Data Explorer

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 easily and powerfully identify trends. These reports will help you make data-driven decisions to fully optimize your account and achieve your goals.

How to Access?

You can access Data Explorer through “Analytics > Data Explorer”. On this page, you will see all the reports you have created and can edit them or create new reports.
 

Create a new report by clicking Create Report.

Interface

The Data Explorer interface consists of 2 sections:

1. Blank Report: to create a Data Explorer report with the criteria and filters you want.

2. Report from Template: to create a report from one of the available templates.
   2.1. Template List: to browse report templates and review their data, including the title, description/summary of the report, and the channel(s) included.
   2.2. Search: to search for an existing template by terms related to its name or description.
   2.3. Filter: to narrow the search based on the channel from which you want to get the template (Email, SMS, Web Push Notifications, Web Content, or Mobile Push Notifications).

In either case, when accessing report creation, the report interface consists of 3 sections:

1. Main Menu: to save the report, save it as a copy, reset it (in case you made changes and want to revert the report to the last saved configuration), rename it, export it as a CSV file, or delete it, as well as to return to the main Data Explorer menu.

2. Toolbar: to select the groupings and metrics you want to analyze.

3. Table: to view the data report results.

You have dozens of metrics and groupings available that will allow you to create all kinds of reports, depending on the area or objective you need to analyze.

How It Works

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

Groupings (or dimensions) are descriptive characteristics of the category. Generally, they are not quantifiable, meaning it does not make sense to perform mathematical operations with them.

Metrics, on the other hand, are data that can be quantitatively measured, such as the amount or number of products in a purchase.

1. Create a Report from a Template

On the main Data Explorer interface, browse the template list (2.1) to choose the one that best fits your needs.

You can use the search (2.2) to enter terms related to the report you want to find.

To narrow the search by channel, in the filter (2.3), click the Channels dropdown and select those you want to include in your report.

Once you locate the template that fits your needs, click on it to access the report.

In the report interface, you can save it directly from the main menu (1) or edit it using the toolbar (2) to further adjust the report criteria before saving it in your Store.

2. Create a Blank Report

On the main Data Explorer interface, click the option to create a blank report (1).

In the report interface, you can select the groupings and metrics that will compose it.

3. Add Groupings and Metrics to a Report

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

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

• "Period": allows grouping data based on a time category. Data can be grouped by:

  • Day: groups data by day of the month.

  • Day of the week: groups data by day of the week.

  • Week: groups data by week of the year.

  • Month: groups data by month of the year.

  • Year: groups data by year.

  • Quarter: groups data by quarter of the year.

• "Contact Profile": allows analyzing data based on your contacts’ characteristics. In this category, you can group information by certain contact attributes and add metrics related to their profile or behavior.
  Data can be grouped by:

  • Segment: groups data by segment.

  • Email domain: groups data by email domain.

  • Age range: groups data by age range.

  • Has email: groups data based on whether the contact has an email or not.

  • Email status: groups data by the contact’s email status.

  • Newsletter subscription status: groups data by newsletter subscription status.

  • Subscribed to web push notifications: groups data based on whether the contact has any web push subscription or not.

  • Has mobile phone: groups data based on whether the contact has a mobile phone or not.

  • Mobile phone status: groups data by mobile phone status.

  • SMS subscription status: groups data by SMS subscription status.

  • Number of contact purchases: groups data by the number of purchases made by the contact.

  • Purchase recurrence status: groups data by purchase recurrence status.

  • Has external ID: groups data based on whether the contact has an external ID or not.

  Additionally, you can add the following metrics:

  • Number of contacts: shows the number of contacts existing at the end of the period.

  • Contact increment: shows the variation in the number of contacts since the beginning of the period. This metric will be negative if the number of contacts leaving the grouping state is greater than the number of contacts entering it.

• "Value Indicators": allows grouping data based on indicators related to the value and purchasing behavior of contacts. Data can be grouped by:

  • RFM - Segment: groups data by the RFM segment in which contacts are located.
  • RFM - Recency: groups data by the contact's recency value, calculated based on the time elapsed since their last purchase.
  • RFM - Frequency: groups data by the contact's frequency value, calculated based on the number of purchases made.
  • RFM - Monetary value: groups data by the contact's monetary value, calculated based on the total amount spent on their purchases.

• "Purchases": to group data based on purchase characteristics.
  Data can be grouped by:

  • Purchase attributed to Connectif: groups data based on whether the purchase has been attributed to any Connectif content or workflow.

  • Payment method: groups data by the payment method used in the purchase.
  • Purchase origin: groups data by the origin from which the purchase was reported to Connectif, e.g., Web, API, or Mobile App.
  • Purchase content type: groups data by the type of content attributed to the purchase.
  • Purchase channel: groups purchase data by channel.
  • Purchase workflow: groups purchase data by workflow.
  • Purchase content name: groups purchase data by the name of the attributed content.
  • Attribution scenario: groups data by purchase attribution scenario.
  • Attribution confidence: groups data by the confidence level of the scenario attributed to the purchase.
  • Purchase source type: groups data by the type of source associated with the purchase.
  • Purchase source name: groups data by the name of the source associated with the purchase.

  Additionally, it allows analyzing metrics related to sales made in your store, such as:

  • Number of buyers: shows the number of contacts who have made one or more purchases.
  • Number of first-time buyers: shows the number of contacts who have made their first purchase.
  • % of first-time buyers: shows the percentage of buyers who have made their first purchase relative to the total buyers.
  • Number of repeat buyers: shows the number of contacts who have made more than one purchase.
  • % of repeat buyers: shows the percentage of repeat buyers relative to the total buyers.
  • Number of purchases: shows the total number of purchases recorded.
  • Average number of purchases per contact: shows the average number of purchases made per contact.
  • Total purchase amount: shows the total amount generated by recorded purchases.
  • Average purchase amount: shows the average amount of recorded purchases.
  • Average purchase amount per contact: shows the average amount purchased by each contact.
  • Number of purchases attributed to email: shows the number of purchases attributed to email-type content sent from Connectif.
  • Number of purchases attributed to web push notifications: shows the number of purchases attributed to web push notifications sent from Connectif.
  • Number of purchases attributed to web content: shows the number of purchases attributed to web content shown from Connectif.

• "Carts": to analyze metrics related to the shopping cart.
  Allows adding the following metrics:

  • Number of cart abandonments: shows the total number of times a cart was abandoned.
    Calculated by summing all recorded cart abandonment activities. The same contact can generate more than one abandonment, for example, if they create a cart, abandon it, return, and abandon another cart.

  • Average number of cart abandonments per contact: shows the average number of cart abandonments recorded per contact.
    Calculated by dividing the total number of cart abandonments by the number of contacts who have recorded a cart abandonment activity. For example, if 10 contacts recorded 20 cart abandonments, the average number of abandonments per contact will be 2.

• "Products": to analyze data related to catalog products.
  Data can be grouped by:

  • Product brand: groups data by product brand.

  Additionally, it allows analyzing metrics related to sales made in your store, such as:

  • Number of products viewed: shows the total number of products viewed.
  • Total amount of products viewed: shows the sum of the amount of products viewed.
  • Average amount of products viewed: shows the average amount of products viewed.
  • Number of products purchased: shows the total number of products purchased.
  • Total amount of products purchased: shows the sum of the amount of products purchased.
  • Average amount of products purchased: shows the average amount of products purchased.
  • Average number of products purchased per purchase: shows the average number of products purchased per purchase.
  • Average number of products in cart abandonments: shows the average number of products included in cart abandonment activities.
  • Number of products in cart abandonments: shows the total number of products included in cart abandonment activities.
  • Total amount of products in cart abandonments: shows the sum of the amount of products included in cart abandonment activities.
  • Average amount of products in cart abandonments: shows the average amount of products included in cart abandonment activities.
  • Number of products added to carts: shows the total number of products added to carts.
  • Number of products removed from carts: shows the total number of products removed from carts.

• "Emails": allows analyzing data related to emails sent from Connectif.
  Data can be grouped by:

  • Email type: groups data by the type of email sent.
  • Email UTM Content: groups data by the utm_content value associated with the email.
  • Email workflow: groups data by the workflow from which the email was sent.
  • Email name: groups data by the name of the email sent.

  Additionally, it allows analyzing metrics related to sales made in your store, such as:

  • Number of emails sent: shows the total number of emails sent.
  • Total email opens: shows the total number of opens recorded in the emails sent.
  • Total email clicks: shows the total number of clicks recorded in the emails sent.
  • Unique email opens: shows the number of unique contacts who opened the email.
  • Unique email clicks: shows the number of unique contacts who clicked the email.
  • Email unsubscribes: shows the number of unsubscribes recorded from the emails sent.
  • Newsletter sign-ups: shows the number of contacts who changed their newsletter subscription status to subscribed.
  • Newsletter unsubscribes: shows the number of contacts who changed their newsletter subscription status to unsubscribed. This is recorded regardless of origin and is not associated with emails, workflows, or content.
  • Temporary email bounces: shows the number of emails that could not be delivered temporarily.
  • Permanent email bounces: shows the number of emails that could not be delivered permanently.
  • Email open rate (OR): shows the percentage of unique opens relative to the number of emails sent.
    Calculated by dividing the number of unique email opens by the number of emails sent and multiplying the result by 100.
  • Email click-through rate (CTR): shows the percentage of unique clicks relative to the number of emails sent.
    Calculated by dividing the number of unique email clicks by the number of emails sent and multiplying the result by 100.
  • Click-to-open rate (CTOR): shows the percentage of unique clicks relative to the number of unique email opens.
    Calculated by dividing the number of unique email clicks by the number of unique opens and multiplying the result by 100.
  • Email unsubscribe rate: shows the percentage of email unsubscribes relative to the number of emails sent.
    Calculated by dividing the number of email unsubscribes by the number of emails sent and multiplying the result by 100.
  • Email bounce rate: shows the percentage of email bounces relative to the number of emails sent.
    Calculated by dividing the number of email bounces by the number of emails sent and multiplying the result by 100.
  • Email conversion rate: shows the percentage of purchases attributed to email relative to the number of emails sent.
    Calculated by dividing the number of purchases attributed to email by the number of emails sent and multiplying the result by 100.
  • Email click conversion rate: shows the percentage of purchases attributed to email relative to the number of unique clicks recorded.
    Calculated by dividing the number of purchases attributed to email by the number of unique clicks and multiplying the result by 100.

• "Web Push Notifications": allows analyzing data related to web push notifications.
  Data can be grouped by:

  • Web push notification UTM Content: groups data by the utm_content value associated with the web push notification.
  • Web push notification workflow: groups data by the workflow from which the web push notification was sent.
  • Web push notification name: groups data by the name of the web push notification sent.

  Additionally, it allows analyzing metrics related to the performance of your web push notification campaigns, such as:

  • Number of web push notifications sent: shows the total number of web push notifications sent.
  • Unique web push notification opens: shows the number of unique contacts who opened the web push notification.
  • Unique web push notification clicks: shows the number of unique contacts who clicked the web push notification.
  • Web push notification open rate (OR): shows the percentage of unique opens relative to the number of web push notifications sent.
  • Web push notification click-through rate (CTR): shows the percentage of unique clicks relative to the number of web push notifications sent.
  • Click-to-open rate for web push notifications (CTOR): shows the percentage of unique clicks relative to the number of unique web push notification opens.
  • Web push notification conversion rate: shows the percentage of purchases attributed to web push notifications relative to the number of notifications sent.
  • Web push notification click conversion rate: shows the percentage of purchases attributed to web push notifications relative to the number of unique clicks recorded.

• "Web Content": allows analyzing data related to web content created in Connectif.
  Data can be grouped by:

  • Web content type: groups data by the type of web content.
  • Web content UTM Content: groups data by the utm_content value associated with the web content.
  • Web content workflow: groups data by the workflow from which the web content was shown.
  • Web content name: groups data by the name of the web content.

  Additionally, it allows analyzing metrics related to the performance of your web content, such as:

  • Total web content opens: shows the total number of opens recorded in web content.
  • Total web content clicks: shows the total number of clicks recorded in web content.
  • Click-to-open rate for web content (CTOR): shows the percentage of clicks relative to the number of web content opens.
  • Web content conversion rate: shows the percentage of purchases attributed to web content relative to the number of opens.
  • Click conversion rate for web content: shows the percentage of purchases attributed to web content relative to the number of clicks recorded.

• "SMS": allows analyzing data related to SMS sent from Connectif.
  Data can be grouped by:

  • SMS workflow: groups data by the workflow from which the SMS was sent.
  • SMS name: groups data by the name of the SMS sent.

  Data can be grouped by:

  • Number of SMS sent: shows the total number of SMS sent.
  • SMS conversion rate: shows the percentage of purchases attributed to SMS relative to the number of SMS sent.

• "Page Visits": to group data according to the type of device used to visit the page.
  Additionally, it allows analyzing metrics on the number of page visits.

4. Define the Date Range

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

• "Today": to view only today's data.

• "This week from Sunday": to view data from last Sunday to today.

• "This week from Monday": to view data from last Monday to today.

• "This month": to view data from the current month.

• "Last 7 days": to view data from the last 7 days.

• "Last 30 days": to view data from the last 30 days.

• "All": to view all available data.

• "Custom range": to view data from a specific period you can define.

5. Data Column Actions

5.1. Sort Data

Sort your report for better data visualization from the context menu of the grouping or metric that should serve as a reference by selecting Ascending or Descending.

5.2. Filter Data

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

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

6. Save a Report

In the main menu (1), click  Save to save changes to your report. If you want to rename the item during the process, click  Save As.

7. Export a Report

Export your reports for processing or analysis from two different routes:

1. From the report’s main menu (1), click (Export Report)

2. From the report list in “Analytics > Data Explorer”, click More and select Export.

8. Delete a Report

You can delete saved reports from two different routes:

1. From the report’s main menu (1), click (Delete Report).

2. From the report list in “Insights > Data Explorer”, click More and select Delete.

Keep Learning!

To take full advantage of your Connectif account, we recommend continuing with the following articles:

• Analytics Dashboards, to get a summary of the most relevant statistics of your account,

• Contact Fields, to learn how user data is stored and distinguished or how to create new custom fields.

• Events Consuming Activities, to learn about the events Connectif collects as activities.

• RFM Analysis, to segment contacts based on their purchasing behavior over time.