Author: Mike Hughes, European MD, 24 7 www.247-inc.com
The rise of big data over the past decade has been one of the key technology trends of that period. Throughout Big Data Week you’ll hear about enterprises using big data to make informed decisions about their organisation and improve business functions such as sales and marketing.
Yet given the depth and breadth of big data and how it can provide remarkable insight into customer behavior and intent, few organisations are using big data to improve the customer experience. Customer service is in fact an area that has been relatively untouched by technology. There are more channels to use than ever before but the nature of the customer experience has not really moved on in the same way.
Omnichannel customer service
Consumers are increasingly using their mobile devices to connect to the web using social networks such as Facebook and Twitter and they expect to interact with organisations at their convenience, using smart mobile devices and employing multiple channels. Recent 24 7 research showed that 93% of consumers regularly use multiple channels when interacting with a brand’s customer service. Consumers now expect and demand the same levels of customer service, irrespective of channel. This has given rise to omnichannel, a key development in customer service that focuses on improving the complexities in customer interactions and enabling a multi-channel (online, mobile, speech, chat, store), multi-modal, and multi-device experience.
Brands need to develop a seamless, omnichannel experience to ensure that the customer is taken through the same simple steps regardless of whether they’re engaging online, speaking to a representative on the telephone, using smart phone functionality or a combination of these. Most organisations already have all the data they need to deliver this modern and intuitive service which could make their customers’ lives easier.
There has never been more data with which a brand can analyse to better understand its customers and learn their intent, history and preferences. It is possible to mine every single customer interaction, including transactional history and customer data from ERP and CRM systems; CRM data on billing history, past purchases, and loyalty programs; location data from smartphone or tablet apps; click-stream and web behaviour data from web analytics software and chat or voice interaction transcripts from contact centres.
Delivering a predictive experience
Big data can in fact be used to anticipate and predict issues before they even occur. This is achieved by analysing the customer data and developing smart models which learn to adapt and intuit customer needs. Using these big data techniques to reduce customer effort will pay dividends in brand loyalty and reduced resources required for managing enquiries and complaints. However, the benefits can also extend into the development of a platform which can support cross-selling and upselling as the system learns to understand customer requirements and patterns and can suggest relevant complementary products and services.
Ultimately, modelling the customer journey has benefits for the customer and the brand. Customers get a more relevant, efficient and omnichannel service and brands get the increased loyalty and improved efficiencies that come with that.
Big data can help companies anticipate what consumers want, simplify customer service interactions, and learn from those interactions so that future experiences are constantly improving. It helps brands deliver vastly improved, omnichannel customer service.
Of all the ways in which big data has impacted business, surely one of the most interesting is how it has enabled such improved customer service?