenner is a globally-recognized keynote speaker, author of  The Content Formula and the CEO of Marketing Insider GroupHe has worked in leadership positions in sales and marketing for global brands like SAP and Nielsen, as well as for thriving startups. Today, Michael shares his passion on leadership and marketing strategies that deliver customer value and business impact. He is recognized by the Huffington Post as a Top Business Keynote Speaker and   a top  CMO influencer by Forbes.

2017 Is Officially The Year Of The Podcast – Should You Start Talking?

Michael Brenner

Listen. Well, that’s what your target market may be doing right now—listening to an interesting podcast on their smartphone or tablet.

Podcasting is still a small piece of the content marketing pie overall. As of 2015, only half of all Americans even knew what a podcast was. Still, this certainly is a medium to keep an ear on. Podcast consumption is on the rise, with a 23% increase in listening between 2015 and 2016 – and a 71% jump since 2013.

Even though podcasts aren’t new – they’ve been going strong since the early 2000s – they never really took hold until now. Most notably in the past three years, there have been a handful of wildly successful efforts and growing interest with everyone from Buzzfeed to the Wall Street Journal creating audio content of their own. You may even listen to a few great marketing podcasts yourself.

What’s driving audio content?

The trend is being driven by two factors. One is mobile usage. People are listening to podcasts on the go. With mobility, listening to podcasts has suddenly become remarkably convenient, launching this content form into the present day as the original podcasters, like Dave Winer and Christopher Lydon had intended.

Listening is, quite simply, one of the most practical ways to spend the modern phenomena we all experience almost daily: spacious time – waiting at the doctor’s office, sitting in traffic, or going nowhere on the elliptical at the gym. You can daydream, meditate, feel frustrated because you aren’t really getting anything done, or you can listen to the latest Freakonomics episode.

The second is quality. Big brands are already taking advantage of this still nascent evolution in content marketing, with companies like GE, Netflix, and State Farm all investing in high-quality audio content. But they aren’t just dishing out audio and infusing it with promotional material and direct brand messaging, as many brand blogs have done. They’re partnering with creative audio creation companies who know how to tell a story. Setting the bar high from the outset is helping to drive interest in this previously shrugged off marketing medium.

The art of branded podcasts

We’re talking Huxley’s Brave New World and Yours Truly, Johnny Dollar type of fascinating content. “The creative bar for branded podcast is much higher than blogs or other online written and snackable content…I don’t think as many brands are going to be able to make that commitment,” says Shoshana Winter, chief strategy officer for Vizeum.

The major brands who are jumping into podcast marketing are clearly well aware of the ad-weary consumer. They realize they aren’t going to get anywhere with a long commercial. People may watch a minute-long promotion video if it’s good enough, but no one’s going to tune into a half-hour audio episode if it even smells like an ad.

The solution – create audio content that begins with answering the question, what do they want to hear?

Open for Business, a branded podcast for eBay, created by Brooklyn-based audio company, Gimlet Creative, is an excellent example of offering a company’s target audience something that can improve their lives. A podcast about building a business from the ground up is something that seamlessly fits into the interest spectrum of one of eBay’s targets – fledgling entrepreneurs.

image source: huntthetruth.tumblr.com

It’s a little easier to create podcast episodes that listeners will fall in love with if you already have a strong story line as a foundation. Microsoft’s Hunt the Truth was created as a narrative that took place within the universe of the popular Xbox video game, Halo. Designed as part of the marketing campaign for the release of Halo 5, the podcast ended up generating more than 5.5 million listeners in the first two seasons and won a “Best Of” award on iTunes.

Another success story is Shopify Masters, created by Pacific Content for e-commerce software solutions company Shopify. Again, there are zero ads, although the show is in itself artful content marketing. Listeners, aka Shopify’s ideal buyers – those who already have or are in the process of setting up an e-commerce site – can listen to episodes like, ‘The Facebook Video that Turned 5 Million Views Into Over $200,000 in Sales” and “Courting VC and Angel Funding to Scale a Food Startup to 40 Employees.”

What makes a podcast listenable?

While big brands with big budgets have a clear advantage, publishing compelling, worthwhile podcasts is in the hands of content producers big and small. NPR produces some of the most popular podcasts around. Take Planet Money, for example, self-described as “Imagine you could call up a friend and say, ‘Meet me at the bar and tell me what’s going on with the economy.’”

Stuff You Should Know by the website and virtual answer box, HowStuffWorks, is another popular choice among podcast enthusiasts. This podcast was nominated for The Webby Awards as one of the best podcasts of 2016, along with the thought-provoking podcast on the “unnoticed architecture and design that shape our world,” 99% Invisible.

What do these audio shows have in common? They are really interesting, educational, and enjoyable. Now, imagine a financial agency producing something as value-driven and fun to listen to as Planet Money. It is through creating really good content – just as with blogging and video – that attracts an audience, gets people to subscribe, and establishes a business as an industry leader and a trusted ally to target buyers.

Are you ready to start talking?

Marketers today can create quality audio shows with all the software and tools that are available. Without a lot of background knowledge, content can be recorded with basic software like Total Recorder or Audacity, edited in a program like GarageBand, hosted in the cloud with Libsyn, and set to iTunes and other platforms. And you’ll need a microphone.

image: copyblogger

Whether or not a podcast is a smart move depends on a lot of factors.

  • Do you have the time and resources to branch out to audio?
  • Would your audience enjoy podcasts? What style of content would they prefer?
  • Are they already listening to other audio shows by other publishers?
  • Would audio content reach out to more of your target audience, perhaps attracting those who aren’t interested in reading a blog or watching video content, or who simply don’t have time to?

It is, as with your tri-weekly or weekly blog posts, is important to commit to. Setting up an editorial calendar and promoting on social media channels can help to build that subscriber list – and generate some great leads. And as with all content marketing, it will take time, effort, and creativity to craft an excellent show that people look forward to listening to.

But if the podcasting trend keeps moving skyward, developing your podcasting skills now may help your content stand out in the future.

For more on content marketing trends, see The Future Of Content Marketing—3 Predictions You Need To Know.

Image: Pixabay

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About Michael Brenner

Michael Brenner is a globally-recognized keynote speaker, author of  The Content Formula and the CEO of Marketing Insider GroupHe has worked in leadership positions in sales and marketing for global brands like SAP and Nielsen, as well as for thriving startups. Today, Michael shares his passion on leadership and marketing strategies that deliver customer value and business impact. He is recognized by the Huffington Post as a Top Business Keynote Speaker and   a top  CMO influencer by Forbes.

4 Challenges For Mobilizing Data In Field Sales And 5 Steps To Overcoming Them

Trent Young

I’ve had many conversations in recent years with companies considering or in the process of implementing mobile analytics and reporting for field sales. Many have struggled with this shift in delivering data to their sales force. It’s not about just introducing a new mobile app – many times it’s about changing behavior, making tough choices, and transforming how data is used in the field.

Here are four of the most common struggles I hear from organizations looking to take their data mobile for field sales and five ways to solve their problems.

“We send this data out daily (or weekly) in Excel. Sales likes it that way so they can pivot and slice the data how they want to analyze their territories.”

Really? Your reps spend time slicing their territory every week?! Imagine having 300 sales reps getting data every week and playing the data analyst role – what an inefficient use of time. Leave data analysis to the data analysts. Step One: Agree on the data and KPIs that really drive performance and get out of the business of making your salespeople into analysts.

“My sales managers ask for too much ad hoc data. If they can’t get the data they need on demand, it won’t work.”

Don’t get me wrong, there’s a time for ad hoc analysis, but usually in sales they are asking for this data to tell a story and often it’s a story around why they didn’t meet the goals for the KPIs you agreed on in Step One above. Step Two: Stop the ad hoc reporting frenzy that enables sales managers to shape the data to explain why they didn’t meet XYZ sales KPI.

“My team uses PDF reports, so giving them interactive visualizations is too big of a paradigm shift for them.” 

It’s true, it is a big change and change is difficult. Step Three: Start with numeric mobile reports and visualize second. Better yet, provide the numbers they are used to and the visuals. Step Four: Focus on the benefits of the interactive visualizations, not the differences. Can you sort and filter a PDF or printed report? Give examples of how they can use the new capabilities to their benefit.

“My team won’t adopt it, we’ve tried new tech before and it failed.”

It’s good to be skeptical when considering new technologies. Just because the latest tech is appealing doesn’t mean it will be embraced. Step Five: Make the adoption of new technologies about transformation and improvement of how sales reps manage their territory. Delivering up-to-date market share, inventory, order, and compensation data in-the-moment and within two taps isn’t about being trendy, it’s about driving decisions and data-driven discussions with customers that yield results.

Learn more

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About Trent Young

Trent works with enterprises to help them transform delivery of company reports from PDFs, spreadsheets and reports into interactive dashboards and mobile analytics. The goal is to enable their end users to save time and increase their ability to make decisions by staying connected to critical business information.

Primed: Prompting Customers to Buy

Volker Hildebrand, Sam Yen, and Fawn Fitter

When it comes to buying things—even big-ticket items—the way we make decisions makes no sense. One person makes an impulsive offer on a house because of the way the light comes in through the kitchen windows. Another gleefully drives a high-end sports car off the lot even though it will probably never approach the limits it was designed to push.

We can (and usually do) rationalize these decisions after the fact by talking about needing more closet space or wanting to out-accelerate an 18-wheeler as we merge onto the highway, but years of study have arrived at a clear conclusion:

When it comes to the customer experience, human beings are fundamentally irrational.

In the brick-and-mortar past, companies could leverage that irrationality in time-tested ways. They relied heavily on physical context, such as an inviting retail space, to make products and services as psychologically appealing as possible. They used well-trained salespeople and employees to maximize positive interactions and rescue negative ones. They carefully sequenced customer experiences, such as having a captain’s dinner on the final night of a cruise, to play on our hard-wired craving to end experiences on a high note.

Today, though, customer interactions are increasingly moving online. Fortune reports that on 2016’s Black Friday, the day after Thanksgiving that is so crucial to holiday retail results, 108.5 million Americans shopped online, while only 99.1 million visited brick-and-mortar stores. The 9.4% gap between the two was a dramatic change from just one year prior, when on- and offline Black Friday shopping were more or less equal.

When people browse in a store for a few minutes, an astute salesperson can read the telltale signs that they’re losing interest and heading for the exit. The salesperson can then intervene, answering questions and closing the sale.

Replicating that in a digital environment isn’t as easy, however. Despite all the investments companies have made to counteract e-shopping cart abandonment, they lack the data that would let them anticipate when a shopper is on the verge of opting out of a transaction, and the actions they take to lure someone back afterwards can easily come across as less helpful than intrusive.

In a digital environment, companies need to figure out how to use Big Data analysis and digital design to compensate for the absence of persuasive human communication and physical sights, sounds, and sensations. What’s more, a 2014 Gartner survey found that 89% of marketers expected customer experience to be their primary differentiator by 2016, and we’re already well into 2017.

As transactions continue to shift toward the digital and omnichannel, companies need to figure out new ways to gently push customers along the customer journey—and to do so without frustrating, offending, or otherwise alienating them.

The quest to understand online customers better in order to influence them more effectively is built on a decades-old foundation: behavioral psychology, the study of the connections between what people believe and what they actually do. All of marketing and advertising is based on changing people’s thoughts in order to influence their actions. However, it wasn’t until 2001 that a now-famous article in the Harvard Business Review formally introduced the idea of applying behavioral psychology to customer service in particular.

The article’s authors, Richard B. Chase and Sriram Dasu, respectively a professor and assistant professor at the University of Southern California’s Marshall School of Business, describe how companies could apply fundamental tenets of behavioral psychology research to “optimize those extraordinarily important moments when the company touches its customers—for better and for worse.” Their five main points were simple but have proven effective across multiple industries:

  1. Finish strong. People evaluate experiences after the fact based on their high points and their endings, so the way a transaction ends is more important than how it begins.
  2. Front-load the negatives. To ensure a strong positive finish, get bad experiences out of the way early.
  3. Spread out the positives. Break up the pleasurable experiences into segments so they seem to last longer.
  4. Provide choices. People don’t like to be shoved toward an outcome; they prefer to feel in control. Giving them options within the boundaries of your ability to deliver builds their commitment.
  5. Be consistent. People like routine and predictability.

For example, McKinsey cites a major health insurance company that experimented with this framework in 2009 as part of its health management program. A test group of patients received regular coaching phone calls from nurses to help them meet health goals.

The front-loaded negative was inherent: the patients knew they had health problems that needed ongoing intervention, such as weight control or consistent use of medication. Nurses called each patient on a frequent, regular schedule to check their progress (consistency and spread-out positives), suggested next steps to keep them on track (choices), and cheered on their improvements (a strong finish).

McKinsey reports the patients in the test group were more satisfied with the health management program by seven percentage points, more satisfied with the insurance company by eight percentage points, and more likely to say the program motivated them to change their behavior by five percentage points.

The nurses who worked with the test group also reported increased job satisfaction. And these improvements all appeared in the first two weeks of the pilot program, without significantly affecting the company’s costs or tweaking key metrics, like the number and length of the calls.

Indeed, an ongoing body of research shows that positive reinforcements and indirect suggestions influence our decisions better and more subtly than blatant demands. This concept hit popular culture in 2008 with the bestselling book Nudge.

Written by University of Chicago economics professor Richard H. Thaler and Harvard Law School professor Cass R. Sunstein, Nudge first explains this principle, then explores it as a way to help people make decisions in their best interests, such as encouraging people to eat healthier by displaying fruits and vegetables at eye level or combatting credit card debt by placing a prominent notice on every credit card statement informing cardholders how much more they’ll spend over a year if they make only the minimum payment.

Whether they’re altruistic or commercial, nudges work because our decision-making is irrational in a predictable way. The question is how to apply that awareness to the digital economy.

In its early days, digital marketing assumed that online shopping would be purely rational, a tool that customers would use to help them zero in on the best product at the best price. The assumption was logical, but customer behavior remained irrational.

Our society is overloaded with information and short on time, says Brad Berens, Senior Fellow at the Center for the Digital Future at the University of Southern California, Annenberg, so it’s no surprise that the speed of the digital economy exacerbates our desire to make a fast decision rather than a perfect one, as well as increasing our tendency to make choices based on impulse rather than logic.

Buyers want what they want, but they don’t necessarily understand or care why they want it. They just want to get it and move on, with minimal friction, to the next thing. “Most of our decisions aren’t very important, and we only have so much time to interrogate and analyze them,” Berens points out.

But limited time and mental capacity for decision-making is only half the issue. The other half is that while our brains are both logical and emotional, the emotional side—also known as the limbic system or, more casually, the primitive lizard brain—is far older and more developed. It’s strong enough to override logic and drive our decisions, leaving rational thought to, well, rationalize our choices after the fact.

This is as true in the B2B realm as it is for consumers. The business purchasing process, governed as it is by requests for proposals, structured procurement processes, and permission gating, is designed to ensure that the people with spending authority make the most sensible deals possible. However, research shows that even in this supposedly rational process, the relationship with the seller is still more influential than product quality in driving customer commitment and loyalty.

Baba Shiv, a professor of marketing at Stanford University’s Graduate School of Business, studies how the emotional brain shapes decisions and experiences. In a popular TED Talk, he says that people in the process of making decisions fall into one of two mindsets: Type 1, which is stressed and wants to feel comforted and safe, and Type 2, which is bored or eager and wants to explore and take action.

People can move between these two mindsets, he says, but in both cases, the emotional brain is in control. Influencing it means first delivering a message that soothes or motivates, depending on the mindset the person happens to be in at the moment and only then presenting the logical argument to help rationalize the action.

In the digital economy, working with those tendencies means designing digital experiences with the full awareness that people will not evaluate them objectively, says Ravi Dhar, director of the Center for Customer Insights at the Yale School of Management. Since any experience’s greatest subjective impact in retrospect depends on what happens at the beginning, the end, and the peaks in between, companies need to design digital experiences to optimize those moments—to rationally design experiences for limited rationality.

This often involves making multiple small changes in the way options are presented well before the final nudge into making a purchase. A paper that Dhar co-authored for McKinsey offers the example of a media company that puts most of its content behind a paywall but offers free access to a limited number of articles a month as an incentive to drive subscriptions.

Many nonsubscribers reached their limit of free articles in the morning, but they were least likely to respond to a subscription offer generated by the paywall at that hour, because they were reading just before rushing out the door for the day. When the company delayed offers until later in the day, when readers were less distracted, successful subscription conversions increased.

Pre-selecting default options for necessary choices is another way companies can design digital experiences to follow customers’ preference for the path of least resistance. “We know from a decade of research that…defaults are a de facto nudge,” Dhar says.

For example, many online retailers set a default shipping option because customers have to choose a way to receive their packages and are more likely to passively allow the default option than actively choose another one. Similarly, he says, customers are more likely to enroll in a program when the default choice is set to accept it rather than to opt out.

Another intriguing possibility lies in the way customers react differently to on-screen information based on how that information is presented. Even minor tweaks can have a disproportionate impact on the choices people make, as explained in depth by University of California, Los Angeles, behavioral economist Shlomo Benartzi in his 2015 book, The Smarter Screen.

A few of the conclusions Benartzi reached: items at the center of a laptop screen draw more attention than those at the edges. Those on the upper left of a screen split into quadrants attract more attention than those on the lower left. And intriguingly, demographics are important variables.

Benartzi cites research showing that people over 40 prefer more visually complicated, text-heavy screens than younger people, who are drawn to saturated colors and large images. Women like screens that use a lot of different colors, including pastels, while men prefer primary colors on a grey or white background. People in Malaysia like lots of color; people in Germany don’t.

This suggests companies need to design their online experiences very differently for middle-aged women than they do for teenage boys. And, as Benartzi writes, “it’s easy to imagine a future in which each Internet user has his or her own ‘aesthetic algorithm,’ customizing the appearance of every site they see.”

Applying behavioral psychology to the digital experience in more sophisticated ways will require additional formal research into recommendation algorithms, predictions, and other applications of customer data science, says Jim Guszcza, PhD, chief U.S. data scientist for Deloitte Consulting.

In fact, given customers’ tendency to make the fastest decisions, Guszcza believes that in some cases, companies may want to consider making choice environments more difficult to navigate— a process he calls “disfluencing”—in high-stakes situations, like making an important medical decision or an irreversible big-ticket purchase. Choosing a harder-to-read font and a layout that requires more time to navigate forces customers to work harder to process the information, sending a subtle signal that it deserves their close attention.

That said, a company can’t apply behavioral psychology to deliver a digital experience if customers don’t engage with its site or mobile app in the first place. Addressing this often means making the process as convenient as possible, itself a behavioral nudge.

A digital solution that’s easy to use and search, offers a variety of choices pre-screened for relevance, and provides a friction-free transaction process is the equivalent of putting a product at eye level—and that applies far beyond retail. Consider the Global Entry program, which streamlines border crossings into the U.S. for pre-approved international travelers. Members can skip long passport control lines in favor of scanning their passports and answering a few questions at a touchscreen kiosk. To date, 1.8 million people have decided this convenience far outweighs the slow pace of approvals.

The basics of influencing irrational customers are essentially the same whether they’re taking place in a store or on a screen. A business still needs to know who its customers are, understand their needs and motivations, and give them a reason to buy.

And despite the accelerating shift to digital commerce, we still live in a physical world. “There’s no divide between old-style analog retail and new-style digital retail,” Berens says. “Increasingly, the two are overlapping. One of the things we’ve seen for years is that people go into a store with their phones, shop for a better price, and buy online. Or vice versa: they shop online and then go to a store to negotiate for a better deal.”

Still, digital increases the number of touchpoints from which the business can gather, cluster, and filter more types of data to make great suggestions that delight and surprise customers. That’s why the hottest word in marketing today is omnichannel. Bringing behavioral psychology to bear on the right person in the right place in the right way at the right time requires companies to design customer experiences that bridge multiple channels, on- and offline.

Amazon, for example, is known for its friction-free online purchasing. The company’s pilot store in Seattle has no lines or checkout counters, extending the brand experience into the physical world in a way that aligns with what customers already expect of it, Dhar says.

Omnichannel helps counter some people’s tendency to believe their purchasing decision isn’t truly well informed unless they can see, touch, hear, and in some cases taste and smell a product. Until we have ubiquitous access to virtual reality systems with full haptic feedback, the best way to address these concerns is by providing personalized, timely, relevant information and feedback in the moment through whatever channel is appropriate. That could be an automated call center that answers frequently asked questions, a video that shows a product from every angle, or a demonstration wizard built into the product. Any of these channels could also suggest the customer visit the nearest store to receive help from a human.

The omnichannel approach gives businesses plenty of opportunities to apply subtle nudges across physical and digital channels. For example, a supermarket chain could use store-club card data to push personalized offers to customers’ smartphones while they shop. “If the data tells them that your goal is to feed a family while balancing nutrition and cost, they could send you an e-coupon offering a discount on a brand of breakfast cereal that tastes like what you usually buy but contains half the sugar,” Guszcza says.

Similarly, a car insurance company could provide periodic feedback to policyholders through an app or even the digital screens in their cars, he suggests. “Getting a warning that you’re more aggressive than 90% of comparable drivers and three tips to avoid risk and lower your rates would not only incentivize the driver to be more careful for financial reasons but reduce claims and make the road safer for everyone.”

Digital channels can also show shoppers what similar people or organizations are buying, let them solicit feedback from colleagues or friends, and read reviews from other people who have made the same purchases. This leverages one of the most familiar forms of behavioral psychology—reinforcement from peers—and reassures buyers with Shiv’s Type 1 mindset that they’re making a choice that meets their needs or encourages those with the Type 2 mindset to move forward with the purchase. The rational mind only has to ask at the end of the process “Am I getting the best deal?” And as Guszcza points out, “If you can create solutions that use behavioral design and digital technology to turn my personal data into insight to reach my goals, you’ve increased the value of your engagement with me so much that I might even be willing to pay you more.”

Many transactions take place through corporate procurement systems that allow a company to leverage not just its own purchasing patterns but all the data in a marketplace specifically designed to facilitate enterprise purchasing. Machine learning can leverage this vast database of information to provide the necessary nudge to optimize purchasing patterns, when to buy, how best to negotiate, and more. To some extent, this is an attempt to eliminate psychology and make choices more rational.

B2B spending is tied into financial systems and processes, logistics systems, transportation systems, and other operational requirements in a way no consumer spending can be. A B2B decision is less about making a purchase that satisfies a desire than it is about making a purchase that keeps the company functioning.

That said, the decision still isn’t entirely rational, Berens says. When organizations have to choose among vendors offering relatively similar products and services, they generally opt for the vendor whose salespeople they like the best.

This means B2B companies have to make sure they meet or exceed parity with competitors on product quality, pricing, and time to delivery to satisfy all the rational requirements of the decision process. Only then can they bring behavioral psychology to bear by delivering consistently superior customer service, starting as soon as the customer hits their app or website and spreading out positive interactions all the way through post-purchase support. Finishing strong with a satisfied customer reinforces the relationship with a business customer just as much as it does with a consumer.

The best nudges make the customer relationship easy and enjoyable by providing experiences that are effortless and fun to choose, on- or offline, Dhar says. What sets the digital nudge apart in accommodating irrational customers is its ability to turn data about them and their journey into more effective, personalized persuasion even in the absence of the human touch.

Yet the subtle art of influencing customers isn’t just about making a sale, and it certainly shouldn’t be about persuading people to act against their own best interests, as Nudge co-author Thaler reminds audiences by exhorting them to “nudge for good.”

Guszcza, who talks about influencing people to make the choices they would make if only they had unlimited rationality, says companies that leverage behavioral psychology in their digital experiences should do so with an eye to creating positive impact for the customer, the company, and, where appropriate, the society.

In keeping with that ethos, any customer experience designed along behavioral lines has to include the option of letting the customer make a different choice, such as presenting a confirmation screen at the end of the purchase process with the cold, hard numbers and letting them opt out of the transaction altogether.

“A nudge is directing people in a certain direction,” Dhar says. “But for an ethical vendor, the only right direction to nudge is the right direction as judged by the customers themselves.” D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


About the Authors:

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

Sam Yen is Chief Design Officer and Managing Director at SAP.

Fawn Fitter is a freelance writer specializing in business and technology.

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The Big (Data) Problem With Machine Learning

Dan Wellers

Historically, most of the data businesses have analyzed for decision-making has been of the structured variety—easily entered, stored, and queried. In the digital age, that universe of potentially valuable data keeps expanding exponentially. Most of it is unstructured data, coming from a wide variety of sources, from websites to wearable devices. As a recent McKinsey Global Institute report noted: “Much of this newly available data is in the form of clicks, images, text, or signals of various sorts, which is very different than the structured data that can be cleanly placed in rows and columns.”

At the same time, we have entered an era when machine learning can theoretically find patterns in vast amounts of data to enable enterprises to uncover insights that may not have been visible before. Machine learning trains itself on data, and for a time, that data was scarce. Today it is abundant. By 2025, the world will create 180 zettabytes of data per year (up from 4.4 zettabytes in 2013), according to IDC.

Big Data and machine learning would seem to be a perfect match, coming together at just the right time. But it’s not that simple.

The connected world is ever-widening, enabling the capture and storage of more—and more diverse—data sets than ever before. Nearly 5,000 devices are being connected to the Internet every minute today; within ten years, there will be 80 billion devices collecting and transmitting data in the world. Voice, facial recognition, chemical, biological, and 3D-imaging sensors are rapidly advancing. And the computing muscle that will be required to churn through all this data is more readily available today. There’s been a one trillion-fold increase in computing power over the past 60 years.

The importance of data prep

But having vast amounts of data and computing power isn’t enough. For machine learning tools to work, they need to be fed high-quality data, and they must also be guided by highly skilled humans.

It’s the age-old computing axiom writ large: garbage in, garbage out. Data must be clean, scrubbed of anomalies, and free of bias. In addition, it must be structured appropriately for the particular machine-learning tool being used as the required format varies by platform. Preparing data is likely the least sexy but most important part of a data scientist’s job—one that accounts for as much as 50 percent of his or her time, according to some estimates. It’s the unglamorous heavy lifting of advanced analytics, and it takes experience and skill to do it—qualities that are, and will continue to be, in short supply even as demand for data scientists is predicted to grow at double-digit rates for the foreseeable future.

It took one bank 150 people and two years of painstaking work to address all the data quality questions necessary to build an enterprise-wide data lake from which advanced analytics tools might drink. That’s the kind of data wrangling that has to be done before companies can even begin to test the value of machine-learning capabilities.

More data, more problems

There’s also the misperception that having access to all this new data will necessarily lead to greater insight. There’s great enthusiasm around data-driven decision-making and the promise of Big Data and machine learning in boardrooms and executive suites around the world. But in reality, says UC Berkeley professor and machine learning expert Michael I. Jordan, more data increases the likelihood of making spurious connections. “It’s like having billions of monkeys typing. One of them will write Shakespeare,” said Jordan, who noted that Big Data analysis can deliver inferences at certain levels of quality. But, he said, “we have to be clear about what levels of quality. We have to have error bars around all our predictions. That is something that’s missing in much of the current machine learning literature.”

Again, this is where the expertise of the data scientist is of critical value: deciding what questions machine learning might be able to answer, with what data and at what level of quality.

These problems are not insurmountable. Tools are being developed to help businesses deal with some of the data management blocking and tackling that stands in the way of advanced analytics. One company, for example, has developed a machine-learning tool for real estate and finance companies that it says can extract unstructured data in 20 different languages from contracts and other legal documents and transform it into a structured, query-ready format.

What is clear is that the business of combining Big Data and big computing power for new insight is harder than it looks. The benefits almost certainly will be huge. But companies are still at the early stages of experimenting with new data types and emerging machine-learning tools and discovering the drawbacks and complications we will need to work through over time.

This blog is the fifth in a six-part series on machine learning.

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About Dan Wellers

Dan Wellers is the Global Lead of Digital Futures at SAP, which explores how organizations can anticipate the future impact of exponential technologies. Dan has extensive experience in technology marketing and business strategy, plus management, consulting, and sales.