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My recipe of Intelligent Service for Manufacturing

As manufacturing enterprises are wading through a pivotal transformation in digitizing their landscape, customer-centric strategies continue to filch the focus with shiny variants of CX solutions being onboarded. Experience enhancement accelerators like Smart Sales, Intelligent Service, Insight based marketing, Personalized Portals are being huddled into the ecosystem in alignment with the foundational principles of the 04th industrial revolution. 

While new and renewed feature sets are being deliberated for both Sales and Service systems, historically, customer service has been a greater focus area or rather one of the key imperatives of the manufacturing sector. This blog touches upon the elements required for concocting a perfect customer service recipe for a manufacturing enterprise, albeit the opinions and recommendations, are purely based on my personal experience, suggestions to which are welcome.

While the ocean of features and solutions is vast, my recipe is based on the top 10 picks which would help in delivering Intelligent, Optimum and Automated customer service for any manufacturing enterprise.

The recipe spins around various aspects associated with a repair scenario wherein, the equipment needs an inspection followed by a repair. 

·     Self- service - Conventionally, while calling the call center to schedule a repair service has been a working model but the same comes with annoyances of long wait time, network traffic and too many transfers. The shiny working model would be to spin a 'Community/ Self-service Portal' for the customer to self- help with features like -

o    Self- log the problem statement

o    Self- educate on the repair process, common queries/ issues.

o    360 degree of his or her portfolio of assets/ equipments/ service history

o    Key alerts/ notifications related to assets upkeep/ maintenance

o    Key notifications - technician arrival time, details, etc.

o    Analytical view of asset health/ key stats etc. for quick decision making.

 


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     Key KPIs Impacted - Net Promoter Score, Total cost per contact, Knowledge Base Traffic, Customer Effort Score.

 

·     Connected Service  -  Typical scenario proceeds ahead with the call center agent, who, having understood the repair service requirement opens the Case and assigns it to the Field Service department for taking it over for inspection followed by shipment. To evade too many handovers, the advanced version of Service addresses this with 'Connected Service' wherein the Case to Work Order to Field Service Appointments hand over happens automatically by right selections of the Case category or Type.

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     Key KPIs Impacted - Net Promoter Score, Number of Handovers, Customer Callback.

 

·      Intelligent Dispatch & Schedule  - While the Service Appointment scheduling for inspection and shipment of the equipment can be handled manually by the Dispatcher, why not hit the jackpot of FCRR (First Contact Resolution Rate) with the 'Intelligent Dispatch and Schedule' operations. Deploy a field service solution that automatically spins into action for dispatching and scheduling the service appointments based on their priority, availability of technicians, skillsets, proximity, territory and more. Some of the variants also, bring in advanced levels of intelligence by creating a fingerprint of the technician using the historical performance patterns for greater accuracy in scheduling.

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     Key KPIs Impacted - First Contact Resolution Rate, Truck Rolls, Travel Time, Non- billable Service Calls, Service Revenue, Service.

 

·     Personalized notifications - The story progresses further with the technician visit confirmation either on-the-call or through an SMS which does not offer many details of who is coming, what time, etc. Intelligent service solutions keeping the personalization quotient high, deliver 'Personalized Notifications' on technician details like his name, phone number, photograph and the time slot of his arrival. Any delay in arrival is further informed with personalized messages and the next best slot covering personalization as well as safety aspects.

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     Key KPIs Impacted - Net Promoter Score, Customer Effort Score, Number of Repeat Calls, Customer Callbacks.

 

·    Omni Channel - Why stop at multi-channel when intelligent service solutions entail 'Omnichannel' features. I inquire about the equipment status via an email or chat or the trendy WhatsApp or portal, the solution will provide a seamless response without having to repeat anytime, anywhere in the process of providing a personalized omnichannel reach.

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       Key KPIs Impacted - Customer retention, Net Promoter Score.

 

·      Smart Bot - A few years back, Live Agent/ Chat was a huge hit until the service industry was shaken by 'Smart Bots' which could virtualize an agent actions and provide the guided help, much needed for a distressed customer requiring to know the details and status of his repaired equipment delivery amidst of peak hours of contact center traffic. Chatbot brings together the power of configurations, NLP/ artificial intelligence to offer a contextualized conversational interface.

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       Key KPIs Impacted - Agent Handle Time, Customer Wait Time.

·      Aftermarket Advisor - Today, the manufacturing industry is taking great strides in the aftermarket scenarios to generate revenue as a part of the service operations. 'Aftermarket Advisor' provides the capability to offer upsell/ cross-sell products and/ or services to the customer during the closure of the Repair related Case/ Service Appointment by either the call center agent or the technician. Based on the interest levels of the customer, the advisor can automatically generate the lead or the opportunity within the Sales system for the Account Teams to nurture it further.

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       Key KPIs Impacted - Service Revenue, Upsell/ Cross-Sell.

·       Service Automation- With the complex processes of the Manufacturing industry like Depot Repair, RMA processes, Inventory management, etc 'Service Automation' becomes a necessary ingredient. Smart Equipment features like Predictive Maintenance, Automated Renewals, Fault-based replenishment, Connected Sensors/ IoT based safety assessment and fault logging etc. are some of the common automation use cases being inducted into the ecosystem depending on the appetite and need.

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         Key KPIs Impacted - First Response Time, First Contact Resolution, Customer Satisfaction Score.

·     Service Analytics - Using 'Service Analytics' for gauging the key Service KPI/ metrics adherence and generating intelligent insights for service operations improvement is not only a cool trend to implement but also a basic need of the hour for service heavy manufacturing industries. Apart from lending a view of the efficacy of the service operations like Aging of the Repair Request, Number of Handovers, Average handling time of the repair request, Customer feedback on contact center as well as field service, etc. Service Analytics insights help in seasonal ramp up, training need s, capacity planning scenarios.

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      Key KPIs Impacted - All key Customer Service KPIs including Conversion Rate.

·       AI-infused Service - Today, AI-powered transactions and analytical views have dominated the customer service arena. For example; Imagine the Repair Service being handled by virtual agents for Inquiry/ Request initiation, collaboration, chatting, moving the order through stages and finally intelligent insights for improvement. Manufacturing enterprises are increasingly adopting AI-infused service solutions for key use cases like training, capacity planning, object identification and guided help in the form of bots or knowledge articles.

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       Key KPIs Impacted All key Customer Service KPIs including Conversion Rate.

The list of picks might go on, but the intent is loud and clear - differentiated customer service. Be it adopting the shiny service capabilities or having an integrated view of data across CRM and ERP systems or revamping the business strategies, the podium is open for manufacturers for innovations and implementations

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