How to Improve CX with Analytics

Business leaders have long identified Customer Experience (CX) as a strategic priority. Even though 80% of them say it’s a high priority, according to Forrester’s CX Index, only 6% of businesses saw any improvement in their CX during 2023.

That’s despite billions of pounds of investment in CX programmes and technologies.

So, what’s the problem? Why can’t companies that say improving their CX is a top priority manage to do it?

Roadblocks to improving CX

According to Forrester’s research, brands struggled to consistently deliver across the three crucial CX criteria measured: ease, effectiveness, and emotion. In 2023 the average score dropped in all three areas, although ease and effectiveness scored lowest.

The decline in emotional performance impacted brands’ ability to deliver satisfying experiences. For every negative emotion, such as frustration or annoyance, invoked by customer interactions, 29 positive emotions were reported. That might seem like a good ratio, but it means that at least 3% to 4% of interactions are not hitting the mark.

Forrester identifies several potential issues that could be causing companies issues when it comes to improving their CX.

Keeping up with evolving customer demands: A significant challenge for brands is the continuous escalation of customer expectations. Meeting these growing demands in a scalable and consistent manner, especially in the face of economic constraints, is challenging. Understanding these demands and how they might evolve could help brands prepare to meet them better.

Lack of clarity: Some organisations believe that becoming customer-obsessed is a key to improving CX; however, they conflate the two ideas. Customer obsession simply means putting customers at the heart of the business. CX is how you deliver and measure customer experiences. A lack of clarity over the goals of CX, regulatory concerns, or what customers want can lead to overthinking, decision paralysis, and the deployment of ineffective strategies.

Resource constraints: The recent tight job market has presented significant challenges in scaling CX efforts and meeting rising customer expectations. Financial constraints in the current, uncertain economic climate also bind most businesses. When resources are scarce and precious, businesses require a deeper understanding of how to deploy what they do have most effectively.

Despite these hurdles, certain industries, like luxury auto manufacturers and retailers, have improved their CX quality. This suggests that while the challenges are significant, they are surmountable with focused and strategic efforts. Doing that requires data and insights.

Lack of information

Research by McKinsey may point to the most crucial roadblock of all. Only 7% of business leaders say they have sufficient information to calculate the impact and ROI (Return on Investment) of their CX (customer experience) decisions.

This suggests that businesses are not getting sufficient feedback from their customers or insights into their needs, preferences, and behaviours to direct their CX efforts effectively.

A recent study by Contact Babel surveyed CX leaders on their preferred methods for uncovering customer insights. While feedback from supervisors and agents remains common, more sophisticated methods like customer research calls and speech analytics are gaining traction.

As you can see from the graph below, the most commonly used methods are gathering feedback from supervisors and agents and interviewing customers. Only 58% of those surveyed conduct post-interaction surveys such as NPS or CSAT, while only 51% use speech analytics to mine customer interaction data

Customer surveys vs CX Analytics

Over the years, businesses have developed a suite of tools including post-interaction surveys to measure NPS (Net Promoter Score) or CSAT (Customer Satisfaction), and VoC (Voice of the Customer) research programmes, which use interviews to gather this data.

These offer a quick snapshot of customers’ feelings towards the company’s offerings. They rely on standardised questions and provide quantitative data that’s easy to analyse.

However, all these methods have limitations, as surveys only capture information from a small portion of the customer base, which might not be completely representative.

CX Analytics encompasses various tools and techniques, including Customer Journey Analytics, Predictive Analytics, Customer Sentiment Analysis, Conversational Analytics, Operational Analytics, and Real-Time CX Analytics.

These tools enable analysts to tap into the wealth of customer insights within the data collected from every customer interaction. This comes in many forms: website metadata trails, transactional histories, and recordings of customer interactions across all channels.

CX Analytics paints a holistic picture of the customer experience. It analyses data from diverse sources, such as website interactions, social media, and customer service, offering both quantitative and qualitative insights. While this approach requires sophisticated tools and involves challenges in data interpretation, it allows you to identify patterns, trends, and hidden drivers of customer behaviour.

Ultimately, the choice between surveys and analytics depends on your specific needs. Surveys are ideal for quickly gauging reactions to specific initiatives or campaigns. At the same time, CX Analytics empowers you to understand the entire customer journey and make data-driven decisions to improve it. Both methods have strengths and weaknesses, and the best approach often involves using them in combination to gain a comprehensive understanding of your customers.

Uses of CX Analytics

CX Analytics transforms customer data into actionable insights, allowing businesses to anticipate needs, personalise interactions, and ultimately, create loyal customers. Armed with this intelligence, you can:

Segment your customer base: To truly understand individual customers, moving beyond superficial demographics is important. CX Analytics allows you to group customers based on past and predicted behaviours, preferences, and needs. This granular grouping unlocks the door to personalised experiences and proactive service, significantly boosting engagement and satisfaction.

Personalise customer experiences: Once you understand individual customer preferences, you can craft interactions, product recommendations, and marketing campaigns that resonate more deeply with each person. This creates a more engaging and satisfying experience, fostering loyalty and trust.

Predict and prevent churn: By identifying those at risk of churning before they even consider leaving, you can intervene with personalised offers, loyalty programmes, or just a friendly check-in. This shift from reactive to proactive engagement empowers you to retain loyal customers, reduce churn, and unlock the full potential of customer lifetime value.

Optimise customer service: Bumpy customer journeys and escalating issues could be a thing of the past. CX Analytics can deliver the insights required to identify roadblocks before they arise, pinpoint potential problems before they escalate, and suggest the best next steps for agents to take during an interaction. By anticipating customer needs, you can deliver a superior, personalised service that fosters loyalty and satisfaction, turning every interaction into a positive experience.

Make smart marketing and sales decisions: Rather than bombard everyone with irrelevant ads, CX Analytics helps you target your marketing campaigns with laser precision, delivering the right message to the right audience at the right time. It also identifies upselling and cross-selling opportunities by uncovering products and services that individual customers will likely be interested in. This translates to more effective marketing campaigns, increased revenue, and a shift from mass marketing to personalised engagement.

Boost CX metrics: CX Analytics doesn’t exist in a vacuum – it illuminates and improves the metrics you already track. From customer satisfaction scores like NPS and CSAT to operational measures like average handling time and first contact resolution, CX Analytics provides deeper insights into the factors influencing those metrics. This allows you to make informed decisions on resource allocation, tailor strategies to drive positive changes in all your CX metrics, and continuously improve the customer journey for long-term success.

Insights that drive improvement

The ultimate goal of CX Analytics is not simply to generate insights but to translate those insights into concrete and actionable strategies. The challenge lies in bridging the gap between data and decision-making to address the roadblocks to CX improvements identified in Forrester’s CX Index report.

For example, understanding how customers’ demands are evolving can help companies plan to meet them by ensuring the appropriate resources and processes are in place.

Clarity around CX goals and objectives – knowing what will move the needle on customer satisfaction – can help companies put the right CX programmes in place and improve their decision-making.

Insights into customer preferences and how their operation works can help companies allocate human and technological resources more effectively – improving the ease and effectiveness of CX metrics.

Finally, and perhaps most importantly, CX Analytics gives deep insights into how customers respond emotionally in each interaction. This can help companies focus on optimising customer journeys and training staff to make customer interactions more emotionally satisfying.