Dig into data for improved customer experiences

Australia's telecommunications industry has a highly regulated, competitive and saturated marketplace. First- and second-tier providers battle it out for the loyalty of today's more informed, sophisticated and price-sensitive customers.

Providing both residential and business services, Telstra is Australia's leading telecommunications and information services company, having one of the best known brands in the country. It offers a full range of services -fixed line, mobile phone, Internet and cable TV­ and competes in all telecommunications markets throughout Australia. Telstra provides more than 8.8 million fixed lines and 10.3 million mobile services, including 3G services to 7.2 million subscribers.

Telstra operates in an extremely competitive environment and faces constant pressure due to the Australian government's promise to deliver its own broadband services to the market. As a result, the company turned to business analytics and predictive modeling from SAS to help enhance customer service, provide relevant and value-added prod­ ucts to its clients, and secure and grow its role as a market leader.

We have jobs that used to take 11 hours to run ... these things are running in around10 seconds.

Sandra Hogan
Director of Customer Intelligence

"We've invested in our analytics environment because we view it as a significant component  of our customer service," says Kate McKenzie, Chief Marketing Officer, Telstra. "Knowing what customer predilections are -like understanding when customers prefer to be called, what language they prefer to use and what services they're interested in -is extremely valuable and important to Telstra."

McKenzie adds that the SAS Analytics environment is having a positive effect across the organisation, and the resulting efficiencies and insight support increased business effectiveness. As a result of predictive modeling capabili­ ties, Telstra can provide its front-line representatives with information that helps them reduce customer churn, cross-sell and up-sell products, as well as drive customer acquisition programs. McKenzie says the company is expect­ing a 15 percent improvement in some of its recent retention campaigns as a direct result of its new analytics environment.

"We help the call center. We can help our shops. We can help the whole organisation make better, informed decisions," explains McKenzie. "We can get information about what customers are looking for to the front -line customer service staff so much more quickly. We do it in such a way that is simple and makes sense to them; it clearly makes a big difference in our service delivery."

Telstra's Teradata enterprise data warehouse is the single database for customer interactions, utilising seg­ mentation, modeling and propensity scores for making marketing decisions. According to Sandra Hogan, Director of Customer Intelligence, quicker and more informed decisions are in part due to the partnership and tight integration between Teradata and SAS.

''A lot of opportunity arises from the integration of the two technologies. We can increase workflow and the controls around model development and maintenance so we can deploy significantly more models, giving us the ability to re-score customers daily rather than on a monthly basis. This gives us improved turnaround time on pricing decisions, promotions and content for improved customer satisfaction," she says. "Aligned data and analytics capa­ bilities allow us to streamline processes; it's all about the timeliness of customer information for us now."

Along with the modeling and predictive analytics provided in the SAS toolset, the telecom leader is using SAS Grid Manager to improve its processing power.

"We've seen benefits already, particu­ larly in processing large amounts of data and analytic computations," Hogan explains. "We have jobs that used to take 11 hours to run. In the new analytics environment, they are running in around 10 seconds. As we get further down the road, we want to increase our ability to track and predict customer behaviour, and improve customer experiences. This environment gives us 10 to 20 times the ability to do that."

"There's not many strong competitors in the analytics space," says Hogan. "We did speak to a couple of other suppliers, but they had nowhere near the level of sophistication and expertise of SAS. It made perfect sense to me."



Needed improved analytics and predictive modeling capabilities to help enhance customer service, provide relevant and value-added products to its clients, and secure its role as a market leader.



Reduced analytics processing from 11 hours to 10 seconds, and expects a 15 percent improvement in its customer retention campaigns.


Los resultados que se ilustran en este artículo son específicos a las situaciones, modelos de negocios, datos aportados y entornos de cómputo en particular que se describen aquí. Cada experiencia del cliente de SAS es única basada en variables de negocios y técnicas y todas las declaraciones se deben considerar no típicas. Los ahorros, resultados y características de desempeño reales variarán dependiendo de las configuraciones y condiciones de los clientes individuales. SAS no garantiza ni augura que todos los clientes lograrán resultados similares. Las únicas garantías aplicables a los productos y servicios de SAS son aquellas que se estipulan en las declaraciones de garantía explícitas en el contrato por escrito relativo a dichos productos y servicios. No se debe considerar que nada de lo aquí mencionado constituye una garantía adicional. Los clientes han compartido sus éxitos con SAS como parte de un intercambio contractual convenido o resumen de éxito de proyectos tras una implementación exitosa de software de SAS. Los nombres de marcas y productos son marcas comerciales de sus respectivas compañías.