Gamification: the why and the how

Loyalty 3.0

by Rajat Paharia

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Published - 2018

Loyalty 3.0 by Rajat Paharia is a step-by-step guide on how to engage customers and employees using big data and gamification techniques to create meaningful loyalty. But as Pahairia says, “…we’ll engage with anything for a little while, if only because it’s shiny and new, but if we fail to derive meaningful value from our engagement, we’ll disconnect and walk away. So it’s imperative, when you’re thinking about how to apply gamification to your business problems, that you understand what’s in it for your end users and what meaningful value you’re providing to them.” I felt this was the most important sentence in the book. It is all about creating long-term meaningful value for both the customer and the company.

While Loyalty 3.0 is only the second book I have read on “gamification” it is so far the most valuable to me because it provides the “why it is important” and the “how it can be applied.” And because of the depth on “how” in Loyalty 3.0, it confirmed that I have been successfully executing key principles of gamification my whole career, but I was missing big data, I used costly small data instead. Principles of gamification were the tools of channel marketing, usually treated as tactics within a larger campaign, not the strategy to achieve a main objective. 

As someone who has built my career studying behavioral motivations, clustering people based on motivational groups, finding the triggers that motivate and direct the decision making processes, designing customer journey roadmaps, and then managing customer motivations and actions at each activation touch-point, I found the structure that Paharia created in Loyalty 3.0 an excellent tool that I will use in the future to make loyalty my strategic Northstar.

oyalty 3.0 is worth reading if you are in marketing, sales, human resources, and the CEO/COO. The book is made up of three Part 1, Vision (the why); Part 2, Execution (the case studies); Part 3, Direction (the how). Below I have included key information from Part 1 to wet your appetite.

PART 1

VISION

“The first step towards getting somewhere

is to decide that you are not going

to stay where you are.”

J.P. Morgan

CHAPTER 1

May You Live in Interesting Times

The Three Faces of Loyalty

When you think of the word loyalty in the context of business, what comes to mind? If you’re like most people, the first thing that will pop into your head is a typical loyalty program, where you earn points for your purchases and can redeem them for rewards.

What is that purpose? It’s to give customers a compelling reason to continue to patronize the business and to resist competitive offers.

Clearly, something needs to change. And the companies that figure it out, that create true loyalty, are going to realize a sizable and sustainable competitive advantage and win in their markets.

The Road to Loyalty 3.0

Loyalty 3.0 is about taking back the word loyalty and making it actually mean something. It does this by combining the latest research on human motivation with the big data generated by your customers, partners, and employees as they interact with you to empower your business to motivate, engage, and create true loyalty.

Loyalty 1.0

We all know Loyalty 1.0 programs; they’re the frequent-flyer programs, cash-back credit cards, and “buy ten get one free” punch cards from the local sandwich shop that have been around for many years. These are purely transactional, completely focused on customers, and absolute failures at generating the kind of loyalty that businesses actually want. For customers, at best, they’re mildly pleasing, and at worst, when a business isn’t living up to its brand promise, they feel like a way for a business to hold them hostage. For businesses, at best, they’re table stakes in an industry where everyone else has one, and at worst, they’re a giant cost center eating into the bottom line and creating a huge liability.

Loyalty 1.0 programs also suffer from fundamental structural problems. There’s an exciting part at the beginning when you sign up for the program and dream about how you’re going to earn spectacular rewards and another at the end (if you get there) when you actually redeem for a (possibly spectacular but maybe not) reward. In the middle is just a very long grind with no motivation, no engagement, and no loyalty being generated. There’s a gulf of lost opportunity in the middle.

Loyalty 2.0

In the early 1990s, 1- to -1 marketing emerged, focused primarily on making the loyalty experience more targeted through segmentation and personalization, with a big emphasis on direct-mail and e-mail campaigns. Data had a bigger role here as businesses took the information they were learning about their customers and used it to “speak to their interests.” While this was effective for a while, open rates on these communications plummeted as the overall level of direct mail and e-mail increased. Consumers were overwhelmed by the sheer amount of noise, and the problem has only gotten worse.

Loyalty 3.0

Loyalty 3.0 has three major enabling components that, when combined, are much greater than the sum of the parts:

1. Motivation. Recent social-science research has much more clearly defined what compels and motivates human behavior, and what causes people to do things or not do things in life and in the workplace. Knowing what truly motivates people—and what doesn’t—enables us to create stronger engagement and true loyalty.
2. Big data. Technology has taken over how we communicate, socialize, work, and play. The amount of data that people are generating as they interact with these systems is exploding, and new technology is enabling businesses to capture that data with more granularity than ever before. Smart businesses can consume this data and use it to understand, engage, and motivate their constituents in ways not previously possible.
3. Gamification. Game designers have been using data-driven motivational techniques for years. Our new understanding of motivation, combined with the emergence of big data streams, has enabled these techniques to be used outside the gaming world, where they can be powerful tools to drive engagement, participation, and high-value activity for customers, employees, and partners alike.

By leveraging these three components together, we can make our customers, partners, and employees more engaged, more active, and truly loyal.

The Four Tiers of Loyalty

• Inertia loyalty. If a brand’s loyalty strategy involves such terms as barrier to exit, it most likely falls into the inertia loyalty category—making it inconvenient to leave the program rather than irresistible to stay. Customers in this tier stick around because it’s too inconvenient to escape.
• Mercenary loyalty. Just as a mercenary will swear allegiance for a price, marketers can pay or “bribe” customers for their loyalty. Most traditional points- and discounts-based loyalty programs operate in this tier because of past effectiveness, but the industry now sees a leveling off of participation rates for this type of program. Yes, the tactic may work, but its major weakness is that the loyalty generated is emotionally shallow—it’s simply about getting freebies or a better price; these programs amount to a complex method of discounting. Here, too, there’s little to stop your competitor from taking customers simply by discounting or paying more.
• True loyalty. Brands reach this tier when a customer has a compelling reason—ideally, an emotional stake in the brand—to resist competitive offers. If a new store opens across the street or a competitor slashes prices, a brand with true loyalty won’t lose customers because the relationship is based on a deeper connection of trust and shared value....All brands can attain true loyalty if they are committed to a win-win relationship with their customers.
• Cult loyalty. Ever see someone who proudly sports a brand logo as her favorite tattoo? Or maybe just a friend who consistently refers to himself as a “____ guy” (fill in his favorite brand name). At the cult loyalty tier, the customer and the brand begin to merge so that rejecting the brand would be like rejecting your own values....Unfortunately for marketers, cult loyalty is next to impossible to artificially manufacture. It emerges only organically—but once it does, it can be cultivated.

What Is Engagement?

There seem to be as many definitions of engagement as there are people. My favorite is from Forrester Research,3 where engagement is defined as having three parts:

• A deep emotional connection with the brand
• High levels of active participation
• A long-term relationship

Note the point about active participation—engaged constituents don’t just feel, they act. They participate, advocate, ideate, contribute, and generally engage in high-value activity that makes your business better. What this definition makes clear is that the path to true loyalty is through engagement.

CHAPTER 2

Whoever Figures Out Motivation Wins

Fueling the Fire

Loyalty 3.0 has two primary sources of fuel—one is big data and the other is human motivation. Here’s the amazing thing about human motivation: If you can tap into it properly, there’s a never-ending supply of it. It’s like cold fusion for loyalty. And whoever figures out how to harness that energy is going to win.

Internal and external factors that stimulate desire and energy in people to be continually interested in and committed to a job, role, or subject, and to exert persistent effort in attaining a goal.

Motivation results from the interactions among conscious and unconscious factors such as the:

1. intensity of desire or need
2. incentive or reward value of the goal
3. expectations of the individual and of his or her significant others

Let’s break the first part of the definition down and understand its parts:

• Internal and external factors. Motivation can come from within a person as well as from outside a person. We’ll discuss the difference between intrinsic (internal) motivators and extrinsic (external) motivators below.
• That stimulate desire and energy in people. This is the cold-fusion part of motivation, our inexhaustible “desire and energy.”
• To be continually interested in and committed to a job, role, or subject. Our “desire and energy” have a context.
• And to exert persistent effort. Remember, Loyalty 3.0 isn’t about passively receiving; it’s about action.
• In attaining a goal. At the end of the day, the person is motivated to accomplish or achieve something. It has some “reward value.

Five key intrinsic motivators for Loyalty 3.0:

• Autonomy is the urge to direct our own lives (“I control”).
• Mastery is the desire to get better at something that matters (“I improve”).
• Purpose is the yearning to do what we do in the service of something larger than ourselves (“I make a difference”).
• Progress is the desire to see results in the direction of mastery and the greater purpose (“I achieve”).
• Social interaction is the need to belong and to be connected to and interact with others (“I connect with others”).

These motivations are innate, not learned, and have been proven to be universal, across cultures, age groups, and time.

Note that we explicitly called these out as intrinsic motivators. As we saw from our definition earlier, motivation is either intrinsic (initiating an activity for its own sake because it is interesting and satisfying in itself) or extrinsic (some external force is influencing, motivating, or requiring you to do something). Most theories of motivation state that intrinsic motivators are more powerful than extrinsic motivators.

There are no doubt problems with extrinsic motivators—studies have shown that extrinsic motivators can “extinguish” intrinsic motivation. If a child loves to play the piano and then you enter her into piano competitions and push her to win, Win, WIN, the natural joy she derived from playing disappears, and playing becomes something she has to do rather than something she wants to do. The extrinsic motivator of competition has extinguished her natural joy and love of making music.

It’s all true, but it doesn’t mean that extrinsic motivators are bad, just that they should be used carefully, in the appropriate contexts, and in a way that doesn’t extinguish any existing intrinsic motivation.

Algorithmic. You follow a set of rules or a checklist to complete a task. Examples might include doing taxes, checking out at the grocery store, and assembling cars. Since these tasks are rule-based, they also lend themselves to automation.

Heuristic. There is no algorithm, no set of rules, and no checklist. You have to be creative and figure out the solution. Writing a book, designing a new product, and crafting a marketing strategy are all examples of heuristic tasks. These kinds of tasks are much harder to automate than algorithmic tasks.

Algorithmic tasks typically don’t engender much intrinsic motivation, and in those cases, extrinsic motivators can work very well. Heuristic tasks, on the other hand, depend on intrinsic creativity and motivation to be successful. So a heavy-handed use of extrinsic motivators, as in the example of the young girl playing the piano, can have the opposite of the desired effect.

And people are complex—it’s not always easy to figure out what is motivating them to do something. As opposed to treating them as binary opposites, another way to view intrinsic and extrinsic motivation is as two ends of a spectrum—motivation sometimes falls cleanly into either category but often lies somewhere in between.

Deep Dive into the Five Intrinsic Motivators

Three of the five motivators form the foundation of self-determination theory (SDT), a theory of motivation created by a pair of University of Rochester professors, Drs. Edward L. Deci and Richard M. Ryan. To these motivators we have added two additional ones that other academics have identified and that our experience has shown to have strong motivational effects.

Autonomy—“I Control”

Autonomy, as noted earlier, is the “urge to direct our own lives” and is the first pillar of SDT. We want to be in control; we want to decide what we do, how we do it, whom we interact with, when, and where. It doesn’t necessarily mean that we want to be antisocial or work or live in a vacuum; instead, we simply want some control over our own lives and our own decisions. Think about how you perform best—when someone is micromanaging your every move or when you’re given the freedom to make your own decisions?

Autonomy in the workplace exists on a continuum—from having none and being told exactly what to do, to working a typical job where sometimes you have autonomy and sometimes you don’t, to what’s now being referred to as a results-only work environment (ROWE).4 First developed at Best Buy, the focus of ROWE, as the name implies, is to give all employees the freedom to do whatever they want, whenever they want, as long as the work gets done. Someone else still typically decides what you need to do, but you get to decide how to do it. Companies that have implemented ROWE have seen decreases in voluntary turnover, increases in productivity, and increases in worker engagement.

Mastery—“I Improve”

The second of the three motivators that we reference from SDT is mastery (which they refer to as “competence”)—the innate desire that we have to be competent and to get better at things. Getting better at things is satisfying on a number of fronts. For some, it means that a job or task gets easier; for others, it means the psychic and possibly financial rewards that come from doing something that (1) we couldn’t do before and (2) not everyone else can do.

Mastery requires a growth mind-set. According to Carol Dweck, a psychology professor at Stanford University, you can place people on a continuum based on their innate views on where ability comes from. Some people have a fixed mind-set, where they believe that basic qualities, such as intelligence and talent, are fixed traits that can’t be changed. Fixed mind-set individuals dread any sort of failure because to them it’s a negative reflection on their abilities, which are immutable. Because of this, they devote a lot of effort to trying to look smart and avoiding looking stupid—they won’t engage in situations where they can fail, especially publicly. Growth mind-set individuals, on the other hand, believe that their basic abilities can be developed through dedication and hard work—that what they have right now is just the starting point. These people don’t fear failure as much because they know that they can improve and that failure is a crucial part of the learning process.

The road to mastery can be long and hard, and there will often be failure along the way, so people need to believe that they can get better and aren’t limited by their current abilities. And many skills and tasks are asymptotic—for tasks such as playing golf or mastering a musical instrument, we can never reach perfection—we can always get better.

Purpose—“I Make a Difference”

I’m sure you’ve all had the experience: You create a great piece of work—a document, a presentation, or a set of plans for a new product. You worked hard on it, invested your time and your energy to make something great, and are proud of your work. The boss accepts your work, gives you a figurative or even a literal pat on the back, praises your work—and then, for whatever reason, your work is never used. The product is canceled, the deal is off, the company changes direction. Your work goes in a drawer, never to be seen again. You do good work you were trained for, you complete it on time, you turn it in, and you get paid. You should be happy, right?

Yet you’re not happy, your motivation has dropped dramatically, and you’re thinking that maybe you should get a new job. Why? Because there’s something missing. And that something is purpose. To quote Steve Jobs, “We’re here to put a dent in the universe. Otherwise, why else even be here?”9 We all need to feel like we’re making a difference and that our efforts and our existence have meaning.

Progress—“I Achieve”

Through careful analysis of the diary entries, Amabile and Kramer discovered what they call the progress principle—that the event that correlated most highly with good days at work, with feeling motivated, was making progress toward a meaningful goal. When we think of progress, we typically think of major milestones or achievements, but the problem is that those are infrequent and by themselves aren’t enough to sustain long-term performance and motivation—they’re too far apart. The good news is that Amabile and Kramer’s research uncovered that even small wins could have a significant, even disproportional impact on motivation and engagement.

People respond well when they see that they are making progress on something they care about, whether in the workplace or in life. The lessons for engagement and motivation are fairly straightforward—make small wins frequent, possible, and visible.

Social Interaction—“I Connect with Others”

The final intrinsic motivator and the third from SDT is social interaction (which Deci and Ryan refer to as relatedness). We are inherently and innately social creatures. We want to connect, we want to interact, we want to affiliate, we want to care, we want to share, we want to be recognized, and we want to understand and be understood.

The desire for validation and recognition from others is another huge driver of our behavior. We post status updates and hope that people “Like” them, we share photos and obsessively check to see what people have to say about them, and we write reviews on product sites and hope that people mark them as helpful. What’s the point of doing these things if no one else can see them?

We also look to others to figure out appropriate behavior. From tip jars, to watching to see which fork people use at dinner, to looking at a newsfeed of activity on a social network—seeing what others are doing, the social norm, gives us cues that tell us how to behave, what possible actions should be, and what’s expected of us. Studies have shown us that people are more likely to adhere to the social norms of others “like” them. That likeness can be in the form of personal or identity commonalities (such as race, interests, etc.) but also situational or contextual commonalities. Your customers, partners, and employees all exist in a shared social context with each other, so if you can establish the social norms in their respective communities, you have a powerful tool to motivate high-value activity and loyalty.

CHAPTER 3

The Next Big Thing Is Big Data

Remember, true loyalty is about building relationships, which starts with getting to know one another. Big data enables businesses to know their customers, employees, and partners in unprecedented ways

What Is Big Data and Where Does It Come From?

Big data, however, has arrived more recently. Traditional data, such as customer or employee records about you, where you live, what you’ve purchased, and how you’ve performed, is “old news,” stored in structured databases and made available to anyone with the appropriate access, the right querying tools, and a schema (i.e., an architectural diagram or schematic) of the database. Big data refers to the explosion in the size, amount, and form of information available around any one individual, organization, or event. It comes from an increasingly wide variety of sources; is assembled in a variety of forms, some structured and processed and some unstructured and unprocessed; and is present in heretofore unimagined quantities.

For years, companies had a standard, structured customer record with name, address, phone numbers, e-mail address, and perhaps some historical transactional data. They might have supplemented this with some externally sourced marketing information, including interests derived through magazine subscriptions or expected behaviors inferred from where you lived or your socioeconomic class. Over the years, this record has grown to contain more and more data—but still in a standard, structured format.

Fast-forward to now, and the expansion of computing power, mobile devices, and other new data-input streams has added another massive layer of available information. Huge new streams of unstructured data have become available to tap into because nearly everything we’re doing is mediated by technology and therefore able to generate data. Among the many sources are “clickstreams,” Internet Protocol (IP) addresses, Global Positioning System, (GPS) locations, mobile phone usage, online shopping patterns, social networks, radio-frequency identification (RFID) chips, sensors and connected devices, mentions in blog posts, customer feedback, and other “public” information you create or read from the Internet. These and almost unlimited other sources have greatly expanded the amount of data being generated and available for businesses to consume.

The data are (1) unlikely to be in one place, (2) unlikely to be owned or controlled by one organization, (3) not managed through traditional “structured” database tools, and (4) gigantic—it is referred to as big data. Analyst firm Gartner defined big data as follows: “Big data in general is defined as high volume, velocity and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.

How Can We Use Big Data?

The upshot of big data in the business-to-individual relationship is pretty simple: With big data, a business can learn a lot about what you do, where you do it, when you do it, and what you like. Another way to look at it is that your constituents are raising their hands and telling you things about themselves, implicitly and explicitly, all the time through their interactions with you. Big-data collection and processing tools enable you to listen and react.

Here are some of the important forms of big-data collection and analysis:

• Cluster analysis. Cluster analysis is a classification technique that partitions a diverse set of objects into smaller groups so that objects in the same cluster are more similar to each other than to objects in other clusters. The key thing to note is that these groupings or similarities are not known in advance.
• A/B testing (also called split testing). This is a technique in which a control group (A) is compared with a test group (B) to determine what treatments (changes) will improve a given objective...Conversion can be any success condition and might include registering, making a purchase, or even something as simple as pressing a button to go to the next step in a flow. Multivariate testing is a variation of A/B testing that enables a business to run several A/B tests at the same time. The size of the sample (number of tests) required depends on the number of variables being tested and the confidence desired in the results.
• Crowdsourcing is the outsourcing of work to a distributed group of people who aren’t known ahead of time, aka “the crowd.” There are numerous forms of crowdsourcing, typically reflecting the nature of the work being outsourced—opinions, piece work, computing power, ideas, and even funding.
• Predictive modeling refers to a set of mathematical modeling techniques created to best predict an outcome. It goes farther than clustering—rather than stop at a group with similar behaviors and attributes, it predicts what that group might do under certain circumstances based on current and historical facts and data....In the consumer space, a predictive model might estimate the likelihood of a customer engaging in or joining a program, staying with a program, or “churning” away from it. Like the weather forecast, the analysis is based on a broad assortment of direct and indirect causal factors and correlations with other behaviors. These models also can predict the likelihood of success of a cross-sell or upsell opportunity. Employers also use predictive modeling to help predict employee churn and turnover or even to predict who their top and bottom performers will be.
• Sentiment analysis analyzes mostly “soft,” unstructured communication streams to try to pick up customer, employee, or partner sentiment on a subject, a product, or other item being analyzed. Sentiment analysis applies natural-language processing (using computers to understand human language) and other analytic techniques to large quantities of source text material, including blogs and other social media, to identify and extract subjective information. The analysis starts with simple keyword location (if the word great is in the blog, then it’s probably saying something good) and expand from there (What if the user was posting about the “great big screwup” the company made. Uh oh. Time to get more sophisticated.). So-called buzz analyzers attempt to identify patterns of written sentiment on a product or a campaign. They examine how much is being expressed and what kind of sentiment or polarity—positive, negative, or neutral comments—is being expressed. More sophisticated analyzers try to figure out the degree and strength of the sentiment. “These new Burton snowboards are really awesome” would send a strong sentiment signal, especially if it appeared all over the Internet. Consumer marketers use sentiment analysis to determine how different customer segments are reacting to their products and actions. Likewise, strong positive sentiment in internal communication is a gauge of engagement with an employer.
• Stream processing refers to the continuous and real-time analysis of data streams from a variety of sources. Stream processing works together with all the techniques mentioned to adapt and modify a digital experience in real time in order to provide tailored interactions depending on behavior, location, context, or any other variable. Real-time fraud detection and algorithm-based high-frequency securities trading are examples of stream-processing applications.
• Outlier detection and similarity search. Often you want to find the outliers, the deviations from the norm, as in the case of fraud detection, clinical trials, voting activities, and manufacturing defects. These outliers can help you to identify problems, lend insight to your product-design process, and expose bad behavior. By feeding big data from various sources into machine-learning systems that can process them, businesses can find correlations that manual human analysis would never identify and surface the outliers. Conversely, big data also provides the data to locate the other objects that are most similar to an object of interest—for instance, “Find other shoes that look like these,” “Find other patients with similar symptoms,” and “Find other songs that sound like this.”
• Cohort analysis. A cohort is a group of people who share a common characteristic over a certain period of time. By dividing users into cohorts, businesses can compare the relative value of each cohort. An example of a cohort that’s relevant to an online retailer would be the source of the customer—“all the customers who came from a Google search,” “all the customers who came from Twitter,” “all the customers who came via referral,” and so on. With each customer assigned to a cohort and the data about each customer’s overall spend, the retailer now has the ability to see which sources provide the most valuable customers. With this knowledge, the retailer can optimize its marketing spending to get the most bang for its buck.

Combined with the overall spend of each customer, businesses then can see if the quality of their customers is increasing or decreasing over time. In addition, if the business is making changes to its product, service, or experience, time-based cohorts enable a business to make an apples-to-apples comparison to see if the changes are having any material impact on its success.

Crunching the Numbers

Many of these tools work only with in-house, structured databases or data warehouses, in contrast to the large, unstructured data sets that are currently being generated, and therefore aren’t suitable for many of today’s web-scale businesses. To address this, the tech industry has created a new set of large-scale processing systems for highly distributed data from multiple, decentralized, and often unstructured data sources. Some of the ones that are good to know about include:

Not Only SQL (NoSQL). This is the blanket term used for a new class of modern, web-scale databases that have to deal with huge amounts of data. Structured Query Language (SQL) is a standard programming language for getting information out of and putting information into databases. Typical SQL databases exhibit certain characteristics that developers have required over the years: They use the relational model that includes ACID (atomicity, consistency, isolation, durability—a set of properties that guarantee that database transactions are processed reliably), and they have a fixed schema. These properties are what enable your credit-card company and stock broker to run their mission-critical systems and ensure that no data is lost and that they are always up to date and consistent, 24/7, around the world.

Today’s high-volume consumer Internet sites such as Facebook and Twitter don’t always need these mission-critical properties. What they need instead is a system that scales easily to handle their huge volume of big data and runs on commodity hardware. Hence NoSQL was born. In practice, most companies are running a combination of SQL and NoSQL databases depending on the needs of each particular application. Some NoSQL systems that you might hear about include Cassandra (developed by Face-book for inbox search), Voldemort (developed by Linked In), Dynamo (developed by Amazon), MongoDB, and HBase. Many of these are open source and have active developer communities that are continually enhancing them.

Hadoop. Named after a toy elephant in the household of Doug Cutting, one of its creators, Hadoop is an open-source free software framework for processing huge data sets across a distributed hardware system. Its development was inspired by Google, one of the pioneers in dealing with web-scale data, and the tools the company built to process and store that data, including MapReduce and Google File System (GFS). Hadoop is used heavily today by Yahoo!, Facebook, and many others for an assortment of tasks. If you’re interested in using Hadoop for your own data analysis, you can either set it up yourself on your own dedicated machines or deploy it “in the cloud” by using an “infrastructure as a service provider” such as Amazon’s EC2. Sensing a market opportunity, there are also several new companies that have formed to help businesses get up and running, analyzing their data quickly, including Birst, Cloudera, Platfora, Hadapt, MapR, Hortonworks, and others.

Beyond these data crunchers (and there are many others), there is an assortment of visualization tools that also can help the big-data user. Visualization tools enable users to make sense of the big data, identify patterns, and derive some insight that ultimately can lead to action and a business result. Tools such as the statistical computing and graphic language R are used often by data scientists and engineers to analyze and visualize their data, whereas business users leverage visualization software provided by companies like Tableau Software that provide interfaces and displays designed for business users.

Big Data in the Consumer Space

When you’re trying to sell more, anything that helps you to get the right message to the right person at the right time is worth its weight in gold. Here are some of the ways that businesses are using big data to drive their top-line revenues:

• Microsegmentation. For years, companies divided their markets into segments based on easily identified traits such as gender, ZIP code, and age. As more data became readily available, such as income, psychographics, and purchase data, companies were able to refine those segments to better address the needs of their customers. The truth of the matter is, though, that no two people are alike—we are each a “segment of one.” Big data takes the existing data that can be collected and inferred about a consumer and then supplements it with online browsing behavior, shopping patterns, social-networking activity, mobile access, and much more data based on actual user behavior to create microsegments. Do you remember when Amazon.com was the same store for everyone? It seems hard to believe that it was ever that way. Today it’s a different store for every single person who visits—because of big data and real-time microsegmentation.
• Targeted advertising and cross-selling. Microsegmentation also enables businesses to craft the “perfect” cross-sell/upsell offer to close or expand a sale in real time. Based on everything they know about the individual shopper, others like them that might exhibit similar behavior patterns, and the current context (Is the user in a physical store? Did the user come to the website from a marketing e-mail?), businesses are able to dynamically and automatically generate compelling offers that will increase shopping-cart conversion and average order size.
• In-store behavior analysis. Real-time navigation analysis can provide fascinating insight into customer behavior. Tracking motion through physical stores with shopping-cart transponders or video surveillance or passively monitoring the location of mobile phones has helped retailers to enhance their offerings and refine store layout and product positioning. Naturally, though, in the Internet age, it isn’t just physical movements that are being monitored; marketers and retailers constantly tune into customer movements through their websites to determine interest and intent. Unlike in the real world, online retailers can easily detect browsing, sharing, where shoppers arrived from, video watching, and abandoned carts, all of which enable them to refine their marketing messages and channels, their offers, their product mix, and their conversion rates.
• Real-time pricing optimization. Driven by sales history, weather, seasonality, available inventory, time of day, data about the customer, and the overall economy (among others) as inputs, retailers can change their prices dynamically to reflect demand. Just as the airlines dynamically price today to optimize their seat utilization, any business can leverage big data to optimize its inventory and pricing. Amazon and other large Internet retailers are already doing this.
• Social-media monitoring. This is part of a larger trend toward what’s known as social customer relationship management (SCRM), where companies monitor their customer relationships, check the “market pulse,” and collect data from their customers using social-media channels. These channels include Facebook and Twitter, as well as conventional blogs and message boards. The business seeks to learn from these channels and add to the conversation where it can, recognizing that the collective message is really owned by the community. The emphasis here is on listening, not on using the channel as an outbound marketing channel. Tools and social-media dashboards such as HootSuite, SocialMention, and salesforce.com’s Radian6 monitor these channels to capture messages, detect sentiment, and classify messages and meanings for use by different departments in an organization.
• Recommendation engines. Businesses can use big data to predict things you might be interested in. When you’re looking at a product on Amazon and the site shows you “Customers Who Bought This Item Also Bought,” the company is using its giant collection of everyone’s purchasing behavior to recommend products that you’re likely to want to buy as well.

CHAPTER 4

Gamification—The Engine of Loyalty 3.0

If motivation and big data had a love child, its name would be gamification. Don’t let the game in the name fool you, because this is serious stuff, and it’s been around in various forms for as long as there have been people. In simple terms, gamification takes the motivational techniques that video game designers have used for years to motivate players and uses them in nongame contexts....Other phrases that you might recognize that also can be used to describe gamification include:

• Measure and motivate
• Recognition and rewards
• Loyalty
• Reputation
• Guiding and amplifying high-value activity

One way that you can use user-activity data to motivate people is by enabling them to visualize and derive some insight from it, which will hopefully motivate behavior change. This concept (some would call it a movement) even has a name—the quantified self—whose purpose is to derive self-knowledge though self-tracking. By capturing and analyzing data about your weight, sleep patterns, computer usage, spending, athletic performance, or anything else, you can better understand those aspects of your life and what affects them and then use that knowledge to motivate behavior change.

Gamification’s goals are the business’s goals, whatever they may be: better learning, increased performance, more page views, more sales, increased collaboration, or anything else a business might want to drive. And it accomplishes them by processing the big data that users generate as they interact with various systems and then using that data to motivate, engage, and drive action.

This Is Not a Game:

The Difference Between Games and Gamification

Gamification is not about creating games at all. With gamification, your core experience is the centerpiece, and the gamification mechanics go around it. The name itself implies this—you have something that already exists—a website, a loyalty program, or expense-reporting software, and it is being transformed, gamified, with the addition of gamification mechanics. And that core experience has to have some intrinsic value of its own. Imagine that you have a website that shows the latest traffic conditions but that only updates once a week. If that’s the case, no amount of gamification is going to help you—before you can even think about gamification, you need to refine your core value proposition. Once you have that nailed down, the gamification mechanics can layer on top of it and drive engagement, activity, and loyalty around it.

Games Are Intrinsically Motivating

So clearly gamification isn’t building games. But it does have a lot to learn from the world of games because games are so powerful at engaging people. Recall our five intrinsic motivators:

• Autonomy: I control.
• Mastery: I improve.
• Purpose: I make a difference.
• Progress: I achieve.
• Social interaction: I connect with others.

The enjoyment from playing games comes not just from the joy of winning (after all, what do we really win, anyway?) but also from the path to that win—in which most of these motivators are triggered:

• You have complete autonomy to make your own decisions in the course of the game. Should you buy Park Place? Sacrifice your pawn for the greater good? Go all in? Within the framework of the rules, you decide how you want to accomplish your objectives.
• You want to get better at the game—that’s the mastery motive. When a game loses any ability for you to get better, you quickly grow bored. Little kids love playing tic-tac-toe until they realize that following a simple set of rules will always lead to a tie and that there’s no way to get any better, at which point they get bored and move on to the next game. Then, as they grow older and smarter, the same thing happens with Candy Land, Chutes and Ladders, and other games until they finally reach games that require skill, strategy, and meaningful choices. Those games, then, can be played for a lifetime.
• When you’re playing a game, you willingly and intentionally set aside the real world and real life and, for the duration of the game, enter what Dutch historian Johan Huizinga referred to as the “magic circle.”1 You are in another world, the game world, and in that world you typically have a single driving purpose—to win. And while that win generally won’t make any difference in the real world, inside the game world, it is the sole reason for existence.
• Games typically give players a clear sense of their progress. If the purpose is to win, then at any point in time, how am I doing toward that goal? Pieces on the chessboard, number of chips in poker, and properties and cash in Monopoly all are clear indicators of progress.
• Social interaction is the primary reason many of us play games in the first place. Games give us a magic circle, a virtual world, in which to engage with our friends and family and compete, collaborate, and connect in ways that we don’t in real life.

Technology in the gaming world serves only to amplify many of these motivators—you can now play with anyone around the world at any time, track your progress in infinite detail, and engage in experiences that provide even more autonomy (“open-world games”) and opportunities for mastery. You also have the opportunity to save statistics about your game play and use those statistics to compete and earn status in a community.

Adding the Spark of Gamification Mechanics

It was out of this technological revolution in gaming that most of the key components of gamification were born. Video game designers have known for years how to incentivize and motivate players by leveraging the data their games generate. Whether it’s the player’s score, enabling players to “level up” at key milestones, providing players with achievements to unlock, or supplying players with a leaderboard of competitors, video games successfully, consistently, and repeatably use data to motivate players to new heights.

Now that same kind of data is available outside video games, from all the systems that we interact with every day. Combine this new big data set with our enhanced understanding of motivation, and we have a powerful mixture to motivate and engage customers, partners, and employees. Much as an electrical spark ignites a fuel mixture in an automobile engine, gamification mechanics become the “spark” that energizes and ignites the mixture of human motivation and big data to provide a compelling user experience.

The 10 Key Mechanics of Gamification

These mechanics are inspired from the world of video games but have been proven to work in any context, and they hit on both intrinsic and extrinsic motivations.

1. Fast Feedback

Intrinsic motivators: Mastery, progress

In online gamification experiences, fast feedback is provided in the form of notifications. These typically appear as “toast” messages, the small windows that slide in from the bottom of the screen that e-mail and instant-messaging clients use to let you know when you have new e-mail or someone is online. In gamification experiences, they’re used to let the user know that he’s accomplished a goal or hit a milestone, to cross-promote other content and activities, to thank the user, and to suggest a next action for the user to take. This last one is especially important—many of your participants will interact with your experience in very lightweight ways, so your challenge is to pull them down the participation chain and motivate them to engage more deeply with you. At a point in time when you’re notifying users of success, suggesting a next action is a great way to do that.

2. Transparency

Intrinsic motivators: Progress, social interaction

In online gamification experiences, this encompasses several of the elements you might see—an individual profile page, a list of goals and the user’s progress toward them, team profile pages, and both individual and team leaderboard pages. Gamification is motivating people through data, so a big part of the user experience is making that data visible and digestible to users.

3. Goals

Intrinsic motivators: Purpose, progress, social interaction

Aside from giving participants a purpose, explicitly defined goals also serve to clearly identify to participants what activities are possible in the experience, as well as what behaviors are valued by the program designer. In gamification programs, goals will usually manifest themselves as a simple list that’s visible to the participant. Each goal will typically include:

• A description of what needs to be done to accomplish it
• An indication of how much time is left before it expires
• A description of any reward for completing it
• One or more visual indicators showing the user her progress toward the goal
• Indications of others in the community who are working toward or have accomplished this goal

Goals can be of various types but probably the most important attribute is that they should be personalized (or segmented)....The participant attributes that are used for personalization can be relatively static things, such as gender and geographic location, or they can be more dynamic, such as, “Has completed training on Product X.” This enables participants to see only what’s relevant to them, individually, at any point in time.

4. Badges

Intrinsic motivators: Mastery, progress, purpose, social interaction

A badge is an indicator of a specific accomplishment or conquest of a specific task or skill—think Boy Scout badges or medals in the military.

[Within a] community, badges have a significant meaning, and that’s what gives them their ultimate value, both to the individual as a mark of achievement and status, and to the community as a way of identifying engagement, skills, and expertise.

Often badges will be awarded for completing goals, so this gamification mechanic and the previous one are often intimately tied together.

Other interesting ways to use badges include:

• Tapping into people’s desires to collect and complete sets (such as baseball cards or any other collectible hobby)
• Enabling users to pick their favorite badges and visibly show them off to their peers
• Creating badges that participants don’t know how to earn, so they have to figure it out
• Creating badges that participants don’t even know exist, so they are surprised and delighted when they receive them

5. Leveling Up

Intrinsic motivators: Mastery, progress, purpose, social interaction

While badges are indicators of specific accomplishments or skills, levels are used as a shorthand way of indicating long-term, sustained achievement and status....Levels also serve to provide players with intermediate goals (small wins) in the long arc of a game.

In gamification programs, levels are frequently displayed anywhere that a user’s name is shown, as an important, highly visible shorthand indicator of the user’s status in the community. Users typically will level up when their point balance reaches certain predefined thresholds or when they accomplish a predefined set of goals. Reaching a level also can act as a key to unlock certain special abilities, goals, badges, content, and rewards.

6. Onboarding

Intrinsic motivators: Mastery

Players get live experience at “doing,” coached along by the system, until they feel they have sufficient mastery to venture off on their own.

It doesn’t feel like training, it doesn’t look like training, but it is training. And businesses that can train their customers to use their products effectively will drive sales and renewals, businesses that can train their partners how to sell their products better will amplify their revenue, and businesses that can train their employees how to perform more effectively and efficiently will see a direct impact to their top and bottom lines.

Gamification programs often use these onboarding techniques to teach participants complex skills or concepts.

7. Competition

Intrinsic motivators: Mastery, social interaction

Competition can take many forms, from straightforward leaderboards (high-score tables), to competing for scarce assets, to just wanting to one-up your neighbor.

Focusing specifically on leaderboards...when you track big data about user activity, you can do a leaderboard on anything—who has shared the most videos, closed the biggest deals, or contributed the best content—and drive competition around it. And all this can be done on an individual level as well as on a team level.

Leaderboards are a double-edged sword, so they should be used thoughtfully. If you have a gamification program with 10,000 participants and a top-100 leaderboard, then 9,900 participants are probably not very motivated by it and in fact may be demotivated. New users who join your program will see the top performers, think “I’ll never catch up,” and not even bother to engage. There are three ways to implement leaderboards to address this:

• Use different time frames. Along with an “all-time” leaderboard, also have a “today” or a “this week” leaderboard. In this way, everyone, regardless of how long they have been participating with your program, always has a chance to get on a leaderboard.
• Shrink the context. Instead of showing users a global leaderboard, just show them one with themselves and their friends or their work colleagues. Most people work and play in small enough units that this cuts down the size of the leaderboard to something where the user can always have a place.
• Show “me.” Rather than always showing the top x, instead, always show current users where they rank, even if they’re in 1,000th place, and show them a few people above them and a few people below them. This gives users a sense of where they rank, gives them clear targets for what they need to do to move up rungs of the ladder, and lets them know what they need to do to prevent themselves from moving down rungs. At the end of the day, the most important person to users is themselves.

8. Collaboration

Intrinsic motivators: Purpose, social interaction

From our social-interaction motivator we know that people have an innate need for social connection and as such love to compete and collaborate as part of teams. Teams provide an opportunity to connect and bond with others “like” you (even if the only similarity is that you’re on the same team) and work together as a cohesive unit to accomplish goals and compete with other teams. At the same time, the peer pressure of not wanting to let down your peers or be seen as the weakest link can amplify behavior and drive dramatic increases in individual and team performance.

Teams can be as big as your entire community, working together to reach a collective goal....Or they can be smaller and more focused, with multiple teams competing in a “league”...affinity is what makes teams so powerful. When people are on teams, they are no longer looking out solely for their own best interests but also for the best interests of the overall team and the other individuals on it. And they’re motivated to excel by their desire not to let their colleagues down.

In gamification programs, teams are extremely effective. Teams work together to beat other teams and to collectively accomplish team missions and earn team badges that benefit all the members. In the workplace, teams can be based on obvious structures (e.g., project teams, business units) or not-so-obvious structures (e.g., cross-business unit, cross-geography, random) and used to drive competition, collaboration, networking, and knowledge sharing in an organization.

9. Community

Intrinsic motivators: Social interaction

Many of the gamification mechanics described here lose a significant amount of their value without a community—there’s no one to compete with, no one to collaborate with, no one to show off my status to, no one to see my badges, and no sense of life and activity. So community, while not essential, is often a crucial prerequisite for gamification, depending on your context. We’re social creatures, so we want to see what others are doing and want them to see what we’re doing. The primary mechanism in gamification programs for providing this ambient awareness of what everyone is doing is a news feed, much like Facebook’s news feed. Gamification systems will automatically add to the news feed any time a user makes a meaningful accomplishment (i.e., completes a mission, earns a badge, or levels up) so that the achievement is socialized to the user’s colleagues and to the rest of the community, and they can both notice and respond. The news feed serves multiple purposes:

• To spread the word about participant accomplishments
• To surface and cross-promote people, content, and activities
• To create a sense of life and activity in the experience
• To establish a social norm—“these are the accepted behaviors here”
• To let you know what your inner circle of friends or colleagues at work is doing

In gamification programs, typically the experience that’s being gamified already has community elements baked in, and the gamification mechanics integrate seamlessly into them. If your experience doesn’t currently have community, it’s still possible to use gamification, but it may not be as impactful.

10. Points

Intrinsic motivators: Progress, social interaction

For participants, points are:

• A number
• That goes up and down
• That indicates how much of something you have
• And that you might be able to spend

For businesses, points are:

• A way of tracking or scoring an attribute of a participant
• A way of rewarding a participant for doing something of value to you
• A way for your participants to reward each other for something
• A way to give your participants spending power

So, in gamification programs, points can be a way of keeping score, such as your number of connections on LinkedIn, in which case their primary function is to convey status. They can be a currency, such as your frequent-flyer miles, which your participants will want to earn and then burn (spend). And they can be the foundation for some of the other gamification mechanics, such as leveling up, as well as a reward for accomplishing goals.

Some other “pointers”:

• A gamification program can have multiple types of points so that you can score or reward your users across multiple dimensions. For instance, you might have “sharing” points and “contributing” points, and users would earn the appropriate kind of points depending on the actions they take.
• You can name your points anything, but if the name has a monetary connotation, such as “bucks” or “dollars” in it, then participants will expect to be able to spend them.
• If points are spendable, then separately track each user’s current point balance (what she currently has to spend), as well as her lifetime point balance (the total points she’s ever earned—this number only goes up and never goes down). The lifetime point balance typically corresponds to the user’s status and level in the community and shouldn’t go down when the user buys something.

Rewards = Meaningful Value

Gamification Mechanic Zero: Choice

You may have noticed that the intrinsic motivator of autonomy isn’t listed with any of the 10 gamification mechanics. This is because autonomy, in the form of choice, is an integral part of gamification and underlies nearly all the mechanics. Participants in gamification programs have choices: which goals to pursue, how to pursue them, whether to engage in competition or collaboration, how to spend their earned points, and more. And these meaningful choices serve to engage participants while fundamentally affecting the nature and outcomes of their gamification experience.

With today’s research and experience, we now know better. All those things just mentioned—badges, levels, and so on—are also being motivated from outside as well, so the gamification mechanics are really addressing a mix of intrinsic and extrinsic motivations.

The Four Types of Extrinsic Motivation

Even self-determination theory (SDT), which considers intrinsic motivation to be more powerful than extrinsic motivation, acknowledges that not all extrinsic motivation is the same. There is a subtheory of SDT called organismic integration theory2 (OIT) that outlines four different types of extrinsic motivation based on their relative levels of autonomy:

• External regulation. Someone is making or incentivizing you to do something. For instance, when my wife tells me to do the dishes, she is externally regulating my behavior.
• Introjected regulation. The behavior is related to my ego, self-worth, and self-esteem. Depending on my motivations, going to the gym could be considered introjected.
• Identified regulation. This occurs when you consciously value a goal or regulation so that it’s accepted as personally important. Religious behaviors often fit into this category.
• Integrated regulation. This occurs when you’ve fully assimilated the regulation or behavior into your being. This is the closest to intrinsic motivation but is still being done for external reasons rather than the joy of the behavior itself. Any kind of behavior, even doing dishes, can become integrated if the context is set appropriately.

People often take meaningful value to mean cash or cash-value rewards. Those certainly have a place, but they’re by no means the only kind of reward or necessarily the most motivating. People value status, as is clearly indicated by job titles at work and rank in the military.

• Recognition and appreciation are simple rewards that can have a profound impact, whether or not they have any monetary value associated with them.
• Early and exclusive access can be very valuable to people.
• Power—giving people new abilities that they didn’t have before. This can be anything from budget authority to spend more at work, to moderation rights in an online community, to the ability to switch your flights at no cost in a frequent-flyer program. Your reward for participating is additional capabilities that enable you to participate in new, previously inaccessible ways.
• Prosocial incentives—enabling participants to give to others. We know that social interaction is one of our key motivators.

Inherent in the view of the critics mentioned earlier, that there’s an unfair value exchange between the business and the user, is a cynical belief that people are dumb and can be taken advantage of indefinitely. I don’t believe that this is true—we’ll engage with anything for a little while, if only because it’s shiny and new, but if we fail to derive meaningful value from our engagement, we’ll disconnect and walk away. So it’s imperative, when you’re thinking about how to apply gamification to your business problems, that you understand what’s in it for your end users and what meaningful value you’re providing to them.

The leading cause of failure is poor gamification design, which comes from a lack of understanding, experience, and a proven process. My goal with this book is to arm you with the knowledge and tools to make you one of the successes.

If you want to learn more you will need to buy the book. Loyalty 3.0 by Rajat Paharia.