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: These define the scope of what is being reported on.
- Visualizations: These allow you to display your data visually in a graph, widget or table.
- Data: This is where you'll find the raw data of the report. It is made up primarily of Dimensions and Measures.
Lightspeed Analytic's 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
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 by in the menu on the left, hover your cursor over it, then click the Filter button.
The added filters will appear in the Filters section of the report.
You can then 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 in order to determine which items have sold out in the last 7 days.
Filtering by date
There are a few considerations to take into account when filtering a report by date, especially as compared to the reports in Lightspeed Retail.
When selecting a date range in Lightspeed Retail, the end date is inclusive, however in Lightspeed Analytics it is exclusive. If, for example, you want to run a report for the entire month of January, you would specify the date-range of Jan. 1 to Jan. 31 in Retail, but Jan. 1 to 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 see each unit of time 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 will yield different results.
| Time Unit | Complete Time Unit |
| Week: This week so far since Sunday. | Complete week: The last full Sunday to Saturday time period to have completed, i.e. last week. |
| Month: This month so far since the 1st of the month. | Complete month: The last full month to have completed, i.e. last month. |
| Quarter: This quarter so far. | Complete quarter: The last full quarter to have completed, i.e. last quarter. |
| Year: This year so far since Jan 1st. | Complete year: The last full year to have completed, i.e. last year. |
Therefore, if you wanted to know how many sales were made since the same day a week ago, you would not set the filter to the last 1 week, but to the last 7 days.
Visualizations
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.
Visualizations are a great tool for identifying trends at a glance.
Data
The Data section is where you'll 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.
Clicking on any dimension or measure will 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, anything that narrows down where you'll be collecting data from. A measure would be 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!