Data Explorer

 

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Data Explorer is a feature that allows you to use all the data collected by Connectif to create detailed reports with which you can analyze your sales, measure the results of your campaigns and search for trends in a simple and powerful way. These reports will help you make data-driven decisions to optimize your account and achieve your goals.

 

How to access it

You can access Data Explorer via “Analytics > Data Explorer. On this page, you'll see all the reports you've created and can edit them or create new reports.

Create a new report by clicking  New report.

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Interface

The Data Explorer report interface is made up of three blocks:

  1. Main menu: to save the report, save it as a copy, restore it (if you have made changes and want to revert the report to the last saved configuration), rename it, export it as a CSV file or delete it.
  2. Toolbar: to select the groupings and metrics you want to analyze.
  3. Table: to view the results of the data report.

You can use dozens of metrics and groupings to create reports of all kinds, depending on the area or goal you need to analyze.

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How it works

Data Explorer presents the data in Categories, which are defined according to their origin, context or the event at the time the data is collected. These categories, in turn, provide groupings and metrics.

Groupings (or dimensions) are descriptive characteristics of the category. In general, they are not quantifiable. In other words, it doesn’t make sense to use them in mathematical operations.

 

For example, dates or workflows associated with purchases.

Metrics, for their part, are data that can be measured quantitatively, such as the sum or quantity of products in a purchase.

 

For example, when a purchase is made, a series of data related to it is collected, including that related to the products purchased and the contact who made the purchase.

The total amount, the number of products purchased, or their average price are metrics.
In turn, the purchase was made by a contact who may have a newsletter subscription status or a specific RFM status, which are groupings.

 

1. Add groupings and metrics to your report

Add groupings and metrics to your report by dragging them to the appropriate section or double-clicking them. As you add groupings and metrics to your report, the central table will display the data in rows and columns:

  

When any activity is registered, Connectif saves and associates the majority of the contact data with it at the moment in which that action is carried out. 

This way, when you generate a report on the number of purchases grouped by the contact's newsletter subscription status, the table will show the purchases that contacts made according to their subscription status at the time of purchase (instead of viewing the number of purchases based on their current subscription status).

Data Explorer presents the data in Categories. Within each category you can find groupings and/or metrics. The available categories are the following:

  • "Period": to group data based on date-type categories, such as day of month, day of week, month, year, etc.
  • "Contact profile": to group data based on your contacts’ characteristics, such as email domain, age range, whether they have email or not, the segments they belong to, etc.
  • "Value indicators": to group data according to certain indicators, such as the RFM segment to which the contacts belong, the RFM-recency, RFM-frequency, RFM-monetary value, etc.
 

Learn how RFM analysis works in this article.

    • "Purchases": to group data according to the purchase characteristics, such as its origin, the payment method, if it is attributed to Connectif and to which workflow or content, etc.
      It also allows you to analyze groupings of data and metrics related to sales made in your store, such as the number of buyers, the number of purchases, the average order value, the total spend, etc.
 

Learn how purchase attributions work in this article.

  • "Carts": To analyze metrics related to the cart, such as the number of cart abandonments and the average number of abandonments per contact.
  • "Products": to group data according to the brand of the product. It also allows you to analyze metrics related to the products in your catalog, such as the number of products visited, number of products added to cart, number of products purchased, etc. 
  • "Emails": to group data based on the type of email, its name, the UTM Content, the dispatch workflow, etc.
    It also enables you to analyze metrics about your email campaigns, such as the number of emails sent and opened, number of clicks, open rate (OR), click-through rate (CTR), etc. 
  • "Push Notifications": to group data based on the name of the push notification, the workflow where it is used, its UTM Content or the sending workflow.
    It also allows you to analyze the data of your push notification campaigns using metrics such as the number of submissions, number opened, number of clicks, open rate (OR), etc. 
  • "Web Content": to group data based on the type of web content, its name, the UTM Content, the submission workflow, etc.
    It also allows you to analyze metrics related to content created in Connectif, such as the number of pieces of web content opened, the number of clicks, the click-through rate of opened web content (CTOR), etc.  
  • "SMS": to group the data based on the name of the SMS or the workflow where it is used.
    It also enables you to analyze metrics such as number of emails sent, conversion rate, etc.
  • "Page views": to group data according to the type of device with which the page is visited.
    In addition, it allows you to analyze the metrics of the number of page visits.

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When the user selects a metric or a dimension it is possible that others are deactivated, this indicates that the set of metrics or dimensions selected is not compatible with them or that it is already selected.

2. Define the date range

You can change the date range you want to analyze in the corresponding selector. The options available in the date selector are:

  • "Today": to view today's data only.
  • "This week from Sunday": to display data from the last Sunday to today.
  • "This week from Monday": to display data from the last Monday to today.
  • "This month": to display data for the current month.
  • "7 days": to view data for the last seven days.
  • "30 days": to view data for the last 30 days.
  • "All": to view all available data.
  • "Custom Range": to view data for a specific period defined by you.
  

Data Explorer stores data on activities related to ecommerce from January 1, 2022 (except for purchases, which may be earlier) or from the completion of the integration, if this is later than that date.

The time period available to generate your reports in the Data Explorer may vary depending on the plan you have assigned.

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3. Data column actions

3.1. Sort data

For better visualization of the data, sort your report from the contextual menu of the reference grouping or metric, by selecting  Ascending or  Descending.

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3.2. Filter data

You can create more accurate reports by adding additional filters to the metrics. To do this, click next to its name to open the context menu and hover your mouse cursor over  Filter.

In the new menu that appears, select the operator (if there is one), set the comparison value and click Apply.

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If a data column has a filter applied, a blue icon will appear next to its name.

 

4. Save a report

In the main menu (1), click   Save to save the changes to your report. If you want to change the item name at the same time, click   Save As

  

You can change the report name at any time using the   (Edit) button next to the current report title in the main menu (1).

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5. Export a report

You can export your reports for processing or analysis via two different routes:

1. From the main menu (1) of the report, click  (Export report)

2. From the list of reports under en Analytics > Data Explorer, click More   and select Export.

  

Once the export process has started, this will be queued. The process can take up to a few minutes, depending on the size of the report and whether there are other exports queued.

You can check the export queue and its progress from Analytics > Data Explorer, by clicking  Export history.

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6. Delete a report

You can delete your reports via two different paths:

1. From the main menu (1) of the report, click  (Delete report)

2. From the list of reports under Analytics > Data Explorer, click More   and select Delete.

  

To avoid accidental deletions, you must confirm the action in the pop-up message. Click   Delete report to confirm deletion. Otherwise, click   Cancel.

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  Congratulations!
You’ve reached the end of the tutorial.

  

Do you have questions?
Don’t forget, our Connectif specialists are here to help you. To contact them, just open a Support ticket by clicking the blue “Help” button on your dashboard.


Keep learning!

To make the most of your Connectif account, we recommend reading these articles next:

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