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Tagged: data

Improving the Customer Experience Through Benchmarking

August 11, 2015

Benchmarking is the process companies use to identify and establish key performance standards, or benchmarks, and measure their performance against those standards over time. With a benchmark analysis, a company can compare its current scores in critical areas against its own past performance, as well as against its competitors.

NewBAR

Done in-house from the ground up, benchmarking can be a dauntingly complex process. Benchmarks must be agreed upon, measurement tools and strategies implemented, research assigned and completed (which, in some cases, means navigating security and permission concerns), and reports compiled. The information in the final analysis can be invaluable, if the right resources, attention, and talent are invested in it.

What’s more, benchmarking is not a one-time exercise, but a living process that depends on continuing collection and interpretation of current data. The shelf life of a single analysis report is fairly short, but properly maintained, a benchmarking strategy can be a gift that keeps giving.

Where does benchmarking fit into improving the customer experience?

Often used to determine how a company is faring against its peers financially, benchmark analysis also has a qualitative application. This includes measuring the critical metrics of customer service and experience that carry the most weight with overall customer satisfaction – what CSP calls key drivers.

Responses to Voice of the Customer initiatives like surveys can be translated into scores and percentages, which then get used to identify the top, bottom, and average range of responses to those metrics. Comparing the most current available scores against these ranges gives an indication of whether the customer experience is excelling, lagging, or falling behind.

Benchmarking is a way for managers to reality-check their perception of how their strategies and employees are performing against what the customers are actually saying.

Benchmarking provides a competitive advantage

The quality of a business’s customer service is often a make-or-break factor in customer satisfaction, loyalty, and likelihood to promote that company to others. In many ways, customer experience is the marketing that keeps happening even after you’ve initially earned the customer’s business.

Benchmarking not only demonstrates a company’s performance against itself, but against a defined peer group of its competitors, measured by uniform standards. While a direct Company A vs. Company B comparison may not reveal much of use, there is valuable insight in identifying one’s overall standing among the rest of the pack.

For instance, let’s say a manager has grown concerned about how long customers are kept waiting before they speak to a representative. Maybe she has noticed longer lines on the sales floor, or customers looking frustrated or impatient while in line.

Through benchmarking, she has been tracking “wait time” as a key driver for six months, and sees that this month, customers have indeed indicated a drop in satisfaction against this metric. She then reviews the wait time satisfaction scores of her peer competitors and determines that they have seen a slight increase in the same period of time, dropping her company back in the ratings from the “top” to “average” category. Now there is a risk she may start to lose customers to the better-performing competitors.

This intelligence informs the manager of an opportunity to improve the customer experience by implementing new strategies to affect the wait time at her location. Continued benchmarking will help her track progress against that goal, and identify any new opportunities for improvement that may come along.

It doesn’t end with the report

Benchmarking is one step in the process – a critical one, but nonetheless, just one. As with all Voice of the Customer data, its ultimate value depends on how the information is used to improve the customer experience with well-informed training, continued evaluation, and timely reporting.

That’s why CSP’s new Benchmark Analytics Reporting Dashboard pairs so nicely with our training and employee support, such as the STARS library available to our clients, to create a balanced ecosystem of process, performance, and progress. The dashboard takes much of the rigorous research and reporting aspects of benchmarking and delivers an easy-to-read analysis that can tell you, at a glance, where you fall among your peer group.

To learn more about benchmarking, the new dashboard, STARS, or any other component of customer experience management, contact us with your questions.

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.

5 Customer Experience Resolutions You Can Make in 2015

December 31, 2014

 

new years resolutions for customer experienceIt’s that time of year again – as the calendar creeps up on the end of December, our thoughts traditionally turn towards the coming year and the opportunities it may hold. It’s a time for reflecting on goals and progress towards those goals, recognizing how far we’ve come, and looking for ways to improve.

Once you’ve decided on what you’d like to achieve personally in 2015, turn that lens on your customers and make some resolutions in the interest of their experience.

1. Embrace Data.

Every interaction a customer has with your business produces valuable information on the key drivers that directly influence the customer experience. Don’t be afraid of it – instead, commit to trying to understand it better. The voice of the customer can be interpreted through the language of analytics.

2. Get Personal.

Personalization is important in an age when customers can customize practically anything. It also means being responsive to the diversity among your customers across multiple demographics. Personalization makes for a more relevant experience, which leads to loyalty and referrals.

3. Adopt an Omnichannel State of Mind.

Speaking of personalization, one thing customers are likely to modify to their own preferences is the combination of channels on which they engage with your brand. Three customers with complaints will go to three different places to air those complaints – maybe one takes to Twitter, one fills out the Contact Us form on your website, and one phones your call center. Are you ready to meet them wherever they find you?

4. Tune Up Your Training.

Training is one of those ongoing goals that can never really be checked off the list, because there’s always room for improvements, updates, new ideas, and feedback. Keep your methods and materials current and relevant, and don’t let educational opportunities pass you by. Consider asking representatives for their input on the effectiveness of your training and what they’d like to see improved.

5. Smooth Out the Seams.

As customers move between the different platforms and channels that connect them to your business, they expect that movement to be free and unencumbered. Seamlessness is the holy grail of the new omnichannel school of thought. Use regular reporting and up-to-date information to identify areas of success and struggle, and be proactive with that knowledge.

Above All: Adapt.

The biggest challenge customer experience managers face is the constant churn of trends, innovations, competition, and news, and evolving customer expectations in the technology world, which is more and more enmeshed with CX by way of data, mobile, social, and online channels. It’s exhausting to keep up with, but they wouldn’t be called resolutions if they didn’t require some resolve.

 

What would you add to this list of customer experience resolutions? Tweet your suggestions to @csprofiles.

How Voice of the Customer Insights Can Improve Employee Training

December 22, 2014

The frontlines of customer service and sales are where the most direct and personal customer experiences happen. It’s also an area where customers tend to be more vocal about their satisfaction, or lack thereof. A good experience can make someone’s day, and a bad one can ruin it – and humans are just predisposed to complain more than compliment.

Positive and negative customer experiences also influence retention and attrition; a good experience can keep a customer coming back for years, but one bad interaction and they might write you off forever.

And in the days of social media, one customer’s bad experience can easily spread to others and affect public perception of your brand.

Training ClassroomWith all of this at stake, no business can afford to deprioritize employee training and coaching. Training builds bridges between customers and customer-facing employees.

Creating, maintaining, and delivering an effective training program is no simple feat, but your customers will thank you for the effort.

One size never fits all.

As convenient as it would be, a one-size-fits-all approach to training is likely to miss the mark in more ways than one.

Every customer base is different, as is every workforce. Employee training initiatives must take into account not only the unique customers’ expectations, but the internal culture of the company. The better aligned these two conditions are, the better experience customers are likely to get, and the more productive employees can be.

Education is always evolving.

Customer expectations change with time, influenced not only by their relationship with your business, but trends and innovations in the marketplace as a whole. What was satisfactory last year may be insufficient today.

Static, standardized training is not sustainable. Regular evaluations of your materials, curriculum, and methods will keep your program responsive and current.

Mind the gaps.

So how do you optimize your employee training? Listen to the voice of the customer. VOC research and insights highlight gaps in employee performance and customer sentiment. This creates the opportunity to customize your training initiatives to focus on the attributes picked up within the research.

Knowledge is power – as long as you act on it. Measurements alone don’t do anything for anyone. At the end of the day, a customized, optimized, VOC-informed training program creates the opportunities for conversations that lead to loyalty and sales.

 

Customized training solutions based on VOC insights are part of the package of services CSP provides our clients. To find out more, visit our Coaching & Training page, or contact us directly with your questions.

What Influential Trends will Drive Financial Service Customer Experience in 2015?

December 15, 2014

dollar-exchange-rate-544949_640

Banks are catching up to their customers, and specifically, how those customers access their products and services. The unprecedented diversity of channels customers see today is influencing how banks allocate resources to each channel to align with evolving customer expectations.

In December, BAI released its latest Banking Strategies Executive Report, brimming with interviews and opinions from thought leaders and retail banking executives from around the country. You can request your own copy of the report from the BAI website, but for those short on time, here are some of the highlights:

Omnichannel Strategies that Revolve Around Mobile

As mobile devices become more central to consumers’ everyday lives, so too has the mobile channel taken a central role on the omnichannel stage, which makes sense: mobile is perhaps the most omni of all channels.

Devices can be used practically anywhere, and for a number of different purposes – checking balances, depositing and transferring funds, searching for information, calling a branch or customer support line, leaving reviews on consumer-facing sites like Yelp, and following a bank’s social media feeds.

Mobile will continue to be a key area of focus in 2015, but more importantly, banks will need to grasp how this channel intersects with and influences others, and how customers move between all of them.

“People are not migrating solely from one channel and leaving another one behind. […] The branch continues to be a significant channel for even the most technologically-savvy customers.”
David L. Stein, Executive VP and head of consumer and commercial banking for Associated Banc-Corp

The adoption of mobile among consumers could have banks looking at mobile solutions for their business customers, too, such as payments and remote deposits. B.C. Krishna, President and CEO of MineralTree, Inc, notes that “the vast majority of B2B payments still tend to be manual, paper-based, ad-hoc, check-oriented transactions” that cost money to process. Could 2015 be the year we see that start to shift?

Personalized Experiences Based on Data

It goes without saying that no two customers are exactly alike, and now, financial institutions have access to the data to help paint a fuller picture of each individual.

But it’s not the data itself that matters, it’s what you do with it. In 2015, banks can use this customer intelligence to deliver a customer experience that not only seamlessly flows between channels, but recognizes each customer’s unique needs.

In fact, through the rise of predictive analytics, banks have more capacity to anticipate these needs and be proactive in offering solutions to each customer – perhaps before the customer themselves has identified a need. Consider this the Small Data within Big Data.

Not only does personalization contribute to the customer experience and to loyalty, it could be a competitive differentiator as consumers gravitate to the providers who best suit their unique needs.

“Many banks have made strong steps towards customizing customer experiences, particularly on mobile and in social media, but not all banks are as far along as they could be.”
Simon Mulcahy, Senior VP Financial Services at Salesforce.com

Refinements on the Frontline(s)

A lot of the data, mobile development, and analytics we’ve discussed so far are things happening in the background, but lest we forget, the frontline of customer service is one of the key direct experiences a customer has with your bank.

“Employees in the frontline environment of the retail bank are important because the frontline largely impacts the customers, and as a result, can influence results – positively or negatively,” warns Malysa O’Connor, director of financial services at Kronos, a workforce management solutions provider.

These days, the frontline isn’t always the teller behind the counter or the rep on the phone. As customers connect to their banks through other channels, like social media, every bank’s training efforts, methods, and materials will need to continue to evolve in order to maintain alignment, not only with customer expectations, but company culture.

 

CSP is thrilled to see our clients forward into the New Year and guide them as they navigate these up-and-coming challenges and opportunities to create the best customer experience.

To keep up with current developments in retail banking and customer experience management, don’t forget to follow @CSProfiles on Twitter.

Customer Intelligence Lies Buried in the Code Halo

December 10, 2014

If you’ve ever been on a diet that involved calorie-counting, maybe you can relate to looking at a piece of food and automatically estimating its caloric content, as if a little number were suspended in the air right above the plate.

sun haloImagine that kind of information-enhanced meta-vision projected onto consumers, and you have the visualization of Big Data. Every interaction we have with businesses across every channel produces a parcel of data, and together those parcels orbit around each person in a cloud – or, you might say, a halo.

Published in April 2014, the book Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business has gotten attention and positive reviews for the authors’ examination of the complexity of data in the modern marketplace and what that means for businesses.

The idea is that these code halos are transforming interactions between individuals, and between customers and brands. Businesses are awash in readily-available information about customers, and it’s more common these days to hear someone describe their enterprise as “data-driven.”

Gone are the days of typifying customers into pre-determined demographics and limited personality profiles. Instead, the buzzwords of the day are customization, personalization, and seamlessness.

It’s the Age of the Customer, alright.

Still, you have to admit … things were a little simpler back in before the data revolution. Customer profiling didn’t arise out of nowhere; it was a useful tool in its day, as secret shoppers, customer surveys, and other tried-and-true methods have been.

Big Data has exploded faster than many enterprises have been able to wrap their heads around it. An entire new spectrum of possibilities and variables has been opened to us, and it’s difficult to determine where to start, what’s valuable, what’s actionable, and what merits attention.

Code Halo points to successful businesses like Amazon, Apple, Google, and Netflix as pioneers who owe their success to masterful management of customer information that propelled them above and beyond traditional competitors like Borders, Kodak, Yahoo! and Blockbuster.

It takes a sharp eye to look at a halo of ever-changing data parcels and find a coherent string of insight, and many customer experience managers are finding that they need to adjust their vision for this new paradigm.

The good news is: you don’t have to go it alone. Helping you make sense of customer intelligence is what experts like CSP are here for. So if Big Data is giving you a Big Headache, we likely have a solution for that.

Follow us on Twitter, Facebook, and LinkedIn for regular news and views on customer experience management, analytics, and voice of the customer research.

The Rise of Predictive Analytics in Customer Experience Management

September 17, 2014

The emergence of Big Data has been one of the most disruptive events of the new millennium, impacting practically every industry.

Technology has leapt forward again and again over the last decade, and brought us new tools for accessing, collecting and delivering data with mind-boggling volume and velocity. With the floodgates open, businesses large and small are still looking for the best way to turn this vast ocean of disparate information into valuable insights, action steps and outcomes.

One new tool enabled by Big Data fits comfortably into the customer experience manager’s tool belt: predictive analytics. By streamlining internal and external sources of customer information, this method of data-mining is applied to anticipate an individual customer’s needs and wants with greater speed and reliability than has ever been possible.

Finding Shapes in the Cloud

Predictive analytics, in a nutshell, means identifying patterns in an existing data set and extrapolating those patterns to deduce what is most likely to occur next. Businesses were already doing this before the Information Age, but by largely outsourcing the task to algorithms, we’re now able to crunch much larger data sets in much less time and come out with much more nuanced portraits of customers.

Another advantage of predictive analytics is the ability to quickly and easily drill down to the individual level. A single customer produces a wealth of data on a daily basis by simply going through the motions of his/her life. By applying resources to examine just that customer (rather than the general demographic or profile he/she fits), a business can design a tailor-made experience with the best likelihood of producing the desired outcome – be that sales, loyalty, or resolution of a complaint.

Export that ability across every individual in your customer base, and you can see how the lines between responsive and proactive are blurring. For example, Wells Fargo rolled out ATMs that deliver a unique display of buttons and options each time a customer signs in, reflecting how that particular customer has used ATMs in the past and will likely use it this time.

Big Data vs. Big Brother

In a way, predictive analytics has taken us back to the Main Street General Store model of doing business, where the proprietor not only knows your name but has your shopping cart all but ready to go when you set foot inside the door. This kind of personal attention is what customers want and what keeps them coming back, right? Yes – to an extent. But it’s deceptively easy to cross the line.

You may recall this headline from 2012: Target figured out one of its customers, a teen girl, was pregnant before her father did. The retailer relied on patterns in her customer data to reach this conclusion and ‘congratulated’ the young woman with personalized coupons for maternity and baby gear. Her father intercepted the mail, leading to a very irate confrontation with an oblivious store manager who had nothing to do with the decision to target (no pun intended) this customer with maternity messaging.

As it turned out, the data didn’t lie, but the damage was done and not limited to just that household. The story spread rapidly across the Internet and became part of the growing narrative of distrustful consumers and intrusive, creepy companies who know just a little too much. Brands want relationships with customers, and customers do respond well to the personal touch, but they sure don’t want to be stalked.

That’s why, even as the technology continues to leap forward, there’s still no real substitute for the kind of expertise that comes from years of hands-on customer experience management. With great power comes great responsibility, and as a discipline, predictive analytics is still maturing. Leaving all decision-making to the algorithms may be accurate, but wisdom doesn’t translate well to automated code.

By integrating CSP’s Voice of the Customer research with actual sales results, our Predictive Sales Analysis (PSA) brings together the best of both worlds. We produce a unique set of key drivers determined by employee behaviors that have the greatest correlation to sales metrics, and coach clients to focus on the areas that are most important to their business strategy. Learn more about PSA.