Use reports in MBI to help you answer business questions - whether you simply want to see this month’s revenue compared to last year or understand your acquisition costs for your latest Google AdWords campaign.
What does that path from question to answer look like, exactly?
To help you visualize this process, that route is mapped out below. This topic sheds some light on both how you approach an analytical question, and the backend logistics required to get you the data you need.
You know that you are constantly asking questions to improve your business, from increasing customer satisfaction to cutting supply costs. You focus on how to translate your questions into analyses that help you drive decisions.
For this example, assume that you want to answer the following question:
It is time to identify a list of possible analyses and measurements to help answer the question. For this example, focus on the following metric:
This reveals the average time that lapses between registration date and the users’ first purchase date and give an idea on how users behave at this final step in the conversion funnel.
Understanding what to measure only gets us part of the way there. To assess the average time from registration to first purchase date per user, you need to identify all the data points that your measure is comprised of.
Break down your measure into its core components. You must know the count, or number, of people that registered, the count of people that made a purchase, and the time that elapsed between those two events.
At a higher level, you need to know where to find this data in the database, specifically:
purchasetable to the
customertable - this allows us to know who made a purchase
At a more granular level, you need to identify the exact data fields that are used for this analysis:
In addition to the native data columns outlined above, you also need a set of calculated data fields to enable this analysis, including:
Customer's first purchase datewhich returns a specific user’s
That is then used to create:
Time between a customer's registration date and first purchase date, which returns a specific user’s time lapsed between registration and first purchase date. This is the basis for your metric later.
Both of these fields need to be created at the user level (for example, on the
user table). This enables the average analysis can be normalized by users (in other words, the denominator in this average calculation is the count of users).
This is where MBI steps in! You can use your MBI Data Warehouse to create the above columns. Contact the Adobe analyst team and provide us with the specific definition of your new columns for creation. You can also use the Column Editor.
It is a best practice to avoid creating these calculated data fields in your database directly as it puts an unnecessary burden on your production servers.
Now that you have the required data fields for the analysis, it is time to find or create the relevant metric to construct your analysis.
Here you want to perform the following calculation:
Time between a customer's registration date and first purchase date] / [Total number of customers that registered and purchased]
And you want to see this calculation plotted over time, or trending, according to a customer’s registration date. And Here is how to create this metric in MBI:
usertable (where you created the dimensions above).
Time between a customer's registration date and first purchase datecolumn in the
usertable ordered by the
Customer's registration datecolumn.
This metric is now ready.
With the new metric set up, you can use it to report on the average time between registration and first purchase date by registration date.
Simply go to any dashboard and create a report using the metric created above.
Visual Report Builder
Visual Report Builder is the easiest way to visualize your data. If you’re not familiar with SQL or you want to quickly create a report, the Visual Report Builder is your best bet. With just a few clicks, you can add metrics, segment your data, and create reports to across your organization. This option is perfect for beginners and experts alike, as it does not require any technical expertise.
|This is perfect for…||This is not so great for…|
|- All levels of analysis/tech experience
- Quickly creating reports
- Creating analyses to share with other users
|- Analyses that require SQL-specific functions
- Testing new columns - calculated columns depend on update cycles for initial data population, whereas those created using SQL are not.
When creating reports that are shared with other members of your team, Adobe recommends adding descriptions which allow other users to better understand your analysis.
Need to include a report in a presentation or document? Any report can be saved as an image (in PNG, PDF, or SVG format) using the
Report Options menu, located in the top-right corner of every report.