As the first in the industry to apply the expertise of world-class data scientists to the challenges of the Zettabyte Age, Razorsight has been active since day one in helping CSPs find and leverage the long-sought ability to grow their businesses through the application of precise BI by customer, product and location. What we’ve learned and how we’ve applied this knowledge has set a new standard in the way that CSPs assess customer value, pricing, marketing, and retention as well as network investment. Carriers now have the power to measure any single customer’s direct contribution and to base business decisions on the current and projected value of said customer, the requirements for product development and the impact on network infrastructure costs.

The result: a true game changer that will positively transform the business of forward-looking CSPs. While their competitors sit on the bench, the industry’s “A” teams will consistently score home runs, an unprecedented batting average made possible by the ability to analyze off-the-chart data volumes and glean, with laser precision, the exact data required to monetize key, profit-laden insights into customers.

Big Data: the carrier’s perspective

Razorsight’s interest in predictive analytics for CSPs was prompted by daily interactions with industry leaders. Time and again we encountered a common thread of issues that troubled them:

• How much is a customer worth, and what drives each customer’s profitability?
• Which customers are likely to churn, and why?
• Which products is a customer likely to buy, and how will his or her decision impact the products’ lifetime value?
• How is my company’s network impacting customer satisfaction, and which customers should it address as priorities?
• Where will my company have capacity or configuration issues in the network, and how will they impact my top and bottom lines?
• How can my company best communicate with customers to drive response rates and lifetime value?

In theory, Big Data solutions should have addressed these issues all along, but the answers never emerged because old-school BI platforms weren’t designed to handle the complex needs of today’s Big Data. Unlike advanced analytics, which thrives on the massive amounts of data that are generated in the new “all things connected” mobile universe, BI can only partially supply the answers that CSPs need to know.

The irony is that some CSPs still aren’t aware of how they’re being shortchanged by their own Big Data platforms. Ask them if they have a Big Data analytics solution and they respond with an emphatic “Yes!” But when you take a close look at their platforms a different picture emerges, one with some obvious problems.

Because these CSPs still house their Big Data solutions in their IT departments, they’re forced to wait days, weeks or even months for answers to their questions, which are often based on hunches rather than facts, while siloed Big Data platforms are plagued by contradictory definitions of metrics that make it impossible to answer even the simplest question, e.g., “What is a customer?” Perhaps most frustrating of all, the personnel in charge of operating the siloed Big Data platforms are forced to manually link sources within the Big Data platform to gain a consolidated view of the customer, leading to long delays, abundant errors and multiple versions of the truth.

The clock is ticking. Under intense pressure from growing volumes of data on one side and profit erosion driven by plateauing revenue and increasing costs on the other, many CSPs continue to lose ground because the answers to their most fundamental business questions remain a mystery.