utilizing humanoid robots for customer engagement · utilizing humanoid robots for customer...

ADITYA KAUL Research Director

CLINT WHEELOCK

Managing Director

Utilizing Humanoid Robots for Customer Engagement Benefits and Challenges, Use Cases and Industry Verticals, and Business Considerations

Published 4Q 2016

COMMISSIONED BY:

WHITE PAPER

Utilizing Humanoid Robots for Customer Engagement

© 2016 Tractica LLC. All Rights Reserved. This publication may be used only as expressly permitted by license from Tractica LLC and may not otherwise by accessed or used, without the express written permission of Tractica LLC

1

SECTION 1

EXECUTIVE SUMMARY

Humanoid robots are starting to see applications in customer engagement roles, armed with advanced facial recognition, emotion recognition, and speech recognition capabilities, and driven by recent improvements in artificial intelligence (AI). This technology leap is happening against the backdrop of the smartphone, web, and social media becoming primary customer engagement channels.

Brick and mortar businesses have largely struggled to keep up with innovations in customer engagement, with the rise of online retail causing more than 5,000 store closures in the United States during 2015. The emergence of humanoid robots can be seen as a silver lining to the ongoing disruption occurring in brick and mortar businesses, providing businesses with a tool to integrate the online and physical worlds. SoftBank’s Pepper and other humanoid robots are enabling new ways to engage with technology by combining a suite of innovations, with technology essentially becoming personified. Pepper, for example, is specifically designed to enable natural human interaction through speech and touch gestures.

Humanoid robots provide a playbook for customer engagement, and can be viewed as an evolutionary step from self-service kiosks to conversational commerce, combining the two in smart and unique ways. Retail is not the only vertical market that is well positioned to take advantage of robots. Financial services, healthcare, travel and hospitality, and quick service restaurants (QSRs) are all expected to see the benefits of customer engagement innovation through robots.

However, humanoid robots need to overcome a number of challenges, especially when they are being used for direct, face-to-face engagement with customers. As these robots become more human-like, there is a danger that they could fall into the phenomenon known as the “uncanny valley,” with human likeability turning quickly from empathy to revulsion. Social and cultural factors also need to be taken into account, with Japanese and Korean cultures being much more accepting and familiar with robots, compared to Western cultures. Cultural factors also play a role in designing the best user interface/user experience (UI/UX) for robots, which would help meet business objectives. The high cost of humanoid robots can also be a barrier to their adoption, with the right financing and leasing options being as critical as the robot itself. With the cost of high-end humanoid robots similar to that of an entry-level sales associate, it is not hard to see why there could be fear and insecurity among existing employees. Brick and mortar businesses need to carefully balance human labor concerns as they pilot and deploy these robots.

In order to take full advantage of robots in a customer engagement setting and enable the full suite of in-store analytics, IT integration and maintenance becomes as critical as the front-end interface. The future adoption of humanoid robots also depends on how successfully they are able to take on the role of platforms, bringing on developers that drive unique and innovative applications.

With customer engagement being such a critical part of brick and mortar businesses, it is time for humanoid robots to start to be seen as a tool for human augmentation, rather than being viewed as an automated replacement. Customer engagement is about connecting to the customer on a personal level, and today’s humanoid robots are capable of making that human connection.



2

SECTION 2

BENEFITS AND CHALLENGES

2.1 MARKET DRIVERS FOR ROBOTS IN CUSTOMER ENGAGEMENT ROLES

2.1.1 ROBOTS ARE A NATURAL EVOLUTION OF CUSTOMER ENGAGEMENT CHANNELS

Customer engagement is changing from being primarily driven by physical in-store touchpoints, TV and magazine advertising, or traditional mail catalogs, to being a diverse range of online channels that include the web, mobile, and social media. The smartphone is the main vehicle that is driving innovation in customer engagement and millennials are largely responsible for this shift. Apart from being an online generation, millennials like to be unique, are well-educated, have short attention spans, are less receptive to traditional advertising, and generally value experiences more than material objects. It is fair to say that millennials have caused a massive shift in marketing strategies, especially because they currently make up the largest demographic in the United States, around 92 million, even larger than baby boomers and Gen Xers. Omnichannel retail is one of the terms used to describe the shift in mindset required for keeping up with the shift in customer engagement. Omnichannel retail suggests a combination of traditional and online marketing channels, and unlike multi-channel retailing, the focus is on having a seamless and integrated customer experience across all channels. We are also seeing the rise of conversational commerce, which includes chat, messaging, or natural language processing (NLP), to interact with brands and companies, with the goal of completing a commercial transaction at the end of it. This includes both human and AI-enabled bots that power the conversational engine, driving this brand new customer engagement channel.

Humanoid robots are a natural evolution of customer engagement channels. As customer engagement has evolved from in-store human touchpoints to mobile and conversational commerce, humanoid robots bring back the face-to-face element to customer engagement, combined with smart AI tools. The emergence of humanoid robots is the result of advanced hardware and software, but also the need for companies and brands to engage with customers at a human level, with customers able to interact intuitively through speech and facial expressions, resulting in a unique, powerful, and everlasting impact.



3

Figure 2.1 The Customer Engagement Evolutionary Cycle

(Source: Tractica)

2.1.2 EXPERIENCES BECOMING THE PRODUCT

There is an ongoing trend in serving experiences as part of the product. Millennials are known to one of the prime demographic segments for consuming experiences, rather than just consuming products. A recent Harris Group poll suggests that 72% of millennials prefer to spend more money on experiences than on material things like cars, watches, or houses. Retailers like Macy’s have started to catch onto this trend by focusing on highly valued experience-based events like Coachella for which millennials might spend money on outfits and other merchandise.

But experience-based marketing extends to the complete user experience, as well. For example, Starbucks is chain of coffee shops, but rather than just selling coffee, it sells an experience that starts right from the time the customer enters the coffee shop, places an order, takes a seat, and spends time at the shop. In addition, it can be argued that Apple, one of the most valuable brands today, no longer just sells mobile phones or laptops, but also sells an experience that starts at the Apple retail store and extends to the full cycle of the customer experience. The rise of experience-based marketing is now part of popular culture, with film, music, and the internet all driving experience-based marketing.

With technology becoming personified into a humanoid robot, it enables brands and retailers to enhance their ability to provide experiences for their customers, rather than just sell them a product. Just as customer engagement is circling back into the brick and mortar retail store, sophisticated experiences can be created utilizing humanoid robots, where customers are able to use natural language to interact with the brand, be entertained, and be provided with personalized recommendations, with emotion recognition technology being used to empower the interactive experience.

Today, it isn’t enough for businesses to simply drive innovation, which is largely innovation for the sake of innovation, but they must also use technology that provides them the tools to

PhysicalStores

Mail catalogs

TV and magazines

Websites

Mobile



4

create new innovative experiences, which goes beyond creating and selling a product. Humanoid robots can be one of those tools.

2.1.3 BRIDGING THE GAP BETWEEN ONLINE CUSTOMER EXPERIENCE & BRICK AND MORTAR

For the most part, customer engagement is moving from the physical world to the online world, where the majority of customer experience strategies are being applied. While omnichannel retail incorporates technologies like tablets, beacons, and self-service kiosks within the store, brick and mortar has been largely ignored when it comes to customer engagement innovation. The rise of the smartphone has led to brick and mortar retailers paying closer attention to shopper behavior, with more shoppers checking prices, reading reviews, and getting more information about products while in-store. However, there has not yet been a coordinated effort around trying to integrate or create a seamless experience for shoppers while they are in-store. Most of the efforts around using beacons or radio frequency identification (RFID) to engage smartphone users in-store have been highly fragmented and difficult to deploy, and requiring users to opt-in makes the user experience feel largely broken from the start. Following the hype surrounding beacons and RFID a few years back, enthusiasm for these technologies has waned.

Figure 2.2 Bridging the Physical and Online Worlds

(Source: Tractica)

Humanoid robots provide another opportunity to bridge the gap between online customer experiences with brick and mortar. Unlike beacons and RFID, they do not require opt-ins from the customer, and provide a more seamless user experience that uses NLP and facial recognition systems to have a conversation with customers. Touchscreens add another familiar user experience dimension, which allows customers to interact with robots in a natural way. Integrating advanced analytics, machine learning algorithms, and customer relationship management (CRM) systems running in the background enables robots to provide personalized assistance and product recommendations, delivered through natural speech and touch interfaces. Pilot deployments have also shown that integrating mobile payment and loyalty apps with robots personalizes and expands e-commerce services. Pilots of humanoid robots have also shown that humanoid robots with touchscreens drive 3 times more engagement than self-service kiosks, as they are much more engaging and personalized user interfaces.



5

A/B testing on marketing messages, new store layouts, product placement, and lighting is possible with humanoid robots through customer surveys or conversational commerce. Brick and mortar businesses are able to perform A/B testing just like online retailers do on their websites or apps. Overall, humanoid robots are well placed to square the innovations that we see in mobile-based conversational commerce and online retailing, bringing them into the store.

2.1.4 ADDING NEW DIMENSIONS TO IN-STORE ANALYTICS

In-store analytics includes customer footfall or people counting, customer service, and customer behavior, such as identifying dwell time and store areas where customers spend the majority of their time, all of which can help with space productivity and category design. The overall goal for in-store analytics is to match customers’ needs with the store merchandise and layout, leading to happy and loyal customers. Technologies such as Wi-Fi tracking, beacons, and video cameras can provide customer movement data through the store to identify hot or cold areas, and manage merchandise, but they fail to go one level deeper into the mind of the customer, to understand what they are thinking or whether they are happy or dissatisfied. Current in-store analytics technologies are good at a high-level overview of customer behavior, but are not very powerful when it comes to personalizing the customer experience. beacons have failed to gain traction in the market as discussed earlier, which puts brick and mortar businesses at a disadvantage in terms of identifying customers and offering personalization.

Personalization requires the integration of in-store technologies with customer data, but unless the customer can be identified, it is very hard to provide that personalization. Humanoid robots have the ability to use NLP and facial recognition to identify customers, or simply use a barcode scanner to perform identification. Once the customer is identified, the robot can recommend products, or provide customized offers based on the backend integration with customer databases. Advanced technologies like emotion recognition can provide new dimensions to in-store analytics, providing brick and mortar stores with an emotional satisfaction quotient for each store. This data can also be segmented by age and gender by using computer vision techniques deployed in humanoid robots. Therefore, humanoid robots are not just powerful tools for personalizing the in-store shopping experience, but can provide additional customer data to help businesses strengthen their analytics capabilities.

2.1.5 EMOTION RECOGNITION AND MULTILINGUAL CAPABILITIES

Human-driven customer engagement is best equipped to recognize customers’ emotions, based on their tone of voice and facial features. But rather than simply recognizing emotions, it is the resulting action that counts. Failure to act upon a customer that looks distressed or dissatisfied nullifies any advantage of recognizing emotions in the first place. Humanoid robots do not just recognize emotions using their advanced computer vision and facial recognition technologies; they can be programmed to take appropriate action as the next step. This could include having an extended conversation with the customer, a change in tone, telling a joke, or possibly an intervention by a human agent. The guarantee that a humanoid robot provides to act upon the knowledge that it has gathered from emotion recognition, gives it an upper hand over humans, whose judgement might be impacted by one’s own emotional state. Emotion recognition is a powerful tool for in-store analytics and gets to the heart of engaging with customers at a deeper level.

Humanoid robots also bring multilingual capabilities, something that is harder to provide with human staff, unless they are trained or hired with those capabilities in the first place. The ability to understand and communicate with your customer is necessary to better service



6

their needs, or to resolve any issues that they are having. For stores or customer branches that see a large amount of tourist footfall, where language could become a barrier, a multilingual humanoid robot is likely to come in handy. For example, in Japan, where Japanese is the primary language spoken, robots can transform customer engagement, attracting a wider audience and boosting sales by simply having the robots speak in English as a second language. With Tokyo hosting the Olympics in 2020, many stores, banks, and transportation hubs are expected to use multilingual robots to cater to the diverse range of languages that one might encounter during the games.

2.1.6 THE NOVELTY AND ENTERTAINMENT FACTOR

At a time when customer foot traffic at stores is suffering a decline, due to the rise of online shopping, or due to customers doing most of their research online rather than window shopping, entertainment and novelty could be one way to bring in customers. For example, in the case of Nestlé in Japan, which has started to use humanoid robots at its retail outlets to help with product recommendations and to greet customers, the company has seen a 15% increase in sales since the robot rollout. As a result, Nestlé has planned to deploy more than 1,000 robots across its stores in Japan by March 2017. Similarly, Nissan’s showrooms in Japan saw a 17% increase in customer visits since the company deployed humanoid robots. One of the main reasons for this increase can be attributed to the novelty and entertainment factor, with customers simply visiting because they are curious about robots, especially kids who are more likely to walk into the store after seeing a robot, resulting in the whole family entering the store, raising the probability of a customer sale. In Japan, it is common to see robots perform for the public, singing and dancing at regular intervals, which becomes a crowd attraction. This is also likely to become a viral video phenomenon with passersby and customers capturing these spectacles on the phone and sharing them over social media, providing added marketing benefits.

2.1.7 AUTOMATING MUNDANE AND REPETITIVE TASKS

Robots are very good at taking over tasks that are mundane or repetitive for humans. The extensive adoption of robots in the industrial and manufacturing sector can be attributed to them performing tasks that humans would find monotonous, and who are more likely to cause errors, due to the repetitive nature of the tasks. It has been said that most adult humans can focus on a given task for about 20 minutes, after which they tend to lose concentration, although they can choose to refocus on the same thing, with varying levels of success. Robots can perform the same tasks repeatedly, do not differentiate between easy or difficult tasks, and do not suffer with limitations related to attention span.

Customer engagement roles can also become mundane and repetitive. For example, receptionists need to greet customers with a smile all day long, and in the case of hospitals and clinics, repeat the same instructions to every patient or visitor. In Japan, humanoid robots have been particularly effective in elderly care facilities that house dementia patients. With dementia, instructions have to be repeated multiple times, before the patient understands. Human caregivers are very likely to lose their patience with dementia patients and become frustrated due to the repetitive nature of instructions. Robots are not prone to losing their patience and will continue to repeat instructions as long as is necessary. Dementia patient care is a good use case where robots are ideally suited, however within retail stores, banks, and hospitality, there are certain jobs that are mundane and repetitive, like that of a receptionist, where robots could come to the rescue. Also at QSRs, where the service speed can become hectic and stressful, robots can ensure that customers are greeted with a consistent level of courtesy, and that job efficiency is not compromised due to human error.



7

2.2 CHALLENGES FOR ROBOTS IN CUSTOMER ENGAGEMENT ROLES

2.2.1 CROSSING THE UNCANNY VALLEY

Humanoid robots face a growing challenge around likeability as they start to appear more human-like, which in cognitive science is known as the uncanny valley. This is based on a concept identified in the 1970s by Japanese robotics professor Masahiro Mori and termed as the “uncanny valley” in the book by Jasia Reichardt, Robots: Fact, Fiction, and Prediction. According to the concept, as a robot’s appearance starts to become more human-like, the human response becomes more empathetic and positive, until a point is reached beyond which the human response is that of revulsion, where the level of likeability drops drastically. As the robot starts to become less distinguishable from a human, the emotional response becomes positive again, after which the robot receives the same response as any other human.

Figure 2.3 The Uncanny Valley

(Source: Tractica)

Today, many humanoid robots face the challenge of the uncanny valley, where they are likely to elicit a negative response from humans. It is up to the designers of robots to make sure they do not look too human-like, which puts them in uncanny valley territory. Part of this is due to robot designers putting too much emphasis on the face, with human-like skin, eyes, and ears; but robot movements remaining mechanical and robot-like, which triggers a negative response. Some recent brain magnetic resonance imaging (MRI) studies at the University of California at San Diego have found that the human brain is always looking for biological appearance and biological motion to be congruent, or else it triggers a mismatch, leading to a negative likeability. Conversational commerce is a key characteristic for humanoid robots; however, many of the current humanoid robots have limited voice capabilities, with hardcoded sentences. This could trigger another aspect of the uncanny valley, putting off customers. At the same time, chatbots and voice-based personal assistants like Siri and Alexa are emerging that have sophisticated conversational

Lik

eab

ilit

y

Human-likeness

Uncanny Valley



8

capabilities. This difference in the conversational experience might put off customers, and could end up relegating humanoid robots to simply being an entertainment showpiece, rather than being something useful.

One way to explain the uncanny valley is the following. When the human brain encounters a human, it is conditioned to expect a number of characteristics from body movements, voice, skin texture, and face, all of which need to fall within certain parameters. On the other hand, when the brain sees a robot, it has fewer expectations, and therefore when encountering a humanoid robot, the brain tries to balance these characteristics and expectations, at some point triggering the uncanny valley. Overall, it is safer for robot designers to stay on the left side of the uncanny valley, rather than trying to cross the chasm.

2.2.2 COST OF HUMANOID ROBOTS

While humanoid robots are powerful tools that can enable new customer engagement channels for brick and mortar locations, their cost could be prohibitive, especially for small and medium-sized businesses. The rapid rise of online retailing has impacted many of the smaller and medium category specialists in the market, while the larger retailers like Walmart continue to compete effectively. In the United States, there were more than 5,000 store closures in 2015, with most of them being small and medium-sized retailers. Even some of the larger category specialists like RadioShack have implemented more than 1,000 store closures recently. Most of these retailers have not been able to compete effectively with online retail giants like Amazon, and have failed to deploy any effective in-store customer engagement strategies to counter the decrease in customer traffic.

Humanoid robots used in customer engagement today can cost between $5,000 and $30,000 depending on the features. Most of the advanced characteristics like emotion recognition and conversational commerce are at the higher end of the cost scale. At the lower end are humanoid robots that can perform basic tasks, such as being a generic waiter, carrying food over a guided path in a restaurant. Retailers wanting to avail themselves of the most compelling characteristics find that humanoid robots are beyond their budget. For example, the average salary of a receptionist in the United States is $30,000, which means that a humanoid robot today is two-thirds the cost of a human worker, which does not necessarily tip the balance in the robot’s favor. For a basic sales associate, the average salary is around $20,000, which is in the ballpark of an advanced humanoid robot.

Other vertical markets for humanoid robots, including healthcare, hospitality, financial services, and QSRs, face the same cost challenges, with human staff being equal to or slightly more expensive that humanoid robots. Humanoid robots are just starting out in the market and most retailers have little or no experience of working with robots, so these costs could seem prohibitive and a non-starter. Financing schemes or robot leasing programs could be one way of overcoming the high costs of humanoid robots. Financing is expected to play a big role in the adoption of these robots. The other way of looking at the cost of humanoid robots in customer service roles is to look at the total return on investment (ROI), rather than just the initial cost, and calculate the increase in sales or footfalls, or increase in job efficiencies, balancing that with capital cost. Leasing robots also helps to build a more attractive ROI, as the costs are spread out across a 2 to 3-year period.

2.2.3 BALANCING HUMAN LABOR CONCERNS

One challenge of introducing humanoid robots into the workforce is to balance the concerns and alleviate fears that human counterparts might have about robots. If a robot takes on the role of a product hero, receptionist, counter clerk, or waiter, human staff is likely to take notice and could start to feel insecure about their role and position. The last thing a retailer,



9

hospital, hotel, or restaurant wants is for their human staff to feel insecure, ultimately impacting service and productivity. Unlike industrial robots, which can automate complete shop floors and displace thousands of jobs, customer service robots are more likely to enhance or augment existing ones. The scale of robot usage in customer service scenarios is minimal, and in most cases, human staff can be retrained for handling or maintenance of the robot, or deployed in higher value jobs within the organization.

However, as robots become more adept at learning different skills, and are able to use advanced analytics and emotion recognition techniques, they could end up taking a larger share of human jobs. According to a study by Oxford University, occupations like cashiers, counter clerks, and receptionists are all susceptible to being automated in the future, all having more than a 90% probability of being automated. Overall, the study estimates that 47% of total U.S. employment is at risk, with a large portion of sales and service-related jobs being part of that automation. No protests against robots and automation have occurred to date, such as the Luddite revolution of the early 1800s when English textile workers destroyed machines as a protest against automation. However, any mass-scale displacement of workers by robots or automation, whether in industrial or non-industrial settings, could lead to a wider movement, which might impact the deployment or adoption of humanoid robots, especially in customer service settings.

2.2.4 BACKEND IT SYSTEMS INTEGRATION AND MAINTENANCE

For brick and mortar retailers to take full advantage of humanoid robots, these robots need to be integrated and connected into backend CRM systems and product databases. Retail, hospitality, healthcare, and financial services generally have complex IT backend systems, especially those that deal with multiple locations and branches, which tend to be the hardest to integrate. For example, with humanoid robots being used as product specialists or product heroes, the robot needs to be able to pull up live supply and stock information on the fly and present it to the customer with minimal latency. Any issues with delay in retrieving the information, or getting the incorrect information will impact customer service, likely putting off customers who expect a robot to be state of the art. The issues could be related to connectivity of the robot, connectivity of the store, or simply IT backend downtime. With speech recognition and facial recognition being important value-added characteristics in humanoid robots, it becomes much more critical to ensure that the backend IT systems and machine learning software responsible for these features are correctly configured to avoid downtime.

Robot maintenance goes hand in hand with IT integration and ensuring minimal downtime. For example, in one Japanese pilot for humanoid robots in stores, it was observed that many robots were turned off and sitting idly in the corner, rather than being active and engaging with customers. It turns out that, in multiple stores, children had mishandled these robots, and for some reason, they had not been fixed, and were waiting for a maintenance technician to repair them. The sight of non-working robots in a customer service environment does not help with branding and is likely to leave a negative impression on customers. Downtime of a robot in a brick and mortar location also means that in-store analytics are impacted, if the robot is scheduled to perform customer surveys or if the robot is collecting information about age, gender, and mood of customers. Downtime becomes much more critical during weekends or busy shopping periods like Christmas, when downtime could have a much bigger impact on business. Therefore, it is important to have quick maintenance responses and minimal downtime for robots in customer engagement roles.

In the industrial robot space, robotic suppliers have started to provide remote service agreements where the robots continuously send diagnostic data in order to perform predictive maintenance, so that issues are identified beforehand. Also, in many cases it has



10

been observed that industrial robots can be fixed remotely, without the need for a technician to go on-site. There is no reason why some of these best practices cannot be observed for humanoid robots in customer service environments, helping to reduce downtime and minimizing any adverse impacts on business.



11

SECTION 3

USE CASES AND INDUSTRY VERTICALS

3.1 USE CASES AND INDUSTRY VERTICALS – MARKET OPPORTUNITY MATRIX

The market opportunity for humanoid robots extends across multiple verticals and use cases. The use cases can be seen as horizontal application areas that are best applicable for humanoid robots, and that cut across multiple verticals. Detailed descriptions of the use cases and vertical markets are provided in the following sections. Based on the current pilots and deployments of humanoid robots, Tractica has identified specific areas where humanoid robots possess the biggest market opportunities. Table 3.1 shows a matrix of use cases and industry verticals, delineating market opportunities where humanoid robots seem credible for usage. Some of these areas are already being utilized in commercial deployments, while some are expected to be deployed in the future, having carried out successful pilots.

Table 3.1 Use Cases and Industry Verticals – Market Opportunity Matrix

Use Cases Retail Travel and Hospitality

Financial Services

Quick Service Restaurants Healthcare

Receptionist X X X X

Product Hero X X

E-Commerce X X

Customer Surveys X X X X X

Entertainment X

Counter Clerk X X X

Waiter X (Source: Tractica)

The retail vertical presents the largest market opportunity; employing humanoid robots for almost all use cases that have been identified. Financial services is the other big opportunity area, with humanoid robots taking on multiple roles within the banking sector. Both retail and financial services see the most humanoid robot deployments, with a general acceptance of robots, and generally a good understanding about how they could bring value. Hospitality and healthcare have lower opportunity based on the use cases that have been identified. For the most part, use cases, such as product hero and entertainment, do not apply in the hospitality or healthcare verticals, and therefore have been left out of our analysis. QSRs are an interesting vertical that has a lot of promise and potential, although robot adoption has been limited so far.

In terms of use cases, the most popular application is customer surveys, which can be applied in almost any vertical. The second most popular use case is that of a receptionist, which again has application across multiple verticals. Counter clerks are generally found in hotels, banks, and retail, and therefore, have medium applicability. Counter clerks are generally considered to be straightforward roles that humanoid robots can perform, and a number of pilots in hotels and travel hubs have taken place. Similarly, e-commerce and



12

product hero use cases do not necessarily apply across verticals and can be considered much more specialized with businesses seeing a lot of benefit, but being hesitant initially due to the complexity of the implementation and backend integration required. Entertainment is a popular use case for humanoid robots, with mostly retailers using robots to sing and dance and entertain customers. The waiter use case is a specific one, which is limited to the QSR category, with a few restaurants in China and Japan having rolled them out, although their capabilities have been very limited.

3.2 USE CASES

3.2.1 RECEPTIONIST

The primary job of a receptionist in a customer service setting is that of greeting visitors and directing them to the right personnel or locations, also answering basic questions about the services on offer. Apart from the initial greeting and welcoming of the customer:

A receptionist in a retail setting would direct you to a product aisle.

In a hospitality setting, they would help with check-in or check-out formalities.

In a financial services setting, they would direct you to the correct counter or personnel.

In healthcare settings like a doctor’s clinic, they would register your arrival for an upcoming appointment.

Efficient receptionists can help reduce wait times, and ensure that customers are directed to the right locations. For the most part, receptionists have a defined set of tasks, which at some level can become repetitive, mundane, and sometimes stressful. For any service-oriented vertical, the receptionist is the first point of contact for the customer, and therefore, the receptionist’s greeting, manner, and tone of welcoming the customer become very important. An unpleasant or stressed receptionist is likely to produce unhappy customers and can have a negative impact overall on the quality of service provided.

Humanoid robots are ideal for receptionist roles, as they are good at performing mundane and repetitive tasks, while being highly effective at simple tasks, such as greeting the customer, and directing them onward. Receptionist robots are already in use in Japan at hotels, mobile phone stores, and car showrooms; in Belgium, at a hospital; and in the United States, at hotels.



13

Figure 3.1 Humanoid Robot – Receptionist Use Case

(Source: JapanTimes, Toshiba)

3.2.2 PRODUCT HERO

The role of a product hero requires being an expert on the range of products on offer, which also requires them to make product recommendations. It usually takes a long time for humans to learn the features of the various products and become a true product expert. However, for a humanoid robot, this process can be as simple as an application programming interface (API) call to a product database, or a product recommendation algorithm running in the background, which makes them a product hero overnight. At the same time, human product heroes can stand out against their robot counterparts with intuition and years of experience that they gather dealing with product features and issues. Nevertheless, just like Amazon has evolved into a much more powerful recommendation engine over the years, empowered with customer feedback and ratings, it can be argued that Amazon has become the ultimate product hero. It is not too hard to see a humanoid robot learning about and mastering knowledge of a product category or a set of products within a retail store, including historic customer feedback. Today, with customers already used to performing Google and Amazon searches for products, using text and increasingly using voice, humanoid robots are well positioned to take up the role of a product hero within a store, and help customers make the right purchasing decisions.

3.2.3 E-COMMERCE

Recently, there has been an increase in self-service checkout kiosks, which can be found at grocery chains, pharmacies, and movie theatres. This encourages shoppers to complete purchase transactions on their own, avoiding long lines and speeding up their shopping



14

experience. Consumers are also getting used to a personalized shopping experience, especially for online e-commerce, which is customized to their needs, based on their browsing habits and past purchases. In order to enable such a seamless shopping experience, both online and in-store, some high-end fashion retailers like Burberry have equipped their sales staff with tablets that help them provide customers with a more personalized shopping experience or customized promotions. According to a 2015 eMarketer survey, 53% of shoppers in the United States bought more from retailers that suggested products based on their browsing and buying history. Humanoid robots can take this one step further by adding in conversational commerce as an element to the personalized shopping experience in-store. Using speech and natural conversation, the robot can verify a customer’s identity and enable a customized shopping experience. Just like an online shopping experience, the customer is able to pay using their preferred payment mechanism, as the robot has been able to identify the customer to create a seamless and personalized shopping experience in-store.

MasterCard has piloted a similar e-commerce experience using SoftBank Robotics’ Pepper robot and partnering with Pizza Hut in Singapore. In the pilot, customers were identified using the MasterPass mobile app, which was integrated with the Pepper platform. Once identified, Pepper could offer the customer their preferred pizza options, and use their MasterCard information to pay for and complete the transaction.

Figure 3.2 MasterCard E-Commerce Use Case for Humanoid Robots

(Source: MasterCard)

3.2.4 CUSTOMER SURVEYS

In-store customer surveys are a good way to capture quick and immediate feedback about customer service, products, store layouts, or other aspects of the customer experience. There are pros and cons of doing in-store customer surveys. In terms of the pros, in-store



15

surveys can make customers feel valued and provide in-the-moment feedback from customers as they experience it. The cons include a small sample size, with results being biased when customers feel pressured, with the added risk of putting off survey-weary customers. Humanoid robots with touchscreens can come in handy for customer completing in-store surveys. Their ability to communicate through voice and engage customers while completing a quick survey can lead to increased participation in surveys due to their uniqueness and entertainment factor. Some humanoid robots like SoftBank’s Pepper have the ability to recognize facial emotions, which can be used to recognize unhappy customers and to understand if there were any particular shortcomings in the store experience. Humanoid robots can bring added dimensions to in-store customer surveys, which are not necessarily available with human-led in-store surveys.

Another element of surveys could be to perform A/B testing within the store, similar to A/B testing done on mobile apps or on websites. By offering customers different options in terms of marketing messages, store layout, product placement, or other elements, such as lighting, brick and mortar can receive instant feedback on A/B testing. This is a powerful tool that enables brick and mortar stores to compete with their online retailer counterparts.

3.2.5 ENTERTAINMENT

Today, robots have the ability to entertain customers by dancing, singing, and putting on a spectacle, which can attract customers into the store. Robots that have been used to entertain customers in retail environments have been found to be particularly popular with kids, who bring in their parents and family members. Although entertainment is a use case that is largely limited to retail environments, it does not really apply beyond retail, in other verticals like healthcare, hospitality, or financial services, which do not particularly need an entertainment quotient, and are regarded as more serious venues.

3.2.6 COUNTER CLERK

Counter clerks are usually found at banks, providing services such as check cashing and deposits, cash services, checking identification, or in some cases, selling financial services. They are also required to provide general information to customers about the bank, staff, and services, or in some cases, resolve basic problems that customers are facing. Counter clerks can also be found at hotels and retail stores, helping with general queries or completing financial transactions. The role of a counter clerk is relatively more complex compared to other use cases, and requires careful designing of a UI as the counter clerk provides a critical service, which requires extensive knowledge of job procedures, and the ability to communicate over a broad range of questions and scenarios. Unlike being a product hero or a receptionist, with a fairly limited range of tasks that the robot needs to learn and perform, a counter clerk could face difficult scenarios like dealing with a disgruntled customer or someone with unlawful intentions.

3.2.7 WAITER

Robotic waiters have already made their debut in China and Japan. For the most part, they have been used as a customer attraction and marketing tool more than anything else. In a few instances, such as in China’s Guangzhou province, some of the restaurants are known to have fired their robot waiters for incompetence and lack of reliability. These cases highlight the downsides of placing robots in an environment without studying the use case thoroughly, and using them as showpieces, rather than as tools for improving customer service and growing their business.



16

3.3 INDUSTRY VERTICALS

3.3.1 RETAIL

Robots have a big role to play within the retail industry and are seen as a good fit in a segment that is experiencing rapid change. The retail industry is seeing a major battle between brick and mortar retailers and their online counterparts, as online retailers like Amazon have led to many category specialist retailers, such as book stores and electronics stores, closing and entering bankruptcy. While retail giants like Walmart continue to dominate and compete effectively with online retailers, the smaller and medium-sized retailers and category specialists are paying the price. More customers perform research online before they buy, resulting in more than a 50% drop in customer traffic in the United States between the holiday seasons of 2010 and 2013, according to data from ShopperTrak.

Robots bring new energy to the retail segment, helping to revive customer traffic where there is a declining trend, while adding new dimensions to retailing like performing smart customer surveys, using conversational commerce as an efficient product hero, or simply being an entertainer. Within the retail industry vertical, humanoid robots can perform the majority of the use cases, including receptionist, product hero, customer surveys, e-commerce, counter clerk, and entertainment; therefore, retail presents the largest market opportunity.

3.3.2 TRAVEL AND HOSPITALITY

Travel and hospitality includes hotels, cruise lines, train stations, airports, and travel agents. In the hospitality space, customers are looking for their hotel receptionist or concierge to give them information about the local area, help with any special needs, and achieve a happy and comfortable stay. There is a surprising amount of openness to and expectation from robots in hospitality, with a recent survey by travel specialist Travelzoo finding that 80% of the 6,000 respondents believe that robots will feature in the travel and hospitality industry by 2020. In addition, three-quarters of the respondents felt that robots would lead to improved travel experiences. Hotel chains in the United States like Hilton and Marriott have conducted pilots with humanoid robots as the concierge or receptionist. The Henn-na in Japan is fully equipped with humanoid robots, including the receptionist and concierge, as well as robot butlers. Although the Henn-na does have humans monitoring and assisting customers in the background, the concept of a hotel run by robots is intriguing, and provides a glimpse of how robots might be able to play a complementary role in hotels, rather than fully replacing humans.



17

Figure 3.3 Henn-na Hotel with Robot Receptionists

(Source: Henn-na Hotel)

Personalized and customized service offerings are also making their way into hospitality. Hotel chains like Ritz-Carlton have deployed a guest preference tracking system called Mystique, which captures a guest’s preferences during their stay, with the goal of matching those preferences at the next visit, wherever that might be, across its global chain of properties. Currently, Ritz-Carlton hotel staff captures these preferences manually, but with a humanoid robot, these could be captured automatically using speech recognition or while performing a customer survey. It is safe to say that most hotel visitors would feel more comfortable conversing with a human, as it provides a sense of comfort and familiarity, especially when they are in a new city or surroundings. However, with advances in AI around emotion recognition, speech recognition, and machine reasoning, combined with careful design considerations for humanoid robots, it is very likely that robots will increasingly be seen as powerful tools for enhancing and differentiating hospitality services, complementing and assisting their human colleagues.

Humanoid robots are also being used on cruise ships, such as the Costa AIDA cruise line, where they can speak in multiple languages and perform surveys. Robots have also been trialed at travel agencies, train stations, and airports, generally performing the role of a receptionist or counter clerk, helping customers with basic instructions, directions, or in some cases, helping with planning a holiday trip.

3.3.3 FINANCIAL SERVICES

There is a growing adoption of automation across the banking and financial services industry. AI financial advisors, also known as robot advisors, are starting to make their way into the financial services market with large financial institutions like Morgan Stanley, Blackrock, and Fidelity acquiring or partnering with robot advisor startups. The key driver includes cost reduction, with the cost savings being passed on to customers via lower fees. In a study conducted by technology consulting firm Cognizant, more than 55% of the 153 banks and financial institutions surveyed in 2015 said that, within the next 3 to 5 years, their front-office and customer-facing functions will see cost savings through automation. In



18

addition, the survey also showed that the increasing use of analytics has led to 45% of the banks seeing a revenue increase of 10% or more. While these robot advisors are not physical humanoid robots, they do provide a glimpse of how automation is taking root in the financial services sector.

Humanoid robots can bring cost savings and analytics to front office and customer-facing functions in banks. Mizuho Bank in Japan has been using more than two dozen Pepper robots since 2015 to sell insurance products at its branches. This has led to increased customer visits and a reduction in wait times across their locations. Mitsubishi UFJ, another financial institution in Japan, hopes to deploy humanoid robots across its branches to speak multiple languages and provide 24-hour banking. The robot learns through each customer interaction, with the ability to match and identify customers as soon as they walk in, providing more personalized service. IBM’s AI platform Watson is also being used to provide wealth advisory services. Watson, combined with a humanoid robot, is a powerful tool that enhances a face-to-face customer interaction with advanced analytics, facial and emotion recognition, and advanced speech processing. There is also the future potential of integrating mobile app behavior with robotic systems, where a humanoid robot knows a customer’s historic preferences and product interests in order to personalize its greeting when the customer enters a branch.

3.3.4 QUICK SERVICE RESTAURANTS

QSRs like McDonald’s have started to roll out self-service kiosks across many of their locations in the United States and Europe. Self-service kiosks can help customers customize their meals, catering to a growing population of millennials already used to touchscreens and online ordering, as well as improving service efficiency and reducing waiting times. As part of its Experience the Future initiative, McDonald’s is aiming to use technology to better serve its customers and improve sales. Other QSR chains like Wendy’s and Panera Bread in the United States are also installing kiosks across their branches in pilots, which are seeing positive results. One of the big drivers cited for the rise of kiosks in QSRs is the critical need to keep lines short. According to a survey performed by Tillster, only 36% of customers will wait in line if there are more than five people ahead of them, resulting in lost customers, with 61% using a kiosk if the line was four people or more.

Humanoid robots offer all the advantages of self-service kiosks, from touchscreen ordering to line reductions, with the added benefit of using conversational commerce. For customers that prefer to speak to someone versus tapping on a screen, humanoid robots can help attract demographics beyond millennials. Pilots have already shown humanoid robots driving 3 times more interactions than self-service kiosks. As shown in the case of a recent pilot run by MasterCard in Singapore, conversational commerce combined with e-commerce and personalized preferences can be powerful tools for QSRs to differentiate their service, increase sales, and have happy customers spreading the word through review apps like Yelp.

3.3.5 HEALTHCARE

Healthcare staff is required to be courteous, empathetic, and sensitive to patients and visitors, possibly more so than any other customer service vertical. There is a higher emotional quotient that is required from healthcare staff, when it comes to interacting and servicing patients and visitors. While humans are best placed to offer these qualities and can be trained around customer service in healthcare environments, humanoid robots today can provide empathetic customer service, and more importantly, do it repeatedly on a 24/7 basis without getting tired or stressed on the job. Within a hospital, clinic, or healthcare facility, the most obvious role for humanoid robots is as a receptionist, guiding and assisting customers,



19

registering them for appointments, or providing basic directions in and around the facility. In a couple of hospitals in Belgium, humanoid robots are being used in pediatric and geriatric department reception areas, while also being able to accompany patients to the departments for which they are searching.

A wider use of humanoid robots in healthcare has been in elderly care facilities and retirement homes, especially in Japan. Robots there have been performing other roles like serving as exercise and mind coaches, helping the elderly perform exercises and brain-teaser activities. Humanoid robots are particularly helpful with dementia patients because they can very easily repeat instructions without becoming tired. Rapidly aging populations across Japan, Europe, the United States, and China means that, by 2030, more than one in four people in these regions will be over the age of 65. This is likely to put significant stress on the elderly care and healthcare systems in these countries, with humanoid robots being one of the likely solutions.

Humanoid robots can recognize emotions, converse like a human, and show perpetual empathy toward patients without becoming tired or stressed, making them strong candidates for customer engagement activities within the healthcare space. They have a particular application in dealing with the elderly and with children within healthcare, as these demographics are more likely to accept and embrace a robot, and follow instructions, rather than pose complicated medical questions.



20

SECTION 4

BUSINESS CONSIDERATIONS AND STRATEGIC RECOMMENDATIONS

4.1 FIVE KEY BUSINESS CONSIDERATIONS FOR HUMANOID ROBOTS

There are five key business considerations for successfully executing on a strategy that incorporates humanoid robots. They are:

Building a business case

Identifying the best UI/UX to meet objectives

Off the shelf vs customized development

Cloud vs on-site implementation

Impact on employee morale and company culture

Each of these business considerations is described further in in the following sub-sections.

Figure 4.1 Five Key Business Considerations for Humanoid Robots

(Source: Tractica)



21

4.1.1 BUILDING A BUSINESS CASE

In order to truly understand the business implications of humanoid robots, the ROI needs to be estimated. The investment includes equipment cost, software costs, and maintenance costs. High-end humanoid robots cost as much $20,000, making it important to take into account financing and leasing programs. Spreading the costs of the robot across 2 to 3 years would help drive a much quicker ROI.

The returns include additional revenue generated as a result of the robot, which help in increasing the bottom line for a company deploying humanoid robots. On average, humanoid robot pilots in retail environments generate between a 10% and 20% increase in customer visits, with close to 80% of customers feeling happy and satisfied with their experience in-store. An increase in visits and happy customers directly lead to increased sales and improved chances of the customer returning. These are encouraging metrics, which can be used as a benchmark to estimate ROI figures for humanoid robots. The returns will, of course, vary by vertical, with areas such as QSRs, healthcare, hospitality, and financial services focusing more on productivity gains, reduced wait times, and improved customer satisfaction, which are harder to calculate. In some instances, humanoid robots provide e-commerce capabilities, enabling businesses to directly measure the number of transactions processed on the robot, which can also be used to estimate returns. Humanoid robots bring a number of in-store analytics capabilities from customer surveys to capturing the mood of a customer, which can help with improved store layouts and product placement. Improved data analytics is ultimately beneficial to any brick and mortar business, improving operational efficiency and improving sales. Another metric that could be included in the returns is the cost savings from deploying additional in-store analytics infrastructure, such as Wi-Fi tracking, Bluetooth, RFID, or other solutions, which can all be replaced by a robot. Cost savings related to the tracking of customers, and operational efficiency gains can also have a direct impact on the bottom line, helping to improve the ROI case for humanoid robots.

4.1.2 IDENTIFYING THE BEST UI/UX TO MEET OBJECTIVES

Humanoid robots should be seen as a business tool that can be shaped and customized to meet underlying business objectives. Businesses need to identify their objective first, or state the problem that they are trying to solve. The UI/UX will determine how a particular objective or set of objectives will be met. Humanoid robots bring a number of UI/UX tools, including touchscreens, barcode scanners, touch sensors in the head or hands, and voice, which is one of the most powerful features. Regional and cultural nuances are also important to note when designing customer interactions for the robot. For example, in Japan, people are generally more used to seeing and interacting with robots, so designers can be a bit more creative in using all of the various UI/UX tools, from touch to voice. However, in Europe and the United States, robots are still a rare cultural phenomenon, especially on the streets and in shops, which means that designers are better off being conservative in their UI/UX considerations. For newer markets, rather than having voice as the primary tool for interaction, touchscreen interaction might be a better way of introducing people to robots, with minimal voice interaction.

Humanoid robots with touchscreen interfaces are very useful; most users today are comfortable using touchscreens on their smartphones and tablets. For example, in one case study, an IT system provider for travel agencies piloted the use of humanoid robots in a travel agency by developing a touchscreen game on the humanoid robot. Visitors are shown multiple images on the robot touchscreen, asking them to choose their favorite images, after which the robot makes recommendations for trips and destinations. While there is a voice element, in terms of greeting and instructing customers, the touchscreen becomes a familiar and powerful way of interacting with customers, delivering a unique and memorable



22

customer experience.

4.1.3 OFF-THE-SHELF VERSUS CUSTOMIZED APPLICATIONS

Just like smartphones, humanoid robots are another platform, with robot companies providing numerous built-in applications, and possibly an app store or skills database, which developers and businesses can download, similar to the app store model. SoftBank Robotics is one of the few robotics companies to have deployed an app store model, but Tractica expects this to become standard in the near future as the humanoid robot market takes off. The decision whether to choose off-the-shelf applications versus customized applications will become easier, to some extent, with an app store model. However, today’s absence of such a model means that businesses need to customize their robots.

Currently, most humanoid robots also come with a higher degree of customizability than smartphones. Humanoid robot platforms like SoftBank’s Pepper allow developers to build applications using a variety of software languages and frameworks, including Python, JavaScript, C++, and Android SDK. Pepper comes with some basic built-in applications like a basic level of facial recognition, basic voice recognition, and conversational abilities. Other humanoid robots like the Furo-S from Future Robotics in Korea comes with robot dancing, basic voice recognition, following mode, face tracking, robot avatar, and four different language translations. The Furo-S service robot also has Adobe Photoshop and Adobe Illustrator, which come installed as standard. Toshiba’s Junko Chihira humanoid robot comes installed with language translation for Chinese, English, and Japanese.

There will always be some level of customization required, especially in terms of the front-end UI, and in terms of integrating the robot with backend customer or product databases, but key skillsets like facial recognition and voice recognition need to be enhanced and customized. This customization can become easier with APIs to other AI platforms like IBM Watson or Amazon Alexa. Therefore, the ability to integrate with third-party AI engines for voice and facial recognition is a key consideration that needs to be taken into account. Over time, voice and facial recognition will become commoditized; therefore, businesses need to ensure that their humanoid robot is open, rather than operating in a closed ecosystem.

4.1.4 CLOUD VERSUS ON-SITE SOFTWARE IMPLEMENTATION

There are a number of factors to consider when deciding between the use of the cloud versus on-site implementation for humanoid robot software in brick and mortar locations. If the robot is using a sophisticated conversational engine that helps with speech recognition and providing intelligent human-like responses, it is most likely that a cloud implementation would be necessary. This is because state-of-the-art conversational engines like IBM Watson, Google Now, Apple Siri, or Amazon Alexa are cloud-based software platforms, which rely on gathering data from multiple nodes, and are constantly training and advancing their algorithms to reduce error rates and improve the overall quality of experience. For businesses that deploy a limited, or fixed conversational system where the questions and answers are hard coded, an on-site implementation would suffice. Although the capabilities with a hard-coded system would be greatly reduced, and could lead to customer dissatisfaction as customers get used to a higher benchmark from using personal assistants and chatbots on their smartphones or at home. Facial recognition or emotion recognition would follow the same reasoning, with sophisticated image recognition engines being cloud-based, and on-site implementations having limited capabilities.

On the other hand, network connectivity and latency are important factors to take into account when deploying on the cloud versus on-site. If a particular branch or store suffers from unreliable or poor connectivity, then on-site implementation is the safer option, with



23

reliability being more important than sophisticated facial and voice capabilities. Security and ensuring customer data privacy is another consideration when deciding on a cloud versus on-site implementation. Humanoid robots are capable of capturing age, gender, images, and other personal customer data, such as emotions, so businesses need to ensure that this data is stored securely on-site, and that any additional data that is being accessed through backend customer databases is accessed using state-of-the-art encryption techniques.

4.1.5 IMPACT ON EMPLOYEE MORALE AND COMPANY CULTURE

Businesses that are planning to deploy humanoid robots for customer engagement at their physical stores and branches should ensure that human staff is trained and briefed about the robots, and that there has been enough time devoted to allaying and fears or concerns that the staff might have about the robots. Pilots are a good way of testing the impact of robots on the in-store staff to identify any issues beforehand. For the most part, existing deployments of humanoid robots in customer engagement applications have proceeded without any troubles. In some cases, such as hospitality applications, human staff at hotels have been known to form an affinity toward robots, treating them as colleagues, and being concerned when robots malfunction. Overall, the reaction to robots has been positive, but at the same time, businesses need to be vigilant about any issues around employee morale and company culture, before and after the release of humanoid robots. Focusing on employee education and being clear about future plans for robots within a business are some of the best ways to tackle any fears or concerns that staff might have around job security and their role within the company. The mainstream media is increasingly focusing on the rise of robots and how that relates to the future of work environments. Employing a robot and successfully integrating it into the company without impacting employee morale should be one of the top priorities for businesses.

4.2 CONCLUSION

Recent technology advances in robots like emotion recognition, facial recognition, and speech recognition have made it possible for robots to have more human-like capabilities. Humanoid robots are now capable of taking on face-to-face customer engagement applications across verticals like retail, travel and hospitality, financial services, QSRs, and healthcare. The robots can also work horizontally across multiple use cases, including being a receptionist, counter clerk, product hero, entertainer, or waiter, performing customer surveys, and helping with e-commerce transactions. The biggest near-term vertical market opportunity remains retail, followed by financial services. Also, customer surveys and receptionist roles are expected to see the largest adoption in terms of use cases.

The past decade has seen massive shifts in customer engagement strategies, with the rise of online retailing, social media, and mobile devices. Brick and mortar businesses have largely failed to take advantage of this shift in the customer engagement innovation cycle. However, with the recent increase of self-service kiosks, conversational commerce, and chatbots, there is an opportunity for humanoid robots to merge the online and the physical, brick and mortar worlds. Humanoid robots can bring new dimensions to in-store analytics and help businesses innovate around customer engagement, helping them automate mundane and repetitive tasks. Overall, it is important for businesses that are considering humanoid robots to build a proper ROI case and identify the appropriate UI/UX and IT implementation to meet their business objectives. Finally, customer engagement robots should not be seen as a replacement, but as an augmentation of human staff, ultimately becoming a tool that helps brick and mortar businesses compete effectively with pure online businesses in terms of customer engagement.



24

SECTION 5

ACRONYM AND ABBREVIATION LIST

Application Programming Interface ........................................................................................................... API

Artificial Intelligence ..................................................................................................................................... AI

Magnetic Resonance Imaging .................................................................................................................. MRI

Natural Language Processing .................................................................................................................. NLP

Quick Service Restaurant ....................................................................................................................... QSR

Radio Frequency Identification ............................................................................................................... RFID

Return on Investment ................................................................................................................................ ROI

User Experience ......................................................................................................................................... UX

User Interface ............................................................................................................................................... UI



25

SECTION 6

TABLE OF CONTENTS

SECTION 1 ...................................................................................................................................................... 1 Executive Summary .................................................................................................................................... 1 SECTION 2 ...................................................................................................................................................... 2 Benefits and Challenges ............................................................................................................................ 2

2.1 Market Drivers for Robots in Customer Engagement Roles ......................................................... 2 2.1.1 Robots Are a Natural Evolution of Customer Engagement Channels .................................... 2 2.1.2 Experiences Becoming The Product ....................................................................................... 3 2.1.3 Bridging The Gap Between Online Customer Experience & Brick and Mortar ....................... 4 2.1.4 Adding New Dimensions to In-Store Analytics ........................................................................ 5 2.1.5 Emotion Recognition and Multilingual Capabilities ................................................................. 5 2.1.6 The Novelty and Entertainment Factor ................................................................................... 6 2.1.7 Automating Mundane and Repetitive Tasks ........................................................................... 6

2.2 Challenges for Robots in Customer Engagement Roles .............................................................. 7 2.2.1 Crossing the Uncanny Valley .................................................................................................. 7 2.2.2 Cost of Humanoid Robots ....................................................................................................... 8 2.2.3 Balancing Human Labor Concerns ......................................................................................... 8 2.2.4 Backend IT Systems Integration and Maintenance ................................................................. 9

SECTION 3 .................................................................................................................................................... 11 Use Cases and Industry Verticals ........................................................................................................... 11

3.1 Use Cases and Industry Verticals – Market Opportunity Matrix ................................................. 11 3.2 Use Cases ................................................................................................................................... 12

3.2.1 Receptionist ........................................................................................................................... 12 3.2.2 Product Hero ......................................................................................................................... 13 3.2.3 E-Commerce ......................................................................................................................... 13 3.2.4 Customer Surveys ................................................................................................................. 14 3.2.5 Entertainment ........................................................................................................................ 15 3.2.6 Counter Clerk ........................................................................................................................ 15 3.2.7 Waiter .................................................................................................................................... 15

3.3 Industry Verticals ......................................................................................................................... 16 3.3.1 Retail ..................................................................................................................................... 16 3.3.2 Travel and Hospitality ............................................................................................................ 16 3.3.3 Financial Services ................................................................................................................. 17 3.3.4 Quick Service Restaurants .................................................................................................... 18 3.3.5 Healthcare ............................................................................................................................. 18

SECTION 4 .................................................................................................................................................... 20 Business Considerations and Strategic Recommendations ................................................................ 20

4.1 Five Key Business Considerations For Humanoid Robots ......................................................... 20 4.1.1 Building a Business Case ...................................................................................................... 21 4.1.2 Identifying the Best UI/UX to Meet Objectives ...................................................................... 21 4.1.3 Off-the-Shelf versus Customized Applications ...................................................................... 22 4.1.4 Cloud versus On-Site Software Implementation ................................................................... 22 4.1.5 Impact on Employee Morale and Company Culture ............................................................. 23

4.2 Conclusion ................................................................................................................................... 23 SECTION 5 .................................................................................................................................................... 24 Acronym and Abbreviation List ............................................................................................................... 24 SECTION 6 .................................................................................................................................................... 25 Table of Contents ...................................................................................................................................... 25



26

SECTION 7 .................................................................................................................................................... 27 Table of Charts and Figures..................................................................................................................... 27 Sources and Methodology ....................................................................................................................... 28 Notes .......................................................................................................................................................... 29



27

SECTION 7

TABLE OF CHARTS AND FIGURES

Chart 7.1 Tractica Research Methodology ............................................................................................ 29

Figure 2.1 The Customer Engagement Evolutionary Cycle ..................................................................... 3 Figure 2.2 Bridging the Physical and Online Worlds ................................................................................ 4 Figure 2.3 The Uncanny Valley ................................................................................................................ 7 Figure 3.1 Humanoid Robot – Receptionist Use Case ........................................................................... 13 Figure 3.2 MasterCard E-Commerce Use Case for Humanoid Robots ................................................. 14 Figure 3.3 Henn-na Hotel with Robot Receptionists .............................................................................. 17 Figure 4.1 Five Key Business Considerations for Humanoid Robots .................................................... 20

Table 3.1 Use Cases and Industry Verticals – Market Opportunity Matrix .......................................... 11



28

SOURCES AND METHODOLOGY

Tractica is an independent market research firm that provides industry participants and stakeholders with an objective, unbiased view of market dynamics and business opportunities within its coverage areas. The firm’s industry analysts are dedicated to presenting clear and actionable analysis to support business planning initiatives and go-to-market strategies, utilizing rigorous market research methodologies and without regard for technology hype or special interests including Tractica’s own client relationships. Within its market analysis, Tractica strives to offer conclusions and recommendations that reflect the most likely path of industry development, even when those views may be contrarian.

The basis of Tractica’s analysis is primary research collected from a variety of sources including industry interviews, vendor briefings, product demonstrations, and quantitative and qualitative market research focused on consumer and business end-users. Industry analysts conduct interviews with representative groups of executives, technology practitioners, sales and marketing professionals, industry association personnel, government representatives, investors, consultants, and other industry stakeholders. Analysts are diligent in pursuing interviews with representatives from every part of the value chain in an effort to gain a comprehensive view of current market activity and future plans. Within the firm’s surveys and focus groups, respondent samples are carefully selected to ensure that they provide the most accurate possible view of demand dynamics within consumer and business markets, utilizing balanced and representative samples where appropriate and careful screening and qualification criteria in cases where the research topic requires a more targeted group of respondents.

Tractica’s primary research is supplemented by the review and analysis of all secondary information available on the topic being studied, including company news and financial information, technology specifications, product attributes, government and economic data, industry reports and databases from third-party sources, case studies, and reference customers. As applicable, all secondary research sources are appropriately cited within the firm’s publications.

All of Tractica’s research reports and other publications are carefully reviewed and scrutinized by the firm’s senior management team in an effort to ensure that research methodology is sound, all information provided is accurate, analyst assumptions are carefully documented, and conclusions are well-supported by facts. Tractica is highly responsive to feedback from industry participants and, in the event errors in the firm’s research are identified and verified, such errors are corrected promptly.



29

Chart 7.1 Tractica Research Methodology

(Source: Tractica)

NOTES

CAGR refers to compound annual growth rate, using the formula:

CAGR = (End Year Value ÷ Start Year Value)(1/steps) – 1.

CAGRs presented in the tables are for the entire timeframe in the title. Where data for fewer years are given, the CAGR is for the range presented. Where relevant, CAGRs for shorter timeframes may be given as well.

Figures are based on the best estimates available at the time of calculation. Annual revenues, shipments, and sales are based on end-of-year figures unless otherwise noted. All values are expressed in year 2016 U.S. dollars unless otherwise noted. Percentages may not add up to 100 due to rounding.

PRIMARY

RESEARCH

SECONDARY

RESEARCH

SUPPLY SIDE DEMAND SIDE

Industry Interviews

Vendor Briefings

Product Evaluations

End-User Surveys

End-User Focus Groups

Company News & Financials

Technology & Product Specs

Government & Economic Data

Case Studies

Reference Customers

QUALITATIVE

ANALYSIS

QUANTITATIVE

ANALYSIS

Company Analysis

Business Models

Competitive Landscape

Technology Assessment

Applications & Use Cases

MarketSizing

Market Segmentation

Market Forecasts

Market Share Analysis

Scenario Analysis

MARKET RESEARCH

MARKET ANALYSIS



30

Published 4Q 2016

© 2016 Tractica LLC

1111 Pearl Street, Suite 201

Boulder, CO 80302 USA

Tel: +1.303.248.3000

Email: [email protected]

www.tractica.com

This publication is provided by Tractica LLC (“Tractica”). This publication may be used only as expressly permitted by license from Tractica and may not otherwise be reproduced, recorded, photocopied, distributed, displayed, modified, extracted, accessed or used without the express written permission of Tractica. Notwithstanding the foregoing, Tractica makes no claim to any Government data and other data obtained from public sources found in this publication (whether or not the owners of such data are noted in this publication). If you do not have a license from Tractica covering this publication, please refrain from accessing or using this publication. Please contact Tractica to obtain a license to this publication.

utilizing humanoid robots for customer engagement · utilizing humanoid robots for customer...

Documents