The back-office (claims teams, billing, fulfillment, underwriting, compliance) has rarely been treated as part of the experience engine. Yet as artificial intelligence (AI), automation, and agentic systems reshape operations, CX leaders are realizing something critical: The back office is no longer behind the scenes; it’s center stage.  

In this roundtable, executives unpacked the operational and cultural shifts needed to finally align these historically separate functions. What emerged was a clear call to action, and a glimpse into how the most future-ready organizations are preparing for what comes next. 

Back-Office Modernization Is Now a CX Priority 

One leader put it plainly: “From the customer’s perspective, there is no front office, there is no back office. There’s just the company.” 

Consumers don’t care which department “owns” a task. They care about clarity, speed, and avoiding repetition. Yet many organizations still invest heavily in front-line tools while leaving back-office workflows untouched, creating the very friction customers feel in the form of delays, inconsistencies, and escalations. 

Leaders agreed on several truths: 

• Back-office operations are essential to the end-to-end experience, not hidden support layers. 
• Most executive teams still underestimate the CX impact of back-office modernization. 
• Teams across the enterprise need to see back-office work as part of the customer journey. 
• Fragmented handoffs, not agent performance, are often the root cause of customer dissatisfaction. 

Silos, Systems, and the Alignment Problem 

If there was one shared pain point, it was this: alignment is still the most significant barrier to progress. 

Executives described a familiar scene: HR systems that don’t speak to CRM, fulfillment platforms that operate independently, product teams designing workflows “in a vacuum,” and data scattered across what one participant called “islands of automation.”  

But the most powerful insight came from a simple observation: Sometimes the most impactful transformation starts with a basic cross-functional meeting. 

In one organization, simply bringing together CX, operations, and product teams in the same room revealed a dozen downstream issues, many of which were quickly solvable. It reminded the group that alignment is not only a systems challenge, but also a cultural one.  

As one attendee shared: “Bringing teams together, they’re like, ‘Oh, I didn’t realize it did that.’” Sometimes awareness is the first step toward modernization. 

From Frankenstacks to Unified Data 

Every executive on the roundtable acknowledged a version of the same problem: the “Frankenstack.” Tools bolted together, inconsistent data definitions, and multiple versions of the truth. And with AI moving from experimental to operational, that fragmentation is no longer just inefficient; it’s risky. 

Leaders stressed the need for: 

• A single data layer 
• Consistent data governance 
• Clear prioritization of 30–90 day value wins 
• Unified KPIs that make back-office contributions visible 

The takeaway was clear: AI is only as good as the data it’s fed. One leader summed it up nicely: “Once we have a better view of what’s going on, we can finally measure the value the back office brings.” 

The Human + AI Workforce Is Here 

Perhaps the most forward-looking part of the conversation focused on agentic AI and the idea of a combined workforce: human and AI agents working side by side. 

Leaders shared early wins: 

• 4× throughput increases 
• 100% auditability 
• Manual tasks reduced from 4 hours to 1 
• Entire queues eliminated 

But they also highlighted new responsibilities: 

• Monitoring AI like a team member
• Building clear governance 
• Ensuring transparency and explainability 
• Training employees to work with, not against, AI systems 

As one participant said, “AI will not replace people. But people who do not understand AI will be replaced.” The future of CX isn’t human vs. AI. It’s human + AI + aligned operations. 

CX Leadership Is Shifting from Cost to Value  

The conversation closed with a noticeable shift in mindset: Leaders are moving away from AI for cost-cutting and toward AI for value creation, quality, and growth. Organizations are building value-realization frameworks, taking incremental wins rather than massive transformations, and focusing on internal AI adoption before rolling out customer-facing solutions. 

Their North Star goals for the next 12 months? Unified data, automated back-office workflows, better regulatory processes, and strengthened centers of excellence. The direction is unmistakable: Modern CX leadership is operational leadership. 

Be Part of Conversations Like This 

This is what makes the Execs In The Know community special: leaders openly sharing, challenging, and learning from one another. Just real problems and real solutions. Our Virtual Executive Roundtables are built on that promise: Leaders Learning From Leaders. 

If you want to be part of these candid conversations, connect with top CX executives, and stay ahead of the trends shaping our industry, we invite you to join one of our upcoming virtual or in-person events. In the meantime, explore our recent report in partnership with NiCE, CX Without Silos: Bridging Front- and Back-Office Operations to Elevate CX.

The post Breaking Down the Back Office: What CX Leaders Told Us About the Next Era of Customer Experience  appeared first on Execs In The Know.

The discussion highlighted a critical challenge: when customer data is fragmented, outdated, or inconsistent, CX teams struggle to deliver seamless interactions. One of the biggest takeaways? Your customer experience is only as good as the data behind it.

• Call center agents face incomplete or conflicting customer profiles, leading to long handle times, frustrated customers, and unnecessary discounts to smooth over bad experiences.
• AI-powered automation falls short when it’s fed incorrect data, causing chatbots and self-service portals to deliver irrelevant or misleading responses.
• Loyalty programs and marketing campaigns miss their mark because duplicate or outdated records prevent brands from recognizing their best customers.

But as Princess Cruises showed, fixing data issues isn’t just about avoiding frustration—it’s also about unlocking millions in ROI.

How Princess Cruises Transformed Their Guest Experience

One of the most compelling stories at CRS came from Princess Cruises, a brand known for delivering world-class guest experiences. However, behind the scenes, disconnected systems and messy data were creating major CX challenges:

• Call center agents struggled to pull up complete guest profiles, leading to longer call times and inconsistent service.
• Outdated or duplicate records made it difficult to recognize loyal guests, impacting upsell opportunities.
• Manual data clean-up processes were time-consuming and costly.

By implementing harpin AI, Princess Cruises achieved:

• Faster, more efficient customer service—agents could instantly access accurate guest profiles.
• Increased revenue opportunities—loyal guests were correctly identified and engaged with relevant offers.
• Significant cost savings—by eliminating the need for manual data reconciliation, freeing up resources for higher-value tasks.

And the best part? They didn’t have to replace their existing CRM, CDP, or other systems. harpin AI seamlessly integrated into their tech stack, enhancing every tool they already had.

Fix Your Data. Fix Your Customer Experience.

If bad data is holding your CX team back, AI and automation alone won’t fix it—they can only work as well as the information they’re given. That’s why harpin AI goes beyond data storage to observe, resolve, answer, and activate customer data:

Observe: Data issues don’t announce themselves—but they’re undermining CX behind the scenes. Observe continuously scans customer, transaction, and asset data, pinpointing inconsistencies, gaps, and anomalies before they cause problems. It’s more than just error detection—teams get real-time insights into data health, automated alerts, and performance tracking, all within the tools they already use. Instead of waiting until bad data impacts customer experience, brands can stay ahead of issues and optimize their operations proactively.

Resolve: Storing data isn’t the same as fixing it. CRMs, CDPs, and data warehouses might hold valuable customer information, but they won’t untangle duplicate records, reconcile mismatched identities, or update outdated details on their own. And when data is unreliable, the impact is huge:

• Call centers struggle with fragmented customer profiles, dragging out resolution times.
• Marketing teams waste spend on campaigns aimed at the wrong people.
• Loyalty programs fail to engage VIP customers because their profiles are incomplete.

Resolve connects and corrects data across systems in real time, ensuring every system—whether it’s for CX, automation, or analytics—runs on clean, trusted information.

Answer: When you need to make a business decision, you don’t have time to dig through dashboards. Answers lets teams ask direct questions—like “Which customers churned after a product change?” or “Where are we losing the most revenue?”—and get an immediate, clear response. No SQL, no waiting on analysts—just fast, actionable insights that help drive better decisions.

Activate: Once data is normalized and insights are unlocked, the next step is making it work where it matters. harpin AI embeds trusted data into existing systems, ensuring that automation, analytics, and AI tools actually perform as expected. That means:

• AI-powered chatbots and virtual assistants operate on accurate customer details.
• Embedded insights flow seamlessly into Slack, Teams, and other collaboration tools.
• Proactive monitoring surfaces potential data risks before they create CX headaches.
• Seamless integrations ensure CRM, CDP, and automation tools work together without disruption.

With harpin AI, businesses can:

• Deliver faster, more personalized service by ensuring agents and AI have the right customer information at their fingertips.
• Maximize AI-driven automation ROI by eliminating data inconsistencies that cause errors.
• Boost revenue from loyalty and marketing programs by accurately recognizing and rewarding customers.
• Reduce operational costs by eliminating inefficient manual data reconciliation.

It’s not about adding more technology—it’s about making existing investments actually work.

Want to see how better customer data can transform your CX? Schedule a meeting with a harpin AI expert to discuss your challenges and explore solutions.

Contributed blog post written by harpin AI.

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But here’s the harsh truth: none of it works if your data is bad.

Think about your current CX strategy. You want:

• Faster resolutions and higher first-call resolution rates
• Personalized interactions that make customers feel valued
• AI-powered chatbots and automation that deliver relevant, timely responses

Yet, time and time again, data gets in the way.

• Agents waste valuable minutes chasing down customer information scattered across multiple systems.
• Loyalty programs fail to recognize VIP customers because of duplicate or incomplete records.
• AI-powered chatbots frustrate users with incorrect or irrelevant responses.
• “Personalization” often feels random because the underlying data is messy and unreliable.

Why Bad Data Is the Silent Killer of CX

Every interaction with a customer relies on data—who they are, their history with your brand, their preferences, and their current needs. But if that data is incomplete, outdated, or duplicated, every touchpoint suffers.

Bad data leads to:

• Higher operational costs: Call center agents waste time navigating multiple systems just to verify basic customer details.
• Frustrated customers: Customers who have to repeat themselves or deal with incorrect responses are more likely to churn. Worse, to compensate for their frustration, your team is forced to hand out unnecessary discounts, credits, or refunds—eating into your margins. Instead of creating loyalty, you’re paying for preventable mistakes caused by bad data.
• Missed revenue opportunities: If your systems don’t recognize customers accurately, you can’t deliver timely upsell and cross-sell offers.
• AI failures: Even the best AI models can’t function properly if they’re fed incorrect or incomplete data.

AI Can’t Save You From Bad Data—But harpin AI Can

Investing in AI won’t solve your data problems—it will only make them more obvious. AI models are only as good as the data they rely on. If your data is fragmented, outdated, or full of duplicates, your AI-powered initiatives will fall flat.

That’s where harpin AI changes the game.

Unlike traditional CRM and CDP systems that simply store data, harpin AI validates, refines, and activates it—ensuring every system, agent, and AI model works with trustworthy, accurate, and complete customer information.

Here’s what that looks like in action:

Call centers see reduced handle times because agents have real-time, accurate customer profiles at their fingertips.

AI-driven service automation actually delivers the right responses because it’s powered by verified, trustworthy data.

Loyalty programs recognize customers instantly, preventing duplicate accounts and missed rewards.

Marketing, operations, and support teams finally trust their data, eliminating the guesswork and inefficiencies that slow down CX.

Meet harpin AI at Customer Response Summit

At Customer Response Summit, we’ll be showcasing real-world success stories from leading brands like Princess Cruises.

Join us to learn how reliable, structured, and validated data can be the foundation for a better customer experience, lower operational costs, and higher revenue.

Want to connect at CRS? Let’s talk. Or visit harpin.ai to learn more.

The post Customer Experience Runs on Data—But Can You Trust Yours? appeared first on Execs In The Know.

She began by emphasizing the dynamic nature of customer expectations, which are continually shaped by technology and societal shifts. She argued that staying ahead in the CX game requires meeting and exceeding these evolving expectations.

This premise set the stage for her exploration of why a robust strategy around the VOC is beneficial and essential in today’s business environment.

Highlights from Tracy Sedlak’s Keynote

Customer Empathy: At the heart of Sedlak’s message was the importance of empathy. Understanding the customer’s perspective and emotions is key to designing experiences that resonate personally.

Data-Driven Decisions: She advocated leveraging data analytics to uncover insights into customer behavior and preferences, enabling more personalized and effective customer interactions.

Feedback Loops: Another central theme was the significance of creating effective feedback loops to capture, analyze, and act on customer feedback. Sedlak pointed out that this process is crucial for continuous improvement and innovation.

Cross-Functional Collaboration: She emphasized the importance of breaking down silos within organizations and called for enhanced collaboration across departments to ensure a cohesive customer experience.

Adaptability: Finally, Sedlak highlighted the need for organizations to be agile, adapt strategies based on customer feedback, and change market conditions to stay relevant.

Why are these points critical? Because in the age of the customer, businesses that fail to listen and adapt risk obsolescence. Sedlak’s keynote made it clear that the Voice of the Customer is not just a feedback mechanism but a strategic tool that can guide the entire organization towards greater customer centricity, innovation, and ultimately, success.

Moreover, she discussed the importance of technology in enhancing CX, from AI-driven personalization to seamless omnichannel

experiences. However, she cautioned against overreliance on technology without the foundational elements of empathy and understanding.

Her keynote was a clarion call to CX leaders to prioritize the VOC in their strategic planning. Organizations can meet and exceed customer expectations in this dynamic landscape by embracing empathy, leveraging data, fostering collaboration, and maintaining adaptability.

Sedlak’s insights serve as a guidepost for those looking to lead in customer experience as the business world evolves.

Thank you to Offerpad and Tracy Sedlak for her leadership, participation, and insights.

To connect with Tracy or to participate in the broader CX conversation, consider joining the Execs In The Know “Know It All” (KIA) Online Community. The KIA Online Community is a private, online community designed exclusively for CX Leaders at consumer-facing brands. Come learn, share, network, and engage to innovate.

Registration for CRS Palm Springs is now open. Join us September 24-26, 2024, for a dynamic in-person Summit tailored for leaders shaping the customer experience landscape in their organizations. This gathering is about fostering learning, sparking inspiration, and forging meaningful connections with your fellow CX visionaries in an inclusive and collaborative setting.

The post Beyond Satisfaction: Key Takeaways from Tracy Sedlak’s CRS Tucson Keynote on Voice of the Customer appeared first on Execs In The Know.

But how can you truly connect with your customers and cater to their ever-evolving needs? The answer lies within the vast, untapped potential of your customer data. In this blog, we will explore how leveraging customer data can breathe new life into your customer journeys, enabling your organization to stay ahead of the curve and drive meaningful impact to deliver exceptional customer experiences (CX).

The Untapped Potential of Customer Data

Organizations collect a wealth of data at every customer touchpoint, from website interactions and social media engagements to purchase histories and support interactions. This treasure trove of information is not just raw data; it holds the key to understanding customers like never before.

By harnessing this data effectively, brands can uncover invaluable insights into customer behavior, preferences, and pain points. Armed with this knowledge, you can align your products and services to address genuine needs and desires, transforming your CX  into one that is truly customer-centric.

Unveiling the Customer Experience Patterns

Within your customer data are patterns waiting to be deciphered. Every interaction and every decision made by customers leaves behind digital footprints that form distinct patterns. By connecting these dots, you can gain a holistic view of a customer’s journey with your brand.

Understanding the touchpoints where they engage the most and the pain points that hinder their experiences can empower you to fine-tune your CX strategy. This insight ensures that your organization remains agile and adaptive to meet customer demands with precision.

Personalization: A Game Changer

In a world where customers seek authentic connections with brands, personalization becomes a game-changer. Customer data provides the necessary building blocks to craft personalized experiences that resonate with individual customers on a profound level.

From tailored product recommendations to targeted marketing campaigns, personalization demonstrates that your organization values each customer as a unique individual. The result? Heightened customer loyalty, increased engagement, and unparalleled customer satisfaction.

Predictive Insights for Proactive Engagement

Beyond understanding the past lies the power to shape the future. With advanced data analytics and predictive modeling, your organization can unlock the ability to anticipate customer needs and behaviors. By analyzing historical data, you can identify trends and patterns that foretell future demands.

Armed with this foresight, your organization can proactively engage with customers, providing timely support and offering relevant solutions before they even realize they need them. This level of proactive engagement not only streamlines operations but also fosters a deep sense of trust and loyalty among customers.

Overcoming Data Privacy Concerns

Prioritizing data privacy and security is key. Trust is the cornerstone of any successful customer relationship, and safeguardin

g their personal information is non-negotiable. Transparent communication about data usage, stringent adherence to privacy regulations, and implementing robust security measures demonstrate your commitment to protecting your customers’ trust and your brand’s reputation.

Building a Data-Centric Culture

To fully unlock the transformative power of customer data, building a data-centric culture is paramount. This requires more than just investing in data analytics tools; it demands a company-wide commitment to embracing data-driven decision-making. Encourage cross-functional collaboration, invest in training your teams to interpret and use data effectively, and implement data-driven KPIs.

When data becomes the guiding compass of your organization, you set the stage for constant innovation and an unwavering focus on delivering exceptional CX.

Embrace Customer Data, Embrace the Journey

As a CX leader, you hold the key to redefining customer journeys and unlocking success. By leveraging the untapped potential of your customer data, your organization can gain profound insights, unveil patterns, and craft personalized experiences that resonate deeply with your customers.

Embracing the power of predictive analytics can help you stay one step ahead and foster a culture that values data-driven decision-making.

The post Redefining Customer Journeys: The Power of Leveraging Customer Data appeared first on Execs In The Know.

For example, in springboard diving, a “3-meter forward dive with a tuck” has a degree of difficulty of 1.4. Judges rate dives based on four categories: approach, take-off, execution, and entry, and multiply by the degree of difficulty to arrive at the final score for the dive. In other words, some dives are easier than others and rewarded accordingly.

It’s similar to today’s business executives trying to optimize business performance with data. Some steps are more difficult than others. Let’s look at some examples.

Approach: What? Where? How?

You may not really know what data exists, where it is stored, or have the technical know-how to get it all together for use and analysis. That’s the starting point for successfully getting insights from your data—but it’s only the starting point.

Degree of difficulty to solve: 5 out of 10

Take Off: Analyzing the Data

If you can get past that first barrier and locate what you have, where it is, and how to pull it together, then how do you analyze all the data? It’s not simple. You’re likely dealing with multiple types of data: structured, unstructured, front office, back office, marketing systems, interaction systems, social media, and the list goes on. There’s so much data that even the clear signals can actually look like noise.

If you can get past that barrier of figuring out your data, the next challenge is determining what do you actually need to know? Besides intuition, experience, current data set of reports, advisors, competitive information, Google searches—and maybe a dart board—how do you know you’re getting the highest caliber information and intelligence and removing all the noise that doesn’t matter?

You need to know what you need know before you start asking questions and performing the analysis. To be successful, insights programs need to follow design thinking principles, otherwise, all you get is noise, false flags, and useless detail.

Degree of difficulty to solve: 7 out of 10

Execution: Decision-Making

Once you’ve determined what you need to know, the next step is using all that data to make the best possible decisions. Intelligence without action is a total waste of time, and actions are not always completely obvious, particularly today when there’s so many choices.

How do you leverage the data, insights, and intelligence to develop a list of options? How do you combine statistical analysis in prescriptive analytics and your experience and intuition to make the best possible choice?

And, by the way, time is of the essence! Every business on the face of the planet needs to move fast because their competitors are moving fast, customer expectations are moving fast, technology is moving fast, markets are shifting and shaping fast, regulatory environments are moving fast. So, you need to make decisions quickly from the best possible data with the highest quality signals addressing exactly the right questions.

Degree of difficulty to solve: 8 out of 10 

Entry: Applying it to Your CX Practice

OK, now you’ve got the ability to make decisions. But more importantly, how do you begin using insights in real time to change customer and business outcomes?

For example, let’s say your customer is in a live interaction with a bot asking a question and the bot dips into the platform, understands who the customer is, their history, their persona, what they are “feeling” now, their sentiment in the past, their past purchases and can predict what they are trying to do now. All of this culminates in a singular response that enables and equips the customer to take the easiest path to resolution, which creates the highest value for the customer and for the enterprise.

Degree of difficulty to solve: 9 out of 10

Ultimately, the next and final step is to quickly understand and assess whether the changes you are driving in the business are creating the value you expected. This constant feedback loop is critical, because without it, you won’t be able to adjust with the scope, scale, and speed that is required to be successful in today’s business environment. It’s essential to measure the right things in the right ways at the right time, and produce future signals that are going to enable you to meaningfully manage the business.

Degree of difficulty to solve: 10 out of 10

Diving into Your Data

You don’t want to get this wrong and end up doing a belly flop. Not only is it painful, but you’d be out of the competition.

Whereas diving has it’s scoring steps, at Concentrix, we use a model of:

Or, in short form: Insights to Outcomes.

Is all of this easy? Clearly not. Is it solvable? Definitely. We’ve built a team of data insight experts that have helped businesses across multiple industries solve exactly this challenge, and do it in manageable chunks. We can help evaluate what data you have, where it’s located, how to evaluate it and turn it into actionable insights, and then measure outcomes and adjust in real time.

Please join our panel discussion “Leveraging Customer Data and Insights to Design, Build, and Run a Winning CX Program” at Execs in the Know’s Customer Response Summit on March 2, 2023 at 2:15pm. I’ll be moderating a panel with CX leaders from United Airlines, Vistra, and iRobot.

I hope to see you there when we discuss how to help you get to a perfect score!

Guest blog post written by Reagan Miller, the Global Vice President of Analytics and Insights at Concentrix. To learn more about this topic and others, visit the events page to check out all of our upcoming events.

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The following is a guest blog by Mandeep Singh Kwatra, VP, Solutions and Capabilities at Hinduja Global Solutions (HGS). For more information about HGS, visit their website. 

As companies gain a deeper understanding of customers through research and predictive analytics, they will use that information to develop more individualized customer experiences. Today, it’s not enough to have a knowledge base. The best, most insightful business intelligence is developed from a contextual knowledge base that can be used by both agents and customers to predict the right answer based on that particular customer’s data, situation, location, and needs. The end result is faster responses, increased issue resolution, reduced customer effort, and happier customers.

Internet and digital channels have shrunk the world of customer information, and now everything is available at the click of a button. Customer loyalty is as fragile as that button click. Customers want brands to understand what they really need. They want everything personalized for them, at every step of the customer journey—from prepurchase research to complaints or when they are contemplating whether to jump ship. Today’s customers want personalized sales cycle, service queues, and complaints management. This means a knowledge base that employs two key elements:

– First, brand knowledge cannot be dated. It cannot be robotic or a copy paste of a manual or process. Knowledge has to be contextual. It has to be natural and language driven. It has to be how customers like to talk.

– Second, today’s predictive analytics answer to contemporary customer expectations, which are: to get the right answer fast, while also meeting sophisticated personalization criteria.

Contextualized Knowledge Bases

This shift from “content” to “context” requires companies to understand and categorize customers in personalized slots. According to a recent survey by Adobe, more than 60% of online users wanted to know why, what, and how web sites select content personalized for them. Companies need to have their personalization strategies backed by solid, accurate customer data. This is made easy by customers leaving a virtual bread crumb trail on their online journeys for brands to follow. But, the first order of business is to build a contextual knowledge base template that can support personalized customer data. Because customer behavior changes from one situation to another, a contextual database should include customer reactions across a broad spectrum of situations to be comprehensive and accurate. A recent study by Forrester Consulting on behalf of EverString found that marketers most often face the two challenges of ensuring data quality and managing data from a variety of sources (both 47%) in attempting to gain greater insights about customers and prospects.

In terms of reducing customer effort, contextual knowledge base helps with predicting the right answer based on that customer’s data, situation, location, and needs. Customer service can provide faster responses, increased rate of issue resolution, reduced customer effort, and happier customers.

Role of Contextualized Knowledge Bases in Personalization

Contextual knowledge bases support brand efforts for personalization by supplying crucial individual customer data for ad and campaign targeting. The same survey by Adobe found that for 33% of marketers, personalization is the one capability that will be most important to marketing in the future.

When implementing personalization, possessing the right kind of customer data is the most important necessity. You need to know the customer’s:

– Preferred communication platform

– Best time to contact

– Spending patterns

– Purchase plans

– Significant life situations (that can affect spending and purchasing patterns)

– Product preferences

Regular customers expect companies to know their preferences and even new ones think that companies should have some idea of what they’re interested in. Keeping up with these expectations means that companies need to build contextual knowledge bases that are capable of recording and linking intricate customer preferences to their contact database. Knowing the advances in technology, customers have come to expect personalized treatment and customer service by their favored brands, and rightly so. Customers expect brands to understand their need or issue and provide personalized solutions for them. However, data given to them in trust by customers, companies have to ensure it is used responsibly and in a transparent manner.

Contextualized Knowledge Bases and Predictive Analytics

According to the same EverString study, predictive marketers are 2.9x more likely to report revenue growth at rates higher than the industry average and 2.1x more likely to occupy a commanding leadership position in the product/service markets they serve. Predictive analytics is a crucial requirement to ensure that you get the best out of your contextual knowledge base and your personalization efforts are optimized for best results. Use of predictive analytics needs accurate data to plot patterns and predict customer behavior to tell you when a customer will indulge in a certain purchase or when they will begin to research products. Your contextual knowledge base should consist of sufficient customer data from different scenarios for analytics to be fairly accurate in predicting customer shopping patterns.

Also, ensure that your predictive analytics software is processing all available and relevant customer data from all sources. In today’s multi-channel environment, customer data is sourced from multiple contact platforms and so counting in every source is important.

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The following is a guest blog written by Lorraine Schumacher, Customer Experience Evangelist at Clarabridge. Learn more about Clarabridge by visiting their website.

Starting a Customer Experience (CX) program is no small feat. For Justin MacDonald, Customer Experience Manager at Infusionsoft, he eats, breathes, and sleeps CX and is a passionate champion and change agent within his business. A Software-as-a Service (SaaS) company that serves small businesses, Infusionsoft needs to earn their customers’ loyalty each month. To keep pulse on the customer experience—whether it’s calling the support center, using the product, or any other interaction—the business relies on customer feedback from multiple sources.

MacDonald shared some key principles that he’s identified as critical to understand when building a CX program.

CX Impacts Everything

It’s critical for a CX team to work cross-functionally because CX impacts all areas of the business, and all areas of the business impact CX. A true omni-source program gathers customer feedback from all sources, on all areas of the customer experience, and then makes that information actionable.

“With entrepreneurs and small businesses, business is personal, and their experience with every element of their journeys with our company and product impacts their business, their customers, and ultimately their vote to continue business with us each month,” said MacDonald. “Customer retention, cost of acquisition, and monthly recurring revenue are all majorly impacted by customer experience. We believe we will hit our business goals because we deliver a great customer experience.”

A true believer that a strong CX program is worth its weight in gold, MacDonald adds, “You don’t make experiences better for customers so that your company benefits; your company benefits because you make customer experiences better.”

Don’t Just Serve Customers—Empower Them.

“Our top priorities around the customer experience are first to make sure they feel understood and valued,” continued MacDonald. “Because small businesses often feel unique and alone, we let them feel empowered and by their partnership with us – not just by our software, but by our services and relationship with them dedicated to their success.”

This principle also applies to B2C companies. Empowering customers to share their feedback on their preferred channel, and to truly impact the business is critical. And on an even more personal level, a process for engaging with customers and closing the loop goes a long way.

Make Data-driven Decisions.

“We implemented Clarabridge about a year ago to feed customer insights to key strategic recipients who have an appetite and an influence to affect positive change in the customer experience and product,” said MacDonald. “All the way from the C-suite to the support floor – we harness champions everywhere we identify them. We currently flow customer sentiment from our NPS surveys and our new customer kick-start transactional surveys.” But it doesn’t stop there. Infusionsoft also uploads its support call NPS surveys into the platform for analysis, so they have a better understanding of the call center experience. “This provides us valuable solicited customer feedback both holistically as well as at a specific touch point in their experience to give us context on that feedback.”

According to MacDonald, the insight that comes out of these listening posts allows the company to understand customer sentiment about their product and service experiences. “It’s eye-opening and game-changing for us to see our customer base in unique segments. It has confirmed our previous beliefs and data in some places and busted myths we once held to be true.”

Because a data-driven approach is so critical to Infusionsoft’s CX program, they’ve invested heavily in implementing more and more customer feedback data sources into their program. They’re growing and maturing their program by going from solicited (survey) feedback to unsolicited feedback that includes customers, end users, partners, and employees.

Tell Stories That Make an Impact

While data is essential, the key to impacting true change is making that data personal. Pulling out individual customer stories and telling those stories in a relatable language is immensely powerful when communicating customer pain points.

“Part of the art and science of CX and Voice of the Customer (VoC) is telling transformational stories tailored to a specific audience, and rooting those stories in the reality of your customers,” said MaDonald. “Our company is continuing to mature to embrace the need to truly put our customers at the center, and it is that shift that is the greatest accomplishment of our VOC program. We are playing the long game.”

To hear more about this topic and others like it, join us at Customer Response Summit Phoenix, February 23-25, 2016.

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