Customer Journey Analytics (CJA)
By Seshachari, October 31, 2017
Visualize the customer’s journey across channels to convert insights into impact, and deliver on Customer Experience Context and Precision.
An analytics practice that combines quantitative and qualitative data to analyze customer behaviors and motivations across touch points and over time to optimize customer interactions and predict future behavior
Changing customer expectations demand more Individualized, data-driven personalization of recommendations, offers and messages. Enterprises have to act better by connecting all customer interactions with strong emotional content. This will not only ensure that customers receive personalized brand messages, but also shape conversation to build long term relationships, with no particular channel bounds.
The Paradigm shift to digital has greatly expanded the number of channels used by customers. Customers experience a journey comprised of a sequence of interactions that span channels and devices, and expect every interaction to be easy, relevant, tailored to their needs, and available on any device. A plethora of tomorrow’s enterprises have started focusing from Moments of Truth (MoM) to Customer Journeys.
Customer Journeys are a discreet set of interactions that a customer has with a brand, across various touch points around their needs. To understand, analyze and optimize the entire sequence of digital interactions, a new breed of customer journey technology analytics solutions are emerging, boasting advance predictive and real-time analytics to know customer behavior patterns, aid next best action, likely to churn, or likeliness to buy a product or service. Additionally, enterprises also personalize the customers’ experience in real-time, by deciding which offers or messages to present during an interaction.
CJA solutions generally cater to 4 phases of the customers’ journey:
1. Gathering: Data gathering across channels for analysis which includes structured, semi structured or unstructured data, involves direct integrations, exporting files, dynamic tag management & SDKs.
2. Connecting: Linking customer with UI unique identifier i.e. email, phone, customer ID, loyalty card, membership card, etc., which are common to multiple channels, matching their UI & session data across all channels for correlation, resulting in progressive profiling.
3. Visualizing: Persona views, latency tables, extracts, interactive dashboards, metrics providing operational excellence and customer experience (CX).Visualization provides insights into how customers are using Omni channels together throughout their journey life cycle, and highlights gaps / deviation between journey path expectation and dominant path.
4. Action: Use of algorithms & processes to recommend actions through journey orchestration and next-best-action capabilities. With CJA, enterprises can visualize the customer journey; find complex hidden patterns in customer behavior; discover and profile common interaction paths; and optimize the customer journey.
a. Visualizations in real-time with a point-and-click interface
b. 360 degree view of all customer interactions to see all customer touch point multi-channel interactions with the Customer Journey timeline
c. Identify the Relationship between Path & Outcome to align with customer dominant patterns
d. To understand deviation & drop off points as against expected customer journey path
a. Improve the overall customer experience
b. Increase revenue per customer
c. Predicting and preventing customer churn
d. Accelerating customer acquisition
e. Lower customer acquisition costs
Some of the major platform vendors who offer distinctive decision frameworks to drive deep touch point analysis and active insights to enhance customer experiences are Adobe, ClickFox, ENGAGEcx, Kitewheel, NICE, Pointillist, Teradata, Thunderhead, Usermind, and Verint.