CX Requires Data and Analytics
Building CX strategies without data and analytics to guide the decision-making will leave teams playing the guessing game.
In-Depth Insights Fuel CX Initiatives
Having data and analytics is just the beginning. Infusing human, cognitive decision-making into the mix allows teams to develop stronger CX initiatives.
Multiple Variables Impact Experience-Based Initiatives
Interactions. Touchpoints. There are many elements, and thus, CX terms that influence the overarching brand experience.
Frameworks Guide Your CX Initiatives
Making off-the-cuff decisions can have ripple effects throughout your experience initiatives. Using frameworks can help keep the ship steered in the right direction.
If you spend any time inside the enterprise world, chances are you’ve heard CX terms tossed around in articles, board meetings, or even around the proverbial water cooler. Terms like Party Data, X Analytics, or Conversational User Guidance might sound cool as they get bandied about in regular speech, but what do they really mean?
Peeling back the layers of this jargon isn’t just important so that you can feel more comfortable in conversations where they arise. Defining these customer experience (CX) buzzwords goes well beyond office dynamics du jour. Knowing what they mean and how they relate to the overarching end goal of your company is critical for staying relevant on the job and helping the organization stay current in these fast-paced transformative times.
If you’ve wanted to brush up on your modern glossary, you’re in the right place. We’ve made navigating these newly popular CX terms as easy as possible by offering the structure and detail to help you better understand where and how to use them in conversation and your job. As you skim through this post, you’ll find five core sections to the world of CX — data, analytics, insights, experience and frameworks. Inside each section are the CX terms you must know for 2023. But first, let’s look at why this type of glossary is so important for leaders to consume in today’s day and age.
The Essential Glossary of CX Terms
There are clear emerging trends when it comes to developing strategic experiences both for customers and for team members. Regardless of your department, from data and operations to marketing and sales, there’s a clear need to understand what’s happening in the customer’s experience better, and the many elements impacting that experience from all angles of the organization.
Understanding experience isn’t surface-level work, though. There is a new language that must be spoken throughout teams and across departments to pinpoint the various nuances and areas where experiential changes impact the growth of the organization. But knowing these buzzwords and being able to infuse them into strategic conversations is only the first step toward thinking through how business gets done. Simply understanding their definitions might not be the game-changer you’d want. Still, having this basis of understanding will help you build trust among your team and leadership while also getting closer to knowing what’s needed to make more impactful decisions for your organization.
Let’s peel back the layers on why these terms matter and what you need to know to stay relevant in the market today, shall we? Grab a cup of tea or espresso, and settle in. We’re kicking things off with CX terms relating to data.
CX Terms Meet Data Buzzwords
Without data, building strategies around the customer’s experience relies purely on guesswork and intuition. While there’s a place for adding human cognitive decision-making into the mix, ultimately, those decisions must be backed by data to know if the ideas have legs or if it’s leading the team down the wrong path. Gathering clean data to support decision-making is critical to developing a sound CX strategy.
TL;DR CX Terms Centering on Data
There’s a wealth of data at our disposal, but without using that information to inform and validate decisions, organizations will quickly lose sight of what’s happening in the market. The CX terms centering on data showcase the importance of having the right data to make core strategic decisions that will enhance the customer’s experience with your brand.
Terms in this Section:
- Data Looping
- Data Warehouse
- Data Engineering
- Data Governance
- Data Mining
- Data Modeling
- Data Visualization
- Data Culture
- Party Data
- Data Monetization
- Data as a Service
- Data as a Product
- Embedded Intelligence
You’ve likely heard the term data-driven. Data-driven organizations are those that use data to make decisions. The problem with this approach is that sometimes the data doesn’t give the full picture. That’s where being data-centric comes into play.
Data-Centric organizations use data to help inform and validate decision-making.
This approach extends beyond data-driven strategies by focusing on the scientific approach of data science and human intellect to form decisions.
With the wealth of information available today, organizations need to know how to wrangle those data points and put them into motion. Simplifying the complex requires teams to leverage data to inform and validate ideas, concepts, and strategies to become more predictive, execute on new paths faster, gather unbiased insights, and break down silo walls.
Check out our post on Humanizing Big Data to dig deeper into how you can become a more data-centric organization.
One of the biggest mistakes we see people make when collecting CX data is this — the data loop doesn’t close, causing data to go bad quickly.
Data looping is a specific system where you can aggregate data, draw insights and then put those concepts into motion.
As the term “loop” implies, this process is ongoing, so data is consistently being mined, modeled and visualized to help teams keep a pulse on what’s happening in the business. Closing the loop requires that businesses go through all seven stages of a data loop:
- Content Design
When done continuously, data loops ensure that teams create retention-driving customer experiences, bring the right people on board to steer the ship, and extract the insights needed to create powerful strategies.
Where you store your data matters, not only for accessibility among your team but also to the customer. Having the right people accessing data allows teams to understand the customer’s experience deeper. In addition, they can gather those insights at the right time, potentially impacting the outcome for both your team and your buyer.
A data warehouse is a centralized location where teams manage various business intelligence tools, access insights, and analyze the findings.
Through the data warehouse, teams can tap into a single source of truth so that those data points can be applied to the outputs and create a customer journey that will accelerate revenue growth.
While a data warehouse is where the insights are stored, numerous frameworks are deployed when uncovering those insights from what’s available. Those frameworks include empathy mapping, customer insights mapping, the bow tie funnel and StoryVesting.
Go deeper into how we gather insights from a data warehouse in our post on the StoryVesting framework.
How do you know you’re moving in the right direction? And how do you use data to help you put the guardrails up around that direction, keeping your entire team on the same page and working towards the same exceptional customer experience? That direction requires effective data engineering.
Data engineering ensures the statistical significance of the data collected, aggregated, correlated and visualized.
It’s critical for keeping teams on the right path toward their North Star Metric and not letting a misunderstanding in the data lead a team down the wrong road. Data engineering is important as teams navigate the S Curve of Growth to find ways to stay relevant in ever-changing times. Through intelligent data engineering, teams can better understand what’s happening at every layer of the customer experience, looking more in-depth at each touchpoint to see how and when to deliver content.
You’ve heard the expression that too many cooks in the kitchen spoil the soup. This concept of having too many people touching a single recipe holds when it comes to having too many people touching data sets. Having some data governance around your data sets is paramount.
Data governance manages who and how teams engage with the data and insights across the team.
This governance helps teams avoid misalignment in how people, processes or platforms interact with the data — misalignment that can negatively impact the organization’s growth trajectory.
Through data governance, teams can use resiliency, trustworthiness, prevalence, measurability and advancement to pull together millions of data points. Then, these points can be leveraged through a sound framework to create a clear strategy for projects across all departments, dropping silo walls and building organizational buy-in.
Pattern recognition is perhaps the most important method for teams to uncover hidden insights in large data sets. Data mining uses this pattern recognition to fuel intelligent decision-making and reliable growth.
Data mining is the process of navigating large data sets using various techniques to predict outcomes.
Data mining itself isn’t enough to steer an organization. A human-centered approach driven by a data-centric framework allows teams to stay focused while keeping the brand experience consistent with the customer journey.
To learn more about how modern technology is being deployed when data mining, check out this post on machine learning models in our blog.
A tremendous amount of navigation goes into viewing and digesting big data sets. Having the data modeled and clarified from a 30,000-foot view allows teams to make more intelligent business decisions based on insights instead of gut reactions.
Data modeling takes all of the data streams at your organization’s disposal and makes connections between the data points.
The data modeling process creates a blueprint for how to structure data so it can be converted into insights. In doing so, organizations bring everyone together on the team across all departments to understand the full scope of data science. This is one of the most complex tasks facing organizations today.
- Who needs access to the data?
- What do they need?
- How will the data flow between departments?
- Where is the data currently and where does it need to go?
Data modeling is no easy feat, yet organizations miss massive opportunities without it.
When approached via a data-centric framework, organizations can model data to deliver a single source of information for the team. Those data points and insights can then be disseminated to the entire organization more strategically, giving teams what they need to perform their job better.
Regarding data visualization. I think it's one businesses end up collecting way too much data. They collect a lot of data right now.
When many think of the term data, visions of rows, columns, 1s, and 0s dance in their head. However, data can be visualized in many ways beyond a numeric jumble’s confusing and overwhelming approach.
Data visualization transforms confusing datasets away from rows and columns into gorgeous imagery.
The goal extends beyond simply looking good. With effective data visualization techniques, teams can identify patterns and make key strategic decisions faster. As evidence of what data visualization looks like in practice, check out this sample dashboard which reflects what we pull together for our clients.
Data visualization isn’t just about aesthetics, though. There’s an art and a science to this approach. Through proper data visualization, teams across all departments can better understand what’s happening with the customer. This approach to drawing insights from the data, paired with human decision-making and strategic frameworks, allows teams to have a more holistic view of the business.
Read more about how we take data and transform it into actionable insights and a clear story in our post on Data as a Service here.
How does your team approach data? How is it used to make, inform and validate decisions? These are important questions as you pull together the right team and create a sublime internal experience. The answers will help you better understand your organization’s data culture.
Data culture speaks to the expectations, behaviors and patterns of your teams when it comes to managing data and making data-centric decisions.
Having a stronger data culture means understanding how and where to gather insights to manage customer and employee experiences. This CX term is important because it sets the tone for what’s expected of every department — not just the data analysts on the team. Without full buy-in and complete support for making insights-driven decisions via a data culture, teams could miss critical insights and ultimately end up on the path of obsolescence. When data culture is embraced on a team, silo walls drop, brand experiences get elevated, and there’s cross-departmental buy-in and better operational efficiencies.
When gathering data around your customer’s wants, needs, and experiential expectations, a wide variety of resources are available. This range of ways and sources is known as Party Data.
Party Data refers to the various places and sources where data gets collected.
- First-party data is everything collected in-house
- Second-party data is any data collected by an outside source, such as a consumer survey
- Third-party data is purchased from an outside source, such as data around online behaviors or propensities
- Zero-party data consists of anything that is voluntarily given by a consumer, such as through a quiz or loyalty program
Having a variety of party data allows teams to get a broader picture of what’s happening inside their organization. But the collection of this data alone isn’t enough. It’s equally important to have guardrails up to keep teams on course and ensure their customer experience initiatives keep the course toward a North Star Metric or constellation of metrics.
There’s often an assumption that data monetization refers to selling your data. When we use this term about the customer experience, we have a very different definition.
Data monetization happens when teams gather insights around revenue-generating activities and transform those insights into outcomes.
For us, data monetization means finding common problems and driving behaviors and then creating solutions. Revenue growth doesn’t come from within the walls of conference rooms or cubicles. It comes from leveraging data to understand the customer experience out in the wild. When teams monetize data, they can extract actionable insights, build personalized experiences, and, thus, gain bigger employee buy-in.
This concept is so robust and needed in today’s CX-driven world that a framework to guide these initiatives is imperative. At RocketSource, we’re outspoken about using the StoryVesting framework because we’ve found it’s the best data monetization framework we’ve seen. To learn more about how the StoryVesting framework can be used for data monetization, you’ll want to check out the backstory around how it came to life and how teams are using it today.
Data as a Service
Many CX buzzwords revolve around data, but with so much data to wrangle, model and visualize, it’s hard for many teams to know where to start. That’s where Data as a Service (DaaS) comes in.
DaaS is the strategy, structure and science behind the democratization of datasets so that teams can extract insights that’ll help shape the customer’s experience.
By working with DaaS providers, teams can monetize big data and make strategic CX decisions that span the entire bow tie funnel. As a result of these intelligent data loops, everything from acquisition to retention becomes stronger.
Read more about how DaaS providers work and why this is an important CX buzzword.
Data as a Product
Data as a Product opens the door to more impactful and CX-oriented ways to drive sales.
Data as a Product (DaaP) offers a way to make data accessible across all departments and teams.
There’s an interconnective and combinatory approach to offering DaaP. Rather than keeping data locked up in silos, DaaP providers allow teams to tap into a single, unified source of truth, shifting how the insights get consumed and operationalized.
How teams deploy their people, platforms and processes, known as the 3 Ps, to tap into this single source of truth allows people more access to quick, CX-centric decision-making.
We’re wrapping up the data section with embedded intelligence because the concept is paramount to keeping up with the swell of CX information pouring into the organization daily. Put simply:
Embedded intelligence is a system that self-manages its performance, allowing the processes to autocorrect and tune its operations while simultaneously bringing back important data for teams to process, analyze and optimize.
Embedded intelligence combines the 3 Ps — people, processes and platforms — to operate more efficiently and create more vested employees via higher-quality intelligence. When approached through a framework like StoryVesting, teams can translate data into actionable insights building long-term success and long-term employee retention. In having this system in place, teams can:
- Humanize automated workflows
- Establish event-triggered growth levers
- Identify security concerns faster
- Conduct real-time analysis
This level of intelligence kickstarts deeper analytical conversations within the workplace, equipping teams to operate more intelligently. Keep reading through this post to discover how we take the data gathered from systems, like Embedded Intelligence, and transform them into CX analytics that tells a strong story.
CX Terms to Know for Deeper Analytical Conversations
Gathering data is only the beginning of a long journey with a customer. Once gathered, those data points must be analyzed to identify trends and pinpoint behaviors. It’s these behaviors that will help teams get a better understanding of experiential data now and how to predict where experiences may be moving in the future.
TL;DR CX Buzzwords About Deeper Analytics
It’s not enough to have the data. You have to be able to dig deeper into the data to extract insights relating to your customer’s experience. Analytics let you honor the nuances of consumer behavior by becoming more predictive and descriptive through the patterns you find in the myriad of data sets. In addition, analytics equip you to tell a stronger story about what’s happening and where the market is moving so you can make better decisions.
Terms in this Section:
- CX Metrics
- X Analytics
- Journey Analytics
- Predictive Analytics
- Descriptive Analytics
- Diagnostic Analytics
Not all metrics relate directly back to the customer’s experience. Knowing how to identify the right metrics to clarify that blurry picture a little bit more helps you hone in on what’s happening from a customer’s point of view.
Customer Experience (CX) metrics are what organizations use to track and measure customer behaviors.
Through this data, teams can take a more competitive stance in the marketplace and innovate to surpass the high expectations of the modern consumer.
There are many CX metrics that teams can track, but not all of them are potent. We look for four criteria when deciding what metrics will make the biggest impact as we monitor them:
- Comparative to visualize historical performance across time periods or in relation to competitors
- Understandable metrics that everyone on the team can absorb and use
- Ratios or rates to analyze more movement over time
- Actionable and behavior-changing metrics to visualize shifts in motivational triggers and behaviors
Perhaps the behemoth of all metrics is the North Star Metric. This metric, or constellation of metrics, guides the course for the entire organization. Roll up your sleeves and dig in to learn more about this critical CX metric and how it’s used for massive growth in our blog post on the North Star Metric.
X analytics are often underrated in terms of just how transformational the insights can be for an organization. From navigating inflection points to deciding where to start with brand experience initiatives, every action stems from some level of experiential data.
X analytics measure all experience data collected from both customers and employees alike.
These analytics are often used to ensure that organizations stay relevant and accelerate revenues while reducing churn. Rather than focusing exclusively on operational performance metrics, such as sales or vanity metrics, X analytics looks closer at behavioral data to uncover the why behind what’s happening.
With X analytics, teams are better equipped to stay ahead of emerging trends and make a bigger impact in the market.
For more information about how we approach X analytics, check out this blog post on brand experience.
Parsing the data from various touchpoints, sources, and platforms is no small feat. Journey analytics make it easier to interpret the myriad of information pouring into organizations daily so that teams can operate more intelligently and efficiently.
Journey analytics aggregate data across the full customer journey to better understand what’s happening behaviorally among your customers and your employees.
With journey analytics, teams can drop silo walls, humanize big data sets, gain buy-in from teams and take a more empathetic stance to what’s happening in the market.At RocketSource, we approach journey analytics through the lens of the StoryVesting framework.
Teams become more proactive instead of reactive when an organization can take a more predictive stance. That proactive ability to stay ahead of the trends and honor emerging customer experience expectations can dramatically impact growth and competitive advantage. Here’s how it works.
Predictive analytics take all the data gathered by an organization to use by mining, modeling and analyzing it to spot patterns or trends that can forecast future outcomes.
These analytics are critical to growth because they allow teams to develop more experiential strategies rather than one-off initiatives.
We use four core predictive analytics models to stay relevant and ahead of market trends.
- Lead/Opportunity/Conversions modeling to predict how to engage with potential customers by identifying the emotional and logical triggers of those buyers with the highest propensity to buy.
- Lifetime Value models to better predict when a customer will churn and which events can help build retention.
- Attrition/Customer retention models to empower organizations to form deeper relationships with buyers at scale.
- Employee retention models to build a more vested team by gathering insights and predicting churn before it happens.
In using these and other models to gather predictive analytics, teams can stay ahead of the curve, leverage insights across the customer journey and enhance the brand experience.
Data alone doesn’t tell the full story. Using descriptive analytics, teams can start to piece together the human element of what’s happening behind the facts and figures and use those insights to improve the buyer’s experience with the brand. Descriptive analytics are what teams use to tell that story and give context to data sets, such as the radar graph empathy maps, which you can see above.
Descriptive analytics are used to identify trends and patterns in historical data so that teams can use those data points to guide decision-making.
These analytics allow organizations to dig deeper below the surface and create more sustainable paths to growth. Rather than simply displaying data points, descriptive analytics allow teams to humanize data sets and connect with today’s buyers. This micro-level snapshot can steer teams toward a North Star Metric or constellation of metrics, guiding organizational growth across initiatives and in the market.
Check out our post on humanizing big data to get a more descriptive (pun intended) view of how we use these analytics for decision-making.
Sometimes, things will go wrong. When that happens, your team can turn to diagnostic analytics to pinpoint where the journey or customer’s experience went off track.
Diagnostic analytics leverage data to diagnose the catalyst(s) for specific events. In gathering these analytics, teams can take a more strategic stance when making decisions or deciding on new initiatives.
Certain core data points must be considered when leveraging diagnostic analytics to make decisions:
- Voice of the Customer allows organizations to understand customers’ sentiments at various touchpoints
- Voice of the Employee gives decision-makers a better understanding of what’s happening among the team
When these data points are laid out across an entire customer journey, organizations can better pinpoint gaps in the customer and/or employee micro experiences and resolve them before they affect the overall brand experience across the bow tie funnel.
To dive deeper into how to effectively infuse insights into a customer journey map and use this type of map to leverage diagnostic analytics, read our in-depth post on Customer Journey Mapping.
The Critical CX Terms to Know to Drive Better Insights
Data and analytics play a crucial role in understanding a customer’s experience with a brand. Still, it’s the insights that tell the story around what’s happening below the surface. These CX terms pinpoint how to use the data and analytics gathered to identify experiential gaps and new opportunities to close those gaps.
TL;DR CX Buzzwords that Deliver Deeper Insights
With the data and analytics, teams are now equipped to extract insightful information regarding the customer’s experience and how it can be improved. Using analytics, you can start to pull out CX intelligence that’ll allow you to map a clearer journey and honor the more nuanced pathways for your organization to serve your audience better.
Terms in this Section:
- CX Intelligence
- Word Cloud Generator Sentiment Mining
- Customized Ratios
- Voice of the Customer (VoC)
- Voice of the Employee (VoE)
- EX to CX Mapping
- Barlow Bands
- Pathway to Purchase
- Customer Insights Map
Too often, organizations pick the path of least resistance, leaning into the obvious reasons buyers buy but rarely peeling back the layers to understand why. CX intelligence goes deeper.
CX intelligence is a process that digs well beyond the surface to use modern data collection practices and insights-centric frameworks to uncover and go deep into what buyers want and need.
It’s here that teams can get a 360-degree view of their customer and then pair that view with the customer journey to get into the hearts, minds and wallets of their customers. Through behavioral nuances, teams can create more strategic growth on the front end while simultaneously developing post-purchase loyalty.
Word Cloud Generator Sentiment Mining
Sifting through rows and columns of datasets is hard enough. Sifting through statements, call center records and other dense amounts of text or verbiage from the market is even harder.
Word cloud generator sentiment mining quickly extracts common phrases and patterns in the text and then visualizes the most relevant verbiage while aligning it with the organization’s why.
Once visualized, teams can leverage sentiment mining by extracting, analyzing and disseminating the qualitative text data in a graphic format. This graphic visualization of the most commonly used words and emotions helps teams to understand better how customers are thinking and feeling about the brand, a specific initiative or a product.
To leverage sentiment mining, there are specific areas where organizations can leverage word clouds to identify trends and insights from qualitative data sets.
- Social sentiment to identify recurring sentiments from the social ecosystem
- Cognitive associations to understand better how the market responds to the brand
- Polling and surveys to sift through responses and identify keywords or patterns
- Simplify complex data and analytics
Take word cloud generator sentiment mining for a test spin with our free word cloud generator tool.
Also looking at custom ratios. It's it's problematic that a lot of businesses when they're looking at what they're guiding North Star is they look at a single metric in isolation.
It’s no secret that LTV is the key to building long-lasting revenues and maximizing the profitability of every buyer who walks through your proverbial doors. When your team implements one of the CX buzzwords on this list, you’re doing so to improve the buyer’s experience while simultaneously building retention. Customized ratios help you stay on track toward that goal.
Customized ratios are comparative, allowing teams to compare how various experiential layers translate into overarching and long-lasting brand growth.
Organizations are better equipped to accelerate revenues and build sustained revenue growth by monitoring and deciphering customized ratios. Examples of what a customized ratio could be and how it can correlate to a bigger organizational mission include:
- Building Retention: Customer Experience to Lifetime Value (CX:LTV) and Employee Experience to Lifetime Value (EX:LTV)
- Aligning Experience Layers: Customer Experience to Revenue Expansion (CX:RevExpansion)
- The Loyalty Loop Lifecycle: Customer Experience to Revenue Acceleration (CX:RevAcceleration)
Voice of the Customer (VoC)
Organizations must lean in when the customer speaks on social media, via call centers, in-store conversations, focus groups, or various other sources. This data, known as the Voice of the Customer (VoC) data, is rich with insights.
Voice of the Customer (VoC) data refers to any type of direct feedback from a buyer. This type of feedback is invaluable for understanding the sentiment around the brand.
Extending well beyond data gained from NPS scores or CSAT ratings, VoC data lets brands give buyers their ear while simultaneously understanding what’s being said across all platforms. Through this strategy, teams can take a more empathetic stance while mining, modeling, and quantifying the qualitative data they gather.
Voice of the Employee (VoE)
All employees at all levels of the organization have valuable insights to share. In gathering those insights, companies are equipped to go deeper in understanding what’s happening regarding the brand experience. Gathering those insights is known as tapping into the Voice of the Employee (VoE).
Voice of the Employee refers to gathering feedback from team members and using that feedback to align internal practices with customer needs better.
An increasing number of organizations are realizing the importance and potent power of shifting from a purely customer-based focus to a more inclusive people-based focus. This includes focusing both on those who buy from the organization and those who work inside the organization day after day. In doing so, this expanded purview creates a ripple effect and acts as a multiplier for better brand experiences overall.
EX to CX Mapping
Having VoC and VoE data is valuable, but where the true transformational insights emerge is when teams can map those insights together to understand better both the employee experience (EX) and customer experience (CX).
EX to CX mapping takes a combinatory approach to transform the internal experience and external experiential data points into a single model so that brands can identify gaps and discover new opportunities for operational alignment.
Through EX to CX mapping, teams can better understand how to lighten the team’s workload while simultaneously creating a better buyer experience. Reducing friction, beating customer expectations and process refinement are just some of the byproducts of this important exercise.
Still, when done without the guidance and support of a framework like the StoryVesting framework, EX to CX mapping could send teams in the wrong direction. By taking a pragmatic, analytical and empathetic approach, organizations can spot problems and weaknesses along both journeys.
Learn more about what Barlow Bands mean for CX and why we think they’re so crucial for elevating experiential strategies.
It’s no secret that data visualization allows teams to understand better what’s happening without needing to be a data analyst to parse through the rows and columns of that data. One type of visualization we often use to compare and contrast various metrics is Barlow Bands.
Barlow Bands, or convergence/divergence bands, are a data visualization method that analyzes two metrics alongside each other to identify gaps and alignment in two data sets quickly.
The combinatory nature of these insights allows teams to monitor transitionary touchpoints. The layered approach equips decision-makers to make more unified and intelligent decisions about where to invest the team’s time, resources, and finances.
Pathway to Purchase
Organizations consistently try to unravel the customer’s journey, from first becoming aware of a need to ultimately deciding to buy from their brand. This journey is known as the pathway to purchase.
The pathway to purchase is the predictable journey customers take when deciding how to solve the problem they’re experiencing and which company to work with to reach that resolution.
With the rise of digital transformation, the pathway to purchase has become far more complex. Organizations know that to stay competitive, knowing what this predictable path looks like and the nuances behind each stage are critical for creating more productive processes, reducing budgets and increasing conversion rates.
Discover how some of the leading organizations in the world operationalize the pathway to purchase and what this could mean for your company.
Customer Insights Map
Modern customer journeys are complex and often difficult to navigate. It takes depth and digging further with insights into the customer’s experience. To get there, we’ve created the Customer Insights Map, a CX term you must be aware of if you’re touching any part of the modern customer experience.
The Customer Insights Map is an in-depth visual representation infused with data to understand the nuances of what’s happening as a buyer moves through their pathway to purchase.
These maps are heavy with insights (hence the name). Each map is created using sophisticated technologies and human intellect. When pulled together, the following data points converge to paint a clearer picture of what’s happening inside the customer’s experience:
- Empathy mapping across all stages of the customer journey
- Touchpoints along a buyer’s journey
- Barlow Bands used to map employee and customer experience scores
- Contributing departments at each touchpoint
- Platforms used at each touchpoint
- Assets available to the organization
- Opportunities at each stage of the buyer’s journey
- Metrics and key performance indicators to monitor
- Path-to-purchase comparison models
This map often extends beyond acquisition too. Mapping the pathway to loyalty allows teams to increase their customers’ lifetime value (LTV) and retain their top employees by building deeper relationships with buyers.
We have an entire post dedicated to unpacking all the nuances and details behind customer journey mapping through the Customer Insights Map. You’re highly encouraged to reserve some time to dig into the details of this powerful asset.
CX Terms to Build Better Experiences
Every interaction. Every touchpoint. The culmination of everything a customer and employee does when engaging with an organization must be managed to create a more positive experience. To tap into how to manage these various elements, it’s important to get deeper into what the key terminology means.
TL;DR CX Buzzwords for Better Overall Experiences
Understanding the human element behind the data and analytics is a start. How you infuse that intelligence into a beautiful, cohesive experience is the next step. This requires getting between your customers’ ears, listening to their voice, aligning what they’re saying with what your employees say, and operating with empathy.
Terms in this Section:
- Employee Experience (EX)
- Customer Experience (CX)
- 360-Degree View of the Customer
- Behavioral Triggers
- Customer Friction
- Human-Centered Design
- Table Stakes Testing
- Product-Market Fit Mapping
- Cognitive Computing
- Conversational User Guidance
- Experience Management (XM)
Employee Experience (EX)
Employee Experience (EX) might seem like an odd addition to a post with customer experience terms, but there’s a good reason for this. Building a beautiful CX starts with having a sublime EX.
The employee experience brings together the many moving parts of your employee’s role inside your company.
From the platforms used to the processes by which they must perform their work and the leadership styles needed to steer the internal ship, there are a lot of components to the EX. If those experiences don’t align with what the customer expects and experiences, it will be exponentially more difficult to deliver a sublime brand experience.
Alignment between the customer’s experience and the employee’s experience happens when your team members become self-proclaimed brand ambassadors. Collectively, everyone internally can directly see how their work impacts the greater good, which empowers them to create an experience for their customers that surpasses all others in the market.
Employee experience is paramount, and we dig into the direct impact it can have on your overall growth in our post on product-led growth strategy, which you’re encouraged to dig into.
Customer Experience (CX)
Modern technology has shifted the power to the marketplace. That shift in power from retailers to consumers has created a distinct need for businesses to answer the customer’s call through transformational initiatives that honor the customer’s experience.
Similar to EX:
The customer experience (CX) is the sum of all of the parts of an individual’s experience, starting from the emotional spark a customer has when feeling a pain point through to the loyalty a customer feels to a brand and everything in between.
The customer’s experience starts with reconciling past experiences with present-day needs. Once that reconciliation occurs, a customer can move forward with an organization. The behavioral patterns that unfold throughout that journey equip your organization to deliver a powerful experience.
To learn more about this journey, crack open our glossary term on Customer Experience, where we peel back these many layers in a little more depth.
360-Degree View of the Customer
Too often, customers are treated linearly. Organizations anticipate their journey as if they’re cogs on a machine belt when there are countless nuances. Connecting the dots between outward behaviors, either online or through in-person interactions, and internal thoughts and preferences is important.
360 Degree View of the Customer refers to the compilation of all the data about a customer in one place.
At RocketSource, we’ve extended this concept further to include a 360-degree view of the employee. That’s because the way the employee relates to the customer simultaneously relates to the organization’s deliverables — products, services, memberships, and otherwise — and leverages that experience to align the business with the customer. Having this asset helps you to:
- Develop machine learning algorithms that align with the customer as a person rather than a cog in a system
- Orchestrate loyalty-to-purchase loops by better understanding the emotional and logical triggers of your customer
- Improve employee experiences by empowering them to resolve problems faster, making their job better overall
- Operate more intelligently by better understanding what your customer needs to streamline your development cycles and keep teams focused.
What makes a buyer click the buy button? What inspires someone to take that next step in their journey with your business? The answers to these questions are rich with nuances and insights about human behavior. To find the answers, you must understand the behavioral triggers associated with that path-to-purchase and customer journey.
Behavioral triggers are the emotional and logical catalysts that move users through decision-making.
Knowing these emotional and logical catalysts requires a data-centric, human-centered approach infused with behavioral psychology. With these multitudes of elements, teams can create digital solutions and experiences that stick. As a result, your team can learn how to build powerful and effective brand experience initiatives to stay relevant to the modern consumer’s wants, needs and demands.
Friction is rarely positive. When a struggle or sticky point enters the journey, customers naturally slow down and resistance to the offer increases. This is known as customer friction, which can slow growth without addressing or remedying it.
Customer friction occurs when a customer meets a negative or challenging spot along their journey with your organization.
Increased attrition and decreased loyalty are two dreaded consequences of friction in the customer’s experience. This friction makes it hard to sustain and predict growth, causing your organization’s own friction as you strive to push up the S Curve of Business.
Pinpointing where friction occurs in the journey is only the first step. After you know where there’s friction, you must also focus your efforts on how you can proactively alleviate that resistance in the customer’s experience. This approach requires a full and empathetic look at your buyer’s experience rooted in qualitative and quantitative analytics.
Let’s face it. Gone are the days when products are commodities. The most successful organizations offer experiences with their products that get infused into consumers’ daily lives. You’re leveraging human-centered design when you approach your deliverable through this lens.
Human-Centered Design looks critically and holistically at the person behind the product while creating the final design.
This approach to design requires a healthy dose of empathy to know how the products or services offered by the organization align with the customer’s thoughts, wants, desires and needs. In addition, it requires that teams feel confident in the organization’s ability to offer this kind of experience and feel empowered to deliver it to the end user. By pairing the two experiences together, teams can find actionable ways to excel and consistently improve to deliver a more sublime brand experience.
See how RocketSource leverages human-centered design in brand experience inside our blog post.
Table Stakes Testing
We often see products get sent into the market only to be met with the sound of crickets. This lack of expected sales could have been avoided had the team gone through table stakes testing before releasing a new product or service to customers.
Table stakes testing infuses data throughout design and development so that teams can validate assumptions, optimize workflows and strengthen Product-Market Fit.
This process doesn’t happen overnight, nor is it a one-and-done type approach. Table stakes testing leverages insights to clarify offerings and ensure the design and development process aligns with the customer’s true pain points and emotional triggers. It’s data, rooted in empathy, that allows teams to come together to navigate every layer of the product, build sublime CX and EX, and achieve Product-Market Fit faster.
Product-Market Fit Mapping
Organizations don’t go through the blood, sweat and tears of creating a new product just for it to hit the market, do well for a year or two, and then fizzle out. Continually maintaining alignment between the brand and customers allows companies to build products with a longer-term impact. That’s Product-Market Fit.
Product-Market Fit is the process of measuring the alignment between the organization’s products and services and the customer’s sentiment toward the offerings and brand.
Through this alignment, teams can create more reliable and sustainable growth at every stage of the product lifecycle. The process starts at the core of both the brand experience and the customer’s experience, aligning the organization’s why with the customer’s core needs and wants. In achieving this alignment, which is no easy feat, the company can better determine whether the products in question are ones the market wants or if adjustments need to be made.
To get the full rundown on the Product-Market Fit framework, we use and how we approach this initiative, check out our blog post.
Innovation can often feel like a pendulum swinging back and forth. One minute, you’re relying on your team to make the core decisions. The next, you’re leaning into AI. Cognitive computing combines both worlds to create a more potent driving force behind major organizational changes.
Cognitive Computing infuses human touch into the continuous improvement of advanced technology as a combinatory means of driving business outcomes.
It’s no secret that having more insights allows organizations to operate more efficiently and strategically. However, collecting data for the sake of collecting data simply checks a box. It doesn’t extract meaningful insights that can be leveraged in a fast-paced market. Cognitive computing’s human-touch element allows organizations to translate the findings from advanced technologies, such as machine learning and artificial intelligence, and then leverage those to predict future consumer behaviors. It’s this predictive stance infused with insights that can fuel better experiences both internally and externally.
Conversational User Guidance
As brands become more predictive through cognitive computing, they’re empowered to create a more personalized experience. That experience unfolds through conversational user guidance.
Conversational User Guidance infuses emotional cues, such as human voice, alongside visual cues to create a more personalized experience when navigating the path to purchase.
Offering this layer of interaction on your website or throughout post-purchase experiences builds user engagement. That engagement is often overlooked, yet it’s a foundational component of any digital marketing or onboarding experience. By adding an extra layer of human-to-human support, organizations can build loyalty and ultimately boost the customer’s lifetime value.
If you’ve clicked on any audio snippets here, you’ve used one layer of conversational user guidance throughout this post. Take conversational user guidance for a test spin in your business, and see how impactful this strategy can be by testing the same tool we’re using over Pulsemotiv.
Experience Management (XM)
You don’t need to have worked in the corporate world for very long to know that the way we do business has changed dramatically over the past decade. Those major shifts have put the power back in the consumer’s hands and require organizations to focus on the end experience. That’s where the critical need for Experience Management (XM) comes into play.
Experience Management is how organizations track, oversee and organize every interaction between the organization and the customer.
Contrary to popular belief, CX isn’t the sum of all customer touchpoints. It’s a holistic experience that spans the entire journey from awareness to beyond purchase. Managing that experience requires that every touchpoint, nuance and interaction meets or exceeds expectations from an emotional and logical standpoint. In focusing on these expectations and market demands, organizations can achieve Product-Market Fit, better brand alignment, build internal buy-in and deliver an outstanding buyer journey.
Managing experiences from a granular and 30,000-foot view require guardrails and direction. We approach XM through the lens of various frameworks, which help keep the guardrails up as teams move through those various layers. We’ll cover these frameworks for the remainder of this post.
CX Term Frameworks to Guide Your Strategies
Before we get into the terms regarding frameworks, let’s get one thing out of the way — being able to talk the talk is only part of the equation. Knowing how to walk the walk is equally important. Implementing these frameworks to make strategic decisions matters as you start to put the concepts above into motion.
TL;DR CX Buzzwords to Guide Your Strategy
Strategic decision-making in CX-focused organizations centers on what’s happening at the customer experience level. That part is clear. What’s less clear is how to leverage all the data, analytics, and insights you found above and turn them into a sound, actionable strategy that will drive results. In this section, you’ll get familiar with the various frameworks we use at RocketSource that shape your business’s direction and upward trajectory.
Terms in this Section:
- S Curve of Growth
- North Star Metric
- Bow Tie Funnel
- Business Impact Analysis
- Stack Impact Analysis
- Revenue Operations
- Revenue Acceleration
- CX-Led Growth
S Curve of Growth
Every company in every industry travels a similar path. Sometimes there are big wins with massive growth. Other times there is a distinct slowdown where strategic inflection points occur, requiring the company to make changes to continue the growth trajectory. This pathway is known as the S Curve of Growth or S Curve of Business and serves as a framework for innovation.
The S Curve of Growth tracks the growth trajectory of organizations, highlighting the upward momentum when revenues are strong and the plateaus or dips where innovation is required to stay relevant in the market.
The core difference between leading organizations and laggards is their ability to spot those plateaus or dips quickly and get out ahead faster. That’s because there are many moving parts to navigate growth out of those inflection points. One foundational element is the customer’s experience with the organization. Organizations can answer consumer needs and refine CX initiatives by tracking this trajectory.
Recognizing the inflection point is only the beginning. Navigating the approach back upwards requires an end-to-end system for improving and promoting that growth.
Discover how we approach the inflection points along the S Curve of Business in our post on this critical term.
The North Star Metric is a critical framework to follow when creating customer experiences. Hear Omar's take on how to best utilize this framework among your team to bolster CX initiatives.
North Star Metric
You’ve likely heard the expression that a rising tide lifts all boats. When that rising tide also moves synchronously to the next destination, all boats can sail with it, leading to a smoother journey, collective arrival time, and more collaborative experience. Having a North Star Metric, or constellation of North Star Metrics to follow as you navigate the seas of the business world, is key to making this happen.
A North Star Metric is a single metric or set of motion metrics that indicate long-term success across the organization as a whole.
Finding the right North Star Metric (or metrics) for your organization requires analytical rigor. These metrics must be easy to understand, showcase the a-ha moment your audience has with your brand, correlate to the growth of your organization, be measurable, have longevity, and be quantifiable. That’s quite a laundry list of requirements, but the benefits are powerful when each box is checked. Sales cycles get shortened. LTV increases along with revenue per employee. Overall, your organization will achieve more engagement for your brand, creating more profitability.
The metric or metrics you choose will stay the same through to your next inflection point on the S Curve of Growth. To go much deeper on how we approach finding a North Star Metric, carve out some time to spend inside our blog post on this core piece of your growth puzzle.
Bow Tie Funnel
Hit play to hear Julia Rakowski, our Content & Digital Strategist discuss the importance of the bow tie funnel
Modern consumers have shifted. The traditional funnel that brings in leads and then funnels them to a sale is gone. Today, that funnel has been flipped sideways and extended to become the Bow Tie Funnel.
The Bow Tie Funnel has reimagined the traditional marketing funnel to include the post-sale stages of the customer journey.
Combining pre-purchase and post-purchase journeys, the bow tie funnel allows organizations to serve and nurture their audience continuously. This dual viewpoint highlights the need to focus on retention alongside (if not over) acquisition, allowing organizations to deliver a more sublime customer experience.
This type of bow tie funnel and continual feedback loop honors the complexities of the modern-day consumer. In taking this approach, teams have more growth levers to pull and can more easily spot incremental changes to operational efficiencies to align with that end-to-end customer journey for growth.
This process is more complex than it appears on the surface. Dive in to learn more about the bow tie customer journey funnel by reading our blog post on the framework.
Ah, StoryVesting. This is the crux framework through which all our business and client business decisions are made. That’s because it’s proven time and again to provide some of the most powerful insights and transformational experiences for customers and teams alike.
StoryVesting is a business transformation framework that equips businesses with the ability to align employee and customer experiences for maximum growth.
This framework includes two concentric circles — the customer experience and the brand experience. The goal is to bring each of these circles as close in alignment as possible so that when one is touched, there is a ripple effect that expands to the other. This constant movement, impact and focus on both CX and BX allows teams to honor the energy transfers between the two experiences while driving faster, more sustainable growth through deeper cognitive associations, intelligent operations and organizational alignment.
It’s worth your while to grab a cup of coffee and dig into the blog post (which could have been a book) written on the business transformation StoryVesting framework here.
Business Impact Analysis
Knowing what to prioritize to stay within the guardrails for your organization is no easy feat. That’s especially true when you bring many voices from all departments to one room to decide where to focus next. Often, there will be a mixed bag of ideas for prioritizing the team’s time and resources. That’s where the Business Impact Analysis comes in.
A Business Impact Analysis is the process of using data to prioritize what needs to happen for the organization to grow continuously.
Leveraging data to better identify priorities allows teams to stay on track toward the North Star Metric and continuously improve CX and EX for your brand. Taking data and plotting the possible business objectives against each other will help you quickly identify the lowest-hanging fruit for growth. As the clear path is decided, your team can collectively build an experiential strategy to fuel growth rooted in data.
Stack Impact Analysis
With the proliferation of technology and platforms, it can be difficult for teams to wrap their head around what to use, whether they’re using the best tools for their goals and needs, and how to leverage the tech stack to deliver an exceptional customer experience. A Stack Impact Analysis can help field many of these questions and concerns.
A Stack Impact Analysis examines the value realized from platforms and how well they improve processes and customer experiences while reducing costs.
Outdated and misaligned technology can quickly erode both your employee and customer experience. Having a Stack Impact Analysis to showcase which platforms are fueling growth and which are hurting growth can help you continually improve, update and solve problems more strategically and effectively. Ultimately, this continuous forward movement allows you to stack the dominos in your favor and accelerate brand revenues through more aligned experience initiatives.
New frameworks. New technology. An explosion of new channels. There are many overwhelming factors when understanding your customer’s journey and what gets them to buy. Having a Revenue Operations (or RevOps) strategy allows you to better understand where your team should lean.
Revenue operations leverages data and business intelligence to make informed decisions regarding revenue acceleration strategies.
RevOps is all about building momentum in an organization so that customers are more likely to take action and build an emotional association with your brand. Unlike decades ago, customers now hold the cards, meaning that organizations must now think more deeply about how their operations reach buyers and keep buyers. Honing every touchpoint and experience is key to building this RevOps strategy and meeting the modern customer’s needs.
We wrote an entire blog post about how RevOps leads to Revenue Acceleration, which is worth reading if this is a strategy that’s caught your eye and has inspired you to start acting within a closer framework to develop better CX.
RevOps leverages the data to make intelligent decisions. Revenue acceleration strategies move the needle in your customer’s experiences.
Revenue acceleration occurs when an organization creates sustained momentum by keeping customers engaged and loyal to the brand.
Accelerating revenues requires an organization to start with the end in mind. By backward mapping what that experience will look like, teams better understand where to focus their efforts and how to spur revenue creation. In taking this approach, every decision and every strategy consistently comes back to the core why to bolster the customer’s experience and build lifetime value (LTV) for the customer.
Learn more about how we manage the Revenue Acceleration framework by reading more about our approach in our glossary.
It all comes down to this. There’s never been a bigger need to keep the customer happy than there is today. Modern consumers are not only more empowered today as we’ve already discussed throughout this post, but they’re also more vocal about their experiences today than ever before. Not just any experiences, though — the negative ones. Having a CX-led growth strategy lets teams manage the expectations and experiences of customers more holistically, helping avoid negative publicity while spurring word-of-mouth marketing.
Customer Experience Led Growth is more than a one-off initiative. It’s a holistic approach to your business model and operations strategy.
As an organization moves upwards along the S Curve of Growth, it’s crucial that they learn how to master alignment with the modern consumer and keep the end user’s experience relevant to their needs. By applying behavioral psychology and motivations alongside innovative digital solutions and experiences, teams can inherently take a more CX-led stance. This approach can move teams from limited brand equity in the market to service experiences and deep cognitive associations of the brand.
These are the types of growth initiatives we help our clients achieve.
Mastering CX Terms for Strategic Growth
While digesting these terms, keep in mind that, as with anything analytical and contextual, the exact definition is less important than the interpretation. Knowing how you can apply these terms to your daily work is more valuable than being able to spout off a definition in the conference room.
We can help you go deeper, turning these buzzwords into blown-out strategies your team can implement and leverage for growth. Our team specializes in simplifying the complex by working closely with your team to identify opportunities, pinpoint gaps in the customer’s experience, and develop creative, effective solutions. Through this work, we bring our clients from struggling to grow to hit the revenue accelerator. Reach out to us today to book a complimentary discovery call to learn more about how we can help your organization.
It's crucial for teams to speak the same language around customer experience (CX) and experience management (XM). In doing so, teams are better equipped to break down silo walls and move cohesively towards a common goal. Knowing the CX buzzwords that matter most today impacts organizational growth and moves companies up the S Curve of Business.
Jonathan Greene & Steven Kiger