Enrich Customer Journey Design with Customer Analytics

In this age of digital engagement, interaction, and commerce, analyses of customers’ interactional and transactional behaviors with the goal of creating actionable business insights are essential in designing effective multi-channel customer journeys. Business intelligence applications and dashboards are useful for reporting and providing historical or near-real time guidance and trends. However, transforming massive amounts of customer information (structured and contextual) into actionable insights is a significant challenge for organizations of all sizes, across all industries and all geographies.  (See “Delivering Big Data Analytics Insights: Why Choose Between Accuracy, Agility or Speed?”)

Why do organizations seek to design effective multi-channel customer journeys? Customers demand it. Technology has enabled consumers to use multiple channels to interact at the time, place, and manner of their preference. In order to defend or retain market share and to potentially increase top line growth and cost reductions, businesses are compelled to respond to customer demands.

Leveraging Omni and/or multi-channel customer analytics & insights to enrich customer journey design has the potential to:

  • Optimize Omni-channel customer interactions and engagement;
  • Enhance employee engagement via “Guided Intelligence™” (e.g. a version of next best offer);
  • Segment, profile, predict and prescribe best practices for optimal types of customer engagement;
  • Mitigate identity theft, fraud & risk, (See “Customer Identity Authentication: Best Practices in Avoiding Identity Theft, Fraud & Risk.”);
  • Improve operational business processes through a customer-centric lens.

Customer Analytics and Insights

Insights gleaned from business intelligence reports and dashboards are worthwhile for decision support, early warning signals or identifying trends that warrant further investigation before taking action. However, advances in analytical technology (cognitive and machine learning) for example—combined with the proliferation of customer engagement channels has created the potential to fuel Omni-channel customer journey design.

At present, there are five main types of advanced analytics:

  • Descriptive-Identifies customer segments using metrics such as frequency, lifetime value, or behavior, in order to create propensity models.
  • Diagnostic-Explores causal relationships like root cause analysis to better understand why customers purchase or pass on offers.
  • Predictive-Uses customers’ past behavior with seasonal or lifestyle triggers to model and predict future behavior.
  • Prescriptive-Optimizes knowledge from aforementioned three advanced analysis techniques via synthesis, and “what if?” or Monte Carlo simulations to suggest best outcomes in the form of guidance.
  • Cognitive-Bridges the gap among machine learning (automated self-learning from experience and the ability to identify associations), the potential of Big Data and practical decision-making in real time with confidence scores that reflect the accuracy of responses.

It should come as no surprise that enterprise-level Omni-channel customer analytics, similar to Big Data Analytics (BDA), encompass numerous information sources, multiple technologies (software and hardware), nimble business processes and specialized human expertise in advanced analytics. Not surprisingly, this Hypatia Research Group study found that global organizations are successfully utilizing various analytical techniques in the form of these types of engagement.

Figure 1:  Plans to Use Customer Analytics to Improve Journey Design Processes

Enrich Customer Journey Design with Customer Analytics & Insights

Source: ©2016 Hypatia Research Group, LLC. All Rights Reserved.

 

Through the lens of customer engagement, the practical applications of these advanced analytical techniques should be viewed as:

  • Descriptive-Who is the customer?
  • Diagnostic-Why are they engaging with your brand?
  • Predictive-What are they likely to want?
  • Prescriptive-How can your brand best engagement with them?
  • Cognitive-When the customer engages with your brand, your brand knows why, what they likely want, and how best to engage with them based on numerous previous experiences.

Perception Versus Reality

It has never been a better time for organizations that seek to enhance their customer-centric interactions and business processes via multiple channels and preferred touch-points. Performance improvements, cost efficacy and cloud delivery mean that enabling software and services have never been more accessible. Conversely, it has never been a more challenging time to select optimal software-based technologies, services and/or solutions. Why? Because semantics influences a purchaser’s perception as to what is required.

Figure 2: Perception: Customer Experience vs. Customer Engagement

Customer Analytics and Journey Design

Currently there are more than 500 software tools, applications, systems and solutions on the market. Each value proposition claimed is a theme or variation on supporting “customer experience management”, or on improving the “customer experience”. Confusing is that these options encompass multiple software categories–everything from customer relationship management, contact center, voice of the customer, digital marketing, business process management and workflow, text analytics and social media intelligence to workforce optimization, scheduling and contact center solutions.

Our Assessment: Galaxy Vendor Evaluations

Hypatia Research Group has benchmarked the current state of vendors who offer customer analytics and journey design solutions for its Galaxy rankings. We believe that enterprises will be best served by applications, solutions and tools that demonstrated the following features and capabilities:

  • Multi-channel digital marketing;
  • Omni-channel customer engagement & commerce;
  • Real-time interaction management;
  • Customer analytics and insights dashboards with visualization;
  • Multi-channel business process visualization;
  • Operationalizing analytics by embedding them within customer engagement workflows; and
  • Highly adaptable business process workflow configuration.

Our research and analysis reveals that the types of customer analytics utilized are just as important as the business processes developed when combined with the ability to execute on these insights. In other words, customer analytics and insights deliver the “Who”, “What”, “Why”, “How “and “When”, however, the decision to act on this insight in a manual, semi-automated or fully automated fashion is often a key catalyst for innovation, organizational and cultural change.

Further analysis is available in our latest Galaxy study: How Customer Analytics and Insights Enrich Customer Journey Design: GalaxyTM Vendor Evaluations.  ©2015-2016 Hypatia Research Group. All rights reserved. No part of this research study may be re-purposed, distributed, translated or published in any format without the express written consent of the Hypatia Research Group, LLC and its management. Permission to link to this research must be requested in writing.

For advisory services or assistance with vendor selection, requirements gathering or business process mapping, contact Research@HypatiaResearch.com. For information on licensing, reprint or purchase of research, please contact Research@HypatiaResearch.com.

1 Guided Intelligence™ trademarked by Hypatia Research, LLC.