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2020 predictions: Analysis VS analytics

(Image credit: Image Credit: Bluebay / Shutterstock)

1. How has the data analytics market evolved to date?

The last ten years or so has seen significant growth for the analytics market, driven by a definite shift away from analysis due to the opportunities and business benefits the analytics process can provide. This is especially true in today’s contact centre industry, where competition revolves around analytics rather than analysis. The effective use of analytics has become a valuable tool for businesses to truly understand their customers, provide a seamless experience across all channels and differentiate themselves from the competition.

Part of this recent market growth has been powered by a string of high-profile data-related incidents (Marriott International, Tesco Bank), as well as the increasing prominence of regulations such as the General Data Protection Regulation (GDPR). This, combined with the threat of hefty fines like the £183 million paid by British Airways in 2018, has forced organisations to take a closer look at how they are using data and whether they are able to provide the combination of privacy and personalisation that customers now demand.

2. How have organisations responded to the developments in the analytics market?

It’s no secret that today’s organisations are under more pressure than ever, facing several challenges when it comes to expanding and attracting new customers. As such, innovation is essential. Contact centres have to be able to predict customer needs and then meet these needs while delivering a superior customer experience - which is where analytics, not analysis, can help.

Whereas analysis is focused on understanding the challenges or opportunities of the past, analytics involves the programmatic study of data to uncover potential trends, to investigate the effects of decisions or events, or to evaluate the performance of a given tool or scenario. As analytics has evolved from descriptive, to predictive and now to prescriptive, businesses have had to evolve as well and embrace new processes.

Analytics has become a crucial area where business intelligence and contact centre performance are closely linked. The ability to use analytics for quality management across the entire workforce and drive operational improvements provides a powerful competitive advantage, while also elevating employee engagement and performance.

For example, it helps organisations to automatically analyse customer interactions. Agents receive next-best-action recommendations through predictive analytics and to get automatic alerts for the most problematic interactions. Analytics enable them to optimise average handle times, reduce call volumes, decrease hold times, increase first call resolution rates and even predict problems before they occur.

However, the challenge is that performing this level of data analytics requires a large amount of data and metadata. Businesses, therefore, need access to solutions that can help them adapt with ease and meet customer expectations, deploy quickly, be up to date and scale with use. Most legacy on-premises solutions cannot fulfil these requirements due to various reasons, so businesses have had to turn to cloud-based operations that provide flexibility, scalability and accessibility.

3. What’s the biggest challenge facing businesses?

When it comes to analytics, businesses have several challenges to overcome. However, the key challenge they all face is being able to cost-efficiently capture the sheer amount of data required. Then have to work out how to process and best use this combination of structured and unstructured data so that they are able to generate useful insights.

4. What advice would you offer to businesses in terms of leveraging the right tools and approach to yield the best results?

Organisations still need to have face-to-face interactions with their customers, but also provide an omnichannel experience, including digital touchpoints on social media, messaging and live chat. It’s all well and good to offer support across these channels, but you need to be able to match all the touchpoints accurately. However, it’s simply not enough to employ a few analysts and data experts; businesses need solutions that can be embedded as a core process throughout the workforce.

With the use of analytics, managers can uncover actionable insights that ensure front-end processes, back-office processes and performance metrics are closely tied to top-priority objectives in near real-time. Organisations can more effectively manage and eliminate common challenges, such as over or understaffing and the creation of time-consuming business reports.

Despite the growing importance of a well-organised back office, operations are often marred with complexities. Typical back-office activities max out productivity at around 50-60 per cent. However, with analytics software, productivity can increase in the range of 10-25 per cent. Data analytics can cut through business complexities by providing a real-time view of operations, highlighting process inefficiencies and providing time-saving alternatives. 

5. What’s the future of data analytics, and how will it disrupt businesses in the years to come?

Data analytics is going to have a key role to play in the future of contact centres. We’ve already seen the rise of descriptive and predictive analytics – used to describe interactions, predict customers’ needs and anticipate their questions – but the market is set to go one step further as it develops over the next few years. This will see prescriptive analytics come into play, providing employees with intelligence and advice on what they should do next when engaging with customers in order to improve the interactions. Using this type of analytics to explain why issues occur and how to fix or avoid them will be a main point of differentiation among customer experience competitors. And it’s not just customer-focused, as it can also be included in employee training to helping enhance their soft skills.

Another major trend will be the increasing adoption of machine learning and artificial intelligence (AI)-driven capabilities, which will be incorporated into analytics platforms. For example, these technologies can help businesses highlight phrases that indicate customer satisfaction via sentiment indicators or provide cross-channel insights into service anomalies and customer pain points.

With AI and machine learning in place, contact centres will be able to quickly identify issues and take immediate steps to resolve them, thereby providing an improved customer experience.

Jonathan Wax, VP EMEA, NICE Nexidia