By Deon Scheepers, Customer Engagement Executive at Pivotal Data
Digitisation is transforming the modern consumer landscape as technology increasingly influences expectations and preferences around engagement and customer experience (CX).
When modern, digitally-empowered consumers engage with a contact centre, they expect personalised service across all interaction points and meaningful and relevant experiences.
Contact centres that fail to keep pace with this evolving customer paradigm and continue to engage consumers in the traditional way, accommodating only legacy communication channels, will fail to meet these new demands.
The ability to individualise engagements across channels to a segment of one has, therefore, become a strategic imperative for contact centre operators that want to maintain relevance and compete effectively in the digital marketplace.
To do so requires a deep, granular understanding of the customer. Thankfully, contact centres have experienced an explosion in customer data due to digitalisation.
Today, most contact centres collect massive amounts of data with every interaction, but the challenge they face is managing and analysing these datasets to extract those salient insights that can best inform actions.
To improve customer experience, service and, ultimately, outcomes, contact centre operators need to apply intelligence to customer data to create a rich, unified view of the consumer and contextualises their individualised needs and preferences.
These capabilities then create opportunities to deliver the hyper-relevant and hyper-personalised services expected from modern digitally-enabled contact centres, and do so at scale.
But due to the sheer volume of data, humans are incapable of effectively processing these big data sets to extract this intelligence. As such, the right business intelligence solution is required to deliver a strategic advantage to contact centre operators.
Fortunately, operators can leverage technologies such as artificial intelligence (AI), machine learning (ML), natural language processing (NLP) and automation to more efficiently and effectively mine large data sets and extract actionable insights through advanced analytics engines.
Given the rise in omnichannel engagement capabilities, it is imperative that contact centres enable these analytics capabilities across digital and voice engagements to monitor 100% of contact centre interactions.
In this regard, contact centres should select solutions that offer analytics capabilities across speech and text, as this functionality creates opportunities to convert customer interactions into business outcomes.
This functionality can significantly improve contact centre quality assessment processes, which gives contact centre managers the ability to rate agent performance against benchmarks. These analytics tools can also reveal insights that improve agent training or inform best practices to further enhance CX.
Importantly, these tools analyse specific customer interactions, which helps contact centres better understand their customers as individuals, and these insights help to craft and deliver the hyper-relevant service that modern consumers demand, regardless of the channel through which they prefer to communicate.
And this ability to monitor customer movement between channels and identify them immediately, without a loss of context or relevance, is a critical function required amid shifting consumer engagement habits.
For instance, digitally-connected consumers tend to switch seamlessly between devices as they move between their smartphone, tablet and PC, often switching from voice to digital channels on demand.
Effectively tracking customers and responding to their demands in an omnichannel contact centre environment requires customer journey analytics capabilities, as this powerful tool can automatically track engagements in real time.
Over time, this analytics engine will stitch together every customer interaction point to plot the customer journey in a manner that can prioritise engagement opportunities and pre-empt customer requirements to significantly enhance the contact centre’s business impact.
Ultimately, data analytics is the foundation on which all customer intelligence should be built in modern contact centres. Big data is no longer a strategic differentiator as everyone has access to information. What matters most are the insights we can extract from the customer data to shape distinctive CX and keep step with constantly evolving consumer preferences.