Companies are realizing the need to provide each customer with great, personalized, experiences. Customer Service Representatives (CSRs) are on the front lines, often with inadequate or dated information, directly impacting the customer’s perception of these companies.
CSRs in many industries are handling customer interactions while relying on antiquated systems that show minimal information about the last 1 or 2 times a customer interacted with the company, if they’re lucky. Providing a unique and personalized experience requires knowing more about a customer’s past experiences; including the context of those experiences and information from any communication channel that has been used. We developed an intelligent Journey Dataset (JDS) that does just this. The JDS is the standard for making cross-channel journey data available to any organization in the enterprise.
Journey data in the hands of CSRs helps them make informed decisions based on observed customer behavior, while helping the customer feel they’re not starting from scratch in this interaction. For example, a new banking customer calling into the care organization recently opened an account, registered the mobile app at a branch location, and failed to complete auto-pay enrollment in the app. An agent equipped with journey data can enroll the customer in auto-pay and send the customer a “new to mobile banking” information email before the customer even asks. With journey data the agent can now see the customer’s multi-touch “on boarding” journey to get a feel what the customer is going through.
Using an automatically scheduled journey dataset to fuel a dashboard displaying the past 7 days of activity across the enterprise can give an agent a heat map of channel usage and behavior. This type of view allows the agent to coach the customer on the observed self-serve failures. Through journey data we can enable agents to be more effective, while also helping customers to become more self-sufficient.
Typical approach for institutionalizing journey datasets in an enterprise.
Journey datasets are easily distributed into operational systems and integrated into existing frontline systems. A JDS derives this intelligent output by connecting data from any source including: interaction channels (e.g. Digital, IVR & Agent), survey, ticketing systems, transactional, segmentation, to name a few. What makes this a net new data asset is the business context applied by traditional business analysts. Business analysts apply journey classifications (e.g. 'customer onboarding' or '30-day journey to poor CSAT') to commonly label segments of the population that meet a specific criteria from within the ClickFox user interface. The JDS contains all necessary customer identifiers, connected multi-channel events and their sequence, along with the business classifications and their results. Business users can create multiple JDS feeds based on exact needs; all being derived from the connected data in the ClickFox platform and generated directly in the Hadoop file system (HDFS) for use anywhere the enterprise needs it.
Automatically syndicating JDS(s) directly to business data lakes allows the enterprise to incorporate journey data into their operational systems. Continuous agent feedback and training increases agent retention while decreasing cost. For example, a regional European bank utilized journey data to reduce 4-6% of repeat calls from their call center. With intelligent journey data available, CSRs are more efficient and accurate, while the customer becomes more brand loyal with each and every great experience.
Read the next installment of the Journey Dataset Series, where we focus on using JDS to determine the behavioral drivers of different outcomes, e.g., NPS.