To elaborate further on last week’s post, let’s delve a little deeper on how implementing a business intelligence (BI) strategy can help improve the telecom customer experience.

For many telecoms, managing the churn rate is vitally important. For example, Shaw Communications recently saw dips in its stock price that exposed concerning churn numbers. It’s a metric that is reviewed at the highest levels as it reflects the company’s complete offering, from pricing and options to the overall customer experience. And it’s the customer experience that powers the entire business. Improving this metric can be achieved through targeted usage of business intelligence applications that provide insights into what is and what is not working for the consumer.

BI can help shape the telecom customer experience by helping companies manage multiple touchpoints, retain dissatisfied customers, and better manage social interactions.

Managing Multiple Touchpoints

According to a Harvard Business Review article, customer satisfaction is not usually ruined by one poor interaction, it is due to “the sum of cumulative experiences across multiple touchpoints and in multiple channels over time.” Managing the entire customer experience takes a concerted effort from service, marketing, sales, and every other area of the business to always ensure the customer’s needs are met and the product itself is flawless.

BI insights provide each of these groups with information they need to make the customer experience seamless from touchpoint to touchpoint – an omnichannel experience. Did the customer contact chat support a week ago about poor cell reception and today they’re in an outlet store? The outlet employee better have access to the chat transcripts so they can quickly assess the situation (calm any anger) and offer an update. The data can also be used by IT staff, if for example they see a sharp drop in new prospects coming through the website, then perhaps there’s a web form glitch or other problem.

Convincing Customers to Stay

Many telecoms employ “save desk” teams at retail outlets, or in the call center. The goal of these groups is to “save” the customer’s business, meaning to retain them with a more attractive contract. Save desks have the most success when they can present a compelling argument to the customer, one that lays out the benefits of the firm, any new programs, and other information? Business Intelligence applications can be invaluable for these teams because it can correlate departed customers with reasons for their dissatisfaction. This granular data can be extrapolated for groups to spot trends in customer pain points, which can be further reviewed against customers that complain but are ultimately retained. While every customer is unique, the save desk teams are much better prepared when they are armed with information that details frequent complaints and suggested proven remedies.

Standing out on Social

Business intelligence applications can not only pull in transactional and operational data between customers, but also data that can be pulled from social media such as Twitter, Instagram, and Facebook. Customers are increasingly taking to social channels to vent their frustrations, and also to engage with customer service.

BI should be an important part of your social media strategy because of its ability to aggregate information and allow marketers to view the overall sentiment of the customer base. The benefit lies in spotting emerging trends. For example, a telecom firm restructures its data plan, which it touts as being simpler and a better deal for customers. If there is a swell of negative social media commentary about the plan’s complexity and how it ultimately costs more, then it’s important to understand this trend quickly. Nimble companies can work those social channels to provide more information while they look at other numbers to see if their plan is indeed flawed. The sentiments from social channels can be combined with data from support chats, phone calls, and in-person retail store visits.

Business intelligence applications can be powerful in shaping the telecom customer experience because they generate correlations between sometimes seemingly unrelated actions or data. It can for example uncover a spike in churn to be caused by not only be geographic service outages, but also a shift in subscriber plans that was misguided. It’s putting together two distinct data events and allowing the user to generate insights, instead of relying solely on intuition and guesswork.