Enhancing the Omni-channel Customer Experience by integrating contemporary tools with state-of-the-art analytics
The contact center has evolved, moving from a reactive service center managing customer inquiries and complaints to providing support in the customer’s preferred channel. Digital transformation further shifts the contact center’s role beyond trying to resolve customer calls in the shortest amount of time possible to using analytics to providing proactive, personalized support and powerful customer experiences.
Next-generation contact centers leverage a fluid integration of technology, data management, contemporary system architecture, analytics and organizational design, to increase call deflection, improve first-call resolution, enhance cognitive interactions and transform the role of customer service representatives from empathetic call takers to empowered, expert, service partners.
From voice to Omni-channel
Contact centers have adapted over the past few decades to take advantage of digital opportunities. Originally resolving customer complaints and questions over the phone, contact centers focused on optimizing the channel costs by decreasing costs for people, infrastructure and telecom services.
Now with advent of digital transformation, contact centers are a critical and important part of the omni-channel customer experience. Consumers can file an insurance claim online through a digital channel, proactively receive text messages from an airline informing them of flight delay and can now have questions about their utilities bill interactively answered by a chatbot mimicking a human agent. Ironically, the omni-channel evolution is, in many ways, digitally mirroring the direct and personal, intimate proprietor experience that keeps loyal customers frequenting the local mom and pop Main Street boutiques.
As digital adoption increases more and more interactions take place over digital channels. Contact centers have seen a 12% drop in phone calls, but have seen an overall increase in the average amount of time for each interaction.
With 82.5% of companies recognizing customer experience as a competitive differentiator, organizations are searching for new ways of making all customer interactions richer, personalized and proactive. This shift has sparked companies to evaluate interactions across all channels (digital, voice, human) to ensure customers receive expert customer service over their channel of choice, while reducing the unit cost of these interactions. Contact center transformation is a critical cornerstone of organizations’ digital transformation and evidence of the ability to concurrently deliver the often competing objectives of customer experience and cost. Analytics is a critical component in transforming the contact center experience. Analytics offers actionable insight into customer’s channels of interaction, delivers context to the customer interaction, and helps to better understand customer behaviors by demographic as well as the value of interaction. Analytics can help organizations determine which consumers are most likely to experience an issue and resolve it in advance through digital channels, increase first-call resolution when the customer calls and help transform the contact center into a value-proposition enhancer.
Depending on the business, 40% - 80% of calls a customer places to a call center is in reaction to an event that occurred. A customer picks up the phone as a result of experiencing an issue or needing information, and a customer service representative attempts to solve their issue in the quickest handling time possible.
Analytics allows contact centers to move from reacting to customer complaints to proactively solving them. By analyzing the questions, complaints or requests customers call in with, contact centers can determine what causes a specific call, from a specific customer persona.
Identifying which behaviors trigger a customer to dial in provides contact centers with the intelligence to use digital or non-digital channels to reach out to the customer in a proactive manner to resolve their issues before ever picking up the phone. This in-depth understanding of who, how, why, and when customers connect with the call center can be used to increase the use of lower-cost digital channels. Analyzing a customer’s behavior can determine whether their issue could be best solved through reaching out proactively via text message, email, outbound automated/ AI enabled calling or other channel.
An insurer uses analytics to discover that customers whose premiums increase by greater than 10% are 85% more likely to call with questions about their policies than those whose premiums increased by less than 5%. To increase call deflection, the contact center designs, builds and beta-tests a ‘fail fast’ solution for the high-contact customer cohort providing information as to why their premiums changed using low-cost automated emails and text messages that answer these questions after policy alterations go into effect.
Contact centers can take call deflection a step further by incorporating a cognitive layer by having robots (chatbots) converse with their customers or having the customer engage with the IVR system through natural language processing and artificial intelligence generation. These channels that are a substitute to real agents can not only resolve issues, but solve them interacting with the customers through a natural language audio (e.g. phone or PC microphone) interface.
Analytics are used to tabulate the most frequently asked questions. Each of the questions are mapped to interactive and cognitive key words that enable the system to understand the customer’s question in English and identify the right answer for their questions. Incorporating machine learning enabled cognitive interventions into a contact center’s chatbots and IVR interface enables these common questions to get deflected through quick, efficient and accurate low-cost digital channels.
For instance, a contact center could use analytics to define the ten most common questions it receives across all of its channels. Based on the complexity of these questions, the contact center could determine which can be resolved using interactive IVR or chatbots and enable the keyword scoring logic with operational processing to contain these queries within the digital channels to further decrease the amount of calls its agents handle.
Of course, a contact center will not be able to proactively deflect every call. In cases when a customer does call in with an issue or question, which is not initially addressed with an AI solution, contact centers can leverage analytics to proactively predict questions adjacent to the customer’s journey and arm the agent with the immediate desktop insight to resolve both the current issue and any potential future issues that may cause a call. Some journies may expose the need for a customer to be periodically informed to prevent future status calls. In these instances, an agent can, with customer permission, activate SMS phone alerts that will inform a customer as the status changes or periodically across defined time intervals.
By matching data on why customers repeatedly reach out to contact centers with other information such as customer demographics, life events, and past issues creates a unified view of the customer. This centralized and curated intelligence allows contact centers to tailor digital and human solutions to the individuals calling for assistance. This highly personalized level of support reinforces a brand’s commitment to service and builds lasting customer loyalty.
A customer calls their bank after their credit card was declined. The customer service representative assists this customer with their issue. After the original problem is solved, the customer service representative is presented with an appropriate follow-up question, on their ‘First Call Resolution’ enabled, agent desktop that if asked of the customer, at this time, can prevent calls from this customer in the future such as asking whether they would like to raise their credit limit or enroll in an automatic payment plan, based on the customer’s circumstances.
The new ‘empowered’ role of the customer service representative
After using proactive status alerts and analytics to increase call deflection, cognitive interactions and firstcall resolution, customer service representatives will receive very few inquiry questions that only require a simple answer. These representatives will instead be dealing with customer issues that take a high level of care, intelligence, creativity and a human touch.
In this environment, traditional metrics for measuring customer service representative performance like average handle time are no longer effective.
Contact centers must not compromise the experience of a customer interaction to further lower the cost of the agenthandled call, at this point in time. With lower complexity inquiry and action calls already deflected digitally, the average unit cost of interaction is already dramatically reduced. This digitally transformed model for analytics-powered contact center operations requires new metrics to measure performance:
• Volume and usage of digital channels
• Number of calls resolved by cognitive interactions with IVR containment, chatbots and virtual assistants
• First-call resolution
Tracking these performance indicators provides a more holistic look at how a contact center is performing effectively, in a digitally-centric era, rather than focusing exclusively on how quickly agents turn calls around.
Achieving next-generation contact center operations
A successful, digitally-enabled, analyticspowered contact center requires an indepth assimilation of customer behaviors and needs. Companies must understand what first triggers a call, install and train machine learning enabled digital solutions to deflect it, predict what future issues may arise to ensure first-call resolution, and empower agents to ensure that future contacts are mitigated and the customer receives an expert advocate experience that far surpasses their expectations.
By integrating digital, analytics and human-centric solutions, contact centers are moving from a reactive model to an omni-channel experience that delivers timely, expert information and solutions to the customer proactively and via the engagement channel of their choice. This next generation of contact centers will enable organizations to provide the personalized, proactive support that creates value recognition, customer advocacy and distinct advantage in the marketplace.