In the customer experience world, memory is a powerful force that shapes consumer-brand relationships. Unfortunately, memory can be misleading.
Thanks to Nobel prize-winning psychologist Daniel Kahneman, we know that a consumer’s memory of an experience—good or bad—does not necessarily reflect an honest average of that experience. Instead, memory is influenced by both the most extreme point and the end of an individual experience, or what Kahneman calls the “peak-end rule.”
Simply put, memory is tied to emotion, and consumer-brand relationships are emotional. The way consumers feel about brands is driven by the memories co-created through mutual experiences. The question is—how can we more effectively use our ever-increasing trove of data to continuously make those experiences better?
Brands utilizing customer perception data alone cannot be expected to productively improve upon the execution of their customer experience. As Kahneman describes, people have two selves: the experiencing self (a biased perception of what’s happening in the moment) and the remembering self (an often-distorted view of what is recalled in aggregate). Simply relying on perception data tells only one-half of the story. Of course, the same can be said about leaning too heavily on operational data. Individual performance indicators don’t mean much if you can’t link them to your end goal of creating strong customer relationships.
Brands can’t control consumer perception, but they can influence it through the intentional design and execution of their experiences. Success is found by striking a balance between the volatility of memory and the standards and processes proven to have the greatest impact on how consumers experience your brand. Use your data to get there with these four steps:
1. Determine outputs and inputs—then aggregate.
With access to so much information, it can be a challenge to determine which data points will bear the most weight for your brand. That’s why step one is understanding the data you have at the touchpoint level and spanning across the entire customer journey. The easiest way to do this is by classifying your data into two types—outputs and inputs:
Outputs tell us what consumers perceive (e.g., the voice of the customer, social media) Inputs show operational performance (e.g., wait time, compliance, problem resolution)
Because customer perception does not always reflect the reality of a company’s performance, outputs need to be brought together with inputs to determine the true state of your customer experience. This baseline is critical for identifying which specific tactics are required to really move the needle on your CX. It will also allow you to establish better governance and efficiency across historically disconnected measurement programs by creating one source of truth for data and, more importantly, a centralized environment for managing the resulting actions and improvement efforts.
2. Prioritize where to focus through analytics.
Sorting your data is the easy part. You’ll still have to make sense of what the data tells you—and that requires analytics. Predictive analytics can be used to correlate your customer and performance data sets to determine which operational practices have the highest likelihood of giving your brand the greatest future lift in customer perception.
Brands are sometimes inclined to start with their lowest scoring metrics, but not all touchpoints are created equal. There are likely areas where you are scoring just below where you’d like to be, and where a little more movement in the right direction can have a major impact on your overall customer experience.
If you’re a car rental company, customers will tell you that the efficiency of the rental process is critically important. At first glance, you might want to focus on a metric like reducing the time it takes for a customer to pick up their vehicle. Without analyzing how those operational behaviors impact customer perception, you may never know that increased speed of service could unintentionally lead to negative consequences later in the customer journey. Perhaps you do not take the time to fully explain fees up front; this will potentially cause misaligned expectations at the end of the experience, negating any positive emotions generated by earlier efficiencies.
You can find opportunity areas by incorporating analytics across data sets. Conducting a key driver analysis with your data is a great place to start. By identifying which parts of the customer experience are most important to your customers, you can determine which operational factors are influencing perception and prioritize action, such as resource allocation and training. This will also help you to determine whether an issue is the result of the design or execution of your experience.
3. Connect opportunities to solutions.
There is no need to completely reinvent the wheel when connecting opportunities to solutions—often it comes down to a simple case of recommending the tools you already have for the right job at the right time, making the choice to take action the easy thing to do.
Brands already collect vast amounts of data regarding their customer experiences and often make significant investments in creating solutions to address common challenges. In my experience, there is often still a gap in connecting those solutions to the challenges they’re intended to solve, making improvement inherently more difficult than it needs to be.
Brands fail to effectively serve up the solutions available at their fingertips—those pioneered by corporate or developed by individual operators—because they are often organized differently or live in disparate systems (e.g., knowledge management system) than how and where the challenges are reported (e.g., business intelligence tool).
Once you know the most common challenges in your customer experience, start by developing a common taxonomy and mapping those challenges to your existing solutions (i.e., training, SOPs, physical assets, etc.). Note, this relationship is not one-to-one but one-to-many where a combination of solutions can address a single challenge. Then, establish a simple interface (e.g., an online action planning tool) that allows users to see their challenges and solutions together in one integrated environment that’s simple and actionable. Once you have this foundation, you can enrich it over time, adding new solutions through systematic development efforts and crowdsourcing amongst your stakeholders.
Just as our data exercise in step one provided us with a baseline from which to plant our seeds and grow, so too can our foundational solutions offer opportunities to innovate.
4. Monitor solutions, then evolve.
What gets measured gets done. What’s ironic about customer experience measurement is that many programs focus on the score as opposed to what’s being done to improve it.
To continuously improve—and do it most effectively—you should monitor the progression of metrics that account for customer perception and internal remediation efforts alike. This creates a system of checks and balances which holds your stakeholders accountable for managing what is in his or her direct control: the operation, as opposed to a score that can be influenced by bias and external factors.
Ideally, a holistic tracking program captures data around the resulting actions that have been performed for each opportunity, including which solutions were applied, when those remediations went into effect, and most importantly what happened afterward (i.e., did customer satisfaction actually improve as a result of my efforts?).
It’s this last point—associating future performance back to specific solutions—where you can drive significant untapped value for your organization. Instead of solely focusing on the gaps in your experience, it allows you to identify and prioritize solutions that are making the greatest impact based on what really works. On the flip side, it also allows you to find gaps in your solution library where you may not be providing the ideal level of support. This creates a virtuous feedback engine that allows your organization to continuously improve the tools for managing the customer experience, as opposed to simply monitoring the experience itself.
CX starts and ends with people.
Thanks to advancements in technology and analytics, a lot of the legwork has been removed from the process of collecting data and generating insights. However, in this age of big data and hyper-transparency, it’s easy to get caught up in the systems and processes like those described above and lose sight of what actually drives change: people.
While a deep understanding of customers is fundamental to managing your experience, it’s ultimately the understanding of the needs, perceptions, and challenges of your internal stakeholders (e.g., your frontline employees) that will make or break any efforts to continuously improve. This comes down to knowing what your stakeholders need, when and how they need it based upon their unique circumstances, and most importantly, creating the environment that empowers them to easily choose to take the right action. So, as you go back to solving your biggest customer experience challenges, keep in mind that the most innovative strategies and the most ground-breaking insights don’t mean anything if you don’t put humanity and empathy at the center of everything you do.
For more on how to get the most out of your CX data, visit www.materialplus.io
This sponsored article was written by Rick Reilly, SVP, customer experience, Material.
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