Customer Focus

In my last post I made the case that the future of business will require more reliance on powerful, computer-based analytics that interact with (not supplant) skilled data scientists who bring both analytic and business context knowledge into the process. Modern, effective customer insight analysis requires this kind of efficient cooperation between the analyst and the analytic engine to meet the business objectives of our customer insight function.

While this cooperation between analyst and the analytic tools is critical to effectively producing useful customer insights, it is equally critical to getting those insights implemented within the business. This is especially true when attempting to apply predictive analytics to the way we manage and interact with our customers. We need a system that is designed around the people for whom the insight is produced - a system that allows the insights to support the decision-making of the people and processes that directly impact your customers.

I have been part of many predictive analytics projects over the last 5 years. Nearly all of them have successfully extracted a set of useful insights that have impacted the way companies think about or interact with their customers. However, very few of them have made an impact on the specific actions taken toward specific customers, which is necessary to experience the full power of predictive analytics. For instance, I once built a model that predicted whether or not a channel partner's revenue to the OEM was going to decrease in the following year. It was a very accurate model, and it highlighted a number of key reasons behind declining revenue. The drivers of decline were immediately seized upon by channel management, and task forces were put in place to better understand and fix them. However, no one was able to find a use for the ability of the model to identify specific partners who were likely to decline in the coming year.

There are many reasons that customer (or partner) focused predictive analytics fail to impact specific decisions made about specific customers. A majority of the reasons I've encountered can be attributed to an excessive gap between the point of insight production and the point where the insights result in actions toward specific customers. In the pioneering book on enterprise decision management - Smart (Enough) Systems - Neil Raden and James Taylor dub this phenomenon the 'insight-to-action gap.'    

In my experience, there are two critical reasons that this gap exists for customer-focused predictive analysis projects:

1. The analysis project was not focused on a specific, customer-focused decision-point. Many insight projects start with the goal to see what we can find that will predict an increase in revenue. This is not a bad thing. Sometimes we need to start this way to understand where to dig further. Just don't expect these projects to yield quick and specific action.

2. There was no forethought or buy-in to the process by which insights will be delivered to the front-line employee for action. This often happens when a customer strategy group gets access to previously unintegrated datasets about the customer and has been tasked with providing insights about a particular issue like low renewal rates. They, rightly, decide that predicting who will and will not renew is more actionable than just looking for drivers of renewal, and a predictive project is launched. I fully support this thinking except there is no definition around getting the 'actionable' insight into the hands of those who will act.

The reason both these situations yield a gap between the insight and action is illustrated in the figure above. After an insight is developed, the next defined step is developing a report and presenting it to group of managers or executives. We bring our amazing project and results, and lay it out for them to approve or disapprove of. The best case is that they approve and say, "We need to use this information to intervene and stop the predicted bad things from happening while capitalizing on the predicted good things!" Then what? Then a group of people, which may now include at least a manager of those who will take the action, is convened to create a strategy for operationalizing the insight. By the time the insight actually impacts a customer it could be months later.

Thankfully, there is a better way, and it's all about beginning with the end in mind. Start by defining the specific customer outcome you want to predict - not something broad like customer revenue, but a specific aspect like customer spend on new products. The next step involves identifying the decision or interaction point at which you will intervene. This requires involving the group who will be responsible for the intervention and designing the process/system to do it. Then we move on to identifying and integrating data, running analysis, putting the insights into action, via the pre-defined and agreed-upon process, and validating the impact. An upcoming post will discuss this process in more detail, but the most important step is knowing exactly what to predict and what you will do with that prediction when it comes. Without that, your well-crafted insights are likely to stagnate. We need to mind the gap.

As January comes to a close, I thought it might be beneficial to pause for a moment and provide some thoughts on what trends we see emerging in the science of customer listening. Over the next several blogs, I will comment on a key trend and discuss the implications for customer strategists. Before delving into our first prediction, we need to discuss what we saw in 2012 from a customer loyalty perspective.

Loyalty in 2012: More of the Same

Source: Walker calculations based on data from http://finance.yahoo.com

It may go without saying that 2012 was a volatile year – the chart above shows the progression of a $100 investment on 1/3/2012 in each of the major stock indices – the Dow 30, S&P 500 and the NASDAQ Composite. The values are not as important as the shape of the curves – it demonstrates that 2012 had many ups and downs in the market. There are a number of reasons for this – the broader global economy, geopolitical unrest, the year-end drama related to the fiscal cliff, and so on. In this period of volatility, the impact on customer loyalty is not surprising – among Walker’s client base, the percentage of customers who are Truly Loyal was flat between 2011 and 2012; on a quarterly basis, we saw more variance in the loyalty scores with a drop in the last quarter of the year.  This is not isolated to Walker; many of the other industry benchmarks suggest that customer sentiment was flat at best in 2012 (and some have not yet published Q4 results).

Source: Walker Benchmark Database, B2B-Oriented Programs

Is Loyalty Dead (or Even Achievable)?

Despite some claims that customer loyalty is dead (or dying), I would offer that loyalty is still achievable – however, the bar is higher. The underlying reason for this relates to the divergence of expectations vs. reality – that is, as the economy has tightened, funds have become more scarce; this scarcity means that buyers are more selective in how they use their funds. This results in customers not only being more price-sensitive, but they also have heightened expectations on what they will receive. At the same time, providers have been forced to scale back on resources (as a result of constrained growth and/or uncertainty in the market), which ultimately means that they are ill-equipped to deliver on these expectations. This creates a “perfect storm” of dissatisfaction, which means that customer loyalty is harder to achieve.

So, this brings me to my first prediction/forecast for the coming year:

Quarterly loyalty scores will remain volatile as long as there is excessive uncertainty in the markets and/or the economy continues to be challenged.

What can we do about this? I would offer the following strategies for consideration:

1. Review your workflows to ensure an “outside-in” perspective – Conducting a review of the experience that your customers have with your organization can be quite revealing. Conducting a customer journey mapping exercise can help to highlight where gaps exist and can assist you in re-tooling processes to ensure an optimal customer experience. This is particularly critical among companies that have recently merged with or acquired another company.
    
2. Communicate – both externally and internally – During periods of economic turbulence, it is better to over-communicate. From a customer perspective, seek to gain an understanding of not only their expectations, but also what drives those expectations. Understand how their business works and how your products and services can help them to achieve their goals.
   
   From an internal perspective, reinforce the role that customer centricity plays in your strategy; on the front line, managers should spend time with their direct reports to identify how to integrate customer perspective into their day-to-day operations. Above all else, though, leaders must walk the talk – leading by example communicates better (and louder) than words.
    
3. Control what you can control – Much (if not most) of the volatility in the markets are outside our control; it is tempting, then, to throw our hands up and surrender – that is, just let the chips fall where they will.

Rather than take a sit-and-wait approach, we would recommend that you identify (from the steps noted above) what aspects you do control – for example, you control how your organization approaches the customer experience, you control how you choose to innovate, and you control how you respond to competitive threats. Focusing on what you control – and then acting on it – can be much more empowering that waiting for the winds of change to blow in your favor.

Even though customer loyalty is more difficult to achieve in these economic times, those firms who successfully crack the code will find that they have one of the few sources of long-term sustainable competitive advantage in their strategic arsenal. I would argue that the payoff is worth the effort necessary to realize customer loyalty.

Over the next few blogs, we will review the other factors that I am forecasting will be the trends and themes that customer strategists should be thinking about in the coming year. In the meantime, I would be eager to hear your thoughts – what are the themes and trends that you are tracking?

Mark A. Ratekin
Senior Vice President, Consulting Services

This McAfee blog recently caught my attention as I realized that although our businesses are very different, the premise is the same as you think about securing your organization. 

From McAfee’s perspective:  “While traditional antivirus technology continues to hold value for consumers and enterprises, it is only one layer in what needs to be a multi-layered defense.”

From Walker’s perspective: While gathering customer feedback through traditional Voice of the Customer programs continues to hold value for your organization, it is only one layer in what needs to be a multi-tiered customer strategy. 

It’s not enough to simply “do surveys” – which can backfire by setting an expectation that customer feedback will result in action. (Reminder: Customer relationships may actually become less secure if you don’t act on the customer feedback.) 

Instead, you need a multi-tiered customer strategy to enhance the customer experience and their relationship with your organization. Here are just a few examples:   

• Customer-Focused Culture: Build customer-centricity into the fabric of your organization
• Predictive Analytics: Use predictive analytics to predict customer behaviors and anticipate customer need
• Customer Insights: Deliver customer information that prompts action and results.
• Securing Buy-in: Get the necessary support and resources for customer intelligence initiatives.
• Engaging Employees: Promote customer strategies within the company
• ROI of Customer Intelligence: Validate the impact of customer initiatives

What are you doing to go beyond customer listening to improve the customer experience?  How are you driving business success through customer insights and understanding?

Kitty Radcliff
Vice President, Consulting Services

Five things a CEO should know from their customers:

• How much revenue is at risk? Aligning Voice of the Customer feedback with purchase behaviors pinpoints how much revenue is at risk and where there is potential to grow market share.
• How do we stack up?  Customers can provide insight into how the organization performs against the competition.
• What’s driving customer loyalty? With an understanding of what influences customer loyalty, executives can allocate the appropriate resources.
• What are the changing needs of customers?  Design with the customer in mind by understanding their current and future needs.
• What about key customers? Customers have unique needs and companies need a system for retaining and growing their most important customer relationships.

One critical aspect of validation is about proving the business impact. It involves tracking action plans that were prompted from the Voice of Customer (VoC) program through to completion and ultimately to a quantifiable ROI. Start by making sure your program is aligned and supports the business strategy. Then work to combine the customer feedback with other authoritative data sources (such as financial and/or operational) to quantify the impact it is having on your business strategy.

Validation can be one of the most challenging essential elements, but it is one of the most important.

For the past few weeks, it seems as though all people are talking about in the US is the potential for going over the “Fiscal Cliff”.  However, I would like to suggest taking time to reflect on another topic.  This is when we traditionally reflect on the year past and look forward to the year ahead - so it is also a good time to reflect on your customer strategy. 

Take stock of what went well and what was accomplished in 2012. And, identify obstacles and root causes for those things that didn’t quite go as planned.  Ask yourself: What were our goals?  Which goals did we achieve and why?  Armed with that information, you will be better equipped to determine what to do differently this next year.

As a customer strategist, you might consider the input from others when answering those questions and in helping to guide what you will do differently (aka “new year’s resolutions”) for 2013.  A great example is a customer experience manager who is focused on bringing the voice of the customer into all areas of her organization. She is in the process of actively soliciting feedback from key stakeholders, as well as reviewing progress on action plans that have been implemented based on customer feedback.  Her goal is to ensure awareness and understanding of the information and insights, how it is being used, and to identify ways to have even more impact next year.

Spending time to reflect on 2012 will help you to refine your VoC strategy and set the direction to achieve 2013 goals.  

"When obstacles arise, you change your direction to reach your goal; you do not change your decision to get there.”  ― Zig Ziglar

Kitty Radcliff
Vice President, Consulting Services

A recent TED Talk by Shyam Sankar (also the subject of this recent blog post by Leslie Pagel) nicely argues that man-machine cooperation is the real story of technological development. In a 2010 article, chess grandmaster Garry Kasparov, who famously played IBM's Deep Blue in the late 1980s, relays a wonderful anecdote illustrating the power of this symbiosis between humans and computers. In 2005, a freestyle chess tournament was held where humans and computers could work together or play separately. At this point in history, a computer program running on a standard laptop could routinely beat many grandmasters. However, this freestyle tournament produced two interesting and relevant results:

1. a strong human player with a weak laptop soundly defeated even the best stand-alone chess computer, and
2. the overall winner of the tournament was not a grandmaster with a powerful computer, it was a pair of amateur chess players using three relatively weak laptops. 

According to Kasparov analysis, the team's winning edge was a superior interface between all humans and computers that effectively counteracted the superior chess knowledge and/or computational power of their opponents.

From this story both Kasparov and Sankar conclude that the decisive factor for determining the analytic capability of any human-computer combo is the friction between humans and computers. By designing a better interface that reduces the friction, you increase the analytic capabilities derived from the same human and computer at an ever-increasing, convex, rate.

While I completely agree that designing friction out of the interface is a decisive factor, I think there is one critical element behind the success of the human-computer team that both Kasparov and Sankar overlook - the rules of the game favored a cooperative strategy. The rules of freestyle chess require players to make moves much faster than regular chess. Therefore, the ability to have a computer crunch the data and provide the human player with a short list of potential moves is a critical advantage. Given more time between moves, the experience, knowledge and creativity of a chess grandmaster begins to override the speed, computational power, and efficiency of a computer chess program.

These two elements of success in chess are perfectly relevant to customer predictive analytics and customer-focused decision-making.

• First, useful predictive analytics require the smooth interaction of a skilled data scientist and a powerful, but usable, analytic workbench and process. It is not uncommon for an analyst to only spend 10%-40% of their project time actually running analysis and extracting usable insights. The rest of their time is spent transforming and merging data or getting outputs into usable/shareable formats. We need more work on reducing the friction between the analyst and the analytic tools if we are to realize the full benefit of predictive analytics. 
• Second, data scientists need to fully understand the context they are working in and the rules that apply to it so they can apply predictive analytics in the right place and using the right approach. For instance, conducting a predictive analytics project within a strategic accounts group with a small set of accounts and deeply embedded account managers is not going to produce as much return as a similar exercise in an outbound call center where fairly inexperienced sales reps are each responsible for hundreds of accounts.

The future of business will require a reliance on powerful, computer-based analytics that easily interact with (not supplant) skilled data scientists who bring both analytic and business context knowledge into the process.

Interest in capturing and quantifying the voice of employees is growing – and in this case, I’m not talking about "employee satisfaction" but rather "voice of the customer" THROUGH the employee’s view point.

This is something companies do all the time, but often in a more anecdotal way.  Some voices are inevitably much louder than others, and often times the anecdotes are not strong enough to persuade quick actions.  Capturing the employee perspective in a more thoughtful, organized, and balanced way can become far more compelling.

An example – recently we’ve developed a targeted study aimed at understanding the factors behind a handful of very large lost deals from the perspective of the sales team.  In this study, we’ll be able to organize a lot of different inputs and learnings about the competition, and make that info available to the sales force at large to help strengthen their positioning on future deals.  We’ll also be able to quantify the loss drivers – price, value, solution, etc.  What’s more, I think we will also gain some important goodwill and buy-in to their overall VOC architecture from this critical internal stakeholder group as a result.

Now, you’ll see the obvious push-back that some VOC managers will face --- Why do we need to debrief?  We’ve got to stay 100% focused on the next deal...   A colleague of mine put it very astutely when he countered … "Tell me about any NFL coach that doesn’t watch reels of film after a game loss."  There’s always something we can learn from our experiences if we take the time to analyze the data in an objective way.

Krista Roseberry

VP, Consulting Services

Walker

In a recent HBR article, the authors give five things companies need to be doing to retain employees.  You might be wondering why employee loyalty is important right now.  It is important because they found 40% of employees plan to start looking for a new job and 69% are passively looking for a new job right now.  Obviously there is a big difference between looking for a new job and actually leaving a company.  However, I have found once someone starts to disconnect by seeing what is available, their loyalty is impacted and they eventually believe the grass is greener somewhere else.  I know there are some who find out what they have is pretty good, but I believe many have the perception that somewhere else is better than where they are so they begin to disconnect and ultimately, leave the organization. 

The authors give five things (and I think these five are a great summary) to do to keep employees:

1. Responsibility. This does not mean you pile on to what the employee is already doing, but find strategic things that help the company, while developing the employee. 

2. Respect. I think this is pretty straightforward conceptually, unfortunately not always executed daily.

3. Revenue-sharing. I have blogged about this before, I love this, and ensures everyone has skin in the game and motivates employees at all levels to help the company be successful. 

4. Reward. While this is similar to revenue-sharing, this goes beyond just compensation but finding ways to reward the employee on a more personal level.

5. Relaxation Time. I have blogged about this before with ROWE or in companies that don't have formal time-off policies.  Employees need to have time to get away and relax as it will ultimately make them more productive. 

Like I said, I think this is a great, concise way to remember key things that will drive employee loyalty and ultimately organizational success. 

Seven approaches that world-class companies use in communicating with customers.

1. The Role of the CEO – To be the chief communicator and believer. Use capabilities such as video and social to showcase this communication.  It’s inexpensive and high impact.
2. Walk the Talk – If you talk about being committed to customers, make certain your actions reinforce that.  This is what we heard, this is what we are doing about it, this is how it will impact you.
3. Create Two-Way Dialogue – Be certain you are communicating back. Communicate with the audience in a format/medium that aligns with how they communicate. (Go where your customers are talking).
4. Face-to-Face Communication – Customers want you to close the loop and to do it in a way that is personal.
5. Having a Shared Plan of Communication – All employees should be aware and committed to the messages.  Use the Intranet as a source of Communication around the branded strategy.
6. The Bad News/Good News Ratio – It is tempting to focus on what is working well; however, you should plan to share some of the less-than-stellar feedback – it will illustrate that you are listening and are intent on improving.
7. Tailor the Content to the Audience – Consider who your intended audience is and what methods work best for them. Communication is a process, not an event –Communicate the what, why, and how, be timely, and make certain the message is relevant.

One of the first rules of acting on customer insights is to simply let them know that you're listening. Unfortunately, too often, customers feel like their feedback goes into a deep dark black hole.

Here is a real-world example: I attended a meeting recently with a small group of customer strategists from technology companies responsible for their voice-of-the-partner programs. Also invited to the meeting were a small group of value added resellers (VARs) - precisely the individuals that they commonly collect feedback from. At some point in the conversation one of the customer strategists innocently asked if their partner managers ever comment on the feedback provided by the VARs.

Silence. Nothing. All the VARs just shrugged and said, "Nope."

The customer strategists groaned as if to say, "Really? I put all this effort into collecting insights from our partners, analyzing what they have to say, and deliver it to the partner managers and they don't even mention it to the partners?!" Their frustration (and embarrassment) was obvious.

Several common obstacles could be the cause of this:

1. They aren't aware. Since they don't know about it or don't receive feedback from their customers, naturally they're not going to mention it.
2. They don't understand it. They may receive reports from the person running the customer insight program, but that doesn't mean it makes sense to them. If they don't understand it, they're not going to talk about it with customers.
3. They don't believe it. They may receive the information, but if it isn't relevant or they don't trust it, they are not going to bring it up with their customers.

Ultimately, this comes down to communication and training. Every customer strategist has the responsibility to make sure the voice of the customer gets put to use. But to do that you have to make sure everyone is aware of it, understands it, and believes in it.

Only then will they start a conversation with their customers with those all-important words, "I heard what you had to say!"

Patrick Gibbons
Principal, SVP
Walker

Focused attention usually generates better results than acting haphazardly without a plan.  I believe that.  And, that belief was reinforced to me a few times this week already.

First, a customer strategist I’m working with – who is conducting their annual Voice of the Customer program – checked in to confirm the definition of “World Class” customer ratings. His team is focused on helping their organization optimize the customer experience. They want to understand their strengths. And they want to know where they fall short so that action plans can be implemented to improve customer perceptions. But making incremental improvements is not enough for this group.  They don’t want to simply be better than they were last year.  Instead, they want to provide a world class customer experience. As a result, they are outperforming competitors, which ultimately is helping drive business success. 

Another Customer Experience Team we are working with met today to assess progress on having a world class customer listening program.  Using the Six Essentials as a foundation, the team identified two areas where they want to make improvements over the next year.  They are committed to making improvements and have even incorporated goals into their MBOs.  Based on changes put in place this year, it is clear that the focused attention is making a difference and they are moving the needle in their quest for having a world class program.  

It’s not just about getting better.  It’s about becoming world class.

Kitty Radcliff
Vice President, Consulting Services
 

In a recent Harvard Business Review article, researchers set out to determine which types of hotels are more likely to post fake reviews on websites such as Yelp!, TripAdvisor and Expedia. They found that independent, small-owner, and small-company hotels appeared to be more likely to manipulate reviews on websites.

What is the key lesson for this finding for customer strategists? I would argure that it is less about these specific findings and more about a basic aspect of a customer listening program – that is, are the results accurate and reliable? In other words, do the results reflect the overall population (and, by extension, what population do the results represent)? I have written on numerous occasions about the importance of the quality of customer lists (see here, here and here for examples); what I would add today to the discussion is the point that diversification matters.

There are two ways to define diversification in this context – first, how much variety is included in the customer list within a given account? This clearly aligns better with a B2B customer listening program – for example, do we have a good mix of end users, decision makers, and executives for each account in our listening data? Having a variety of contacts from the same account will yield, in the words of James Surowiecki, the “wisdom of crowds.” This means that the group in total is generally smarter than any one participant in that group. Sampling theory tells us that as the base size of a study increases, the error around the mean estimate will be minimized. This is applied in the context of a total sample, but it can also apply to the findings from an account – think of each account as a sub-sample. By getting a variety of perspectives from customers within each account, we increase the likelihood that we will be getting a clearer picture of the health of those accounts. This can provide clues to astute strategic account managers – for example, if there is significant variance in the scores from within an account, it may speak to confusion that should be teased out and/or managed; this can often lead to incremental sales opportunities.

The second type of diversification relates to how we listen – when customer loyalty research was in its infancy (called customer satisfaction research at that time), we asked customers for feedback because there were no other mechanisms to gather those perspectives. CRM systems did not exist that allowed us to tie together disparate data to arrive at “the big picture.” This is why we had to ask about which products a user was familiar with, even though the customer would (rightfully) argue that we should already know that information – there was no way to tie all the data together.

The world is changing, though. Not only are CRM systems providing a more well-rounded view of customers, there are new and different ways of listening to – and analyzing – customer feedback. In the same HBR article, the authors talked to doing a “web scrape” to gather data on the hotel ratings. In addition, we can scan data in Twitter, look at Facebook pages for the number of “likes” a company has, and so on. Operationally, we can link customer behavioral metrics as well as internal quality indicators to our listening data. We can literally swim in the data.

All of this data prompts some pundits to proclaim that the need for customer listening via surveys is gone. I could not disagree more. It is certainly getting more difficult to gather customer feedback – response rates are more challenging to achieve, and the proliferation of DIY survey tools means that anyone can send a survey, regardless of how bad it is – but to say that surveys are dead is a bit extreme. I would argue that this diversity of data sources provides an opportunity to gather, analyze and understand customer sentiment from a variety of perspectives, which is valuable. My colleague Jen Batley recently wrote about the uses and challenges of this. The bottom line: we have many sources of customer data to rely on, and we should be wary of focusing on just one. Making the connections among these sources means we increase our odds of understanding what makes our customers tick.

Mark A. Ratekin
Sr. Vice President, Consulting Services

Whether you are looking to engage colleagues or customers in your customer intelligence strategy, avoid these common mistakes:

1. Focusing on the moment instead of the desired outcome: It’s easy to get caught up in the moment, but it is more productive to stay focused on the desired outcomes.

2. Not realizing that every conversation creates an emotion: Consider what type of emotion you want to create and adapt your communications accordingly.

3. Fear of losing: This fear stifles engagement. Look for ways to spot and stop these fears from driving your behavior.

Customer insights are becoming an increasingly important part of how service organizations are measuring their performance and driving improvements.  Transaction satisfaction programs are a standard, and these enable a broad range of customer analytics that integrate perceptions of services with hard operating metrics about specific services interactions.  They also allow one-to-one follow up with customers who are reporting significant issues – follow up which has been proven to increase future satisfaction with the company overall.

This is great for those customers who DO respond to the voice of customer programs that companies have in place … but my guess is that for every customer who responds to your transaction survey there are four, five, or even more who chose NOT to respond.  What about these non-responders?  How can we respond to a voice that isn’t audible?

Customer analytics are enabling organizations to get predictive about this group of customers by identifying a set of them who, based on how they profile relative to those who did respond to a survey, are most likely to have had a negative service experience.  Armed with this list of customers, service leads can get proactive, reaching out to these customers to preempt further erosion in their perceptions and in their business. 

Imagine the impact of contacting a customer to resolve an issue that they never even told you about… this is customer delight!

This is the power of customer analytics. 

And this is Voice of Customer without the Voice.

Predictive analytics leverages a variety of techniques that use current and historical data to make predictions about the future. Predictive analytics has tremendous value for customer experience management by confidently detecting unknown or future issues to mitigate risks and take full advantage of growth potential.

Below are three examples of how predictive analytics can be used:

• Predicting customers who are not likely to renew enables the organization to take preemptive actions to increase renewal potential and drive top-line growth.
• Predicting customers who are likely to purchase new products creates efficient targeting and faster market penetration of emerging technologies.
• Intervening with customers who are likely to be dissatisfied with their support case mitigates the negative impact on overall loyalty to the company.

Is it just me, or do you find the acronym for Data Rich, Insight Poor appropriate? Whenever I hear companies talk about this challenge, I think of a leaky faucet. But, instead of water going to waste, I see customer intelligence drip, drip, dripping away.

Companies continue to be faced with a tremendous challenge. And, while the challenge hasn't changed (check out this blog from three years ago), the volume of data continues to multiply.

In order to compete in an environment where customers demand personalized service, customized products, and immediate gratification, customer intelligence professionals must start laying out a plan that includes multiple sources of information. Taking full advantages of existing information sources delivers stronger predictive analytics that can create a truly differentiated experience.

One place to start is the journey map.

Journey maps (or touch point mapping) is a collaborative process that engages customers and cross-functional teams in an exercise to map out the customer interaction points, and highlight critical moments of truth and unique strengths. It is a tool to help companies prioritize where to focus, pin-point the information sources that are available or missing. And, with the right support, journey mapping can be accomplished in relatively quick order.

Let's stop the DRIP.

Photo credit: Maegan Tintari

Many companies overlook branding their customer intelligence program. What often occurs is the program being called something generic like, “The Customer Survey,” or even “The Walker Survey.” If this sounds familiar, consider these three reasons to brand your program:

• Companies today have an overwhelming amount of information. Customer intelligence is no longer just about surveys. It’s about harnessing all of the information to support decisions throughout the organization.
• Companies who develop a thoughtful name for their customer initiatives provoke an emotion that is consistent with their corporate brand, sending customers a positive and consistent message.  
• A strong brand for your customer intelligence program will increase awareness and communicate to customers and employees that it is an important, strategic initiative.

One common mistake customer strategists fall into when using predictive analytics is believing the analytics process alone will find the answer to the key business question. This Ted video from Shyam Sankar highlights the benefits of problem solving when the right interface is achieved between humans and computers.

Can't see the video? Click here.

Sankar mentions several instances (including a Chess match and finding terrorists) in which the best solution was identified not by a computer alone, but those that involved collaboration between human and machine.

His presentation suggests an important application for customer strategists. When leveraging predictive analytics to solve a business challenge we must ask ourselves how we can design the human around the process, not the process are the computer.

If your engineering organization craves more granular customer insights, think about trying these 3 approaches -

NPI Feedback – NPI stands for New Product Introduction.  In companies with a large product development focus, a lot of highly valuable information can be collected from customers early on in their use of a new product.  That information can help a company assess whether the product is living up to the "sales pitch" and helping customers accomplish what they had hoped with the product when they purchased it.  An NPI-focused customer feedback process can also help identify systemic issues earlier, help assess the growth potential of new products, and gain assessments around the professional services and support provided to customers during setup and testing.

Support Case and Customer Feedback Analysis – Your organization likely already tracks the number, types, and content of support requests by major product line and uses that insight to help develop patches and new releases.  But, are you feeding support-oriented VoC back to engineering?  If not, this is a great place to look – find the common questions, concerns and needs for your major product lines that are raised through service/support transactional studies.  Package and share that information with the product engineering teams.

VOCE, or Voice of Customer through the Employee -- Build a process for your front-line employees to pass back customer feedback in a systematized way.  Cataloging and mining the feedback from sales, delivery/install technicians and service professionals will yield more granular feedback about what’s working well and where there are opportunities to improve customers’ perceptions about your products.

Krista Roseberry
VP, Consulting Services
Walker