Artificial Intelligence in your service centre

Einstein Service Cloud arrives (Image Credit Salesforce)
Einstein Service Cloud arrives

Salesforce has announced Service Cloud Einstein to deliver artificial intelligence solutions to customer service agents. Salesforce pushed Einstein, its AI platform, heavily at Dreamforce last year. It has a huge development focus on the product. This effort has culminated in the release of Einstein for Service cloud. It delivers artificial intelligence, arguably machine learning, to the service industry.

Salesforce have release three component parts in the initial solution and are promising more of them in the future. Each component targets different stakeholders such as service organisations, management, customers and field service.

Helping management

Einstein Supervisor aims to deliver predictive analytics that inform management about trends that can impact the business.  It uses data discovery in real-time to evaluate trends across the data set and deliver insights. The examples given include recognising trends in agent availability, queues and wait times in call centres. The results is a set of recommendations for management to identify where improvements are needed. For example is this an HR issue, external influences or something else? Management can then plan and take the appropriate action to correct the issue.

Within industry the system will correlate faults registered and identify commonalities between them. It uses the data to detect whether machines are sourced from a single supplier or factory. Management can then implement a recall, remote fix or field service visits to rectify the problems. This prevents them becoming a major issue.

Salesforce has fallen short of making this solution deliver prescriptive analytics. That would have actually arranged and dispatched field service agents to carry out the task in the most efficient manner. In theory this is the next step of that evolution. It will be interesting to see whether companies connect insights to actions or merely have a human oversight. Potentially this will reduce management costs as scheduling becomes even more automated. Salesforce cite Accenture who reported following research that 79% of IT and business executives “agree that AI will help accelerate technology adoption throughout their organizations”. They also said: “AI is poised to enable companies to improve the experience and outcome for every critical customer interaction.”

Einstein Supervisor is available now. It combines Omni-channel Supervisor with Analytics Cloud’s Service Wave analytics app and Smart Data Discovery. While Salesforce states pricing for both Wave Analytics and Smart Data Discovery it does not appear to impose additional costs for Omni-channel Supervisor.

Helping customers

There is a race for companies to develop bots to integrate with their ERP solutions and knowledge bases. Companies are developing bots such as Pegg from Sage and WeChat from IFS to improve customer response. This frees up resources for simple Q&A. Salesforce are taking this a step further with Einstein Case Management.

Salesforce is looking to improve the efficiency of inbound service calls. This could be by delivering the appropriate information quickly following an initial analytics into the problem. If the call is not resolved by the AI it gets routed to the most appropriate agent to resolve the call. For example, a tenant calls into a service centre with a water leak. The AI can determine if the problem lies with a plumber or general maintenance. It can then talk the tenant through shutting off the stop cock. This lessens the damage to the premises in that instance.

This benefits the customer as question trees can get more complex with less repeated questions. Einstein can potentially personalise the response for each caller using historic data. This can reduce the number of and increase the complexity of questions asked. For agents it reduces the frustration of repetitive questions and enable them to rapidly get to the heart of the matter when the call reaches them.

This could also have an impact on triage and other uses in healthcare. Steven Mascola, IT Director, STANLEY Healthcare commented: “At STANLEY Healthcare, our goal is to deliver superior patient care and service. We’re excited about the introduction of Service Cloud Einstein and the opportunity to deliver even more personalized and connected support for our customers.”

Additional features allow for predictive close times. This further helps with allocation of calls and management of available resources. For example if a service request has an estimated duration of 30 minutes it is better to place it with an incoming agent rather than one going off shift in ten minutes time.

Einstein Case Management is available later in 2017, prices are not yet available

Helping field service agents

Salesforce has also announced Intelligent Mobile Service (aka Field Service Lightning). This is an app available from the Apple Store and is also supported on Android (in pilot currently). The mobile app uses advanced algorithms to improve scheduling and routing. Sensibly Salesforce has included an offline mode. This means that employee working in remote or underground/in building locations with no signal can interact with existing call information without the need to return to the surface to complete the administration. The app includes all relevant information about the call, customer and history. For calls where additional parts are required service centre agents are routed to appropriate pickup locations prior to attending site.

Intelligent Mobile Service is available now. It starts at $150 per user, per month for organizations that have at least one Enterprise Edition or Unlimited Edition Service Cloud license.

The future of Einstein

A blog by Mike Milburn at Salesforce highlight some of the future features that might be seen in Service Cloud Einstein. This includes integration with the Salesforce IoT Cloud. Manufacturers of complex equipment are already using IoT to analyses failure rates of components and improve up time of equipment. The most commonly cited example of this is GE who use IoT and digital twins. They apply the IoT data to the digital twin so that they can track performance and maintenance in real-time.

If a washing machine company can install connected sensors to detect failing components one can see a future where consumers rent equipment based on usage rather than time. The Salesforce ecosystem will easily support this shift should it happen. Call centres can proactively contact customers before their machines are failing arranging maintenance calls to repair machines when appropriate rather than waiting for a domestic catastrophe.

Conclusion

Adam Blitzer, EVP and GM, Service and Sales Clouds, Salesforce (Image credit Linkedin/Adam Blitzer
Adam Blitzer, EVP and GM, Service and Sales Clouds, Salesforce

This is early days yet for Einstein in Service Cloud and with the Case Management still some months away it is hard to see the impact it will have. Some partners are no doubt working on Einstein solutions to support their customers. It will be interesting to see who the launch partners are when it reaches general availability.

Adam Blitzer, EVP and GM, Service and Sales Clouds, Salesforce commented: “Customers today expect and demand great service experiences. Service Cloud Einstein empowers companies to transform any customer service interaction into a smart conversation that drives brand loyalty and creates customers for life.”

There are many use cases of AI, or machine learning and there are also some challenges still to be resolved. As AI starts to replace jobs in some industries nobody knows what the backlash will be. For companies who have not considered these personnel issues carefully there could be problems. For others it is an opportunity to cut costs and increase efficiency if done well. Bots do work, but there are times when customers prefer the human touch. Organisations that get that balance right will do well.

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