Customer Experience Design

Today, more and more products are connected, in the sense that they have some kind of communications capabilities to provide their location and other telemetry such as health, usage and other key datum.  These connected devices include smart phones and TVs, home automation and security products, and innovative new devices that are becoming increasingly common.  And, this is happening both in the home and at the office.

One of the most innovative of these products is the Nest learning thermostat (and now the new Nest Smoke Alarm).  This beautifully designed device is gaining rapid consumer acceptance, and is now even distributed by energy companies as an incentive to manage energy more responsibly.  Nest is a wireless-enabled device.  From the moment it is turned on, it searches and connects to the wireless network within the home, and even calls back to a cloud-based server to notify the company that it is on, at this location, and working. 

While this is all well and good, the designers of this product took everything a generational leap forward.  They designed the customer experience into the product itself!  Even prior to rollout, Nest executives seemed to know that they had to deliver a world class customer experience that included easy installation, quick and accurate problem resolution, and most importantly an army of independent yet certified Nest technicians wherever Nest was sold.  Through intelligent design and implementation of a contractor strategy, they have succeeded in mobilizing an entire field force, none of which are on the payroll, to become enthusiastic Nest evangelists.  Nest owners have their own digital place to report problems, open cases, seek out these technicians and even rate them post service call.

Most product manufacturers have little experience in a direct-to-consumer relationship, having been removed from the actual customer by retail channels, both on and off line.  To contemplate a direct-to-consumer experience, manufacturers must consider the following five key areas of that relationship:

Registration: How do you get customers to register their product(s) with manufacturers?  This involves everything from package design and in package forms, code-based on device registration.  Regardless, the manufacturer must have a carefully designed incentive to drive higher registration rates.

Engagement:  Once registered, how do you drive engagement with those customers?  Key here is the notion of strategic lifecycle messaging.  Contrary to accepted batch and blast emails strategies, lifecycle messaging is a formal and well thought out program that involves triggered, data-driven messages at key points in the lifecycle with a customer.  This can include post-purchase, at registration, pre-warranty expiration and any other event where an opportunity exists to provide highly targeted and relevant messaging.

E-Commerce:  At every point of the lifecycle, manufacturers have the opportunity to drive additional, hidden revenue streams through the complete integration of ecommerce.  This can be during the registration process, within each lifecycle message, and within an owner center, set up specifically for each individual customer.

Service:  With registered customers and within owner centers, manufacturers have the opportunity to provide self-service solutions to both increase customer satisfaction, as well as deflect service costs.  This requires having the knowledge and support assets ready to be delivered on-line.  Additionally, customers should be able to log support issues and initiate service cases directly from their owner center.

Support:   Should a problem occur, how does a manufacturer effectively deliver an in-field service experience that enhances the overall brand experience, and solidifies the customer relationship?  This is made harder when the manufacturer must rely on independent 3^rd parties for support.  But even with fully owned support, quality, reliability and customer satisfaction must be continually managed and monitored to deliver that experience.

Customer Experience Design involves weaving each of the above functions appropriately into the overall customer experience, in such a manner that the experience is optimized for each customer.  It is important to note that this experience must be considered in terms of many customer “flows,” with a flow being defined as the steps and process by which a customer accomplishes a specific set of tasks with a targeted goal in mind.  For example, there is a registration flow designed to minimize drop-off and maximize registration.  There is a service flow for each identified potential support issue.  And there are multiple purchase flows that result in add-on sales of both ancillary and related products based on current customer holdings.

The art of Customer Experience Design is to identify each customer goal, design flows for those goals and define and implement the content that is dynamically targeted for each individual customer, including the specific events and messaging strategies to support optimizing the results of each flow.

The benefits of Customer Experience Design are significant:

Direct, High Margin Sales:  By providing the ability to buy additional products and services, manufacturers can define new sources of high margin revenue, outside of margin crushing retail channels.

Enhanced Customer Satisfaction:  Giving customers the tools they need to have a direct relationship with the manufacturer only enhances customer satisfaction.  This leads to customer advocacy in the form of reviews, recommendations, social sharing and many others.  Turning customers into advocates also increases the value of that relationship.

Decreased Support Costs:  By designing service and support flows into the experience, brands realize a significant decrease in support costs, including fewer phone calls and reduced return rates.

Designed right, Customer Experience should become a true profit center for the manufacturer, and pay for itself in just a few short months.  Also, this can be done as an enhancement to the retail channel, and not a threat to it, as that channel itself can be designed into the overall experience.  Today, every manufacturer, whether product be connected or not, can benefit from proper, strategic customer experience design to achieve significant and lasting benefits in the overall customer relationship.

Making Optimization Work

It wasn't that long ago that direct marketers were a breed apart: data-obsessed spreadsheet jockeys who were constantly tweaking the knobs and dials of campaigns to yield incrementally better results.

Now, of course, everybody's data-obsessed; everybody's busy tweaking the knobs and dials. If you're marketing digitally, you're a direct marketer -- period.

Think about some of the hot trends in digital marketing -- from behavioral retargeting to real-time bidding on ad exchanges -- and they're all about direct marketing to individual consumers. Even image-burnishing branding campaigns that don't have an e-commerce component (i.e., they're not specifically designed to prompt a consumer to click through and make a purchase) are deployed using cookie-based data to target, in real time, consumers as they surf the web.

What direct marketers have known for years is that more data means better targeting, and better targeting means better results. And the best results are all about optimization. Of course, "optimization" means different things to different people. That's the problem with industry buzzwords: they tend to get diluted and distorted. So let's start with a couple of conventional dictionary definitions:

1. Making the best of anything.

2. A mathematical technique for finding a maximum or minimum value of a function of several variables, subject to a set of constraints, as linear programming or systems analysis.

When most companies talk marketing optimization, they mean the former (basically, Let's give it our best shot!). But the "mathematical technique" approach to optimization isn't necessarily complicated either, conceptually speaking. For instance, in key marketing areas such as email- or website-optimization, the most common techniques used to optimize are A/B testing and multivariate testing.

With A/B testing, a marketer will deploy two versions of an email, or two versions of a web landing page, and watch how each performs. The difference in metrics -- e.g., open rates, click-through rates, conversion rates, etc. -- might be subtle, or they might be dramatic, but either way the goal is to pick a winner and then keep on testing with new A/B sets.

Multivariate testing simply expands the number of elements that can be monitored at once. Essentially, though, A/B and multivariate testing are sort of a general version of "making the best of anything." They're old-school, see-the-forest-not-the-trees approaches in that they look at consumers as relatively monolithic groups; the underlying characteristics of individual consumers are ignored. The goal may be to try to get as many trees as possible in the consumer forest to sway a particular way, but the focus isn't on any individual trees within that forest.

The traditional response to the underlying weaknesses in A/B and multivariate testing approaches has been to customize content based on individual data elements - e.g., location, age, sex, etc. - or by delivering different content versions based on statistically determined segments. But in no case has specific content been statistically and mathematically optimized for each specific consumer according to their relationship at that point in time (i.e, "in real time") with a brand.

Optimization only gets really interesting when individual consumers are regarded as, well, individuals. Consider, for instance, a 34-year-old working mother, an existing customer of a brand, who visits a brand's website. Cookie-based data can tell an incredibly rich story about her that can allow the brand marketer to, you might say, hyper-optimize. The idea is to "see" the website visitor as a specific consumer with a relevant past - meaning she has a transactional history with the brand consisting of all her past purchases, as well as a track record of reactions to marketing campaigns (e.g., emails opened, clicked, etc.).

Wouldn't it be cool if the next email sent by the brand contained references to the content she's just consumed, as well as suggestions about a next logical purchase based on past purchase history? Imagine if the email also contained messaging specific to her psychographic characteristics. And then suppose an offer included in the email had been tailored specifically to her needs and desires based on real-time analytics.

That's the potential of optimization. When optimized campaigns work, they can be incredibly powerful for brands, and heartening for the consumer, who no longer feels like just another face in the crowd.

Read more: http://www.mediapost.com/publications/article/150752/what-you-need-to-know-about-real-time-optimization.html#ixzz2fMJkxud1

Behavioral Personas In the Mainstream

In the world of omni-channel offer optimization, we tend to devalue those who tout their demographic-based marketing plans. Why? Because they are based on a system developed before the data-rich consumer world of digitization. And more still because personas are far better indicators of consumer subsets and thus a statistically superior methodology for crafting content and messaging that moves the bottom line. After years of learning and unlimited means for parsing and making data actionable, we are dying for the big marketing machines to “get it” -- and even more so, to “implement it.”

So it was with a cheer that I read this recent article from the savvy Joe Mandese of MediaPost who explains how NBC News Digital is switching from a demographic-based ad targeting method to a persona-based one -- in a system that uses consumer behavior within the digital news stream, no less.

In that post, Kyoo Kim, vice president-sales NBC News Digital, explained that “focusing on behavior versus demographics gives our customers better insights into the tendencies of our viewers.”  Instead of parsing content experiences by traditional class-gender-race-location-based data, they were making the moves to deliver experiences based on these personas:

·         “Always on”: Consumers who are constantly connected to news feeds across multiple devices.

·          “Reporters”: “Digital natives” who grew up consuming news via online and mobile media and who disseminate news.

·         “Skimmers”: Consumers who are not passionately connected to news.

·         “Veterans”: Consumers who primarily rely on traditional media as a trusted source for news.

As we have deployed behaviorally based personas for years, we were thrilled, of course -- but not completely satisfied. Why? Because this move alone is not sufficient to optimize the objective of NBC News Digital, which at the end of the day is to sell all ad space at the highest price possible. 

Let’s break that down a little further.

Personas must be developed with a purpose

Any persona scheme to be developed and deployed must have a solid business objective. Two different business objectives could end up with two wildly varying persona schemes. Personas are a textured output of rigorous statistical analysis of data, colored in with domain expertise. They should quickly emit data points with every transaction -- your customer is not a number. 

In order for the process to work, the statistical analysis must be guided by an objective, which may be to “register,” “purchase,” “sign up,” “open,” “vote,” or “donate.”  In this case, NBC News Digital has developed its personas based on historical digital news consumption. Does this provide a true differentiator to advertisers who want those personas to buy something from them? Not necessarily.

It seems that the NBC personas are useful in helping to optimize the timing and frequency of display ads, as well as the actual construct of the ad, but not necessarily the content of the ad. Combining purchase and intent data in the development of the personas would be a great next step.

Demographics can still play a role

Once behavioral personas such as these have been developed, demographics still play a key role. First, if there are any demographic consistencies among the behavioral personas, those demographics can be used to help physically describe the personas to be more understandable to advertisers. For example, the “Reporters” above would seem to trend younger since they grew up with digital media, but are they statistically younger than the “Always on”? And the messaging of marketing content is always a key consideration. Suppose that you are selling the benefits of Product A.

Wouldn’t it make sense to message those benefits differently to a family than a single renter -- although they both reside in the same persona, based on digital news consumption? Adding a demographic edge to the personas would greatly also enhance this effort for advertisers.

Personas must be narrow enough to provide real value

In this case, NBC News Digital has developed four personas. Generally, successful projects have between 8 and 12 personas in order to provide enough focus to enable successful differentiated content strategies.  We have found that schemes with five or less are simply too broad to be successful. There is too much diffusion in a few large personas to provide real value in targeted marketing efforts. Adding in purchase and intent data would certainly help advertisers in media buying across the NBC News Digital properties.

Despite these issues, NBC News Digital must be applauded for taking this important first step in moving from demographics to behavioral personas. It is the only way to engage consumers with differentiated content, but more progress must be made in order to sharpen and refine these personas. As test results begin to pour in, NBC News Digital must use these results to continually improve their personas in order to achieve their objective of maximizing ad revenue.