CSP Happenings





Topic: Customer Intelligence

Positive customer feedback matters

May 24, 2017

Passionate customers tell you what makes your brand exceptional

Often, customer experience research focuses too heavily on business shortcomings.  Managers want to know when customers are dissatisfied, what caused their dissatisfaction, and how to fix the problem.  As a result, decision makers overlook positive customer feedback.  Managers expect positive feedback, and when it’s received, they don’t celebrate the occasion. Instead, managers continue to search for shortcomings in their businesses – they don’t want to be complacent, even if their customers are happy.  However, this oversight misses an opportunity: a chance to understand what drives customer passion and excitement.

Word-of-mouth advocacy is a powerful driver of new business, and positive customer testimonials received during customer experience research help highlight the topics brand advocates are most likely to talk about with friends and family.  To maximize the value of this feedback, businesses should ask customers the following questions about their experiences:

  • How does our service/product/interaction make you feel?  When a customer describes a positive experience, asking them about their feelings helps businesses understand the type of value their services bring.  Are customers relieved? Excited?  Do they feel in-control?  Understanding the specific emotions they feel helps businesses understand why a service/product/interaction is important, and what emotions are driving the customer’s behavior.
  • How is our business different from others?  When it comes to positive customer experiences, unique positive experiences are true brand differentiators.  Identifying those unique positive experiences allows businesses to replicate that experiences across their customer base.  Once the experience is consistent, that unique positive experience is a brand differentiator, which can be used to solicit new customers.
  • How does our business make a difference in your life, even if it is small?  Asking customers to relate a business’s services to their lives helps communicate those services in the customers’ language.  For example, customers might not care about the UX testing, which guided development of a bank’s mobile app; but they DO care that the app is easy to use and saves them time.  Managers and directors are prone to talk about the services they provide in their own terms – from the behind-the-scenes perspective, talking about the nuanced details of the services they provide.  Conversely, customer feedback vocalizes positive experiences in ways mangers struggle to verbalize, and their feedback provides a template for how managers should talk about the services they provide.

Beyond the benefits of analyzing positive customer feedback, the process provides a venue to build morale among employees and recognize their hard work.  By addressing positive feedback, employees are incentivized to continue (and increase) positive behaviors, which lead to positive customer experiences, because they know their good deeds are noticed and valued.

In 2017 and beyond, managers continue to look at positive customer experiences to identify, replicate and reinforce aspects of their businesses leading to positive feedback.  Once reinforced, branding/marketing managers use these competitive advantages to drive new business, while customers drive business on their own through brand advocacy.

Responding to negative customer feedback is important, but most organizations already do a good job at identifying their own shortcomings.  Many managers overlook positive feedback at their own detriment, and those who utilize feedback to create a model for consistent positive experiences will come out on top.

The Dangers of Overlooking Low-Value Customers

March 23, 2017

One way to segment your customers is by their lifetime value. Compared to many other measurable customer attributes, lifetime value is the kind of big-picture description that can be difficult to observe or estimate at a glance. But it’s also one of the most valuable pieces of information you can have about your customers.

Customer lifetime value is a prediction of how profitable your relationship with a given customer will be over time. Lifetime value can be calculated a number of different ways, from simple formulas to complex equations. Some of the factors that go into this calculation include how long you expect the customer to stay a customer; how much money that customer tends to spend with you, and how often; what it costs to keep that customer loyal; and the average rate of churn throughout your customer base.

Essentially, a lifetime value measurement boils down your relationship with a customer to a dollar amount. But the benefit of is not just quantitative: it influences businesses to prioritize the long-term maintenance of customer loyalty, compared to more expensive efforts like customer acquisition.

Using Customer Lifetime Value for Segmentation

customer segmentation based on lifetime customer valueOnce you’ve predicted the lifetime value of each customer, you can then group them into tiers, from most to least valuable. The most valuable customers are those who shop with you frequently, generate the most profit, and are most likely to stay. The least valuable customers may be new or casual shoppers who split their attention and money between you and your competitors. In the middle are the rest: regular, if not devoted, customers who don’t have the most to offer you, but don’t cost you much to keep, either. These are customers who could possibly be influenced toward more value if tended correctly – and if not, may slip down to the bottom tier.

For the highest third, the ones you can’t ask much more of, the goal is to make sure they stay. For the middle third, you can try to grow their value by appealing to them with additional services or products, or offering loyalty rewards, like discounts.

But what about the lowest tier – the one that experiences the most churn? Do they have anything to offer? Would you be better off without them?

Don’t Write Off Your Low-Value Customers  

Once you’ve singled out your most valuable customers, it’s only natural to want to gravitate in their direction – to reward their loyalty with perks, to provide them the best service, and to otherwise do everything in your power to keep them around and keep them spending. All this effort is still less costly than investing the time, energy, and budget to convert lower-value customers up the ladder.

All of that would seem to justify prioritizing your top tier. But do so at your own peril. Every customer’s “lifetime” with your business has to start somewhere, and many of them start in that lowest tier. It’s rare to simply acquire a high-value customer out of the gate: they must be nurtured, and this tier is where that relationship-building has the most impact.

Converting an existing low-value customer into a higher-value one is still less expensive than acquiring a new one, with unknown value. Despite the investment they demand, it’s easier to see a customer move up the value ladder, while the ones at the top are not terribly at risk of slipping back down (unless you really mess up). Besides, if you don’t devote attention to the least committed customers, chances are that your competitors would be more than happy to take them off your hands.

The easiest way to make your low-value customers into VIPs is to treat them like VIPs.

No matter how many invisible dollar signs hang over their heads, every interaction with your business and brand should make them feel valued and respected. They can also be a valuable source of insights and intelligence. Don’t be afraid to ask them directly: What would make you shop here more? How can we best serve you? Voice of the Customer research is your friend, especially among this group. What applies to some can likely be used to woo others.

Of course, some customers will just never be converted and end up taking up more resources than they’ll ever be worth to you. Customer divestment was once practically an anomaly, but these days, some companies see it as a smarter move than keeping low-value customers on the books. (Read more: The Right Way to Manage Unprofitable Customers on HBR.org – though we at CSP don’t necessarily stand behind that headline.)

Bottom line: Give each customer the attentive and inviting customer experience they deserve, and watch the overall value of your customer relationships grow.


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Customer Segmentation in the Big Data Age: Where Banks Find Value

February 8, 2017

Customer segmentation helps banks get to know their customers on a more granular level. Segmentation reveals specific intelligence that could otherwise be obscured by the sheer volume of data. These insights, in turn, inform messaging strategies for marketing and customer service strategies. Segmentation can also help banks better understand the customer lifecycle and predict customer behavior.

Examples of common customer segmentation criteria:
  • Customer value – How many products & services customers purchase and what kind of revenue that generates for the bank – past, current, and predicted for the future
  • Demographics – Age, geography, gender, generation (e.g. Millennials and Baby Boomers), income level, marital status, and other “vital statistics”
  • Life stage – Slightly different from age, focused instead on customers’ journeys through various milestones and markers; for example, graduating college or starting a family
  • Attitude – Customers’ subjective stances on things like the financial industry as a whole, online and mobile banking, the economy, and their satisfaction with their bank
  • Behavior – Interactions and transactions between customers and their bank, which channels they use and how often, and which products they adopt

Similar criteria can be applied to banks’ business customers – profitability, number of employees, “life” stage (start-up, established, legacy), and so forth.

These are the traditional ways that customers have been segmented for decades. However, relying just on these categories is not going to yield many actionable insights.

In the age of Big Data, you sometimes have to think small. The real power of segmentation is not the quantity of data you can collect – which, with today’s technology and methods, is virtually infinite. It’s in the ability to drill down to the information that actually teaches you something about your customers.

Often it’s not the segments themselves, but where they overlap, where you’ll find the most valuable intelligence.

customer segmentationSome examples: unmarried, home-owning, degree-holding women under 45; middle-income married parents of high-school-age children in a particular school district; and minority Millennials who are starting their own digitally driven businesses.  Any of these micro-segments may prove valuable customer niches for banks to prioritize. But first, you have to conceive of their existence. Second, ask the right questions. And third, conduct the relevant research to answer those questions.

To understand how this can come in handy for banks, just think about the sometimes bizarre categories that show up in your Netflix queue based on what you’ve been watching lately. Vintage sci-fi with a strong female lead? Critically acclaimed British nature documentaries? Criminal investigation murder mysteries based on books? The more they know your tastes, the more likely you are to keep using their service based on their recommendations.

The options for how segments can overlap are nearly limitless.

Nearly. There is a bell curve to the usefulness of segmentation. Too broad, and the results are less than insightful. Too narrow, and the value of the insights gained will have minimal bottom-line impact.

This is where it helps to have experienced data scientists on your side. The purpose and advantages of segmentation are easy to enough to grasp, but the farther you get into analytic methodology, the more highly technical it becomes, and the more you need to understand about mathematical models and formulas. If things like our guide to data visualization make your eyes glaze over, chances are that the nuances of segmentation will put you right to sleep, too.

But you’re in luck, because CSP’s customer experience & research experts are passionate about getting you the insights you need out of the wealth of data we can gather. So if you are interested in getting to know your customers down to the niche level that segmentation empowers, give John Berigan a call at (800) 841-7954 ext. 101 or contact us by email to start a conversation.


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Why You Need More Than One Metric to Describe Customer Loyalty

August 31, 2016

As a business leader, you know the importance of keeping your finger on the pulse of customer loyalty. A critical part of customer relationship management, customer loyalty goes well beyond a customer making a purchase. Loyalty is steeped in the relationship between the company and purchaser.

A loyal customer believes your organization offers the best option. Loyal customers will purchase a product or service from the same brand, over a long period of time, while turning down competitors, and spreading satisfaction through word of mouth. Loyal customers will stay with you even in trying times. 

Customer loyalty can’t be summed up in a single number.

customer loyalty can't be summed up in a single numberWhile loyalty may appear as a single topic on your priority list, it would be a mistake to try to measure it with just one indicator.

As an example, many businesses looking to improve customer satisfaction use a Net Promoter ScoreSM (NPS®). This system measures the likelihood that customers will recommend a product, service, or company to others, and is often touted as “the only number you need to know.” Likelihood to recommend is certainly worth measuring; CSP uses the NPS® system ourselves. However, this score alone does not tell you enough.

Think of it this way: You wouldn’t use your blood pressure as the sole indicator of your total health, right? It’s important, sure, and it would be convenient if that was all you needed to pay attention to, but it’s not the only vital statistic your doctor needs to track to assess your overall well-being. The same logic applies to customer loyalty.

Instead, what you should aim for is a customer loyalty index that reflects multiple measurement methods and tracks them over time. This allows you to break down the customer relationship into feedback, perceptions, and issue resolutions. Ultimately, you’ll be able to see what you need to do to maintain and increase your loyal customers.

Aim for a full picture of your organization’s brand loyalty.

Measuring customer loyalty in a variety of ways gives you a more comprehensive, multi-dimensional view of your customer loyalty situation. In addition to at-a-glance scores like NPS®, a customer loyalty index can include attitudes and behaviors such as overall satisfaction with customer service, and likelihood of a customer to make a future purchase.

Capturing this data will yield many benefits, among them:

  • Producing a good view of your current standings with the customer,
  • Predicting future retention, and
  • Providing the foundation for building a loyalty profile for your customer.
Closely examine your metrics at the outset.

According to IRI, 44% of Millennials claim to be brand loyal. With their impressive purchasing power, figures like that should motivate you to keep the company-customer relationship at the forefront of your strategic planning.

What do you want your measurements to tell you? Start with the results you want to see to help you decide how to prioritize the data you collect. You will likely find you need more indicators than you thought, but taken together, all these measurements complement one another.

Studying the results of your customer research will produce opportunities to compare your organization against industry standards and your direct competitors, identify your strengths and weaknesses, and zero in on customer preferences. CSP’s Customer Experience Management solutions are designed to provide exactly these opportunities, with the added benefit of guidance from seasoned experts to help you identify what to focus on and what steps to take.


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Net Promoter, NPS, and the NPS-related emoticons are registered trademarks, and Net Promoter Score and Net Promoter System are service marks, of Bain & Company, Inc., Satmetrix Systems, Inc. and Fred Reichheld.

Insights at a Glance: The Power (and Pitfalls) of Data Visualization

April 8, 2016

The process of gathering and analyzing customer experience data involves several translations.

  • Desired outcomes are translated into measurable attributes.
  • Attributes are translated into feedback tools (such as survey questions).
  • Customers translate their sentiments into quantifiable scores – data points.
  • Data points get translated into ratios, averages, and frequencies.
  • The collected data can then be translated into knowledge.

Customer experience researchers and data analysts are charged with the task of following all these translations step-by-step, but in the end, most non-analysts are only interested in that ultimate goal – the knowledge.

That’s where data visualization comes in. As humans, our understanding of data relies heavily on how that data is presented to us. Visualizations are among the best tools for making that final translation from information to insight.

Visualizations make data memorable.

Have you ever struggled to remember the name of a particular actor even though you can see his or her face clearly in your mind? For most people, it’s easier to remember something they have seen than something they have heard or read. Once translated into an image or graphic, data becomes less abstract and makes a distinct impression – one with staying power.

Visualizations make clear connections between parts of the whole.

Insight comes from connecting A to B to C and so on. A number by itself doesn’t say much until it’s put into a context of other numbers. Sometimes, even a simple table can help, but the more complex your data, the more difficult it is to glean insights just from reviewing the figures. Visualizations are handy shortcuts that make the relationships between data points immediately clear, getting you straight to that “light bulb moment.”

Visualizations influence how data gets interpreted.

Data is objective, but visualizations are subjective. There are a number of factors that influence the message a person receives from looking at a graphic: size, scale, color, even font choice. What’s more, the most basic types of visualizations – pie charts, bar charts, line graphs, and scatter plots – are each best suited to different purposes. Using the wrong kind of graphic for the type of data can be misleading or obscure the possible conclusions.

This pie chart can show what percentage of respondents in 2015 chose each answer. It cannot show a comparison to other years, nor can it show any other metrics.

This pie chart can show what percentage of respondents in 2015 chose each answer. It cannot show a comparison to other years, nor can it show any other metrics.

This bar chart can show all three years’ worth of data at once. It’s decent for showing the change in each measurement over time, but a line chart would be a better fit.

This bar chart can show all three years’ worth of data at once. It’s decent for showing the change in each measurement over time, but a line chart would be a better fit.

This line chart shows how each measurement changed over time. Note that instead of representing the total for each year between 2013 and 2015 (which would produce very short lines with little variation), this chart shows month-over-month trends for each response. Line charts work best when comparing a more thorough set of dates.

This line chart shows how each measurement changed over time. Note that instead of representing the total for each year between 2013 and 2015 (which would produce very short lines with little variation), this chart shows month-over-month trends for each response. Line charts work best when comparing a more thorough set of dates.

A scatter plot, not shown here, would be a good choice for displaying each response to a particular survey question. The above charts each show the total number of responses for each category, out of 1,285 responses to the same question, and each of those totals represents one point on the chart (or one slice of the pie). In a scatter plot, each of those 1,285 responses would generate its own dot, and the way those dots group together would reveal the trend.

Beware: Things aren’t always what they seem.

Visualizations are useful for drawing conclusions at a glance, but sometimes looks can be deceiving. Like statistics, visualizations can be manipulated to produce a particular effect – for better or for worse. For example, bar and line graphs depend on the scale of their vertical and horizontal axes. By increasing or decreasing the scale of either axis, bars can be made to look smaller or larger, or trends to look more or less dramatic.

Because the maximum value on this chart is 560, the top of the range (vertical axis) is 600. The red bars for “mostly satisfied” are far longer than any of the light blue bars for “completely dissatisfied,” making it look like hardly any respondents chose the latter. Because the maximum value on this bar chart is 560, the top of the range (vertical axis) is 600. The red bars for “mostly satisfied” are far longer than any of the light blue bars for “completely dissatisfied,” making it look like hardly any respondents chose the latter.

This chart uses the same data as the previous one, but omitting some of the categories. Without the higher-scoring “mostly satisfied” values, now the maximum value is 338, making the top of the range 400 instead of 600. Even though none of the actual values changed, now the blue “completely satisfied” bars look much more significant. Likewise, some of the light blue “completely dissatisfied” bars that barely appeared on the first graph are now visible here. The second chart uses the same data as the previous one, but omitting some of the categories. Without the higher-scoring “mostly satisfied” values, now the maximum value is 338, making the top of the range 400 instead of 600. Even though none of the actual values changed, now the blue “completely satisfied” bars look much more significant. Likewise, some of the light blue “completely dissatisfied” bars that barely appeared on the first graph are now visible here.

All it takes is a closer look to see whether the graph’s scale is skewing the effect, but ideally, you should be able to get an accurate sense of the information at just a glance. Otherwise, the visualization isn’t doing its job effectively.

These aren’t the only kinds of visualizations, of course, especially in this age of customized metrics and creative infographics. They do, however, represent the basis of data visualization, and knowing how to read them prevents those valuable insights from getting lost in translation.


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How Banks Can Evolve Alongside Their Customers

August 18, 2015

We’ve written at length on this blog about important changes in the evolving banking industry, including the rising popularity of universal bankers, online customer support, FinTech firms (especially among Millennials), and an omnichannel approach to improving performance across all points of contact with customers.

As the industry forges ahead, so must the banking customer experience. It begins with asking the right questions about the key components of the customer relationship lifecycle:

  • Acquiring Customers: Which products and services capture potential customer’s interests? Which marketing channels are the most productive for prospecting customers?
  • Maintaining Customers: How can you better manage customer expectations? How could you better fulfill promises to keep customers satisfied?
  • Maximizing Customers: What opportunities do you have to up-sell and cross-sell? How could you improve your referral and recommendation solicitation?
  • Customer Loyalty: How else could you increase your customers’ purchasing power? What customer loyalty programs might you consider offering?
  • Customer Retention: How can you keep your good customers and reduce “churn?”

It’s enough to make any bank manager feel a little lost in the dark, feeling around for a light switch that will illuminate a clear path through. Every bank will have different goals, different needs, and different customers motivated by different key drivers, so while the destination is the same, no two enterprises will walk the same path.

The Three Stages of the Journey to Improvement

The three stages of the journey to aligning with customers

It begins with Stage 1, Data Infrastructure – the collection and reporting of Voice of the Customer data from feedback tools like surveys and evaluations. This becomes the Customer Intelligence that is the backbone of every successful CEM strategy. With this foundation, banks can better anticipate their customers’ needs and be proactive in offering personalized solutions.

Stage 2 is Performance and Insight. Once the data is collected, it’s time to do a deep analysis of the performance of all metrics, down to each branch and each retail position.  In this step, we identify what’s changing in customer needs and expectations by sifting through data currently siloed in various channels and integrating it into a complete, 360-degree view of the customer experience.

Stage 3 is Holistic Strategy. Using the data and information from the previous two stages, the real work of improvement begins. This is the opportunity to perform an alignment check on the bank’s internal culture to see how closely it matches customer needs, wants, and expectations, and make necessary adjustments to establish and maintain the proper alignment.

There you have it: a clear path from Data to Information to Knowledge.

In our 25+ years of Customer Experience research, CSP has served as a “trail guide” to hundreds of banks walking their own paths to improved customer experience. We believe a bank’s value to its customers is defined through relationships. Employees, not smartphones or laptops, should remain at the center of those relationships.

Our experts are here to lead you through the three stages along the journey. More articles like this one can be found in our STARS library, available to current CSP clients as part of our full-service delivery. Contact us with any questions you may have.

What is Customer Experience Research?

March 6, 2015

Traditionally, Customer Experience Research falls into two main categories.

In the first category, there are market research firms that take an academic or scientific approach to collecting data and presenting the findings. These providers emphasize the purity of their data and the rigor of their methods and processes for collecting that information.

In the second category, there are data collection firms that specialize in gathering, storing, and organizing vast amounts of data from a variety of sources. Through their proprietary systems and tools, they make their findings accessible and digestible to the end user.

What does customer experience research capture?

The two metrics most important to customer experience management are customer satisfaction and customer engagement, which exist on a continuum and influence each other in both directions.

Customer satisfaction is an immediate measurement of an experience, from something as small as an interaction with a customer service representative to the overall feeling a customer has that his or her expectations and needs are being met. This is arguably the starting point for all customer research.

Customer engagement is what keeps customers coming back. It captures the long-term equity that is built on satisfying experiences by measuring things like loyalty and how likely a customer is to refer others to their preferred brands and businesses. In this way, it’s a more useful measurement than simple satisfaction: customers who are strongly engaged over time are more willing to overlook or tolerate the occasional less-than-satisfying experience.

A great example of this comes from the consumer technology industry. Brands like Apple and Google each have dedicated, loyal audiences that will continue to buy their products and tout their benefits to friends and family, even when the products themselves fall short of 100% satisfaction (think: buggy software releases or smartphones so thin they bend in your back pocket). This is the kind of engagement every brand dreams of.

The Journey From Data to Information to Knowledge

data information and knowledge

Both the academic and data-collection approaches to customer experience research have value. Market research can reveal trends, insights, and patterns across large populations and broader spans of time. Data collection, meanwhile, has grown so sophisticated as to merit its own industry, aimed at helping the everyday business manager access intelligence about their customer – because it’s unlikely they have the expertise or time to sift through it all themselves.

Both methods also have their limits. Statistical research may be useful in an ideal world where all customers have the same expectations and needs, and all businesses face the same challenges in meeting those expectations. But in a real-world setting, the insights garnered from this research often ends up “watered down” and are unlikely to apply to each unique business or brand the same way.

It’s not unlike the idea of the self-help book, which can be a useful way to talk about people in general, but won’t always apply on an individual level. You can do everything “by the book” and still fall short of your goals if the book you’re going by doesn’t account for the nuances of your business or your customers.

In turn, data collection is exactly what it sounds like: collecting data and presenting it as information. But turning that into knowledge that you can act on? That part is up to you. These firms often step out of the picture at that point, leaving you to figure out how that information factors into your strategies and tactics, what merits your attention and what doesn’t, and what steps come next.

Bridging the Gap Between Research and Reality

The shortfalls of traditional customer experience research are how businesses end up thinking they know their customers, without actually knowing them. There’s a break in the process that prevents them from getting to that next level of knowledge and using that knowledge to improve their customer experience.

In our 20+ years of customer experience research, CSP’s guiding principle has been to not only gather and present the information, but to then guide our clients in creating the roadmap to a better customer experience based on a thorough understanding of their unique customers.

Why should anyone have to figure this out from scratch? CSP has seen it all before, and we know what works and what doesn’t. Our experts are flexible enough to adapt to any given brand or business with a methodology that’s personalized every step of the way. Your specific questions about your customers, your market, and your competition are built right into the program, along with ongoing support, tools, and coaching to help you define and achieve your goals.

This level of customization and personal attention is hard to come by with traditional research models, but we believe it’s the key ingredient to successful customer experience management. We’re not passionate about data – we’re passionate about improving the customer experience, full stop.

For more information about CSP’s customer experience research methodologies and the programs we build to support them, contact us today by phone at (402) 399-8790 ext:101, via our website, or on Twitter @csprofiles

Release the Customer Intelligence Trapped Within Data Silos

February 25, 2015

Big Data is a big topic. In all the conversation about the potential for data to reveal key customer insights, broad statements and big promises are far more common than specific examples of the real-world answers a business might hope to gain.

There’s a reason that the word “data” is plural. An individual datum reveals very little on its own; it’s the connections, intersections, and overlaps of data that form the actionable patterns and trends.

Yet customer data is often still “siloed” into separate sources: direct customer feedback, employee performance measurements, web and mobile analytics, customer service interactions, standardized reports and evaluations, and social media impressions, to name a few.

Together, all of these data points can shed an entirely new light on the customer experience, but businesses are still learning how to effectively and efficiently connect the dots. Customer data is hardly self-explanatory, and legacy systems weren’t designed with this kind of interconnectivity in mind, leaving those insights trapped in silos.

transaction dataFor an example, consider financial service institutions. An article in BAI’s online edition rightly points out how these businesses are flush with transaction data generated by customers using credit cards, debit cards, checking accounts, ATMs, and mobile payments on a day-to-day basis.

This resource alone can tell the institution the number, types, locations, and frequency of transactions; the devices being used to complete these transactions; the breakdown of service and card types; and withdrawal/deposit amounts on a real-time basis.

Not only does this summarize the customer experience, there’s a direct connection to daily operations like cash inventory and technical support for digital tools (think: error code reports from a malfunctioning ATM).

Without systems in place to gather all of this customer data and deliver it in a digestible and useful format, to the correct teams, and in real time, valuable customer intelligence stays trapped in the Transaction Data silo.

Data is a living organism.

It consumes, it grows, it morphs and takes on new shapes, dimensions, and patterns. Each source of data depends on the others; by keeping customer data in silos dictated by their sources, a business risks starving itself of the vital information it seeks to gain by gathering data in the first place.

At CSP, we believe in the indispensable value of customized data delivery solutions designed around each business’s unique goals and customer experience. Don’t miss out on trapped data – talk to our customer intelligence experts today.

CSP can be reached by phone at (402) 399-8790 ext:101, via our website, or on Twitter @csprofiles.

What is Customer Intelligence?

January 21, 2015

what is customer intelligence

 

Customer Intelligence (CI) is a discipline within Customer Relationship Management (CRM) that relies on the collection of customer information to gain insights into behavior.

Using Customer Intelligence methodologies, companies can assemble and examine data to uncover customers’ preferences, motivations, patterns, wants and needs, and ground their strategy in that information to deliver a better customer experience.

Measurement & Analytics

Customers reveal things about themselves in their daily actions and inactions. Customer experience research, Voice of the Customer programs, and market research create a detailed and specific picture of the customer journey.

Integration & Context

The value of Customer Intelligence is in the scalability of the knowledge it confers. Within the cloud of data, you can find valuable insights about macro trends across your customer base and micro variations from customer to customer.

Prediction & Personalization

Let your customers know you value the quality of their experience by using customer intelligence to optimize their journey, target your messaging and efforts, and adapt proactively.

Conversion & Retention

By continuously striving to improve the customer experience, expect to have an impact on customer satisfaction, referrals, and opportunities to cross-sell.

 

Move from thinking you know your customers to really knowing them. Find out what kind of customer intelligence you could be missing when you talk to an expert at CSP today.

As banking paradigms shift, voice of the customer insights are critical

June 23, 2014

A significant shift is underway in how banks across the country are relating to and responding to their customers’ needs and expectations.

Spurred on by emerging technologies that put more control in customers’ hands – most notably, mobile banking – and a decrease in branch foot traffic in the last decade, some banks have begun experimenting with new customer service models to reshape the customer experience.

The June edition of American Banker magazine highlighted some of the initiatives being tested in select branches and markets, such as PNC’s “universal bankers,” employees who can handle tasks from a simple cash withdrawal to account and small business services. Read the full centerpiece article here.

The Battle for Branch Relevancy
It’s a trend that’s already disrupting other industries and has bled over to banking: Automated and self-service options have made today’s customer less reliant on branches and tellers, prompting speculation about the future of brick-and-mortar locations.

Yet, as the article points out, people are not yet ready to abandon personal interaction with their institutions, preferring to at least have the option of a human face or voice, even if their first stop is an app or ATM.

The shared goal behind these new models of customer service is seamlessness.

Branches may become extensions of a bank’s digital presence, and vice versa. Customers may still prefer to handle certain interactions in person, but they expect the person they’re dealing with to be more knowledgeable and flexible about transactions, products and services, and less roped off from one another (literally).

Temperature-Testing
It’s still early to tell whether and how quickly this integrated, flexible approach to banking service and sales will catch on – that growth will largely depend on how the concept is rolled out to market and how much change customers are willing to navigate at once.

To stay nimble, banks will need to make sure the voice of the customer does not get lost among the shuffle of new ideas and experiments. CSP will be watching, and more importantly, listening with great interest as customers encounter and evaluate the next generation of experiences crafted to exceed their expectations.