2. Leveraging Mobile: Some of the world's most cutting-edge marketers are leveraging the Wi-Fi signal from a customer's cell phone in order to better understand how the customer moves about the store, as well as where and when the customer purchases items. Even more specific data can be gathered if that customer is a member of a loyalty program. For example, if the customer used his or her phone to register or log into a loyalty program app, the marketer may recognize that device when it enters a restaurant and begins transmitting a Wi-Fi signal. The data on a customer's purchasing behaviors and movement throughout the restaurant can then be integrated with the historical and demographic data already known about the customer to create a more customized line of offers targeted at him or her, even while that person is still seated. This data gleaned from a mobile device can also help companies determine where to place products and the best store layout for maximizing purchases.
3. Column-Stored Databases: Traditional databases are referred to as row-stored databases, because each record is stored in a row and fields are stored in columns—much like a typical Excel spreadsheet. But a column-stored database reverses this and stores all the values of a field in a row, which allows for much faster calculations because the software only needs to read one row. Companies will find column-stored databases useful any time analytics are run, although real-time analytics will see the biggest benefit from this format.
Collaboration: The ability for multiple platforms to work together is critical for maximizing the use of analytics, and allows a company to dive deeper into its data to more accurately target customers. Your company may have a traditional data warehouse platform that is good at transactional and operational reporting and dashboards. But today, big data platforms are required to work with a high volume and variety of data elements, as well as an analytic platform that can perform rapid, complex analytics to support the iterations required by data scientists and business managers. Companies are gathering more data and demographic information than ever before, but the data is not effective or helpful if the right platforms are not used for analysis. Collaboration among these three types of platforms will bring about the much-needed performance improvements with a lower cost, quicker turnaround and lower error rate to generate better results for your marketing campaigns.