The Real Value of B2C ecommerce market07/04/2015
How much does a Facebook business page really cost?27/12/2016
Just 6 Steps to create a great Analytics report using Google Analytics or any other software tool.
Company teams that want to create a great report are likely to be simultaneously working in one or more of the steps to execute analyties work in any project-especially in globally distributed companies that have matrixed organizations working on multiple concurrent projects. These major 6 steps support them by providing the input necessary for the next phase to continue.
Step 1: Understanding what to analyze
The first phase requires gathering business requirements and goals, understanding the current data environment and the data within it, and developing a plan to execute work
Step 2 Collecting and verifying data
The second phase involves determining if data is available and accurate and, if not, making it so. This work generally involves data engineering and implementing new data collection, data models, or databases. Data governance and master data management are implemented
Step 3: Dashboarding, reporting, and verifying
The third phase is when dashboards, reports, and other artifacts that show data are created, verified, and made available
Step 4: Analyzing, communicating, and socializing
During the fourth phase, the team analyzes data beyond the creation of reports and dashboards. Business questions are answered. Insights are generated. Analysts talk to stakeholders, meet with them, and ensure they understand the analysis. Narratives and stories are constructed and presented for discussion.
Step 5: Optimizing and predicting
The fifth phase is when the “data science” occurs and advanced analytical methods are applied and used to predict what could happen and recommend what should be done next. Data science is not magic and it’s very hard to apply in some cases.
Step 6: Demonstrating economic value
The sixth phase is when the analytical outcomes are gathered, and the business impact is quantified financially. The value of the analytics team and work is demonstrated by showing how it increased revenue or reduced cost.