For most companies, customer journey management involves a collection of siloed tools and processes that demand extensive resources and provide very little actionable insight, if any.
Enterprises tend to use a variety of different vendors, databases, and processes to try and understand customer journeys.
What they often lack is a single, unified view of a customer’s journey. Enterprises struggle to show how managing journeys can impact overall business objectives across channels.
Customer journey tools could include:
- Actionable dashboard
Each of these tools can provide tremendous value when used in conjunction with the others, especially when they are enabled by Artificial Intelligence (AI) and Machine Learning (ML). Used alone or in isolation from other tools, their value is more limited.
By bringing these capabilities together into one centralized view of the customer journey, you create huge efficiencies of scale, reduce work, and achieve better ROI while enabling true journey intelligence.
First, we need to understand the customer journey ecosystem.
Journey analytics provides tools and automated insights that allow an enterprise to better understand customers and improve their experience.
Journey analytics: a practice that combines quantitative and qualitative data to analyze customer behaviors and motivations across touchpoints and over time to optimize customer interactions and predict future behavior (source: Forrester).
Customer journey analytics include the following types of data, among others:
- Basic demographic information on customers
- Account or user-based information (e.g. account types, balances, or payment trends)
- Time series event data that captures every interaction on every channel between a customer and a business
- Behavioral data (e.g. how long a customer spent on the phone with a call center agent, when and where they abandon a cart)
- Business process details like new device procurement and delivery, internal approval processes, trouble tickets
- Voice-of-customer (VOC) surveys, such as how satisfied customers are, how likely they are to recommend (Net Promoter Score), and other data resulting from customer feedback
Analytics are the building blocks of any customer journey effort. Until we know what our customers are already doing and how they feel about it, we can’t begin to influence their behavior toward desired outcomes or understand what an ideal or problematic journey looks like. Analytics are foundational to customer journey success.
Analytics alone are not enough. Typically analytics are deep dive, moment-in-time, data-mining exercises that do not provide enough context for informed decision making. Without the additional context of mapping, orchestration, and trended dashboard capabilities, analytics just provides data without actionable intelligence.