Exciting News From The XM Institute

The time has finally come for me to tell people to stop purchasing Temkin Group research reports. Are we eliminating them? No. Are they irrelevant? No. We’ve just decided to give them away for free on the Qualtrics XM Institute site.

That’s right, you can now get access to almost our entire research library for free. One of the reasons we joined Qualtrics was to be able to help more people and organizations. This move shows you the commitment that Qualtrics is making to help the world understand and deliver on the promise of Experience Management (XM).

One of the things you’ll notice on the XM Institute page is a filter to select reports based on Six XM Competencies. Yes, we’ve created a new model. It’s based on the following six competencies:

  • Lead. Architect, align, and sustain successful XM efforts. Driving XM transformation requires a strong program and active support from senior leadership.
  • Realize. Track and ensure that XM efforts achieve business objectives. For XM efforts to have lasting, positive impact, they must align with the overall priorities of the organization.
  • Activate. Create the appropriate skills, support, and motivation. People generally gravitate towards the status quo. To help overcome that inertia, the organization must ensure that employees have all the appropriate XM-related training and support needed.
  • Enlighten. Provide actionable insights across an organization. At the center of XM is the constant flow of data being transformed into useful information and shared with those most capable of taking the appropriate action.
  • Respond. Prioritize and drive improvements based on insights. An organization must act on what it learns by making constant improvements as insights are uncovered.
  • Disrupt. Identify and create experiences that differentiate the organization. Truly successful XM efforts go beyond simply reacting to problems to proactively developing innovative experiences that give the organization a competitive advantage.

That’s just a quick summary. We will be publishing much, much more on this model in the future. It will be the primary lens for all of our content, which is why and we’ve created categories on this blog for the Six XM Competencies.

Enjoy all of the free content on the Qualtrics XM Institute site!

Six Categories Of X&O Data Insights

Last week I attended SAP’s SAPPHIRE and CX Live events in Orlando. It was great to see 35,000 or so of my new friends. As you might expect, Experience Management (“XM”) was a dominant theme. Just about every SAP or Qualtrics keynote speech discussed XM, and it was a topic at many of the concurrent sessions. I really enjoyed seeing the XM message come to life in so many different ways.

One of the cornerstones of XM is the combination of operational data (“O-data”) and experience data (“X-data”). While each type of data can provide valuable insights on its own, the combination can unlock new levels of intelligence across an enterprise. These more inclusive datasets will increase in value as organizations expand their use of predictive analytics, as the combined data is inherently more insightful.

To help you think about where you can find valuable opportunities to combine X- and O-data within your organization, we identified the following six categories of use cases:

  • X Why: Find something happening in O-data and look for an explanation in X-data
  • O Drivers: Find something happening in X-data and look for operational situations that are causing the situation
  • X&O Predict: Build projections based on an analysis of X- & O-data
  • X&O Personalize: Adjust how you treat people based on a combination of X- & O-data
  • X&O Alert: Send alerts and other proactive information based on a combination of X- & O-data
  • X Value: Measure the value of improving experiences by examining the impact that those changes have on business results

1905_CategoriesOfXODataInsights_v2

The graphic above provides some customer experience (“CX”) and employee experience (“EX”) examples, but it’s not meant to be an exhaustive list of use cases. Hopefully the table provides you with a good sense of the insights that can be unlocked with the combination of X- and O-data.

Now that you understand some of the ways for gaining insights from X- and O-data, think about how the combination can impact your organization. If you have some ideas or examples of how it’s worked for you, leave them in the comments section of this post.  I’ll try and highlight some of the most interesting items.

The bottom line: Combine your Xs & Os to unlock more insights.

 

CX Myth #6: Compensation Drives Good CX Behaviors

CX Myths: Debunking Misleading Beliefs About Customer Experience

Many common beliefs about customer experience are misguided, based on oversimplifications or a lack of consideration for real-world constraints. In this series of posts, we debunk these myths.


CX Myth #6: Compensation Drives Good CX Behaviors

What’s Wrong: Many organizations try to drive behavior change by tying employees’ compensation to customer experience metrics. While some level of compensation tied to CX can be helpful, it is often overdone. When you overly compensate on a single metric, it can often lead to unintended and detrimental consequences. Symptoms of these counterproductive behaviors include pestering customers for scores; focusing on activities that may improve scores, but aren’t good for the business; and actively debating the accuracy of the metrics. Rather than engaging in these activities, we want employees focusing on ways to improve customer experience.

What’s Right: Don’t use compensation to drive behavior change; instead, use it to reward good behaviors. With that in mind, you need to find other mechanisms to drive change, such as appealing to employee’s four intrinsic needs; their sense of meaning, control, progress, and competence. As I’ve previously written, keep in mind these three underlying principles about compensation:

  1. If there is significant compensation tied to any metric (including customer feedback), then people will look for ways to manipulate the measurement.
  2. If people don’t understand a metric, then tying compensation to it will have little impact on their behavior and any downside in compensation may create negative behaviors.
  3. If people don’t understand how they personally can affect a metric, then tying compensation to it will have little impact on their behavior and any downside in compensation may create negative behaviors.

What You Should Do:

  • Treat CX as a team sport. Your customers’ experience is almost never the result of a single person, even if that person is the only one interacting with the customer. So focus on team-level metrics and compensation that encourages key groups of employees to work together towards a shared objective.
  • Use an organization-wide CX metric. Developing a core CX metric for the entire organization that is tied to some compensation (not too large), is a great way to show commitment to improving CX, and it will encourage a regular dialogue about your overall CX performance.
  • Bias rewards towards the upside. Consider starting with a compensation plan that is biased towards upside. In other words, you may want to introduce the plan where there is little negative impact on compensation if the group doesn’t hit a goal, but there is positive impact of they exceed it. This can help eliminate some of the negative perceptions early in a program.
  • Celebrate good CX behaviors. Compensation is not the only reward system in an organization. If you want employees to behave in a certain way, then provide them with positive role models. Find ways to highlight employees who are demonstrating the behaviors that you would like others to emulate. This can include monthly or quarterly awards, shout outs at company meetings, or highlights across your internal communications.
  • Make it unacceptable to game the scores. When an employee asks a customer to “give me a 10 on a survey or I’ll get fired,” can you really count on the accuracy of that customer’s rating? This may be an extreme example of “gaming feedback,” but many versions of this behavior occur all the time. To keep gaming feedback in check, it’s important to be explicit with employees about what the company considers to be unacceptable behaviors.  I’ve identified five rules that you should strictly enforce with employees, which includes not talking with customers about survey questions, scores, or consequences.

The bottom line: Use compensation to reinforce, not force, good CX behaviors.

What’s All This About X- And O-Data?

1811_XODataYou might have heard Qualtrics discussing X-data (experience data) and O-data (operational data), and wondered, should we care? The answer is yes, and here’s why.

Let’s start with a basic premise that no individual experience exists in a vacuum. People form their opinions about any experience based on a collection of different factors. The more we can understand those factors, the better we can extrapolate the insights about a single personal experience to form a deeper understanding about other people’s experiences.

Now to my discussion of Xs and Os, starting with customer experience (CX)…

Let’s say that your company has this data:

  • X-Data: NPS responses
  • O-Data: Customer product ownership and support history.

With X-data, you can calculate an NPS for the customers who responded. You can also dig into their feedback, and hopefully understand what’s causing promoters and what’s causing detractors.

That’s extremely valuable, but it only tells you what’s going on with the people who happened to respond to the survey.

By combining O-data with your X-data you can examine (especially through predictive analytics) what types of products and service interactions lead to promoters and detractors, and use this data to calculate the NPS for large portions of your customer base–—even for customers who never responded to a survey.

It could be that ownership of a certain version of a product tied together with a specific type of customer service problem is highly likely to create detractors. You can identify all the customers with that profile and take proactive measures to correct the issues — even though they may never have complained.

Result: More loyal customers and more targeted use of your resources.

This works across all areas, even with employee experience (EX). Let’s assume you have this data:

  • X-Data: Employee satisfaction study
  • O-Data: Employee tenure, promotion history, most recent performance rating

With X-data, you can determine how employees feel about their next steps at the company. You can also dig into their feedback, and hopefully understand what’s causing higher vs. lower levels of career satisfaction.

By combining O-data with your X-data you can examine what influence tenure, promotion history, and performance may have on satisfaction, and use this data to identify segments of employees to invite to participate in a high-potential development program.

Result: More high-performing workforce because you’re investing in the right employees.

Hopefully you can see how the combination of X- and O-data can increase your CX and EX insights. The same dynamic also holds true for brand experience (BX) and product experience (PX). By combining and analyzing the different types of data, you can use feedback from a few people to build an understanding of many, many more. This allows you to better prioritize investments, while making more targeted and impactful changes.

The bottom line: X- and O-data together provides an analytics goldmine.

CX Myth #4: Net Promoter Score Is The Best/Worst Metric

CX Myths: Debunking Misleading Beliefs About Customer Experience

Many common beliefs about customer experience are misguided, based on oversimplifications or a lack of consideration for real-world constraints. In this series of posts, we debunk these myths.


CX Myth #4: Net Promoter Score Is The Best/Worst Metric

What’s Wrong: People often argue that Net Promoter Score (NPS) is the greatest metric, while other people argue that it’s a terrible metric. Both of those points of view are off the mark.

What’s Right: We rarely see a company succeed or fail based on the specific metric that it choses. That doesn’t mean that you can chose a ridiculous metric, but most reasonable metrics provide the same potential for success (and failure). In many cases, NPS is a reasonable choice, as our data shows that it often correlates to customer loyalty. The way you use a metric is often far more important than the metric that you chose.

What You Should Do:

  • Pick a simple metric. It’s important that you choose a metric that employees will understand, so they are motivated to help improve it. The metric can be based on customer attitudes (like NPS), behaviors (like repeat purchases), or even results (like first call resolution). Just pick a simple metric that aligns with your business goals.
  • Follow our five steps. To drive improvements using the metric, follow Temkin Group’s five steps. to a strong CX metrics program: 1) Determine a core CX metric, 2) set achievable goals, 3) identify key drivers, 4) establish key driver metrics, and 5) make the suite of metrics actionable.
  • Focus on all four action loops. People often discuss an action loop with CX metrics, but we’ve identified four customer insight-driven action loopsImmediate responsecorrective actioncontinuous improvement, and strategic change. Any CX metrics program should put in places processes to close all four loops.
  • Don’t compensate too much. When companies establish CX metrics, they often establish compensation based on them. While this can be a valuable approach to raise awareness and alignment, it can also be a problem if the level of compensation is too large (can encourage bad behaviors), it focuses on individual results (CX is a team sport), or the goals are too precise (some metrics are inherently jittery).
  • Have very clear sampling strategy. The approach for sampling often has a very significant impact on results. If you have multiple segments of customers and they each have a different profile (as many do), then your overall scores can change wildly based on the mix of those customers that are included in your calculations.

The bottom line: Obsess about your metrics program, not your metric.

CX Myth #3: You Can’t Manage What You Don’t Measure

CX Myths: Debunking Misleading Beliefs About Customer Experience

Many common beliefs about customer experience are misguided, based on oversimplifications or a lack of consideration for real-world constraints. In this series of posts, we debunk these myths.


CX Myth #3: You Can’t Manage What You Don’t Measure

What’s Wrong: When people talk about CX, they often repeat a popular saying “you can’t manage what you don’t measure.” That’s just not true. Most of the things we manage in life don’t have a formal measurement. Every day we wake up in the morning, get dressed, and get to work – all without any specific measurements. The same is true at work, and with CX. If we see an employee make a client upset, we don’t need a score on a customer survey to know that it’s a problem.

What’s Right: The correct saying should be “you can’t manage what you don’t understand.” Unfortunately, leaders sometimes just slap measurements on CX, which leads to the suboptimal approach of blindly managing by the numbers. When you talk with customers and employees about different aspects of customer experience, you can often discover insights that either never show up in your measurements, or appear long after you should have known about them. Ideally, you use CX measurements to enhance your understanding, not to replace it.

What You Should Do:

  • Increase leadership CX IQ. If you want leaders to be less metrics-centric and more successful at driving an organization towards becoming more customer-centric, then those leaders need to have a clear and consistent view of how a customer-centric organization operates. A good place to start is by having leaders review Temkin Group’s CX Competency & Maturity Model. After that, you can create measurements that map to the leaders’ understanding of CX.
  • Prune action-less metrics. Since leaders are often enamored with metrics, they tend to track an increasingly larger number of them over time. The growth remains unfettered, as very few organizations have a good approach for stopping measurements once they’ve been created. Every year or so, companies should have a metrics cleansing period, during which time there’s a pro-active focus on removing metrics that have not recently provided demonstrable value.
  • Prioritize qualitative research. The push to metrics often causes organizations to put most of their market research budget on quantitative studies that result in trackable measurements. But deep insights into customers often comes from qualitative studies that examine why customers think and behave the way that they do. Look for places to explicitly fund more qualitative studies by cutting back on the least impactful quantitative studies.
  • Measure collective results. CX success requires efforts across an entire organization. So watch out for measurements that isolate the activities of individual people or teams. The narrower the measurements you use, the more likely you are to de-incentivize collaborative behaviors. Focus on metrics that capture real-world team-based activities.
  • Look for leading indicators. Most metrics represent backwards-looking scorecards, describing how an organization performed in the past. While a retrospective view can be helpful, it’s more valuable to understand what activities will impact your organization’s future CX trajectory. Use predictive analytics to identify what activities with different customer segments will most improve your CX metrics in the future.

The bottom line: CX insights don’t always require CX metrics.

CX Myth #2: You Need A 360-Degree View of Customers

CX Myths: Debunking Misleading Beliefs About Customer Experience

Many common beliefs about customer experience are misguided, based on oversimplifications or a lack of consideration for real-world constraints. In this series of posts, we debunk these myths.


CX Myth #2: You Need A 360-Degree View of Customers

What’s Wrong: If companies had an unlimited set of resources to plow into their customer insights efforts and an equally unlimited number of people prepared to take action on those insights, then shooting for a 360-degree view of your customers would be viable. But this is not the case for most organizations. So striving to understand everything about every customer (360-degree view) pushes organizations to over-invest in data and squeezes out the critical focus on taking action on the insights.

What’s Right: Organizations need to focus their insights efforts in areas where they are prepared to take action. Rather than aiming for a 360-degree view of all customers, organizations would be better served with a more targeted approach, focusing their insights investments on understanding key customer groups during specific parts of their journeys.

What You Should Do:

  • Separate the notions of Detect and Diagnose, which are two parts of the Six D’s of a Voice of the Customer Program. You can track the high-level feedback from a large number of customers (“Detect”) and then use those insights to identify areas where you should dig deeper to drive action (“Diagnose”).
  • Identify the actions that your organization is prepared or willing to take based on customer insights. This includes items across all four action loops: immediate response, corrective action, continuous improvement, and strategic change.
  • Define the target customers that you need to understand in order to support actions. This should include the type of customers and the specific stages of their journey that you’re most interested in understanding.
  • Make it as easy as possible for people across your organization to use the insights. Tailor the information to the specific ways that people in your organization make decisions. Minimize the requirement for non-analyst users to interpret and manipulate the data to uncover actionable insights.
  • Whenever you’re presenting customer insights, try not spend more than 20% of the time discussing data. Use the majority of the time talking about what the data means,  implications, opportunities for improvement, and next steps.
  • Help stakeholders across your organization understand new and more impactful ways that they can use customer insights to drive action. They may not immediately understand how to best use insights, so you may need to help them evolve through seven stages to a data-centric mindset.

The bottom line: Focus on developing the most actionable insights.

Propelling Experience Design (Infographic)

In the report Propelling Experience Design Across An Organization, we examine how companies can best use a very important skill, experience design. This infographic provides an overview.

Here are links to download different versions of the infographic:

Here are some of the reports with data included in the infographic:

What is Net Promoter Score? (Video)

Net Promoter® Score (NPS®) is one of the most popular CX metrics, so we are often asked to discuss it with clients. In addition to helping build successful NPS systems, we often provide a basic overview for executive teams and broader audiences of employees. That’s why created this video. It’s meant to explain what NPS is all about and why it may be a valuable approach for some companies. It’s a great video to share across your organization if you are using or considering using NPS. If you’d like more information, check out our NPS/VoC program resources.


CX Sparks: Guides For Stimulating Customer Experience DiscussionsThis video is a great introduction to a discussion with your team. That’s why we’ve created a CX Sparks guide that you can download and use to lead a stimulating discussion.


Video Script:

You may have heard of Net Promoter Score, which is often referred to as NPS. It’s a popular customer experience metric. Let’s examine what it is.

Walt Disney once said “Do what you do so well that they want to see it again and bring their friends.” He understood the incredible value of customers who actively recommend a company.

NPS is a measurement system that helps companies track and increase the likelihood of customers recommending an organization.

First of all, let’s describe the actual NPS measurement. It begins by asking customers a simple question:

“How likely are you to recommend this company to a friend or relative?”

Customers choose a response from an 11-point scale that goes from 0 “not at all likely” to 10 “extremely likely.”

Based on their response, customers are placed into one of three categories:

  • If they choose between 0 and 6, then they are DETRACTORS.
  • If they choose 7 or 8, then they are PASSIVES.
  • If they choose 9 or 10, then they are PROMOTERS.

NPS is calculated by taking the percentage of Promoters and subtracting the percentage of Detractors. You then multiply the percentage by 100 to get a whole number between -100 and +100.

Calculating Net Promoter Score (NPS)

Let’s say that 100 people answered the question, and 40 are Promoters, 50 are Passives, and 10 are Detractors. To calculate NPS, we would take the 40% for Promoters, subtract the 10% for Detractors, which leaves 30%. After multiplying it by 100, the NPS is 30.

While NPS provides a score, 30 in this case, the power of the system does not come from overly focusing on the number.

The goal of using NPS is to find and correct issues that create Detractors and to find and repeat activities that create Promoters. So it is important to understand what is causing customers to choose their responses.

That’s why most NPS programs include a follow-up question that asks the customer why they chose the score that they did. This question should be open-ended, not multiple choice, so customers can express their views in their own words.

What do you do with the data?

First of all, you want to “close the loop” with the customers who responded. This means contacting at least some of the customers who respond. Companies often try to reach out to all of the Detractors, to find out more about their problems and to see if their issues can be resolved. They also often contact Promoters, to thank them and hear more about what they like.

Next, you want to examine the opportunities to improve NPS by looking at what situations and activities cause Promoters and Detractors. This requires analyzing the responses from each group separately, and often involves incorporating other information about customers. You may also want to examine what drives Promoters and Detractors across different business areas or customer segments.

There’s no value in identifying the items that are driving NPS up or down unless a company does something with what they learn.

That’s why companies establish processes for reviewing, prioritizing, and taking action on the items that they uncover. In other words, the way to improve NPS is to have an ongoing approach for improving customer experience.

When used correctly, NPS helps companies follow Disney’s advice and do what they do so well that their customers want to see them again and bring their friends.

If being customer-centric matters to your organization, then why leave it to chance? Contact Temkin Group, the customer experience experts, by emailing info@temkingroup.com, or visit our website, at TemkinGroup.com.

Note: Net Promoter, Net Promoter Score, and NPS are registered trademarks of Bain & Company, Inc., Fred Reichheld and Satmetrix Systems, Inc.

Report: What Happens After a Good or Bad Experience, 2018

To understand how the quality of a customer’s experience – whether it was good or bad – affects their behavior, we asked 10,000 U.S. consumers about their recent interactions with more than 300 companies across 20 industries. We then compared results with similar studies we’ve conducted over the previous seven years.

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Purchase and download Temkin Group report: What Happens After a Good or Bad Experience, 2018

Here are some highlights:

  • Purchase and download Temkin Group report: What Happens After a Good or Bad Experience, 2018About 18% of the customers who interacted with TV & Internet service providers reported having a bad experience – a considerably higher percentage than in other industries. Of the companies we evaluated, 21st Century, Comcast, Cox Communications, and New York Life deliver bad experiences most frequently.
  • We created a Sales at Risk Index for all 20 industries by combining the percentage of customers in an industry who reported having a bad experience with the percentage who said they decreased their spending after a bad experience. According to this Index, TV & Internet service providers stand to lose the most revenue (6.4%) from delivering bad experiences, while utilities stand to lose the least (1.4%).
  • When it comes to recovering from delivering a bad experience, Investment firms are the most effective and TV & Internet service providers are the least effective.
  • After customers have a very bad or very good experience with a company, they are more likely to give feedback directly to the company than they are to post about it on Facebook, Twitter, or third party rating sites. Customers are also more likely to share positive feedback through online surveys and share negative feedback through emails.
  • Compared to previous years, customers are less likely to share feedback across almost all channels, with a particularly large drop in the percentage who post on Facebook or Twitter.
  • Across almost all age groups, consumers are most likely to share their feedback directly with the company. Consumers between 18 and 34 years old are the most likely to share their good and bad experiences on Facebook, while older consumers tend to use 3rd party ratings sites more than Facebook or Twitter.

Download report for $195
Purchase and download Temkin Group report: What Happens After a Good or Bad Experience, 2018

Here is one of the 12 graphics in the report:


Report Outline:

  • Bad Experiences are Prevalent in the TV & Internet Services Sector
  • Bad Experiences Can Be Very Costly
  • Consumers Give More Feedback After a Bad Experience
    • The Channels for Direct Company Feedback
    • Feedback Differs Across Age Groups

 

Figures in the Report:

  1. TV & Internet Service Providers Deliver the Highest Percentage of Bad Experiences
  2. Companies That Deliver The Most And The Fewest Bad Experiences
  3. How Consumers Cut Their Spending After A Bad Experience, By Industry
  4. How Consumers Cut Their Spending After A Bad Experience, By Industry
  5. Sales at Risk Due to Bad Experiences
  6. How Industries Respond to Bad Experiences Overall
  7. How Consumers Give Feedback
  8. How Consumers Give Feedback to Companies
  9. Changes in How Consumers Give Feedback After a VERY GOOD Experience, 2013 to 2017
  10. Changes in How Consumers Give Feedback After a VERY BAD Experience, 2013 to 2017
  11. How Consumers Across Age Groups Give Feedback After VERY GOOD and VERY BAD Experiences
  12. How Consumers Across Age Groups Give Feedback Directly to Companies After VERY GOOD and VERY BAD Experiences

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Purchase and download Temkin Group report: What Happens After a Good or Bad Experience, 2018

Mastering Customer Experience Metrics (Infographic)

As an organization’s customer experience efforts mature, CX metrics become a critical guidepost for all of its activities. You can see different ways to download this infographic below.

Mastering Customer Experience (CX) Metrics Infographic

Here are links to download different versions of the infographic:

Here are links to the research referenced in the infographic:

Making AI Customer-Centric

Making AI Customer-Centric (Temkin Group Report)Temkin Group just published a new report, Making AI Customer-Centric. Here’s the executive summary:

The use of Artificial Intelligence (AI) – often in the form of chatbots and intelligent virtual assistants – is becoming more widespread in customer experience. However, despite its prevalence, few companies are employing AI in the right scenarios or using it to its fullest potential. In this report, Temkin Group creates a model and shares best practices for AI-Driven Interfaces (AIDI), which we define as digital interactions with customers that are being directly manipulated by machine learning algorithms.

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Purchase and download Temkin Group report: Making AI Customer-Centric

To successfully deploy customer-centric AI, companies need to:

  • Integrate the elements of the Human Conversational Model into the design of AIDI.
  • Bring together Five Ingredients: Conversational Design, Targeted Use Cases, Optimized Data Aggregation, Responsive AI Engine, and Continuous Tuning.
  • Determine Organizational AI Readiness before deployment by tying AI to business strategy, auditing data sources, assessing employee skills, and planning for agent/AIDI interactions.

Five Ingredients of Customer-Centric AI

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Purchase and download Temkin Group report: Making AI Customer-Centric


Report Outline:

  • Current AI Efforts Miss the Mark
  • Five Ingredients For Customer-Centric AI
    • Ingredient #1: Conversational Design
    • Ingredient #2: Targeted Use Cases
    • Ingredient #3: Optimized Data Aggregation
    • Ingredient #4: Responsive AI Engine
    • Ingredient #5: Continuous Tuning
  • Determine Organizational AI Readiness

 

Figures in the Report:

  1. Artificial Intelligence Terminology
  2. Five Ingredients for Customer-Centric AI
  3. The HumanConversational Model
  4. American Express Platinum: Handoff to live agent
  5. Organizational Personality
  6. Organizational Personality: U.S. Army’s SGT STAR
  7. Attributes of Good Initial AI Use Cases
  8. How AI Supports Contact Center Agents
  9. NorthFace: Identify Intent in the Moment
  10. Questions For Determining Organizational AI Readiness
  11. Changing Responsibilities for AI Development

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Purchase and download Temkin Group report: Making AI Customer-Centric

The Future of VoC Actionable Insights: Assistance Engines

Earlier this week I gave a speech called “The Future of CX: Humanistic, Prescriptive, and Responsive.” During that session, I discussed a missing link in today’s VoC technology: Assistance Engines. Here’s a picture of the future that I have in mind.

Architecture For Prescriptive Customer Insights

Before I describe Assistance Engines, I want to go back to 2010 when I labelled VoC technologies as Customer Insight & Action (CIA) Platforms. The naming was important, because it correctly identified that vendors needed to focus more on “insight & action” than on customer feedback.

It turns out that this is still the case. In the future, VoC vendors will be completely judged by results that their clients get from taking actions on the insights that these vendors provide.

Action is the holy grail! All of the efforts around surveying, integrating data, analyzing, etc. are only as valuable as the actions that they lead to. Most of the vendors now understand this key concept, and are working feverishly to improve the actionability of the insights they provide.

Companies still have a long way to go in taking action on their VoC insights. As you can see in our recent infographic, only 24% of large companies think they are good at taking action.

To help refine the insights, most vendors are developing some sort of an Intelligence Engine. This technology combines direct customer feedback with other customer information, and then applies different analytical and machine learning approaches to create predictive insights about large groups of customers.

While this technology is helping companies to better understand their customers, the output does not often translate directly into actionable insights. Why not? Because there’s a wide gap between insights from the Intelligence Engine which are often delivered in charts and dashboards, and the types of information that employees need to make their a day-to-day decisions.

No matter how much smarter these platforms get about customers, they won’t be truly actionable until they also get smarter about employees.

That’s where Assistance Engines come into play. What is an Assistance Engine?

A set of technologies that uses analytics and machine learning to provide increasingly valuable advice to help different employees across an organization make customer-centric decisions.

Or you can think of it more simply as…

Technology that recommends employee actions based on customer insights.

Assistance Engines will provide timely, actionable insights that are embedded within role-based processes, and delivered as answers and recommendations, not as charts and numbers. This technology will also fine-tune its recommendations based on feedback from employees about the types of recommendations that they find valuable.

Think of the Assistance Engine as being like an analyst who works for the employee. A good analyst can comb through data in an Intelligence Engine, understanding her bosses needs, and translate the customer insights into a very relevant set of recommendations. Over time, the analyst gets better at anticipating what her boss needs or wants to see.

Here are some examples of insights that an Assistance Engine might deliver (think about the employee simply asking Alexa a question):

  • When a product manager is defining a new product, the Assistance Engine will recommend a set of features that a product manager should include in its next release.
  • When a contact center supervisor finds that she has 15 minutes free, the Assistance Engine can tell her which agent to spend time with and what to cover during the session.
  • When an executive is looking to improve the companies NPS, the Assistance Engine will identify the regions to focus on and the activities that should be improved in those regions.

The early use cases for Assistance Engines will likely focus on recommendations that are already being made by analysts. But instead of having someone spend a lot of time manually digging through troves of data, the Assistance Engine will simply answer end users’ questions.

Companies still have a long way to go in building out their Intelligence Engines, so we do not expect to see Assistance Engines become mainstream for several years. But the maturing of end-user responsive analytics such as IBM Watson and Amazon Analytics will help accelerate the development.

The bottom line: Actionability requires more focus on employees.

 

Building A Strong Voice of The Customer Program (Infographic)

Voice of the Customer (VoC) programs are a critical component for many CX efforts. This infographic examines those efforts. Make sure to visit our VoC/NPS Resource Page for more help in building your VoC program.

Here are links to download different versions of the infographic:

Here are links to the research referenced in the infographic:

Report: Propelling Experience Design Across An Organization

Propelling Experience Design Across An OrganizationWe just published a Temkin Group report, Propelling Experience Design Across An Organization.

Although customer experience (CX) management has become a relatively common activity within large organizations, companies still struggle to deliver consistently positive experiences to their customers. One major issue impeding companies’ current CX efforts is that few organizations design customer interactions in a purposeful and deliberate manner. This report explores how companies can use Experience Design – which we define as a repeatable, human-centric approach for creating emotionally resonant interactions – to craft consistently excellent interactions and how they can share and spread these capabilities across the entire organization.

Download report for $195
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Here are some highlights from this report:

  • The Experience Design process is made up of three generic phases (Clarification, Generation, Realization), each of which contains two stages (empathize and synthesize, conceptualize and materialize, scrutinize and actualize).
  • To help propel Experience Design capabilities across the organization, we developed The Federated Experience Design Model, which is made up of three tiers of employees – Experts, Boosters, and Dabblers.
  • We share over 30 examples of best practices from companies that are spreading and sharing Experience Design capabilities throughout their entire organization.
  • We also provide some tools that employees can use across the six stages of the Experience Design process.

The move towards propelling CX across an organization is part of a broader trend that we describe in the report, The Federated Customer Experience Model.

Here are two of the 22 figures in the report:

Process, Mindsets, and Skills of Experience DesignFederated Experience Design Model

Download report for $195
download the state of customer experience management


Report Outline:

  • Customers Suffer from Haphazard Experiences
  • Components of an Experience Design Methodology
    • Phase 1) Clarification: Understand the Objectives
    • Phase 2) Generation: Explore Potential Solutions
    • Phase 3) Realization: Share Solutions with Customers
  • Federating Experience Design Across an Organization
    • The role of Experts, Boosters, and Dabblers
  • Simple Experience Design Tools Support Federation

Figures in the Report:

  1. Process, Mindsets, and Skills of Experience Design
  2. Experience Design Mindsets
  3. Experience Design Skills
  4. Examples Across the Experience Design Processes
  5. Examples Across the Experience Design Processes
  6. Examples of Empathizing
  7. Three Levels of a Federated Experience Design Model
  8. Federated Experience Design Model
  9. Means of Providing Ongoing Coaching and Support
  10. IBM Design Thinking Badge Program
  11. Tools Across the Three Levels of Employees
  12. Tools for Clarification: Empathize
  13. Tools for Clarification: Synthesize
  14. Tools for Generation: Conceptualize
  15. Tools for Generation: Materialize
  16. Tools for Realization: Scrutinize and Actualize
  17. Customer Journey Maps
  18. Customer Journey Thinking™
  19. Temkin Group’s SLICE-B Experience Review Methodology
  20. Temkin Group’s SLICE-B Experience Review Assessment
  21. Empathy Maps
  22. Starbursting

Download report for $195
download the state of customer experience management