Organisations struggle to align their CX strategies to voice of customer (VoC) feedback, with 59% having no formal process for considering this data and 14% which capture no feedback at all. Only 16% fully define, and track the value contribution of CX and less than a third (32%) are able to connect data relationships between channels – leaving the rest operating ‘blind’ with no full view of the customer ecosystem. That said, the collection of VoC feedback by organisations is improving year on year - there has been a 45% improvement globally since 2019 in those capturing some form of feedback and 7% now perceive their VoC programme to be at an advanced level across all channels.
“Customer expectations are higher than ever - businesses cannot afford to fail in CX,” said Rob Allman; Senior Vice President, Customer Experience at NTT Ltd. “However, most companies are missing valuable insights that are integral to better connect with and stay relevant to customers across every touchpoint. By listening to the voice of the customer, integrating data across systems, in addition to adopting emerging technologies like AI and RPA, companies have the unique opportunity to gain a competitive advantage.”
Listening starts with strategy
A successful CX strategy is proven to improve customer and brand engagement, and drive commercial performance, yet many organisations are still stuck in the developmental stage due to siloed technology systems, inconsistencies in experience, and a lack of clear processes. Specifically, challenges include:
Creating a smarter CX with data analytics
While almost three quarters (73%) of organisations indicate that they are satisfied with their customer satisfaction capability, only 10% of their customers rate customer experience at ‘advocacy’ level. Worryingly, just 2% of AI and robotics users say customers rate their experience at advocacy level, exposing the gap between emerging technologies and satisfaction levels.
This demonstrates that businesses need to create a smart strategy which bases AI on optimum data, organisations must learn to fill the gap between data management and integration, and prioritise an efficient data management platform. As it stands, less than half (41%) of data capture needs are defined and aligned to desired business outcomes, and just 26% have a dedicated team managing the company’s entire data lake. In fact, 18% have no data management strategy at all. Because of this, data is becoming increasingly difficult to manage. More than half (54%) of all teams are evaluating and learning how to use available data and over a third (34%) do not have the required data management skills or resources to do so.
An increasing number of organisations are moving towards the use of smart data to inform CX decisions but are often overwhelmed by this transformation. Half of businesses confirmed data analytics and data management will be one of the top three tech initiatives prioritised by the CX team. Analytics (54%) is expected to be the top factor in reshaping the CX industry within the next five years. This is closely followed by artificial intelligence (49%), technology integration (43%), and service personalisation (44%).
Overcoming business organisational structure challenges
Many organisations believe AI and automation is the future for creating operational efficiency, hyper personalisation and providing an effortless customer experience. Rules-based robotic solutions “are the preferred option both now and in the short term with AI being the top five year priority.”
The vast majority (78%) of organisations also believe customer operations will be positively impacted by AI and CX robotics in the future, followed by business insight and customer intelligence (53%) and workplace management/operational productivity (51%). However, the implementation of AI remains difficult. Looking forward, businesses must find a solution for the current lack of skills across the business, which is currently considered a challenge for more than half (57%) of organisations today.
“Businesses must look at how technologies such as AI and RPA can work as part of their organisational team structures,” said Allman. “But to do this successfully, AI needs to work with the voice of the customer data which is collected by advanced social listening tools. This data must also be compiled from across the business’s value chain in order to help AI realise its potential. Therefore, design thinking and an ecosystem focused approach is imperative.”