It’s a maxim as old as business itself: in order to succeed, you must first know your customer. With the data analytics and customer experience analytics technologies available to modern organisations, we’ve never had such a clear and deep insight into who the customer really is: what motivates them, what are their pain points, their barriers and objectives, and what they want.
Of course, something that every customer wants regardless of industry, is a smooth and efficient customer experience (CX). That means personalised interactions, streamlined processes, satisfactory resolutions and a meaningful, rewarding journey.
While this is not a given, it’s a standard worth chasing: 9 out of 10 organisations compete in terms of customer experience, according to SuperOffice, and 86% of consumers will actually pay a higher price for an improved CX (SuperOffice). Applying this in real terms enables potentially-revolutionary business benefits: McKinsey found that ‘data-drive’ organisations are 23x more likely to acquire new customers, 6x more likely to retain existing customers and, as a result, a staggering 19x more likely to be profitable (McKinsey Global Institute).
Data analytics – more precisely, the insights afforded by customer experience analytics – allow your organisation to reliably deliver an outstanding CX, time after time. Understanding data analytics to improve customer experience is a vital ingredient of elevated communications and ongoing business success; today, we’ll inspect this in closer detail.
What is Customer Experience Analysis in 2023 and Beyond?
Customer experience analytics is the process by which you gather, record, interpret and analyse user information related to your customer interactions. It also includes the way you use data analytics to inform your customer experience strategy and execute an ongoing CX strategy.
Detailed user data, buying patterns, motivations, pain points and history of interactions are all included as part of the customer experience analytics model.
Who benefits from customer experience analytics?
The short answer is: everyone benefits from customer experience analytics.
With a properly-executed CX strategy, each and every one of your customers stands to gain from a streamlined, personalised and overall improved customer experience.
Likewise, your entire organisation will feel the benefits of data analytics. Customer relations agents and support staff will be equipped to perform their job responsibilities at a higher standard, because they’ll have the customer analytics infrastructure needed to support clients in a more effective way. This will mean improved employee retention rates and higher rates of staff fulfilment.
Equally, support managers will oversee a more valuable communications department, and therefore be able to achieve higher, more ambitious operating KPIs. These key metrics can be the evidence you show to senior management and stakeholders, helping to convince them in signing-off new projects or green-lighting expansion projects.
In short, your customers will benefit from an improved service, and your entire organisation will benefit from more informed decision making, all as a direct result of customer experience analytics.
Data Analytics Role in Improving Customer Experience
Customer experience isn’t a matter of ‘hit and hope’. Even minor changes to the user journey can have dramatic consequences for the final CX; and, while it’s possible that you’ll blindly guess your way from right decision to right decision, the chances are that sooner or later you’ll start damaging the customer experience.
This is why you’ll need data analytics to improve customer experience.
Collecting information is the first stage of customer experience analytics, but the tale doesn’t end there. In order to turn that information into a competitive advantage, you’ll need to conduct analysis and interpret the raw numbers into something actionable.
Customer analytics is the process of illuminating and following the best path forward through statistical insight and informed decision making.
However, this is easier said than done. In the Closing the Customer Experience Gap Report by Harvard Business Review, only 3% of organisations said they are equipped to act on the customer data they collect, and 21% reported a very low ability to respond to data analytics (Harvard Business Review).
Predictive analytics
One way around this issue is to implement predictive analytics.
This is the implementation of computer modelling and predictive algorithms to reliably predict future realities. Predictive analytics works by analysing present and historical data to identify trends (in buying patterns or consumer behaviour, for example), and establishing the likelihood of these trends repeating with predictive algorithms.
This allows your organisation to be proactive about the customer experience by optimising it ahead of time.
As Investopedia puts it, predictive analytics allow “businesses and investors to adjust where they use their resources to take advantage of possible future events. Predictive analysis can also be used to improve operational efficiencies and reduce risk” (Investopedia).
Predictive algorithms are one of the future-proof functionalities your organisation is set to take advantage of by implementing our Virtual Contact Centre. Our VCC software can help you mine data regarding the customer experience and optimise it before the fact.
Protecting and Growing Your Customer Lifetime Value (CLV)
One of the key metrics by which your communications team will be judged is customer lifetime value (CLV); that is, the overall value the average customer represents to your business, from the start of their purchasing lifetime to the end.
Your communications are only profitable when they are ‘in the black’, or when the CLV outweighs the total amount of investment in each customer. Customer retention is the key ingredient of positive CLV because, comparatively, keeping customers is much cheaper than acquiring new ones – 5x cheaper, to be precise (Invesp).
It’s something of a simplification, but you can actually draw a direct line between customer retention and profitability, via CLV. And, going forward, how do you make sure your CLV is as healthy as it should be? By implementing data analytics to improve customer experience.
To increase profits, improve CLV; and to improve CLV, use data analytics. That’s the heart of the matter.
How to Use Data Analytics for Better Customer Experience
There are a number of ways you can use data analytics to improve customer experience. Data is a wonderful thing in optimisation terms, partly because it’s so flexible; you can pull together potentially-limitless combinations of various data sets, concerning all manner of different things, and bring them to bear on specific improvements throughout your communications department.
Below, we’ll outline three key ways data analytics can improve your customer experience.
Meet the customer in their preferred channel
Half the battle with customer experience is knowing where an individual customer prefers to communicate, and meeting them there – and, crucially, doing so at the right time.
Where some customers prefer to interact with a brand via email, for instance, for others, this is a real annoyance. Some users may enjoy a phone call with a human agent, while others are more interested in live web chat, or social media interactions.
Customer experience data analytics can give you this information at an individual level, and allow your organisation to meet customers in their preferred channel. In user communications, after all, the medium is often as important as the message.
Use data to inform personalisation
It’s well-documented that a large part of the customer experience relies on unique, tailored experiences.
Any company that provides ‘cut-and-paste’ email replies, for example, or needs to repeatedly ask a user to confirm their name and address, is setting itself up for difficulty.
The best customer experiences are so successful because they make the relevant customer information accessible when, and where, it’s needed. This is gold dust for the customer experience strategy.
Customer segmentation insight with analytics
In the same way that customer analytics can provide insight into individual customers – including their behaviours and buying patterns – the same is true for entire user demographics.
Through data analytics, you might find that male customers aged 41-50 in the UK are more responsive to emails sent 5-7pm Mon-Fri, than at the weekend, for example. This is a potentially-valuable piece of customer information that you can leverage, and use to create the conditions for success with an entire user segment.
Illuminate areas of competitive advantage
Data analytics make it incredibly simple to find out exactly what customers love most about the experience you deliver. As well as giving you the opportunity to give you and your support team a well-earned pat on the back, this information actually shows you where your organisation excels in comparison to your competitors.
According to Gartner, ove 66% of companies compete directly in terms of their customer experience (Gartner), so it certainly pays to know which touchpoints and CX elements are working best for your business. Data analysis can give you that knowledge.
Optimising Customer Experiences With Our VCC
As we’ve seen, data analysis and the savvy interpretation of customer information are key pieces of customer experience optimisation. With our Virtual Contact Centre technology, that data (and the subsequent customer experience analytics) are at your fingertips.
For every organisation – whether they operate in the charity, construction, public services, retail sectors, or any other industry – CX really is a make-or-break consideration. Improving it is a journey all organisations must commit themselves to – but, in order to ensure a successful optimisation strategy, data is the fuel that will take your organisation from strength to strength.
Discover the ways our VCC can transform your communications and revolutionise your customer experience strategy – book a free discovery call with our team today.