Digital transformation (DX)
Digital transformation (DX) has become a buzzword and for a good reason. Depending on who you talk to the market size is estimated to reach anywhere between $400 billion to $2 trillion by 2025. Part of the reason for the wide range in estimates is the definition of what constitutes a digital transformation.
For the purpose of this article we will use the definition as defined by Wikipedia below:
Digital Transformation (DX) is not necessarily about digital technology, but about the fact that technology, which is digital, allows people to solve their traditional problems. ” – Wikipedia
Missing element in current Digital transformation strategies
As part of DX strategies majority of organizations are focused around improving their internal technologies, operational procedures and offering intuitive self-service interfaces to their customers. While a majority of these initiatives are well-intentioned the challenge organizations are running into is that the vast majority of digital transformation initiatives fail.
“Virtually every Forbes Global 2000 company is on some sort of digital transformation journey. Some are getting it right and others struggle. Basically, one in eight got it right.” ( Source: Forbes – Why 84% of companies fail at Digital transformation by Bruce Rogers).
One of the major reasons for such a high failure rate is focused around technology offering and not making CX management one of the key drivers for digital transformation. CX management involves understanding every journey customers undertake and actively listening to customers’ feedback across multiple channels. Without listening to customer feedback and taking actionable measures organizations might be solving the wrong problem or make the problems worse than what they were prior to the transformation undertaking.
A comprehensive study done by MIT Sloan management review very aptly describes the key problem with current digital transformation initiatives.
”When we looked at customer satisfaction scores across all retail bank customer profiles, we found that digital-only customers had the lowest scores. Put simply, personalization and customer experience have taken a back seat to ease of use and digital reach.” – MIT Sloan Management Review ( Bernardo Rodriguez).
Based on similar findings from other leading research studies on this topic it is becoming clear that enterprises both B2B and B2C need to make customer experience (CX) management focal point of their digital transformation (DX) initiative.
In today’s digital world customers have wide options to communicate their preferences, dissatisfactions, and requirements across multiple channels to their product & service providers. The first step in CX management is to ensure customer feedback is gathered and analyzed. So it is imperative that organizations create omni channel customer feedback listening mechanism.
Creating an omni channel Customer Experience (CX) strategy
To create a successful CX strategy firm have to address several organizational structural issues and leverage relevant technologies for omni channel customer feedback analysis. Some of these key actions include:
BREAK ORGANIZATIONAL SILOS FOR CUSTOMER FEEDBACK ANALYTICS
Major challenge that enterprises have today when it comes to analyzing customer feedback is the silo’d nature of the organization structure as outlined below. In addition, unified customer feedback analytics are not widely available across the organization.
It is clear from the above depiction that information sharing regarding customer feedback across channels is lost. Some recommendations to address this issue.
Include CX management as part of core digital transformation (DX) initiatives to ensure proper strategic alignment and visibility at the organization level. In terms of organization structure, there should be a centralized CX leader (possibly reporting to CEO/CTO) to ensure customer feedback analytics collected by Product Marketing, Customer support, CX teams, and social media teams is centrally organized and accessible.
A unified platform approach to share customer feedback analytics across channels to every employee in the organization. A role-based access should be considered so different employee groups have access to different customer feedback analytics. This ensures organization-wide visibility into customer analytics thereby creating a unified CX management vision.
USE AI/NLP CAPABLE PLATFORM FOR CUSTOMER FEEDBACK ANALYTICS
For a scalable and flexible 360 degrees view of customer feedback analytics, it is critical that enterprises leverage a true AI platform that specializes in unstructured data analytics to analyze and tie them to business initiatives. Some typical attributes of platforms supporting customer feedback analytics should include:
Consume data in unstructured format from typical customer feedback channels like Email, Chat, Call center recordings, Twitter, Facebook, NPS scores, survey data, and external review sites.
Support for domain-specific ontologies and lexicons. There should be a mechanism through the platform for enterprise customers to plug-in their own domain-specific terminology.
Offer advanced NLP capabilities including sentiment scores, emotion detection, intents at corpus/document/sentence/clause level and auto-detection of categories, entities, phrases, keywords, etc.
True Machine learning capabilities to learn from existing data and improve text analytics accuracy iteratively.
Ability to create predictive models with what-if analysis by correlating customer feedback analytics (unstructured data) to enterprise data. For example, a hospitality client might be interested in correlating customer feedback to occupancy rates and come up with predictive models for occupancy rate so they can better understand revenue impact. Similarly, a telecom company might be interested in understanding the root cause of customer churn based on customer sentiments.
IDENTIFY CUSTOMER JOURNEY ACROSS DIGITAL AND TRADITIONAL CHANNELS
One of the primary challenges business face when it comes to Customer experience management is to pro-actively identify customer pain points before a customer churn happens. Identifying customer journey across channels and coming up with insights will greatly help enterprises in identifying root causes for customer dissatisfaction.
As part of customer journey analysis enterprises should ensure below analytics are captured to ensure meaning business impacting analysis.
Customer touch points in realtime for products/services across the offering channels. Resulting data points should include a sequence of customer interactions along with specific actions they took. For e-commerce sites this is typically this is achieved through Clickstream analytics.
Intuitive customer journey map that is easy to understand. Journey map should include customer sentiments where possible along with trends over time.
Tie customer journey analytics to customer feedback analytics that aligns with business objectives. This could provide a root actionable insights and root cause analysis of for example why a customer is churning.
A typical customer journey framework is illustrated below
CREATE ACTIONS FROM CX INSIGHTS
The final step—and the most critical one for businesses—is taking customer experience insights and turning them into action. Whatever platform businesses choose they should have a mechanism to create actionable items based on pre-configured threshold levels. Some typical notification mechanisms might include:
Notify account manager via email/text alerts if a customer sentiment on a specific channel or across channels dips below a threshold level.
Automatically create a case and assign to support team when customer satisfaction score or sentiment dips below specific levels.
Track performance trend over time. Using customer sentiment as a Key Performance Indicator (KPI).
Enterprises are optimizing traditional processes and systems as part of their digital transformation efforts. It is crucial that customer experience (CX) management is considered a core component of the digital transformation journey. Several advances in AI & Natural Language Processing (NLP) technologies are making it feasible to process unstructured customer feedback data from multiple channels. This feedback along with understanding customer journey forms the backbone of a CX management strategy.
How is your organization’s Customer Experience management progressing? Are there any firsthand lessons you learned that you like to share? Would love to hear your thoughts in the comments below.