In today’s technology-driven world the idea of a loyalty program is a widely recognised and accepted concept. Both High Street and online retailers offer consumers rewards in return for their purchasing information.
These programmes help companies attract consumers and build brand loyalty. Retailers around the world recognise the value of these schemes and are actively looking for high-performance platforms and analytics to help them to make the most of the data they provide.
AIMIA’s unique analytics technology provides a platform for designing, launching, and managing effective loyalty programmes. The value derived from these programmes drives innovation for companies looking to stay ahead of their competitors.
AIMIA collects data from point-of-sale terminals and loads it into the AIMIA analytical environment for examination and manipulation. This provides companies with the ability to obtain a better understanding of product and promotion performance within the wider retail context. Correlating campaign execution with sales, analysing brand switching trends, and assessing the impact of store layout changes is incredibly powerful. Companies provided with this information can begin to effectively streamline strategic processes to drive growth in sales and revenue and promote additional loyalty programmes to existing customers.
AIMIA’s UK based loyalty card program was struggling to deliver a unified set of offers to their 25 million users and the company was keen to provide an effective and stable solution. They had tried multiple platforms to deliver this functionality, but none were capable of handling the rapidly growing data requirements of the business. Some market analysis programs were taking days to return answers, degrading the accuracy of the captured data.
The company wanted to improve service confidence and satisfaction and to assure customers that the majority of reports could still be run in real-time, as promised by many competitors. In order to drive this success, AIMIA needed to create an analytical environment where all transaction details could be analysed as they were generated. Accomplishing this with a conventional data-base would be impossible, due to the speed required and the size of the datasets involved.
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WHISHWORKS setup the Hortonworks Data Platform on Amazon Web Services using dynamic scaling to handle the growing data load and analyse all point-of-sale data volumes as they were generated. WHISHWORKS set up the Hortonworks cluster, tested it, and completed the platform within just 5 months.
The platform greatly increased the performance of their analytics capabilities, generating personalised offers in just 8 hours for sales of products across multiple categories. With the Hortonworks platform at its core, AIMIA is able to offer customers the ability to generate highly personalised offers with near real-time processing capability. In addition to this the Company was able to save around £700,000 per annum on their data storage and processing costs.
The Hortonworks solution uses a high performance, parallel processing technology, designed to work on low-cost servers which are easy to build, maintain, and replace, and provide a quick and effective scaling solution to handle future growth of the business. The system is capable of holding huge quantities of data in-memory for quicker performance of in-depth analysis models.
Thanks to the infrastructure solution built and supported by WHISHWORKS, many of the world’s largest companies and retailers rely on AIMIA to provide detailed analytics and customer insight. Clients have access to a market leading service, which helps them stay ahead of their competitors in an increasingly competitive retailing environment.
The ability to analyse promotional campaign performance allows companies unparalleled insight into the trends and patterns behind customer buying behaviour; all supported by the Hortonworks platform, built and developed by our team. AIMIA has new confidence in their IT infrastructure and is building loyalty strategies for more companies than ever before.