Jim’s Coffee Shop is a regional coffee chain that’s become something of a local phenomenon thanks to its unusually strong commitment to personalized customer service. They recently hired a new Chief Executive Officer, known for building upon the success of young companies and turning them into household names. He is committed to building the chain into a national brand, but he wants to ensure that it’s done in a way that feels authentic to the company’s core value of building strong customer relationships.
His “customer centricity initiative” is his top priority, and he expects the next 24 months to be focused on transforming the company’s technology, insight development, and customer engagement strategy as it strives to become one of the top national coffee chains. The initiative is bold, and Jim’s Coffee Shop is starting from scratch. Almost everything related to the application of customer knowledge had historically been done by individual employees at a specific coffee shop. In order to achieve scale, they would need to make some big investments, and some big process changes. And, of course, they knew they would face challenges along the way. Let’s take a look at Geek Nerd Suit in action, beginning with chapter 5.
To get started, Jim’s Coffee Shop needed to focus on the basics, including simple things like remembering a customer’s last order in the mobile app to make reordering a favorite drink easier. They also needed to start tracking basic behavioral data, such as how frequently (or infrequently) customers made a purchase. This basic information would allow them to start targeting promotions to increase visits among the more casual customers, and hopefully build better relationships with their best customers. Their biggest challenge to overcome at the beginning of this journey is to rocket beyond standard customer courtesies directly to things that will help build closer relationships with customers.
To address this need, Jim’s Coffee Shop invested in building a “customer preference center” that would help develop their knowledge of customers beyond the standard transaction-based measures they had been using. They opted to use an out-of-the-box solution from a standard preference center developer, but quickly realized that the standard categories that came with the solution were not going to work for their customers.
Since some customization was clearly required, Jim’s Coffee Shop wanted to be sure that the extra efforts were not wasted. Their first order of business was to figure out which types of preferences mattered most. By talking to both customers and employees, they cultivated a list of the types of preferences that were used most frequently and would make the most difference in their customers’ experience-most of them drink-based concepts such as foam, temperature, or milk preference. In addition to giving customers the ability to set these preferences directly online or through the mobile app, Jim’s Coffee Shop also analyzed previous drink order history to infer these preferences and default to these options when customers were placing orders.
The leadership team at Jim’s Coffee Shop had recently invest in new online and mobile ordering features, and customer option of these new options was tracking to expectations. A few months after the rollout, however, they started receiving a small but steady stream of complaints from both customers and employees about challenges related to the provision of customer support in the coffee shops.
There are always kinks in technology rollouts that need to be ironed out, but usually frontline employees are prepared and equipped to help customers fix them. Because the digital channels were rolled out separately, however, none of the online order data was easily accessible to employees in the shops. Orders arrived via a separate system that wasn’t connected to the main register system. If anyone had a problem with a mobile order, employees had no way to verify order history or confirm payment, which frustrated employees and customers equally.
It was clear that Jim’s Coffee Shop needed to integrate its physical and digital data systems so they could tie all customer behavior together. Industry-specific technology solutions were driving the company’s point-of-sale systems, and those systems were not easily modified. They also realized that their e-commerce platform had grown quickly since the online ordering system’s launch, and it now boasted the largest database and number of APIs. In the end, company leaders decided to use the e-commerce platform that was already in place to be their customer data master repository, while customizing the connection points and data structure so that they aligned with what already existed in the point-of-sale system. Now customer data is tied together in a way that allows real-time links to be made whenever new data is captured.
In order to keep up with the competition and set the stage for their desired expansion, Jim’s Coffee Shop knew they needed more than just their physical stores. They needed a digital presence. The company’s marketing team wanted to launch both an online and a mobile channel at the same time so they could build an integrated digital experience and spare themselves the headache of trying to add another channel later. However, with limited capital investment funds available, they found themselves struggling to navigate the internal approval process.
To begin building their case, they first commissioned a marketplace research study among current and potential customers to demonstrate interest in and intent to use a digital channel for ordering from Jim’s Coffee Shop. Customers were wildly supportive of the idea. In fact, many indicated that they had previously abandoned a coffee shop visit because of perceived long lines. With online or mobile app ordering capabilities, these customers could place their orders in advance and avoid those long lines.
Encouraged by the research results, the marketing team then got funding to build a small prototype of a mobile ordering device to implement in one store. Although not exactly the same as using a website or mobile app at home, the rapid adoption of mobile device ordering within the test store was enough to convince leadership that the demand for a digital presence was real. Ultimately, an updated website with ordering capabilities and a mobile app were rolled out at the same time across all regions where they had physical stores.
Jim’s Coffee Shop was thrilled to have all their customer data living in one place. However, it wasn’t until they saw it in aggregate that they realized how much customer data actually existed. What started out as an exciting exercise in building a body of customer knowledge has produced a mountain of data that had to be dug through to make it useful. Nobody knew how to transform it from an unapproachable pile of raw input into a gleaming source of inspiration. So instead it sat languishing, largely unused, in an ever-growing e-commerce database. But the company knew it needed to do something. Ultimately, company leaders assigned a customer data master whose sole responsibility (at least temporarily) was to address the data volume problem.
This “master” started things right by taking an inventory of every piece of data that was being captured and stored. After conducting interviews with business leaders across the organization, he noted plenty of data elements that were being captured but weren’t being used and wouldn’t be useful in the future. Everything on that list was marked “purge.” Further, he leveraged the analytics team to create models that consolidated strings of individual data elements into the core behavioral components the company was really interested in. For example, instead of keeping the individual clicks from each mobile interaction, the team tracked summaries of important details (e.g., number of clicks per visit, preferred store) and behavioral outcomes (e.g., orders placed, dollars spent). After these cleanup efforts, the data became far easier to navigate-and real insights stood out far more readily.
For several quarters, Jim’s Coffee Shop’s sales were growing at a modest but steady rate. The collective leadership team routinely rolled out new operational processes, product enhancements, and marketing communications based on guidance from their team of experienced leaders. Since business was improving, everyone assumed that the growth could be attributed directly to those decisions, and leaders accordingly felt confident that they were on the right track.
They certainly didn’t have any indication that a problem might be brewing (ahem) until, during a break at a regional store operations meeting, a few managers happened to start talking about how they hadn’t been seeing as much of their best customers. Business was good, they said, but somehow the crowd was different. The VP of sales overheard their comments. So he asked the head of analytics if someone could take a look at customer trends in those particular stores.
The analyst discovered that, although same store sales had been showing moderate but positive growth, revenue was actually starting to skew more heavily towards new, more casual customers. Conversely, the number of loyal, frequent coffee drinkers had declined over the same period. Jim’s Coffee Shop conducted a quick online survey among some of those customers who weren’t coming as often, and it turns out the rapid introduction of new products-along with the retirement of a few preferred classics-was driving them to seek other alternatives. The company brought back a few favorite drinks, and saw quite a few of those customers return.
One of Jim’s Coffee Shop’s goals for the year was to improve the efficiency of their operations, including staffing optimization. Corporate planning requested a number of customer traffic studies, and the team had clearly mapped customer arrival times at the store level. They even broke down traffic analysis into three sections of the day, loosely structured as breakfast, lunch, and dinner. In their initial report back to operational leaders, they reported that the average peak customer arrival for the morning shift was 7:30am. Their recommendation was to ensure that all employees shift to customer service functions during that window to be able to support that peak.
When the results came back to the head of operations, he immediately saw the flaw in the data: 7:30am was actually an average. In fact, two separate peaks were typically experienced in the morning. The first peak, at 6:00am, brought in a swarm of businesspeople on their way to fight morning rush-hour traffic. The second peak, at 9:00am, was created by a combination of parents who had just dropped their kids off at school and independent workers who were looking to start their day in their office-away-from-home. By staffing for a peak at 7:30pm, the company would completely miss optimizing for their busiest times.
Recognizing the oversimplification that resulted from averaging, the analytics team moved from a general practice of reporting averages to a revised general practice of sharing distributions. This helped them spot trends they otherwise would not have seen, and gave their internal clients a more complete picture of what was happening.
As part of its growth strategy, Jim’s Coffee Shop hired a new VP of customer experience to help improve the ambiance within each store and to more formally shape the interactions happening between customers and employees. Taking a cue from what worked at her previous company, this VP immediately zeroed in on efficiency tactics, shaving more than 15 seconds off the drink creation process and trying to increase the number of customers they could serve. As she personally identified with significant time constraints, getting her drink faster felt like a big win and was easily solvable with a few key changes, including a maximum customization and substitution limit on each item.
While efficiency spiked and more drinks were moving out the door than ever before, customers started to become disgruntled with the new restrictions. In fact, the ability to customize each drink was what customers liked best about Jim’s Coffee Shop in the first place. With the new “maximum efficiency” measures in place, the company started to lose what separated it from other coffee shops-a personal feel and a team of employees who wanted you to make your drink your own.
Fortunately, the VP of customer experience was accustomed to spending time on the floor, and she made sure to work the new process directly so that implementation went smoothly. From behind the counter, things seemed great. But after a few hours spent just sitting in the coffee shop, she started to sense customers’ frustration. After regrouping with the front-line managers, she came up with a refined process that allowed the customization to come back in. Although it added a few seconds back to the drink fulfillment time, it also caused a jump in customer satisfaction.
Jim’s Coffee Shop’s structured customer database enabled them to develop a basic understanding of who their customers are. They had started to build out a customer foundation, and had access to customer profiling and customer attributes. The analytics team was also developing behavioral summary reports on a regular basis. However, the company had not yet conducted any research to explain why the things they were seeing were happening in the first place.
This wasn’t a problem until the company started actively tracking the success of their newest market-the West Coast. Although existing customer behavior had been used to design the launch of West Coast stores and build a business forecast, results were not living up to expectations. To figure out why, they needed more than just a summary of what was happening. They needed an attitudinal overlay to explain why customers weren’t as enthusiastic as the company had hoped.
So, they started doing some research. They talked to West Coasters who had tried Jim’s Coffee Shop and those who hadn’t. What they learned was that customers in this particular region really valued locally sourced menu options and ingredients-something they never would have learned from analytics alone. Based in this insight, the regional director worked with the product team to add some new items to the menu, and the marketing team started promoting those products. Within a few weeks, sales began to improve and to better align with expectations. The success of an expanded approach to insight encouraged leaders to consider multiple types of customer data before making other big decisions.
The success of Jim’s Coffee Shop’s continued expansion came with an unintended consequence. As the company sought to reach into new markets, they necessarily had to invest in new customer acquisition efforts. Not surprisingly, this emphasis on acquisition caused them to lose focus on maintaining their relationship with active customers in existing markets. Those customers started to feel like they were no longer a priority, and Jim’s Coffee Shop started to see the effects.
While most customers visited their local coffee shop on a daily basis, recent customer reports showed a decline in visit frequency among the chain’s best customer segment. Amid all the new customer volume, this decline had initially been missed.
To address this attrition problem, the company commissioned research to uncover the source of customer dissatisfaction so they could directly address what was causing the problem. Based on lapsed customer research findings, they learned that customers had first enjoyed Jim’s Coffee Shop because of the local feel and personal touch when they interacted with employees. The focus on new customers had caused existing customers to feel less valued and to receive service that fell below their expectations. Armed with knowledge of the challenge, they launched a “we miss you” campaign inviting lapsed customers back, coupled with employee training that emphasized personal interactions. And they learned an invaluable lesson: never ignore the heart of the customer lifecycle.
Jim’s Coffee Shop’s marketing team was pretty amazing. They were engaged, they actively sought to understand their customers-and they were customers themselves. They also believed in the power of the messages they had to deliver. Their big challenge, though, was that they had too many of those messages.
The company’s marketing team was organized by channel. There was a strategy team, a mobile team, an email team, a direct mail team (because they’re still old school like that), and a site marketing team. They each had budgets, and for most of them (sorry, direct mail team) the cost per impression was pretty low. But as a result, a tremendous number of individual marketing communications made it on the calendar-including a daily email.
Customers didn’t need to see the same message multiple times in a row, or via all their devices. But because of the way the marketing team was structured, it took the company awhile to realize what was happening. It seemed obvious that they needed to reduce their communications. But nobody knew what the collective impact of that move would be, and less than nobody was willing to be the first to try out a reduction in frequency.
To solve this problem, they assigned a master customer communications owner who had responsibility for managing the budget-and touchpoints-in aggregate. Then they did some advanced, customer-level modeling to help them understand which customers responded to messages in which channel. The customer communications owner ran a test that “right sized” both the number of and the channels for customer communications, and proved that they were able to actually improve customer engagement with fewer, more orchestrated touches.
By this point, Jim’s Coffee Shop had addressed a number of standard growth-related challenges and come out the other end better than before. Customer retention and satisfaction were at an all-time high, and the national expansion couldn’t be going better. Nobody wanted to rock the boat if they could help it.
The company’s testing team was already stretched fairly thin due to the company’s rapid expansion goals, and there was a fear that asking them for anything else-even a small marketing test-might cause them to lose focus (and make them mad). Further, leaders were afraid that any negative results could put the company’s growth at risk. As a result, most new testing ideas were shot down before they were even fully spoken.
But continued growth would require continued evolution, and the VP of marketing believed this evolution would be best achieved through a formal testing process. Despite all rock-the-boat fears, she worked with her team to design one test. It was small scale (one email), required limited resources (creative design that could be outsourced), and was designed with a proper control group so that results could be validated. Through her sheer force of will, the test was executed. The results were interesting: the test yielded a small but significant uptick in click-through rates and mobile app orders-just big enough to convince the leadership team that testing was worthwhile.
As Jim’s Coffee Shop evolved, so did its menu. Iced coffee, blended coffee drinks, hot teas, cold teas, and some innovative sparkling fruit beverages were soon added to the chalkboard. Because the company was still heavily focused on customer service, they also allowed customers to almost endlessly customize their drinks-with everything from the standard whipped cream and array of milk options to the chance to sprinkle their drinks with fresh chili powder. The in-store beverage delivery was about as personalized as you could get, and customers raved about it.
However, despite collecting all of these intricate drink order details in its transactional database, none of them were being used to inform the company’s communications with customers. Mass emails, sent to everyone, featured five random drinks that any specific customer may or may not care about. Display ads heavily promoted new drinks, even if they were in a drink category never purchased by that customer. The mobile app remembered the last drink that a customer ordered, but it didn’t transfer preferences (e.g., nonfat milk) when different drinks were purchased. In other words, digital communications were not even on their way to being considered “personalized.”
The company spotted the problem and began building a personalization roadmap. They started by asking each digital channel owner to make a “personalization wish list” that included everyone’s thoughts on where to invest. The analytics team conducted a high-level analysis to estimate the potential benefits of personalizing in each of those areas, using industry benchmarks. Once they had identified the highest-impact channel (email, in their case), they began the process of building new email functionality. Instead of blasting a single email to all customers, they started creating different versions based on drink preferences (e.g., hot versus cold) and saw an immediate increase in conversion.
After tackling its data challenges and developing a customer-centric business strategy, Jim’s Coffee Shop was ready to complete its nationwide expansion. New markets were quickly identified, and a handful of new stores soon opened their doors. The preliminary success of the test markets had given everyone a boost in morale, and the excitement and confidence felt by company leaders was contagious. They hired aggressively, and made sure that every new employee-from cashiers to baristas to managers-understood how important the success of the national rollout was to the company.
But the intense drive to make the launch successful caused a few problems. The company had started measuring performance based on metrics like the speed of operations and the “throughput” of customers. But that focus was having a negative impact on the customer experience that Jim’s Coffee Shop had become known for. The company’s unique culture became diluted as industry-standard practices were put in place. Customers in the new markets felt like Jim’s Coffee Shop was just like all the other coffee shops they were already used to.
So, the head of customer experience called an emergency meeting for all regional and district managers, and reset the performance metrics that were being used to measure success. Instead of the heavy focus on operational metrics, managers would now also be held accountable for managing customer experience ratings. More importantly, the team received customer insight and culture training, which helped them better understand their key customer groups and reinforced the culture of customer centricity that had been diluted as the company grew. Initially, the improved customer service caused wait times to increase. But after a few months, both metrics started to move in parallel.
Jim’s Coffee Shop had been running the same loyalty program for more than a decade-a frequency-based program that provided customers a free beverage of their choice after they purchased 10 beverages of any type. The program was still managed by a punch-card system that had a slew of downsides, including frequently lost cards, unsupervised punching activity, and an inability to track customer behavior.
To piggyback on the success of its mobile app ordering system, Jim’s Coffee Shop decided to bring its stale loyalty program into the digital age. They started with their customers: watching them, interviewing them, and surveying them to understand what they loved about the brand and what they didn’t. Then they tied those research results back to customer data so that they could correlate drivers of the experience to frequency and revenue. Only after that point did they start to whiteboard new loyalty program concepts.
Some of what they’d learned was not surprising: customers wanted (expected!) to be rewarded based on how many dollars they spent on any item, not just on how many drinks they purchased; they also expected to be acknowledged by employees for their loyalty. But other insights proved surprising. Customers wanted an incentive to try new drinks (sometimes a risky proposition), and said they’d jump at the chance to influence the new menu. In the end, Jim’s Coffee Shop launched a new mobile-based loyalty program that offered rewards for both dollars and visits, and created an invitation-only online panel of high-value customers who got to vote on potential menu additions. Further, they used what they knew about their customers’ explicit and implicit preferences to periodically surprise and delight them-like by adding their favorite wafer cookie to a drive-through order, or offering them $3 off their favorite whole-bean coffee.
With growth underway and national expansion within its sights, Jim’s Coffee Shop’s leaders began launching tons of new projects designed to strengthen and accelerate the company’s development. Leaders were working on everything from building an automated ordering system and updating marketing technology to designing custom swag and redesigning the website. Many of these projects were cross-functional, and the entire company seemed positively buzzing with energy about all of the projects underway.
As expected, when the leaders of those various projects eventually came to IT for technology support, to analytics for insight development, or to marketing for a custom communication request, not everything could be accommodated. In what used to be a consensus building culture where organic growth came from aligned leadership, now there were dozens of conflicting priorities. Worse still, there wasn’t a process for identifying and prioritizing all of these requests.
Primarily because resources were deadlocked while leaders fought for project priority, the CEO of Jim’s Coffee Shop brought the executive leadership team together to conduct a prioritization exercise-twice, of course! In the first round, each leader could choose no more than three priorities for their division to pitch to the collective group. After each individual had presented, everyone had to cast their vote for three projects-none of which could be their own. At the second meeting, they had another vote, resulting in five priorities. Those five priorities were shared company-wide at all levels of the organization, ensuring that everyone made decisions that supported the business overall, not just their specific area.