Magento BI helps you answer your business questions - whether you simply want to see this month’s revenue compared to last year or understand your acquisition costs for your latest AdWords campaign.
But what does that path from question to answer look like, exactly? We’re so happy you asked! We’ve mapped out that route below, shedding light on both how we approach a business intelligence question and some of the backend logistics required to get you the data you need.
Business leaders are constantly asking questions to help grow and improve their business, from improving customer satisfaction to cutting supply costs.
Let’s say we want to answer the question “What is my company’s average time to conversion?”
With our question in hand, it is time to identify a list of possible measurements to help answer our question. For this example, let’s focus on the following measure:
Average time from registration to first purchase date per user
Understanding what to measure only gets us part of the way there. In order to assess the average time from registration to first purchase date per user, we need to identify all the data points that our measure is comprised of.
Let’s break down our measure into its core components: we need to 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, we need to know where to find this data. Let’s locate:
At a more granular level, we need to identify the exact data fields that will be used for this analysis:
In addition to the native data columns outlined above, we will also need a set of calculated data fields to enable this analysis:
Customer’s first purchase date
That will then be used to create:
Time between a customer’s registration date and first purchase date
Both of these fields need to be created at the user level (i.e. on the `user` table) so that the average analysis can be normalized by users (i.e. the denominator in this average calculation will be the count of users).
You can leverage your Magento BI data warehouse to create the above metrics. 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 we have the required data fields for our analysis, it’s time to find or create the relevant metric to construct our analysis.
Here we know that mathematically we want to perform the following calculation:
SUM of `Time between a customer’s registration date and first purchase date`
Count of customers that registered and purchased
And we want to see this calculation plotted over time, or trending, according to a customer’s registration date. To build this metric in Magento BI:
This metric is now ready to report on the average time between registration and first purchase date by registration date.
Now the fun begins. With the new metric set up, we 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 new report using the metric created above.