The News

Today Salesforce announced the next release of its Service Cloud. It brings together more Einstein AI as part of the Service Cloud and adds Quip to it. This enables more agent empowerment and efficient work. In order to augment the tools with the necessary knowledge and soft skills, Salesforce also just launched Trailblazers for the Future, a program that is targeted towards increasing the soft skills of service managers and service agents. Einstein now is delivering reply suggestions as well as article suggestions to inquiries that the service representative can easily use to reply to questions. At the same time Einstein suggests so called next best actions that are designed to help increase satisfaction and unearth cross- and upsell opportunities. Additionally, Einstein now optimizes case routing leveraging machine-learning processes on the inquiry to find the ideal queue for processing it. Additionally, Salesforce embedded the collaboration tool Quip into the Service Cloud to increase productivity and to increase service agents’ access to knowledge. The press release is here but for your convenience you can read it below.

The Press Release

Salesforce Empowers Service Agents with Einstein AI and Quip for Service  Service Cloud expands Einstein AI portfolio with new intelligent recommendation and routing capabilities so agents can spend more time where it matters most — building customer relationships and solving complex problems New Quip for Service boosts agent productivity with incident swarming and cross-team collaboration available directly in the agent console   SAN FRANCISCO—March 19, 2019—Salesforce , the global leader in CRM, today announced new artificial intelligence and productivity solutions that empower customer service agents to focus more of their time on the human side of service — tasks that require social intelligence, critical thinking and creative problem solving skills. As customer service rapidly evolves from a reactive back-office function to one that impacts every stage of the customer’s journey, service agents are continually asked to do more. With new AI-powered recommendations, automated routing, and embedded productivity and collaboration capabilities, Salesforce is reimagining the agent experience to meet the needs of today’s connected customer.   From Case-Centric to Customer-Centric: The Service Agent’s Role is Evolving Service agents are on the front lines of all customer interactions, from the moment a consumer begins researching products all the way through to post-sale support. And while agents have historically not had the necessary resources to deliver world-class customer experiences, that is now changing. According to the third edition of the Salesforce State of Service report released today, 82 percent of service leaders acknowledge their company’s customer service function must transform to stay competitive, and 77 percent of service organizations plan to make significant investments in agent training this year. This is causing a dramatic shift in the service agent’s role, with 71 percent saying their jobs are more strategic than just two years ago and 75 percent saying their organizations now view them as brand ambassadors by their companies.   Making Agents Smarter with Einstein for Service Over the last three years Salesforce has embedded new AI capabilities into Service Cloud — such as Einstein Bots and Einstein Case Classification — to make the agent console more intelligent and the agent’s job easier. Building on this, the AI innovations being announced today are:

• Einstein Reply Recommendations uses natural language processing to instantly suggest the best responses to agents over chat and messaging, so they can save time and improve the quality of replies to customer inquiries. And using a machine learning model that learns what has worked over time, Einstein Article Recommendations automatically recommends the best knowledge articles to agents, giving them the information they need to solve cases quickly.
• Einstein Next Best Action leverages business rules and predictive intelligence to suggest the best course of action at the point of maximum impact during agent-customer interactions, helping to increase customer satisfaction and uncover cross-sell opportunities.
• Einstein Case Routing fully automates the routing process with machine learning that filters cases to the right queue or agent based on preset criteria, such as who is best qualified to solve them based on expertise or past outcomes.

  Making Agents More Productive with Quip for Service Agents often spend more time hunting down answers than focusing on customer engagement given how difficult the collaboration process can be — corralling input from multiple teams, hunting for answers or documentation, and switching between multiple applications when doing so. Now with Quip for Service, agents have a productivity and collaboration tool embedded directly within the agent console:

• Quip for Service enables agents to co-author documents, bring in subject matter experts across the business to swarm on complex problems, and have live collaborative conversations directly within the case record.
• Admins can build and easily publish flexible Quip templates in the agent console, as well as customize them based on different use cases and specific organizational needs.

 Einstein AI and Quip for Service in Action Together, these new features will fundamentally change how service agents get their work done. For example, when a customer contacts a manufacturer about a malfunctioning refrigerator, Einstein Case Routing will automatically complete the case details and route it to the right agent for faster service. Einstein Article Recommendations will then automatically provide the agent with knowledge articles containing technical details on how to fix the product. Alternately, if the customer reaches out via chat, Einstein Reply Recommendations will instantly suggest responses to the customer’s questions to the agent. Should the agent need to enlist product experts across the company to help fix the refrigerator, Quip for Service allows them to collaborate directly in the agent console, then capture that solution to be used again in the future. Finally, based on the conversation and the customer’s purchase history, Einstein Next Best Action flags that the customer qualifies for a free extended warranty, then walks the agent through the registration process. All of the guesswork is removed, and both the customer and agent have a better overall experience.   Skilling Up the 21st Century Workforce Empowering companies with the right technology only solves part of the challenge, as access to training is another significant obstacle customer service organizations face. To address this, Salesforce offers training programs and networking opportunities that provide managers and agents with the skills they need to bring their contact centers into the digital era and accelerate their career growth. These include the Trailblazers for the Future regional workshops hosted by Salesforce employees and customers, Trailhead content on service related issues, Service Cloud Specialist Certifications, and direct access to a community of 25,000+ service agents. Learn more at: https://www.salesforce.com/events/trailblazers-for-the-future/   Comments on the News

• “We are living in a new age of service where today’s customer expects great experiences at every stage of the buying cycle and across any channel, making the agent’s role more critical and more challenging than ever before,” said Bill Patterson, EVP and GM, Service Cloud, Salesforce. “With these innovations we are empowering agents to rise to the occasion with a console built for modern customer service that is intelligent, collaborative and connected.”
• “At Overstock we are constantly looking for new technologies that will help us continue to adapt to our customers’ needs and deliver personalized experiences,” said Kamelia Aryafar, Chief Customer and Algorithms Officer, Overstock.com. “Einstein AI has shown in our pilot tests that it has the potential to help us meet those needs by recommending offers and perks that our care associates can offer customers based on their shopping history and past interactions. Ultimately, Salesforce is helping us provide our customers a more personalized, human experience.”
• “Tapping into Einstein helps us get maximum value from the information stored in our Salesforce CRM, and with that data we have been able to optimize all of our customer service department’s internal processes,” said Zenconnect CEO Yann Mercier. “After implementing Einstein AI to automatically classify cases, our customer service agents saw 25 percent productivity gains, freeing them up to focus on higher level projects.”

  Salesforce Empowers Companies to Transform Customer Service Service Cloud, the world’s #1 customer service platform, empowers every service employee from the contact center to the field with the innovative tools, unified data, and embedded training needed to deliver world-class customer service. Across every channel — whether it’s messaging, communities, chat, phone, in-person, or IoT signals — Service Cloud is enabling Trailblazers to put the customer at the heart of every service moment and deliver personalized, consistent, transformative experiences.  Additional Information:

• Get more details on the State of Service report at: salesforce.com/blog/2019/03/customer-service-trends.html
• Learn more about Quip for Salesforce in this blog post: https://www.salesforce.com/blog/2019/03/introducing-quip-for-salesforce.html
• To learn more about Service Cloud, go to: https://www.salesforce.com/service-cloud/overview/
• To learn more about Quip, go to: https://quip.com/quip-for-service

 Availability and Pricing

• Einstein Next Best Action is generally available and included within Service Cloud Einstein, an add-on to Service Cloud, for $50 per user per month.
• Quip for Service is generally available and included within Quip Enterprise when added to Service Cloud for $25 per user per month.
• Einstein Article Recommendations, Reply Recommendations and Case Routing are currently in pilot. Pricing information will be made available at general availability.

The Bigger Picture

These times are characterized by the fact that products and services are becoming increasingly interchangeable. As a consequence, companies need to find another means of distinguishing themselves from their competition. This other way is the ability to engage in a way that results in positive experiences. On the other hand, the profession of service agents is surely one of the more stressful ones, albeit crucial for experiences. Service agents need to balance a high degree of empathy, knowledge, and the ability to deal with simple and complex topics in parallel. At the same time the range of topics they need to cover is increasing and service becomes less of a post-purchase only offering. Customers demand – and have the right to demand – answers at nearly every place and time of their individual customer journey. The way to address this double challenge is to empower service agents by not only giving them responsibility but also authority and room to take decisions. In order to be able to this one needs to give them two things:

• Agents need the right tools that help them concentrate on the tasks where humans excel by offloading those that are dull and repetitive. Solving these is something the machine excels in.
• The second thing, an agent needs is ready access to education and knowledge. This means training and an available network of knowledgeable colleagues.

My PoV and Analysis

With this release Salesforce continues on the track that was paved last July, when the company infused Einstein into the Service Cloud. And they strengthen the Service Cloud by giving service agents what they need to be successful, with Trailblazers for the Future being the icing on the cake. This type of crowdsourcing is a stroke of genius. Einstein takes away the duller parts of the work by suggesting replies and knowledge articles, which can be directly incorporated into the chat. According to Peter White, Sr. Director Product Management, Einstein learns from service agent interactions to improve reply accuracy, i.e. Einstein takes into account which or whether suggested replies are used. The addition of Quip to the Service Cloud is important for the ability to deal with more complicated inquiries/incidents. It allows the access to and documentation of additional knowledge and therefore may speed up the resolution of a service case. However, there are caveats. Using a collaboration tool like this has the potential of disrupting the experts that get asked and who may or may not have the time to reply to inquiries. Secondly, it is important that the documents that get created through Quip are used by Einstein in order to be able to suggest more reply and possibly articles in reply to a customer inquiry. Which leads me to two ideas that might improve the Service Cloud even further.

• It would be interesting to add the ability of suggesting the best matched expert to be contacted via Quip. Based upon knowledge ranking Einstein should be easily able to do this. Sources for this could include answers given by the persons, amongst others. All in all this could result in something that is similar to the ranking that is used in communities. Combined with an availability status the quality of replies could even increase while the whole inquiry process becomes less disruptive to the workforce.
• Based upon the constant creation of new codified knowledge it might be interesting look into the ability of creating micro articles, which then are combined into an individualized whole article that then is given back to the customer. This way, the relevance of replies increases, which in turn results in higher customer satisfaction.

As said, these are ideas. Overall I was impressed by what I have seen and got told. It is clear that Salesforce will continue to stay one of the top contenders when it comes to service functionalities.

The News

A few days ago Salesforce released a new iteration of its Service Cloud Einstein after infusing its artificial intelligence, Einstein, into the Service Cloud in February 2017. This release comes with three major enhancements to the Service Cloud:

• Einstein Bots for Service
• Lightning Flow for Service
• Einstein Next Best Action

Einstein Bots for Service is providing the ability to easily configure chat bots that enable instant response to customers and a seamless handoff to customer service agents. Lightning Flow for Service gives companies the ability to automate processes with contextual, step-by-step guidance for fulfilling requests and resolving issues, using a graphical interface. Einstein Next Best Action is delivering intelligent recommendations and offers on any channel to increase customer satisfaction. While Einstein Bots for Service and Lightning Flow for Service are in General Availability since July 11, 2018, Einstein Next Best Actions will remain in a Pilot phase for some more time. The reason for this is that Salesforce wants to be double sure that this functionality is reliable. It needs a good amount of data and a good training set. And Salesforce cannot look into the data. The bots themselves do need to get trained and, once active, take feedback from the service agents. All three features work hand-in-hand. Salesforce uses a credit card scenario to make this point. When a customer goes to the web site for help the chat bot takes over and gathers the necessary contextual information and then escalates the issue to a customer service agent who continues the chat at the position the chat bot exited with all information available. A Lightning workflow then guides customer and agent through the resolution process. This is also where Einstein Next Best Action comes into the picture. Based upon the customer’s history and the conversation Next Best Action provides the agent with a tool to suggest offers matching the customer’s profile. According to Bobby Amezaga, Senior Director Salesforce Service Cloud Product Marketing, all three innovations are about helping Salesforce customers to “create the digital service experience they are asking for” and to be able to provide a guided experience by connecting data.

The Bigger Picture

This triplet of interacting features intends to solve a dilemma facing companies. Customers expect that they are known to the company and that their current interests are acted upon, using the communications channel of their choice, and across communications channels. On the other hand employees need to become more productive while following a trusted process. In addition, with an increasing number of millenials in the workforce, it is increasingly necessary to also provide a better than just good user experience. This is especially true in service center scenarios where we often see young people and a high attrition rate. Bot capabilities are limited and will continue to be for some time going forward. They are powered by rule based systems and narrow AIs. We do not see anything that is close to a general AI. Still, employees are in fear of AI as a technology. They fear that their jobs are moved to the machines. As a consequence of the need to do more with less and the employees’ fears it is double necessary to have bots and human agents work hand in hand instead of in competition. This is also true for customers that are exposed to the bots. It is still necessary for them to know whether they are interacting with a bot or with a human. This might change over time with humans becoming increasingly used to interacting with chat bots, but for now it is a matter of ‘etiquette’ to identify what is bot and what not. The recent fierce discussion about Google Duplex and its capabilities made that clear abundantly, one more time. After all, humans introduce themselves, too. So, why shouldn’t bots do the proper thing … The narrow nature of the tasks that a single bot can perform as per now also makes it necessary to easily build and maintain bots, ass well as monitor and improve their performance. It needs swarms of bots that are interacting with each other and with human agents – and that continue to ‘learn’ on the job. Last, but not least, there is the matter of training the AI. To deliver accurate results it needs a well performing training set. Which for time being makes companies rely on data scientists to create this data set. This is especially important for prescriptive scenarios like Next Best Action. These scenarios also need a lot of data that in all likelihood does not lie in a Salesforce database. It is here, where the acquisition of Mulesoft has a good chance of paying dividends. The Integration Cloud, as it is named now, enables customers to enrich Salesforce data with data coming from a plethora of different sources.

My PoV and Analysis

With this release Salesforce reinforces its strategy of embedding AI and Machine Learning directly into the application. This is also where it belongs and similar to the strategy that also Microsoft and SAP are pursuing. AI for AI sake is not a winning proposition. As Marco Casalaina, VP Product Marketing Einstein put it “AI alone does not bring your business forward”. We see a seamless integration that provides a handover from bot to service agent, along with a sense of important details. The bot, for example, introduces itself as a bot. This helps building trust. The bots itself being built using rules and Natural Language Processing (NLP) suggest an ability to not only escalate from bot to service agent but also an ability to hand-off from one bot to another. If not, this is surely something that I’d encourage Salesforce to look at, as this ability will further reduce the strain on service agents and help them focusing on the tough issues that will continue to need human to human interaction. Additionally, and this is a bit more challenging, companies will benefit from pre-trained intelligences and from a transparent method that improves solution accuracy and broadens the covered scope on an ongoing basis. Right now Salesforce helps customers with a service offered by their own data scientists. Additionally, some partners offer pre-trained models. The bots are learning on an ongoing base only by feedback that is given to them by agents. It should be interesting to see two measures being implemented. Bots running as sidekicks to agents while they handle issues that are handed off to them. This will help in increasing accuracy and broadening a bot’s skill. Secondly, I propose an engine that identifies a training set for resolving a pattern of issues and then trains an AI with it. This has the potential of building bots more efficiently. The combination of these would help training a group of bots until they reliably reach a minimum accuracy and helps them maintain this accuracy in a changing world. I’d love to see both of these in action, especially in combination.  

On July 12, 2017 Salesforce announced its new, Einstein-enhanced version of Field Service. This release brings mainly three innovations to the already strong Service Cloud, which is the leading Customer Service solution according to Gartner Group. Here the complete wording of the press release, in case you did not want to follow the link but still are interested in it: Salesforce Delivers Einstein AI and Analytics For Field Service Lightning Built on the Service Cloud Platform, new innovations for Field Service Lightning arm the mobile workforce with image recognition technology, smart equipment management and deep analytics to bolster productivity and efficiency Companies including Atlantic Energy are harnessing the power of Field Service Lightning to deliver insight, onsite SAN FRANCISCO—July 12, 2017—Salesforce , the global leader in CRM, today introduced Einstein AI and Analytics for Field Service Lightning, empowering companies to deliver a smarter onsite customer experience that is built on the world’s #1 customer service platform. Field Service Lightning now brings together the insights and intelligence mobile workers need to increase productivity, boost onsite efficiency and drive revenue. The Salesforce Service Cloud has redefined customer service across every major technological shift—cloud, mobile, social, messaging and more. And last year with the introduction of Field Service Lightning, Salesforce extended the power of Service Cloud to create a full service platform for managers, dispatchers and mobile workers. However, as the multi-billion dollar field service market expands into new industries—including finance, healthcare, manufacturing and retail—there is even more demand to deliver onsite service. Field service technicians have to deal with complicated equipment, don’t always have the right parts and often lack insight into pre-existing customer issues. This leads to confused employees, frustrated customers, and in the end, multiple trips to resolve customer issues. Field Service Lightning Brings Insights, Onsite Now, Salesforce is taking field service a step further, arming mobile workers with the intelligence and insight they need to be more productive and improve first-time fix rates. With three new innovations, Field Service Lightning enables a service organization—managers, dispatchers and mobile workers—to move with speed and efficiency. New innovations include:

• Einstein Vision for Field Service harnesses the power of artificial intelligence to bring image recognition to field service. Companies can leverage pre-trained image classifiers—or train their own custom classifiers—to handle a vast array of specialized image-recognition use cases. For example, with similar looking parts and serial numbers, dishwasher repairs are often complex. Now a dishwasher repairman who needs to replace a water inlet valve can simply snap a picture of the valve, and Einstein Vision for Field Service will quickly identify the exact product type—saving time for the customer, repairman and company.
• Equipment and Inventory Management leverages scheduling automation to ensure the correct work crew, equipment and trucks are always where they should be. Managers and dispatchers are able to send technicians into the field with confidence, knowing they’re armed with the equipment and knowledge they need to complete any job during the first visit. For example, a cable company dispatcher is able to use Equipment and Inventory Management to automatically see which technician is closest to the customer and has the correct cable splitters necessary to get the customer’s television set up successfully.
• Field Service Analytics provides actionable insights for managers to improve productivity throughout their mobile workforce. Service managers can now integrate all of their data into one easy-to-use application for a complete view of their mobile workforce. And then, they can take action right from their dashboards. For example, a service manager at a medical device company can quickly see that several of her technicians are struggling to install an EKG machine, enabling her to identify classes and set up times for them to shadow senior technicians to get on-the-job training.

Comments on the News:

• "For nearly a decade, Salesforce has paved the way for innovation in the service industry," said Adam Blitzer, EVP and GM, Sales and Service Clouds, Salesforce. "Today, we're excited to bring our innovation a step further. With the introduction of Einstein and Analytics for Field Service Lightning, our customers will be able to deliver a smarter, more efficient onsite customer experience."
• "At Atlantic Energy, our goal is to create a cleaner, more energy efficient world," said Noel Zammit, CIO, Atlantic Energy, LLC. "With Field Service Lightning, we're able to arm our technicians with the intelligence and insights they need to service our customers faster than ever -- reducing energy consumption and costs around the globe."
• "While the direct customer experience has benefitted from digital transformation, field technicians still struggle to deliver a modern onsite experience. Customer expectations have escalated across the board, and so have expectations for in-the-field diagnostics and issue resolution," said Mary Wardley, Program Vice President, Customer Care and CRM, IDC. "With features including image recognition, automated equipment tracking and analytics baked into the field service process, digital transformation is reaching the field and will enable companies to run their field service organization faster and more efficiently."

About Service Cloud Service Cloud, the world’s #1 intelligent customer service platform, enables companies to transform the customer and agent experience with an AI-powered, agile platform built for the modern era. Whether engaging customers via messaging, video, communities, web chat, in-app, email, phone or even communicating directly with IoT-connected products, Service Cloud helps leading brands use service as a competitive advantage by delivering personalized, connected customer service experiences across every channel and adapting service operations to business needs quickly. Companies that have deployed Service Cloud have seen an average of 31 percent faster case resolution, an average of 28 percent increase in agent productivity, an average of 26 percent increase in customer retention, an average of 22 percent decrease in support costs, and an average of 35 percent increase in customer satisfaction, according to a third-party research report sponsored by Salesforce. Salesforce has been recognized as a leader for nine consecutive years in the Gartner Magic Quadrant for CRM Customer Engagement Center. Pricing and Availability

• Einstein Vision for Field Service is currently in pilot and is expected to be generally available in the first half of 2018.
• Field Service Equipment and Inventory Management is generally available today with any Field Service Lightning license, which starts at $150 for organizations that have at least one Service Cloud license in Enterprise Edition or above.
• Field Service Analytics is generally available today with any Service Analytics and Field Service Lightning license.

Additional Information

• To learn more about Salesforce Field Service Lightning please visit: https://www.salesforce.com/products/service-cloud/features/field-service-lightning/
• To learn more about Service Cloud, please visit: https://www.salesforce.com/service-cloud/overview/
• Discover how Service Cloud can help companies deliver personalized service to their customers via Trailhead: https://trailhead.salesforce.com/trail/service_cloud

Connect with Salesforce

• Like Salesforce on Facebook http://facebook.com/salesforce
• Follow @salesforce and @servicecloud on Twitter

About Salesforce Salesforce, the Customer Success Platform and world's #1 CRM, empowers companies to connect with their customers in a whole new way. For more information about Salesforce (NYSE: CRM), visit: www.salesforce.com. Any unreleased services or features referenced in this or other press releases or public statements are not currently available and may not be delivered on time or at all. Customers who purchase Salesforce applications should make their purchase decisions based upon features that are currently available. Salesforce has headquarters in San Francisco, with offices in Europe and Asia, and trades on the New York Stock Exchange under the ticker symbol “CRM.” For more information please visit http://www.salesforce.com, or call 1-800-NO-SOFTWARE. Field Service Analytics - Source Salesforce These three innovations shall enable customers to drive revenue by increasing field service personnel effectiveness and efficiency plus giving managers actionable intelligence about field service operations and assets. This encompasses the following main features:

• Einstein Vision helps techs identify a part that they do not quite recognize. Einstein responds with details, including the part number, a description and, importantly, a recognition confidence. Field technicians simply take a picture of the object in question and upload it to the Chatter feed. Einstein needs to be trained with around 100 – 150 images of an object from various angles and lighting conditions in order to identify an object.
• The solution got additional ‘smarts’ to help with optimizing equipment and inventory management. This helps to optimize the scheduling of crews, equipment, and trucks.
• Lastly, there are a number of new management dashboards that allow a drill down and analysis into the organization performance and KPI’s that are intended to give managers actionable insight into what is happening in their realm of responsibility.

The first two releases are supporting the field technicians by being part of the mobile apps that they use, while the third one is helping the managers. The mobile enhancements are available on iOS whereas Android is still in a beta phase. This release, according to Mark Bloom, Senior Director Strategy and Operations, Service Cloud, is the continuation of Service Cloud’s journey covering social, mobile, video, in-app messaging and, since March 2016 also Field Service.

My Take

This release seems like an incremental evolution of the existing functionality. For me the most relevant innovation is the improvement in the equipment and inventory management in combination with the new analytics capabilities that are exposed by the dashboard. Of course the image recognition capabilities are amazing, too, but I would put this more into the ‘sex sells’ bucket. It surely can help (junior) field service technicians identify a device but I see only limited value for it unless augmented by more functionality, e.g. an AR overlay rendered into some glasses that helps the technician to safely replace a broken element while keeping the hands free to actually do the work. The equipment and inventory management component has been mainly there before but now has some additional intelligence that helps in making sure that the right materials are available to the technician when (s)he needs it. This is some intelligence under the hood that should help in avoiding unnecessary roundtrips or in getting to the shortest way to resupply. The management dashboard shows a lot of interesting data and analytics, including travel time that will help a manager analyzing what is going on in the team. This is again something that was there earlier, too, and in my eyes is lacking an alerting component. Not every technician that has long drive times or takes long time to fix an issue is a problem. This may be the specialization and/or the locations of the jobs. I would have wished for an alerting component here that looks into anomalies and drives the managerial focus there. Lastly, I am missing a predictive maintenance component here. After all this is something where AI can excel. Unluckily this is something that is only on the roadmap, maybe because it also needs cooperation with the IoT team. Overall I’d say we see a solid round off with Einstein Vision being a nice eye catcher here, as opposed to a big leap. Having said that, the integration of AI technology into the business functionality is mandatory in order to enable a number of scenarios that are not yet possible to deliver. I am curiously looking into future releases of Service Cloud.