The communications industry has seen an unprecedented growth in data over the last few years. With smart phones bringing internet access to practically every household, content consumption has increased significantly. Now, imagine the amount of data generated in the global communications ecosystem, as billions of people interact through smart devices. And since communication service providers (CSPs) have access to this ‘voluminous’ data, they are sitting on a gold mine of information. CSPs can use Big Data and analytics to derive vital insights about customer preferences, behavior, and usage. These insights, when plugged into decision support systems, will undeniably drive better business outcomes.
Creating targeted marketing strategies was never this easy
As the communications space becomes increasingly commoditized, thanks to so many attractive options from multiple CSPs, Big Data and analytics can come to rescue. Armed with insights on buying patterns and browsing behavior, companies can refine their marketing strategies to ensure customers stay engaged with their brand for as long as possible. Not only this, Big Data and analytics can help companies identify, forecast, and prevent customer churn – a common problem in the communications industry. According to this report, T- Mobile USA successfully leveraged Big Data and analytics to reduce instances of customer churn. The telecom company analyzed the buying patterns and purchasing style of its customers to offer targeted products, which helped it reduce churn by 50% in just one quarter.
What works for one may not always work for the other. Implementing a common upselling campaign strategy for all customers may not be effective. Therefore, service providers must accurately analyze customer data to design targeted campaign strategies. Marketing strategies supported by advanced analytics methods will also yield higher ROI. Advanced analytics provides a clear picture on which promotional event will be successful among which set of customers. Based on this information, referral bonuses can be offered to customers.
Improving operational efficiencies is the need of the hour
In an industry marked by plummeting margins and surging costs, ensuring efficient operations is of paramount importance. Big Data and advanced analytics can help CSPs improve the efficiency of their operations by promoting smart network planning, preemptive customer care, and cell-site optimization. Network planning solutions rooted with advanced analytics can help CSPs correlate information from various network data sources. This information helps providers implement vital network changes, especially during peak traffic at data centers when network resource are exhausted. Advanced analytics ensures that network operations run smoothly by monitoring varying traffic patterns. Routing during high traffic is also vital to achieve operational efficiency.
Enhancing customer experience
Analytics can play a vital role in making customer care personalized, and thereby, more effective. It lends a more proactive flavor, than a reactive one, to the customer service philosophy. Companies can leverage consumer data and transactional information to enhance business opportunities. Advanced analytics techniques can be used to track customers and their social personas (through social networking profiles) to craft contextualized servicing strategies. For this, companies need a unified view of the information collected from multiple touch-points. CSPs can build a 360 degree view of a customer based on various parameters such as customer location, social network involvement, sentiment, and inclination to purchase to offer them services with product discounts.
Deriving maximum business value from Big Data and analytics
While Big Data and analytics offers multiple advantages, it is important to sketch an implementation strategy considering which areas it can be applied to with ease. You can begin by using it to enhance customer-centric outcomes in order to provide better services to customers. Therefore, outlining the scope of Big Data explicitly is important for organizations. An analysis of the current data available within the organization is necessary to achieve near-term results, which will further help them develop long-term plans.
Further, in order to get maximum benefits from Big Data, analytical tools like dashboards and metrics are necessary.
Building predictive analytics capabilities will help CSPs identify the patterns of customer purchasing style accurately. Finally, organizations need intelligent analytics to target right customers at the right time.
Has your organization assessed the benefits Big Data and analytics can bring in? What is your strategy in this regard?