In this digital age, our individual actions every day are generating a previously unforeseen amount of data. Most of this data is merely transactional in nature, like the printed receipt from your grocer or the smart card you swiped at the train station. Businesses today have an abundance of customer data available from an increasing number of sources, but many organizations struggle to turn this information into actionable insights. These small bits of data put together across millions of customers is what usually constitutes “big data,” and in this data are the hidden keys to growing, acquiring and retaining users that could easily translate to a competitive advantage.
Let us take the example of The Cincinnati Zoo & Botanical Garden. It is one of North America’s most popular attractions, and each year more than 1.3 million people visit its 71-acre site, which is home to more than 500 animals and 3,000 plant species. Cincinnati Zoo takes pride in the fact that it has the lowest public subsidy of any zoo in Ohio and generates more than two thirds of its $26 million annual budget through its own fundraising efforts. In the current challenging economic conditions, the Zoo wanted to reduce its reliance on subsidies even further by increasing visitor attendance and revenues from secondary sources such as membership, food and retail outlets. It sought the ability to analyze membership, admissions, food and merchandise sales down to the individual level, in order to understand visitor behavior.
By leveraging the IBM big data and analytics platform, the organization is now capable of delivering the desired goal. The solution provides reports and dashboards that give everyone from senior managers to Zoo staff access to real-time information that helps them optimize operational management and transform the customer experience. The solution enables them to:
- Cut marketing expenditure, saving $40,000 in the first year, and reduce advertising expenditure 43 percent by eliminating ineffective campaigns and segmenting customers for more targeted marketing
- Increase food revenues 25 percent by optimizing the mix of products on sale and adapting selling practices to match peak purchase times
- Increase overall attendance, prompting at least 50,000 new "visits" in the first year through enhanced marketing
Moving to an example from the energy sector, Petrol d.d., is the principal strategic supplier of oil and other energy products for the Slovenian market. Through approximately 570 service stations, Petrol offers a broad range of automotive goods and services and a wide selection of household items, food products and other merchandise. The company wanted to use historical and transactional data from its retail stores to improve sales, but its analytics environment could not manage the required query volumes or complexity, especially when transactions occurred 200,000-300,000 times per day across all their stores. Using an IBM solution, the organization went beyond accelerating transaction-based, single-record business analytics queries to analyze and predict individual customer behavior. The aggregate queries now provide company purchasing managers, marketers and merchandisers with product- and brand-level sales trends that are geographically focused. Using the new system, the organization has experienced the following benefits:
- Reduced query times to help increase sales
- If the customer is a loyalty customer, the employee can see what he’s purchased in the past and make decisions on what other products to suggest at the point of customer contact
The use of big data and analytics to acquire, grow and retain users is not only limited to marketing. In the following example, data is being gathered and used for a comprehensive, real-time performance tracking system in a bid to improve performance and keep more students on track to graduate.
Like most school systems, Mobile County Public Schools had no shortage of challenges, including the need to improve academic performance and, more prominently, to decrease the share of its students who drop out of school. Having an early warning system to spot at-risk patterns among students is necessary, but not sufficient for dropout mitigation. Using an IBM big data and analytics platform, there is now in place an intelligence-based system that gives teachers and counselors a new level of insight into students and the triggers they need to intervene early—when they can make a difference. As a result, the school reported:
- 3% increase in graduation rate through the ability of teachers, counselors and staff to intervene with at-risk students before they drop out
- Improvement in test scores due to curriculum and teaching changes inspired by the solution’s metrics
Big data is more than simply a matter of size, and analytics provides the opportunity to find insights in new and emerging types of data and content. To truly acquire, grow and retain its customers, organizations need big data and analytics to have a complete understanding of their customers and to improve the customer experience by converting insights gained from analytics into added value for their customers.
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