In-database analytics in the real world
Users in multiple industries are saving time and refocusing resources on heavy analytics
You’ve heard that running SAS inside your Teradata database can save processing times and improve the quality of your results. But how does that play out in the real world of banking, retail and telecommunications? Read on to find out.
Large bank increases response rates and reduces bad debt
When a large national bank faced increasing competition and complex compliance challenges, management developed a comprehensive plan of attack: integrate data across business lines, increase marketing response rates, reduce bad debt on credit cards and help business analysts work more productively.
To help reach these goals, the bank uses SAS and Teradata technology to consolidate data and segment customers. Now that analysts are no longer spending 80 percent of their time pulling data together, regulatory requirements are easier to meet and there is more time to focus on improving the bank’s bottom line. For example, by leveraging data from third-party marketing partners, the bank can rank customers by lifetime value and make timely offers that match customers’ needs – resulting in an increase in response rates from less than 1 percent to 20 percent.
To strike the right balance between risk and reward, the bank now analyzes each customer’s risk profile – along with their needs and propensity to respond – prior to sending out offers. The bank also segments late-paying customers to determine methods to help those customers reduce their debt. This approach has enabled the bank to reduce bad debt by 5 percent.
Retailer achieves double-digit growth
More than 10 years ago, when a national retailer specializing in outdoor merchandise was making the move from being primarily a catalog company to a growing, multi-channel business, it needed deeper – and faster – insight into customer preferences and buying patterns than its homegrown IT systems could support.
Previously, analysts had to spend one to two weeks per month just bringing together disparate data sources. Now, with the integration of SAS and Teradata, data is available in seconds rather than days or weeks. Statisticians can build models faster, have more time to uncover high-value business insights and use up-to-date insights to optimize real-time customer interactions.
For example, they can more quickly:
- Choose up-sell offers and schedule promotions to drive sales.
- Identify potentially ideal new prospects before the competition does.
- Help customer service reps personalize their interactions based on each customer’s value.
- Identify each customer’s favorite channel to selectively send related marketing materials.
- Focus marketing efforts on the most profitable geographies (an approach that has boosted response rates by 60 percent).
The retailer is currently in the process of using in-database analytics to identify the clickstream patterns of online customers so they can put the perfect offer in front of them – in real time – based on the historical patterns of similar shoppers.
Telco becomes a top carrier worldwide
The largest mobile carrier in the UK is using an integrated SAS and Teradata data warehouse solution to help achieve their goal of becoming one of the top five carriers worldwide. Prior to implementing the new solution, fragmented data volumes had grown exponentially and it was taking approximately 40 days for management to access the customer insight needed to help drive growth. The company faced increasing and ever-changing customer demands, increasing churn risks and intensifying competition – and lacked access to the timely insight needed to respond to customer needs swiftly and in a personalized way.
In-database analytics have enabled the company to reduce the cost of using analytics and reduce the speed of information delivery from 40 days to one day. Now the telecommunications company can:
- Identify customers most likely to churn early enough to offer them the best services and plans to keep them from going to a competitor.
- Drive the most meaningful content specific to each subscriber.
- Shorten the time required for the company to execute marketing plans by integrating its Teradata customer data warehouse with SAS Analytics.
- Improve the turnaround time of decisions on pricing, promotions and content for improved customer satisfaction.
These types of situations are not uncommon. Most companies simply can’t aggregate, analyze and process large volumes of data quickly enough to support critical decisions that must be made in hours, minutes or seconds. Nor can they ensure the security of corporate information, because IT has to extract, copy and replicate data from an enterprise data warehouse (EDW) prior to analyzing it.
With SAS and Teradata, now they can.
Jim Watts is a Business Relationships Manager at SAS.