drowning in data no insights

A Lot of Data, Not Enough Insight

A month ago I saw a Forrester presentation on Customer Experience measurement that began with a great quote from the Global Bank: “We are drowning in data and starving for insight.”

Aren’t we all?

Most organizations have more data than they ever could have wanted, but that data is either sitting idle in databases or cloud environments, or it is used sub-optimally. Why is it that WeWork can build a tool to manage its 350 properties as a website and digitally view every detail about every building, but Fairway regularly emails me with first time user coupons that I am not eligible for as an existing customer?

Make Data Usable

The answer to this question is fundamentally simple, but practically complex. The first step is to centralize and clean the data so it can be used in an actionable way to extract insights. For existing companies this requires organizational redesign. That makes this step complex, political, and difficult to execute.

In one case, a major brand acquired three small start-ups with the business strategy to grow its customer base. The brand worked on learning how the three customer segments feel and what each segment wants in order to optimize the brand’s offering with three different products. Even though this was the correct first step, the strategy did not progress well. The company was not ready to centralize the customer insights systems and the teams of the three distinct brands they had acquired. Each start-up had its own customer database and customer definitions. None was open about giving access to that data. Thus no insights were derived from any of the three brands.

This case only scratches the surface of how companies miss opportunities with data. Accessing and aggregating data is an essential first step for all organizations, but that is not enough to derive insights. Even after teams and data are centralized and aggregated, insights are not available until the definitions of the data are aligned. How is a customer defined? How far back should the data go? What spend per customer makes that customer “valuable”?

Get Everyone in the Room

Organizations must answer these and many more questions in order to make available the capability of data insights. Often, companies complete step one, aggregate the data, but fail to analyze it and define the key parameters of it. Why? The answers should come from the consumers of the insights, not the technology teams building the insights. And those people are not in the room. Until there is a real engagement by the business and a collaboration among the teams, no one is getting any insights from their data.

Democratize Data

The last step of getting insight out of data might seem the simplest, but it is often missing. The quality of insights is directly correlated to the quality of the questions asked from the data. I will repeat that. The questions asked of data are the engine of the insights derived from data. This is where democratizing the cleaned data with a very user friendly UI is key. Good questions are rarely formed on the spot. As business challenges arise and new situations emerge, questions come out. It is important that access to the data is readily available (no coding or SQL skills necessary!!) to all so the end users can run reports and get the answers they need – and can act upon – in real time.

Successful brands like WeWork turn data into a tool. When companies perceive data as a tool, they create real value for customers. And when they fail to make the difficult steps of organizational redesign and pay for cleaning the data, we receive those coupons we can’t cash in.

View more of our conversations about data, and send us your questions about how to democratize and optimize data to improve customer experience in your organization.

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*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations

data tips for customer experience

Lessons Learned at the Forrester Conference: “Data is the New Sexy”

Once a year I look for an event or a conference to attend where I can learn something new and get better at what I do. This year I attended the Forrester Global Council Meeting and the CXNYC2018 Forum in New York.  Usually, the big win from events like this is the opportunity to network and meet new contacts. This year, though, the Council meeting felt like school – which I loved. These are the aha moments I am eager to share with you.

“Stop decorating. Start renovating.”

Do not build a CX strategy that is disconnected from your business strategy and that nobody knows. Don’t maintain a VOC program that tries to fix journeys that were never built with the customer in mind. And stop obsessing over NPS scores versus improving the customer experience.

Instead, focus on your customer needs and what your customers perceive as value, then build your competitive advantage around that. Listen to your employees, who often have the best ideas. Create customer business value. Then execute, execute, execute!

Research is a real thing!

There are many tools customer experience professionals can use to conduct customer research. Depending on which phase of your discovery you are in, or how strategic or tactical the question you are working on answering is, you can use different tools. The broader the question you are asking, the more qualitative your methods should be.

At the discovery phase, when you are looking to find what problems exist, you can do interviews, diary studies or ethnography. If the problems are defined and you need to find the best way to solve those problems, you can get more specific with surveys and usability testing. If you are looking to evaluate a solution that you have built, you can do A/B/multivariate testing and cognitive walkthroughs.

“Data is the new Sexy!”

Customer obsession is nothing more than a dream if you lack the analytics to drive it. You achieve productive customer insights only when you are able to capture and analyze data across channels. CX insight professionals need to be comfortable looking at data from online to offline channels, and they need to derive insights from known data to anonymous data.

Customer analytics methods are interconnected and have dependencies that must be kept in mind. It is impossible to get to customer lifetime value without a solid grasp on customer churn. Understanding the sequence and educating your executives about the complexity and funding required to get end-to-end insights from data is imperative to your organization’s success and your customers’ satisfaction.  Without data, your strategy is based on opinion. You need a data-led strategy to survive.

Now start aggregating data!

If you like this article, please share with others so they can benefit. Sign Up for our newsletter to continue learning how to increase your skills and transform your organization! When you register now, you will get free access to our whitepaper on how to go from CX Novice to CX Expert

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.

What Is Big Data and Why Should I Care?

What is Big Data and Why Should I Care?

Big data has become part of our daily language. We read about big data. We see companies that are “experts in big data.” LinkedIn is filled with big data engineers and analysts. But what is big data, where did it come from, and why is it widely available now when it wasn’t ten years ago?

Big data is actually exactly what it sounds like. Big. Data. It is comprised of an enormous amount of 0s and 1s that carry all kinds of meaning. The volume and complexity of the data sets is so large that the Excel or Access analytical tools that we are used to no longer allow us to understand or manipulate the data. Big data is not new. It has always been available.

The big news about big data is that, now, the data no longer needs to be structured in order to be analyzed (read: less work for all of us to “prep” the data for analysis) and it is available real time vs. in weeks (read: no more need to schmooze your IT contacts to run a report for and send it a week later). I remember the days when I was in the banking industry and needed to analyze a set of trades within a month. It would take a week just to find who to talk to, build the relationship, explain what I need, and then another week to get my answers.

All of this inefficiency has been eliminated. Now, we have access to a real-time, friendly system that can answer questions about transactions as they happen. The enabler for all of this is new data storage options. In the past, it was impossible to store data in a flexible way. With the current advancements, that is now possible, making big data widely available.

This is the baseline answer to the “what is big data” question. Josh Ferguson, CTO of Mode Analytics, dives deeper to explain. “Big data is the broad name given to challenges and opportunities we have as data about every aspect of our lives becomes available. It’s not just about data though; it also includes the people, processes, and analysis that turn data into meaning.” In other words, just because we have more data, does not mean we have all the answers we need.

It is necessary to derive insights and information from the data. This is where most companies fail. They aggregate more and more data and never operationalize it. Sometimes they do not even report it. So much data is sitting dormant across all industries because there is no one engaging with it in an analytical way. Consider airlines and kiosk data. Airlines collect performance/usability data (how many days/hours the kiosk was working and/or was used), usability/UX data (which screen of the interface gets abandoned by the customer and how often), and a variety of transaction data (how quick was the kiosk response when people engaged with it). Does this data help airlines on its own, even if the data was collected for 12 months? Absolutely not.

Here is why this matters for customer experience professionals: because we can be the masters of data and control the insights and the messaging that comes from the insights. As customer experience leaders, we can recommend which kiosks should be REMOVED from the system because they barely get used (i.e. save total costs). We can build a dynamic maintenance contract to have maintenance performed only AFTER a certain usage number is reached vs. a static every 3 months maintenance cycle for all kiosks (i.e. lower maintenance costs). Consider how we can use insights that show when customers drop off. Finding that information allows a CX expert to fix the problem and increase the self-service conversion. That means more savings for the company! If a company has service agreements with partners, transaction speed data makes it possible to manage those SLAs much better. In other words, big data with the right critical thinker on top is a source of immense power and leverage. And that is why we should all care about big data.

So, the next time one of those companies approaches your organization saying it will empower your data, ask them who will be extracting the insights from that power, and make sure to build an in-house team of very smart people who can do the magic for you. Once that is set up, start asking good questions and fuel the engine of competitive advantage you can build with big data!

Learn more about Big Data

Rutgers University is offering a deep dive class on Big Data that gives you more of the tools you need to capitalize on this powerful resource. They have been kind enough to offer DoingCXRight readers 20% off the cost of the class. Sign up here to grab your discount and connect to the class.
*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.
customer experience applications for ai

How Well Do You Understand AI Applications?

Last week I spoke about AI at the Argyle Forum webinar and at the ConnectID Conference in Washington, DC. Technology is emerging and we need to find a way to integrate it. In order to get approval for AI initiatives from our CFOs and/or boards and to get AI adopted by our customers, it must meet a specific customer experience need or fill in a journey gap.

As Jessica Groopman summarizes, AI can be broken into 3 major streams: big data, vision and language. These streams come with various applications that have clear business cases that we can learn from.

AI Big Data Application

Ancestry uses big data to explore DNA and compare it to hundreds of thousands of records it already has in its database to provide customers with insight about your genetics origin. Even my genetics specialist suggested last week that my husband and I check our ancestry there. Information is power, and knowing more about who we are and where we come from is a big gap in our journeys as individuals. Ancestry utilizes big data and creates a product and a customer experience that makes sense to the end user.  This is why their product is being adopted by customers.

AI Language Application

At Waverly Labs  Andrew Ochoa and his team are using machine translation to break down language barriers around the world. With an ear piece and an app, users can travel anywhere in the world and hold a real-time conversation with locals without learning the language of the country they are visiting. That is real game changer in communications. Imagine finally having a real conversation with your waiter in a small French bed and breakfast and ordering the best local dish. Or speaking to your mother or father-in-law without having to learn the mother tongue of your spouse (although understanding each other better could deteriorate that in-law relationship :)). These real customer experience gaps drove 22K people to fund Waverly Labs on IndieGogo and helped Andrew Ochoa raise $4.5M.

AI Vision Application

Facial recognition is one of the most common applications of vision AI. Yesterday at the ConnectID Conference we saw a variety of trials that prove the use of facial recognition at the airport to enhance efficiency and security for the customer and his/her journey. Airlines and airports all over the world are working on refining the value proposition of these deployments with the seamless biometrically enabled journey as the end goal.

Last year we wrote about eBay and their big bet to make AI the center of their product design. E-Bay is building the ultimate personalization, making it possible to design an outfit that does not exist!  We are all learning, but one thing is certain, chatbots are not the only application in AI and if you are a competitive customer experience professional, you better learn all the answers AI has to offer before you find yourself with a stupid chatbot in your contact center while  your competitor used AI to reimagine the customer experience, embracing a technology that drives them straight into the future.

If you like this article, please share with others so they can benefit. Sign Up for our newsletter to continue learning how to increase your skills and transform your organization! When you register now, you will get free access to our whitepaper on how to go from CX Novice to CX Expert

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.

How to Prepare for AI: Dispatches from CR Summit, Charleston

On the eve of the #CRSummit in Charleston, customer experience leaders from various industries held the first AI Committee meeting. AI is a challenging topic to cover since it has varied customer experience applications depending on a brand’s growth cycle, customer base and business challenges. Companies like eBay place big bets on AI, while others use natural language processing (AI) only to build smart chatbots.

Regardless of their approaches all companies have one thing in common – they all need to prepare for AI implementation by having a comprehensive data strategy with flexible architecture and a lot of storage. This is the missing piece for most companies. Organizations have different reasons for lacking intelligent data. Some brands are too young and have homegrown systems that need major overhauls to even scale for the growth of the companies. Others have more robust data repositories, but have been built without the customer as the common unit.

There is a third scenario: companies that have third party CRM systems that also host the data. This makes it almost impossible to have the end-to-end data to use for building personalized experiences. It is important to learn the necessary foundations so when you meet with sales reps you can recognize the option that will fit your technology needs.

Another foundational and somewhat counter-intuitive aspect of applying AI is the need for humans. The biggest misconception about AI is that it will “remove jobs”. Meanwhile, customer experience leaders are all struggling to persuade CFOs to fund new teams of data scientists, people who would tag existing data, or people who watch for the “triggers” to use the data. Once this is done, brands will need data councils to add new elements or to design new uses of AI. Companies will always need more people to manage AI effectively.

Lastly, we all want to build solutions that will save operating costs today and enable a future customer experience transformation. So when we build, we need to think about scaling and building further, with the customer at the center.

There are still questions we need to answer. How do we begin the process (especially without much funding)? How can we make AI a reality and not just talk about it? What are the tradeoffs (if any) that we will have to make in the process?

Stay tuned for the next post on AI.

 

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.

Why I Don’t Love Chat Bots

Today, we tackle the value proposition that chat bots are more valuable to companies than customers. I reject this.  The ROI simply is not there, especially since better customer experience is not there. I have experienced both fully automated bots and “augmented” service agents interactions using the chat channel, and neither delivers on the promises of chat bots as the game-changing resource we all need.

For our blog we use a photography subscription service. They push chat support heavily. When I used it, it was slow. The person either did not know English well enough or was multi-tasking several chats, but it felt like he was not present. On occasion, it felt like he was not answering the question I was asking, but rather providing a generic response. The base for effective communication is connection. When I felt unheard by the “support,” my frustration almost led me to drop the service (there are plenty of options for photography sources). Suddenly the chat offering threatens to cause the loss of a customer… and the organization PAID for it, for its integration, monthly support fees etc. I do not like that. It makes no sense.

empathetic response ai photos

AI presentation photo by Liliana Petrova, CCXP

Let’s talk about the fully automated chat bots. Allegedly, this is where companies see the real efficiencies. Again, no real value for customers unless the automated chat function allows them to fully self-serve. The problem is, the fully automated chat bot today is stupid. It can perform only very distinct functions.

The customer faced with a chat immediately tenses up with anxiety. He/she knows that the chances are pretty high he/she will have to channel switch pretty soon. How many bot interactions have you had that allowed you to solve your problem without switching to a human? Chat bot is supposed to deliver customer-centric experience. It is supposed to be customer directed, but the customer feels anxious that the minute the bot gets “stupid,” the customer loses control of the experience. Suddenly, the power is with the bot.

What is the future for chat bots? Disturbing is a word that comes to mind. Soul Machines is the company to check for the preview. They have developed a digital human that has a BRAIN built on a virtual nervous system. Now that is equally exciting and terrifying. It reminds me of the AI empowered female voice that sounds like a human one (the digital human is also female…just saying). It will take some time before the digital human agent becomes the norm, but one thing is for sure, the next version of “stupid bot” will have empathy.

According to Forrester, 60% of us prefer not to use a chat bot at all. I bet you if you ask why, you will also hear that the bots just stupid. So how can chat bots become smarter? We are back to the data conversation. Chat bots are as smart as the power and scope of the underlying data they can pull/learn from. In the case of the JetBlue customer experience team, without an integration to our reservation system, the chat bot cannot change or re-book a passenger’s ticket. Until then. customers will keep reading “please speak to an agent.” That is hardly a way to feel the love.

 

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.

AI

How Smart Do Humans Want AI To Get?

Last month we covered the basics of AI and what it is in theory. Today we will talk more about the existing practical applications of AI and reflect on what that means to us. We will also share some caution about AI, which, similar to IoT does not have existing laws to follow due to the speed of its development. It is a fact that there is no real regulation on IoT products today and there are cases filed against familiar brands like Bose.  Last month I bought my team Google home minis to inspire a culture of innovation. Sometimes I wonder… what exactly did I buy them?
 
Currently, one of the most impressive real expressions of AI is the voice-generating AI that is indistinguishable from humans. Now that is a real capability that can generate significant efficiencies in call centers (given that you have the clean data and the cloud enabled applications to power the “brain” of the AI).
 
The AI voice re-imagines the how of the interactive component of the customer experience. The innovation part is that, to the customer, there is no real change in the emotions they experience during the call. The customer still hears a friendly female voice. This AI application does to the call center what the touch screen did for cell phones in 2007.
 
Keep in mind that as you converse with the friendly female voice, the AI that powers it is learning – it is getting smarter and smarter. The question is how smart can AI get. A better question, how smart do humans want AI to get? We all have heard the story of Frankenstein. If we are not careful, we might build our own replacement.
 
If you think I am exaggerating, listen to Elon Musk who has been cautioning us against AI for years. “I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it’s probably that… I’m increasingly inclined to think that there should be some regulatory oversight, maybe at the national and international level, just to make sure that we don’t do something very foolish.” We should most certainly embrace the future. However, we need to make sure we keep the control. With regulation and legal framework speed we might build the guardrails too late. Let’s also not forget that the master computer voice in Terminator, like those used in call centers, was female. I wonder if that is just a coincidence….
 
AI is not capable only of generating voice. It is able to “read” and to analyze human voices in a manner we have never seen. The term for this is “voice profiling.” Apparently, humans cannot detect the data/information in our voices the way AI software can. So the next time your bank asks you if you consent to record your voice for “additional security” on your account, think twice (too late for me… the TD Bank AI already has filed me away). The advancement went as far as creating a face to the voice in December. “Your voice is like your DNA  or your fingerprint.” according to Rita Singh. Thanks to today’s advanced algorithms and the large computing power available, our DNA is out in the digital space, ready to be “profiled.”
 
The reach of AI goes beyond customer service and personal banking. AI is now making hiring decisions today. Companies use AI technologies to shift through the large volume of online resumes they receive. Ostensibly, AI creates a leveled ground for all candidates and alleviates existing biases during interviews. An industry has emerged predicting either candidates’ skills based on online clues in the case of Fama or on their actions through Entelo that “guestimates” who is likely to leave a job. The situation gets creepier when we start talking about companies like HireVue. On the surface, HireVue’s solutions sound innovative  – “databased, unbiased talent decisions.” In reality, HireVue has the potential to read our faces when we speak and determine whether we are not truthful. No more saying at an interview you are leaving your current employer to pursue further development. HireVue will know you did not get along with your boss, or that you hate banking. A world in which we cannot have our internal lives sounds like a scary and lonely place.
 
What is next for the brave new world? According to the cofounder and CEO of Nvidia Huang it is “… the ability for artificial intelligence to write artificial intelligence by itself.” In other words humans will no longer be needed or even capable of running the new technology since it will be beyond our capacity to comprehend or manage. I don’t want to go back to Terminator and the Transformers, but it is hard not to see the resemblance in the plots. On the bright side, one can make a fortune in the next decade investing in those underlying technologies that will be running themselves or us in the future. This is how Huang made his fortune. We can always follow in his footsteps.
*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.
eBay

CX Bold Moves: eBay’s Vibrant Marketplace of the Future

Two years ago RJ Pittman and eBay made a big bet and made AI (artificial intelligence) a core discipline of the company, similar to brand marketing and sales. The organization was able to focus and build upon existing technologies to create a truly personalized experience on eBay. This is the definition of a big bet, and the reason why eBay is part of our AI (Artificial Intelligence) series.

In the retail world of RJ Pittman, the conversational commerce does more than assist us in buying an outfit, it uses predictive analytics and AI to design the outfit if it does not exist anywhere in the world.  Now that is the ultimate personal relationship any brand can have with a customer. Once eBay is able to consistently deliver this value proposition to the customer and to scale it for the 3Bn online users today, Amazon will finally have a match – and become less ubiquitous.

How did eBay get here?

“Don’t start from the tech, start from the experience and start with transformative experiences that your customers will feel…” is how RJ Pittman summed up his approach at the Forrester conference in San Francisco this fall.  eBay is an excellent case study of a brand that followed the principles for self-service that we laid out last week – the brand will enable the customer of the future to post and sell any item without any effort or friction. Through computer vision, deep science looking at images, real time pricing, conversational commerce with interactions, and a world price guide, eBay is building an AI-enabled ecosystem that will have the power to create many real personalized experiences for all of us.

What about the eBay brand?

“The brand is the product is the brand” are the words of RJ Pittman that sum up the future of marketing. Today marketing is less about ad campaigns and more about a brand’s products and the customer experience that accompanies them. This year JetBlue achieved $33M of ad spend equivalency with its launch of facial recognition technology at the gate. This is much more brand exposure than an ad campaign. Without the existing social media and mobile technologies, that would have been impossible. But in the world in which we live, the brand is more about keeping and living the promises you have made as an organization and less about what those promises are.

This is an important note of caution for all those who have brand marketing and customer experience under two different executives. How are you ensuring that there is a real alignment between those two legs of your customer relationship?

What did eBay really do?

eBay applied technology to build a dream no one has imagined yet. The innovative brand did not merely optimize its responsive website (some of us actually even call responsive design digital revolution:( ), it invested heavily in a conversational commerce that will define how customers purchase in the future.

This disruptive strategy is not a science project. It is the birth/built of a vibrant marketplace of the future. Rik Reppe said on stage in San Francisco that courage, flexibility and imagination will make or break our efforts with AI. Listening to RJ Pittman it felt like he has all three of them. Do you?

 

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.

Is AI Really The Answer?

Earlier this week we shared some of the pitfalls of implementing  self-service and highlighted the importance of strategic and empathetic implementation.  AI (artificial intelligence) is one of the self-service tools in the customer service professional toolbox today. It is also one of the new buzzwords, together with blockchain (for the curious ones  – my favorite explanations of blockchain are this video and this article).

The primary current positioning of AI is in call centers. The value proposition is that with AI, companies will empower customer service employees to make better decisions/recommendations, thus increasing employee engagement. Additionally, through AI, organizations will achieve significant ROI by automating the role of the customer agent (in JetBlue’s case, the crewmember) and scaling customer support without incremental headcount.

So what exactly is AI? Do you really understand what this technology can and cannot do? If you do not, keep reading as all working professionals today should understand at least the basics of AI. If you are like me, you probably get 100 sales emails every week telling you that you are running late and must leverage AI in your call centers. But do you really need AI? What problem do YOU need to solve? And is AI the best way to do that for your company?

Last month I was invited by Execs In the Know to join their AI Advisory Committee with the below mandate:

“The final group output will come in the form of a report. The exact nature of the report will be determined and framed by the group, but may include areas such as:

  • A summary of ways AI is enhancing CX channels
  • Best practices on where and how to start
  • Trends and technology in AI to improve service
  • ROI of current AI customer service initiatives
  • Perspectives and predictions about the future of AI and customer service”

This is no small mandate and it is encouraging that we have a group of professionals who are examining these questions before we all get ahead of ourselves with AI and compromise the ROI we all want so much.

The most common use of AI is ML (machine learning).  Basically, this is data mining and predictive learning on steroids that enables a computer to make decisions and interact with a human. With that basic understanding I already have a few questions to all the companies that are calling, emailing, inmailing etc., to offer me AI enabled solutions. Who, or rather what, is enabling those solutions? Is it my company’s data? Because if it is, I have a lot more work to do internally before I respond to those sales pieces.

Erik Brynjolfsson and  Andrew Mcafee provide a comprehensive explanation of what AI is and what it is not in their publication The Business of Artificial Intelligence. In it they state that AI technology is ready for implementation in the business world and that “[t]he bottleneck now is in management, implementation, and business imagination.” I do have the business imagination, but I also am taking my time to know exactly what capability I am buying with AI. It might be cheaper to streamline processes and fix existing software tools or integrations to enable my employees to deliver excellent customer service, instead of paying for yet another software integration that makes decisions based on my bad data (since I would have prioritized the purchase of the expensive AI solution over cleaning my existing data).

Although it is clear that AI will be a solution that needs demonstrated ROI and employee adoption for success while it is learning, it is also clear that we cannot wait too long to get comfortable with this new technology. As Erik and Andrew say, one thing is pretty sure: “[o]ver the next decade, AI won’t replace managers, but managers who use AI will replace those who don’t”.

That is the exact reason I chose to join the AI Advisory Committee. More to come!

 

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.

Liliana Petrova

From Pain Points to Magical Moments: Transform the Customer Experience

Argyle Journal recently interviewed customer experience professional (and Doing CX Right writer) Liliana Petrova about emerging self service technology and meeting and exceeding customer expectations in airports.

Liliana brings out a point that is integral to all technology-based customer experience solutions, namely that “[w]e want to create something that feels like magic, without breaking any foundational rules.”

Of that magic and the quest to create it as part of customer experience, Liliana explains, “[i]f there is a way to create a seamless and invisible experience, we want to find a way to get there.”

Read more about how she and her team are working to do so.

Play the audio below to hear Liliana speak about the magical customer experience.

 

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.

CX Bold Moves: Uber Bets On Self-Driving Cars With Big Volvo Purchase

For anyone brave enough to imagine the future it is clear that autonomous vehicles are coming and that the flying cars taxi chase of The Fifth Element will be a reality soon after. The question that remains unanswered is who will be part of the future of transportation. More and more players are claiming a stake in the multibillion market place, but like any innovation the odds of winning are 50%/50% until the industry gets mature enough for us to even see what it will be. So who are you betting on? Uber? Lyft? Yourself?

The Uber bet

Uber is going for the vertical integration – the whole pie. The future industry of urban transportation will be made of players in three different categories: cars, self-driving software, and ride-sharing network. With the #UberVolvo deal Uber made a stake in the cars part of the equation. They already have the ride sharing network and the in house research and development of self-driving software. Every company struggles with the right balance of internal development vs. partnerships. There are pros and cons of either approach. The factors in the final decision are costs of maintaining the technology (capital vs. operating), level of customization available (much harder when the technology is built by a partner) and speed to market (depending on the staffing level of the internal teams the speed can be faster or slower if the R&D is internally driven). Uber is betting on taking all the risk and owning all parts of the autonomous vehicle ecosystem.

The Lyft bet

In contrast, Lyft approaches the future through partnerships. Their vision improving lives with the world’s best transportation inspires the creation of cities for people, not cars. In the last two years they have formed multiple partnerships with various small and big players in the new tech space. The choice of partners: Waymo, nuTonomy, Drive.ai (self-driving software) and the large direct investment by GM (cars), proves that Lyft plans to be an integral part of the autonomous vehicle solution (ride-sharing network), but not the whole technology stack. Their strategy is much more tactical in nature. Lyft does not need to build the whole future of urban transportation. It suffices to be the bolt without which the system will not function. The success of this approach is founded on successful partnerships and is collaborative in nature.

The George Hotz belt

And if you still want to own a car in the future, the self-driving platform Openpilot and the Neo device may be the way to go. The Neo will transform your Honda or Acura into an autonomous vehicle that you can control with Openpilot. George Hotz’s company Comma.ai has activated users to share driving data to perfect the self-driving algorithms for the future by learning from drivers today. In his opinion “Self-driving cars need nothing but engineers in order to solve it.”

The approach to autonomous vehicles of Lyft is more congruent with the sharing nature of the future economy. Sharing is rooted in partnering and collaborating with others. The future generations are less likely to associate themselves with a conglomerate that monopolized the market space. It looks like Lyft, although a smaller player, does have the more sustainable strategy to autonomous vehicles. Then again, we are missing a big piece of the puzzle. We really do not know how the government will play in this space and if it will come up with regulatory obstacles that require a lot of funding to overcome. Smart brands put equal time and energy in building partnerships with the government agencies. So far Uber is behind on that front too. Both Uber and Lyft are making bold moves in the autonomous vehicles space. The question is, who has the winning strategy?

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.

 

 

self-boarding with facial recognition at a JetBlue gate.

CX Bold Moves: JetBlue Paperless And Deviceless Boarding

This year JetBlue entered the ranks of the innovators who disrupt industries and not only imagine the future, but also build it. With our award winning facial recognition boarding technology we were able to provide a preview to our customers of what traveling will be in the future. The fact that JetBlue’s facial recognition trial was named as one of the 100 greatest innovations of 2017 by Popular Science was one of the many signs we received about the excitement of the public about innovation in the airline space. JetBlue realized that our customers are not only ready, but also eager to step into a world of  new experiences that are personal, helpful, and simple.

So why is it so hard to eliminate the friction points on the travel journey and enable repeatable, intuitive, and empathetic experiences when we fly?

Variability is almost impossible to manage

In the book “Uncommon Service” Frances Frei and Anne Morriss lay a whole customer management process for successful brands. They present several examples of Progressive Insurance and Shouldice Hospital where through different processes these organizations are able to select the right customers for the experiences they have built. Airlines cannot do that. We cannot choose who we fly. Since the industry is driven by small margins, every customer flown counts. JetBlue’s mission bring humanity back in the air travel is driving us to welcome on board anybody who would like to fly us. And we consistently design all our product and experiences with that in mind!

Integrated experiences are based on integrated technologies

The future of flying is here only if we are able to integrate virtual reality and other technologies in a meaningful way that adds value. In JetBlue we are collaborating with JetBlue Technology Ventures and Strivr to test VR for training of our maintenance crewmembers.  The technology is more advanced in helping with decision making and not necessarily recreating the feeling of loading bags under the plane. For those immersive experiences the integration, build and scaling of the experiences is much more complex. Integrated and intuitive experiences are not hard to imagine, they are very complex to create and personalize.

Somebody has to pay for it

The moment we begin scaling and implementing customer journeys that use technologies of the future, we have to build the business case and its ROI. CFOs see customer experience design projects as process effectiveness work that increases output of existing infrastructure. Customer experience is much more than that of course, but knowing your audience is half the battle. Regardless if you agree with finance or no, you need the funding they hold. If you list the funding and maintenance requirements for a VR or a biometric solution very quickly you will see that to extract value from future technologies, you also need other future technologies to be cheaper. We all depend on a faster network (5G, 8G, 10G?) and even cheaper storage (cloud that is free to maintain and does not hit your operating expense every year?). Until that happens we probably will trial more and scale less.

We all share the excitement for the possibilities that new technologies like facial recognition and VR bring to us today. Some of us even venture to realize and share those possibilities with our customers. Customers have the power to add and co-design their experiences, which is really exciting too. In JetBlue we  used facial recognition boarding  to lead the industry. Our innovation was embraced by our customers and that is why we all won at the end!

# biometrics #facial recognition #VR #disruption # customer experience # game changer #NY Times #JetBlue

 

 

*All opinions expressed on the DoingCXRight Blog and site pages are the authors’ alone and do not reflect the opinions of or imply the endorsement of employers or other organizations.