Every report in Lightspeed Analytics is made of the same basic components, whether it's a report that comes with Analytics or a report you've designed yourself. These components are divided into three categories:
- Filters define the scope of what is being reported.
- Visualizations allow you to display your data visually in a graph, widget, or table.
- Data is where you'll find the raw data of the report. It is made up primarily of Dimensions and Measures.
Lightspeed Analytics' key strength is that it allows you to build your own custom reports that are specific to your needs. In order to do so effectively, you'll need to understand these components and how they interact.
Filters allow you to constrain your results to only what is relevant for you at the moment. With filters, you can focus on results from a particular date range, a specific store location, or a selected vendor, for example.
To add filters to an existing or custom report, find the metric you wish to filter in the menu on the left, hover your cursor over it, and then click the Filter by field button:
The added filters appear in the Filters section of the report:
Use the drop-down menus and fields to set up how you would like the filter to be applied. In the above example, we started with the Recent Sales report and added filters to isolate sales that have taken place in the last week and items that have a current quantity on hand of 0, to determine which items have sold out in the last 7 days.
Filtering by date
There are some considerations to take into account when filtering a report by date, especially as compared to the reports in Lightspeed Retail POS.
When selecting a date range in Lightspeed Retail POS, the end date is inclusive, however, in Analytics, it is exclusive. If, for example, you want to run a report for the entire month of January, specify the date range of Jan 1—Jan 31 in Retail, but Jan 1—Feb 1 in Analytics. This means that you can never include today's activity in an Analytics report.
When selecting your unit of measurement for a date range (days, weeks, months, etc.), you'll notice each unit of time similarly represented twice:
Lightspeed Analytics does not define a week as the last 7 days, but as a time period from Sunday to Saturday. Similarly, a month is defined as a calendar month, not a number of days. When selecting a complete time period, Analytics will look for the last unit of that time period to have a completed data set. This means whether you select the past week or the past complete week, it will yield different results.
|Time unit||Complete time unit|
|Week: This week so far since Sunday.||Complete week: The last full completed Sunday to Saturday time period. For example, last week.|
|Month: This month so far since the 1st of the month.||Complete month: The last full completed month. For example, last month.|
|Quarter: This quarter so far.||Complete quarter: The last full completed quarter. For example, last quarter.|
|Year: This year so far since Jan 1st.||Complete year: The last full completed year. For example, last year.|
Therefore, if you want to know how many sales were made since the same day a week ago, you set the filter to the last 7 days, not the last 1 week.
Visualizations allow you to present the information in your report graphically. To do so, simply select the kind of graph you want to see (bar graph, line graph, pie chart, etc.) from the Visualization bar.
Example of a pie chart:
Visualizations are a great tool for identifying trends at a glance.
The Data section is where to find the raw numbers of your report in table form:
These tables are assembled by combining Dimensions and Measures. Dimensions and measures are added to the report by selecting them from the side menu on the left of the report:
Click on any dimension or measure to add it to the table.
Dimensions are qualitative while measures are quantitative. A dimension might be a month of the year, a customer's name, a Sale ID, a brand, a vendor, or anything that narrows down what data you're collecting. A measure is the numerical value pulled from the dimensions, such as number of sales, profits, quantity on hand, or average basket size.
Building a custom report
Now that you have a working understanding of the moving pieces that make up a report, you're ready to learn about building a custom report to suit your needs!