In the last decade there’s been a marked increase in the overall use of digital marketing, and with it has come an increased need for excellent digital marketing analytics, particularly as it pertains to web and social media analytics. In online marketing, information comes from many different sources and requires a platform that can both integrate it seamlessly and allow it to be manipulated and investigated for insights, patterns, and trends. Digital marketing data analytics help marketing entities to determine the best social media channels to use, analyze what content is most effective, keep track of impressions, clicks, and engagement, provide cost-per-click analysis, forecast future trends, and identify preferred customers as well as the most effective brand ambassadors.
Digital marketing necessitates information on social comments, mentions, likes, and shares which are used to gain insights into targeted segments regarding general behavior and customer perception of the brand. In digital marketing, traffic is key, and a good marketing BI tool will highlight where traffic is coming from, what is being looked at on a site, and provide insight for how to increase it.
Regardless of the product or service in question, digital marketing requires the assimilation of large amounts of data from disparate datasets to create a unified pool that can be queried, manipulated, and drilled down to extract useful business intelligence insights. Creating a standardized way of recording and storing information, updating BI tools regularly with new data, and making sure the relevant technology can handle massive pools of data are vital for organizing and using big data in a way that can generate actionable insights, and improve overall performance.
When choosing a BI platform for digital marketing, the first concern is having a tool that can integrate large and incongruent datasets into one unified pool. Once integrated, there needs to be an ability to query the data, break it down, and manipulate it in different ways to extract granular data and usable insights, along with the capacity for quick and automatic refreshes to maintain data freshness. Also important is a system that can be used by non-IT personnel so that different departments within an organization can build and maintain their own BI dashboards, thereby allowing for quicker self-reporting, and limiting the amount of time needed by IT for setup and maintenance. A good platform will also provide a high level of security to keep all internal company information and customer data safe at all times.
Sisense developed a platform that accounts for all the needs mentioned above. It’s made to assimilate large and disparate datasets that can be manipulated and drilled down to granular data points in order to gain a better understanding of problem areas, trends, and positive outcomes. It’s also built with the ElastiCube technology which enables it to be used by non-IT workers in order to promote quick and accurate self-reporting by marketing departments within a company while lessening the strain on IT departments to create and maintain dashboards. What’s more, with the hybrid model of Sisense, a 360° view of a digital marketing company can be accessed with the capability for building Live Data Models in both SQL Server and Amazon Redshift which can then be put alongside historical data models in order to compare, spot patterns, and identify trends that might not otherwise be seen. Last, Sisense developed the platform with safety in mind to ensure that all internal company info and customer data remain private and secure.Start Free Trial