Your company wants to promote a data-driven culture. As the resident data guru, part of your job entails recommending what tools and process the organization should adopt to get the right data into the right hands to help drive internal decision making. For example, you may be asked explain the pros and cons of dashboards vs reports; or to provide a wider set of options for data sharing.
You could simply give everybody access to the company’s Google Analytic accounts. But, after a little bit of thought, you realize that will probably not work. After all, most of the marketing team doesn’t know how to use Google Analytics to get the data they need, and they are too busy to learn. Also, maybe handing over full Analytics access to
everyone in the building isn’t the best idea.
And truthfully, not everyone wants all the data. What the marketing staff wants is easy access to data that helps them make the specific decisions they need to make. It’s the data most relevant to their story. They need to answer questions, such as:
- Which campaign generated the most sales last month?
- Did the new checkout design reduce abandoned carts?
- Which acquisition channel is doing the best job bringing in visitors from our target demographic?
- How does the conversion rate for the latest Twitter advertising campaign compare with the one we ran last month?
- Is the new AdWords remarketing campaign contributing more to sales than it costs?
Each of these questions
can be answered with Google Analytics. However, it takes a skilled web analyst driving the tool to bring forth the data to do it.
The key to a data-driven culture is leveraging the abilities of your skilled web analysts to produce data the entire marketing department can consume. This means providing your data gurus with tools to automate the process of producing the data, and also – possibly – some administrative support to help them pull everything together.
As you work on designing and implementing your organization’s solution, you are going to need to decide whether to distribute the data using dashboards, reports, or both. Dashboards and reports each have their strengths, but are suited to different purposes.
This post explores when you should use dashboards and when you should use reports.