Advisor

What’s Hindering Organizations’ CX Management Initiatives?

Posted February 22, 2019 in Data Analytics & Digital Technologies

To meet increasingly elevated customer expectations, organizations are implementing detailed strategies for distributing and standardizing customer experience (CX) practices and technologies across their various lines of business.

Results from an ongoing Cutter Consortium CX management survey show that approximately 71% of organizations either now have, are planning to develop (within the next 12 months), or are seriously investigating detailed strategies for deploying CX practices and technologies. However, the survey also finds that organizations are struggling with a number of issues that are hindering their CX efforts.

According to surveyed organizations, the top five biggest challenges (ranked by importance) impeding their efforts to implement CX strategies and supporting technologies include:

  1. Inability/difficulty in providing a seamless CX across all customer channels

  2. Difficulty defining and mapping what the customer journey/experience should be

  3. Lack of CX professionals within the organization

  4. Outdated customer service and customer information systems

  5. Data integration and data integrity issues

Organizations are struggling to define just what the CX should be and with how to ensure that it is cohesive across all their virtual and actual properties and LOBs. They also indicate that mapping customer journeys can be complex. Consequently, they are turning to various technologies to assist them. Two technologies often cited by survey participants are customer intent/journey mapping and analysis tools, and omni-channel customer engagement hubs and marketing platforms. Others include behavioral modeling/analytics and AI.

Organizations are using the former to visualize and analyze the journey customers take, and the experiences they encounter, across an organization’s channels, to effect better (and standardized) CX and customer satisfaction in general. Some of these tools primarily provide general visualization and mapping capabilities. Other, more advanced tools bring statistics and other quantitative and qualitative findings from various customer touchpoints into the mix to support more detailed analyses.

Organizations see omni-channel customer engagement hubs and marketing platforms as a way to better manage customer data and for supporting multi-channel (e.g., mobile, social, messaging) marketing and loyalty initiatives via their real-time customer interaction capabilities.

Customer analytics and behavioral modeling also play a major role in organizations’ CX efforts. This includes for analyzing customer interactions, identifying trends and patterns, and for building detailed customer profiles, which organizations can use to optimize omni-channel customer engagement hubs and marketing platforms.

Organizations show a strong interest in using AI to assist with more advanced CX initiatives. AI-powered bots (i.e., “smartbots”) and intelligent virtual assistants are getting lots of attention. They are seen as especially applicable for mobile, voice, and chat-driven sales and customer self-service systems that offer advanced capabilities for understanding user wants and needs that go beyond standard keyword-based solutions.

You might have thought that with many organizations today having well-established data warehousing and business intelligence practices that data integration and data integrity issues would not be a major factor when it comes to CX management. However, that appears not to be the case, as surveyed organizations indicate that they are finding it difficult to integrate data because of outdated customer information systems. These same outdated systems also pose problems for organizations in their efforts to provide a (seamless) CX across all their customer channels.

Data integration issues are likely to intensify due to the trend in which organizations seek to integrate CX data sourced from systems of engagement (social media, mobile apps, surveys, and other customer feedback platforms) with operational data (from ERP and other enterprise systems, etc.) to effect more dynamic CX management. The goal: to respond faster to rapidly changing customer expectations. This is why SAP bought experience management software provider Qualtrics last November.

Finally, as you would expect, organizations say that all of these issues are further complicated by a lack of internal staff experienced with CX practices and technologies.

That said, even while confronted with all these issues, as I noted before, more and more organizations are proceeding with CX management initiatives.

Further Research

If you have not done so already, I urge you to please take our CX survey on how organizations are adopting or planning to adopt CX management practices and technologies.

We would like to hear from organizations regarding what they see as the benefits and opportunities offered by CX practices and technologies and if they are actually achieving such benefits as a result of their efforts to date. We also want to identify the specific CX practices and technologies they are using, and the important issues and other considerations organizations are encountering in their CX efforts.

I thank you in advance for your help. Your input is extremely important because it helps us separate fact from hype, providing us with actual technology adoption and usage trends you can use to measure your own organization’s CX adoption efforts. I will report my key findings in upcoming Cutter research. You can comment at the link, below, email me at chall@cutter.com, or call +1 510 356 7299 with your comments and questions.

About The Author
Curt Hall
Curt Hall is a Senior Consultant with Cutter Consortium’s Data Analytics & Digital Technologies and Business & Enterprise Architecture practices. He has extensive experience as an IT analyst covering technology trends, application development trends, markets, software, and services. Mr. Hall's expertise includes artificial intelligence (AI), cognitive systems, machine learning, conversational computing, and advanced analytics. He also… Read More