> Synerise Documentation — Analytics > > This file contains the complete "Analytics" section of the Synerise documentation. Each article begins with a top-level "# " heading. The manifest listing all sections is at https://hub.synerise.com/llms-full.txt # Introduction to geoanalytics Geoanalytics in Synerise allow users to analyze events in the context of the location where they occurred. A single geoanalysis is created on the basis of the `start.session` event. This event gathers longitude and latitude parameters based on the IP addresses. On the basis of such an analysis, you can adjust communication and marketing strategies to the location of your customers. ## Business benefits --- You can also better leverage the increasing volume of location-related data. Thanks to this, an extended analysis of customer data will allow you to make better decisions that will help you boost your revenue. - Better decisions related to marketing strategy that relies on location. - The ability to check how many of your customers are in a specific region. - The ability to estimate which region is best for a promotion for a specific product. - The possibility of identifying customers from a specific region and sending them specific personalized messages. -
# Introduction to dashboards
Dashboards is the feature that allows putting all your analyses together in one place so you can examine and compare key data about your business. This way you can investigate the results of carried out activities with full transparency.
Another benefit of this feature is the possibility to [display dynamic data](/docs/analytics/analytics-dashboard/creating-dashboards#dynamic-data-in-dashboards). Thanks to that, you can preview the results of particular messages sent to customers, sales results of a particular product, observe the activity of an individual customer, and so on.
Due to the additional options that facilitate editing the dashboard layout and the presentation mode, you can use a dashboard in business meetings.
## Business benefits
---
- The possibility to combine all types of analyses into one place
- Displaying the dynamic data in real time
- Sharing dashboards with non-Synerise users
-
# Dashboards
Dashboards is the feature that allows putting all your analyses together in one place so you can examine and compare key data about your business. This way you can investigate the results of carried out activities with full transparency.
Another benefit of the feature is the possibility to [display dynamic data](/docs/analytics/analytics-dashboard/creating-dashboards#dynamic-data-in-dashboards). Thanks to that, you can preview the results of particular messages, sales results of a particular product, observe the activity of an individual customer, and so on.
Due to the additional options that facilitate editing the dashboard layout and the presentation mode, you can use a dashboard in business meetings.
## Business benefits
---
- The possibility to combine all types of analyses into one place
- Displaying the dynamic data in real time
- Sharing dashboards with non-Synerise users
-
# Introduction to reports
A report is a visual presentation of data aspects contained in metrics. Each parameter ( for example, event parameter, customer attribute or expression) analyzed in metrics can be presented in reports as a dimension in a report. Reports can take the form of a bar or line chart and a table. The reports present the top and last values (for example, top 10 products added to cart or last 5 bought products). Analytical reports are a basic feature in Business Intelligence-class systems.
## Business benefits
---
- Increased understanding of risks and opportunities
- Reduced costs
- Improved efficiency
- Anticipating customer behavior
- Aid in planning marketing campaigns
-
# Introduction to trends
A trend is a presentation of event occurrences over time on a chart. It allows you to check the results of events you track and predict their direction. Having this knowledge, you can undertake the appropriate business activities.
## Business benefits
---
- Combining different data and finding correlations between them.
- Tracking changes in selected events over time.
- Building your own analytical models.
-
# Introduction to Sankey Diagrams
Sankey Diagrams in Synerise allow users to reconstruct the flow of customer actions before or after an occurrence of a particular event. Using an event as a reference point, users create diagrams that present steps to get the answers to questions such as "how much?" and "how is it connected with each other?".
## Benefits
---
- Personalize the user experience on the website.
- Minimize the number of steps to conversion.
- Verify the most popular conversion paths and their soft spots.
## Contents
# Funnels
A funnel is a division of a customer journey into steps which allows you to follow the journey step by step until the conversion point. This way you can detect soft spots as you see at which step you lose the customers in the process. Another advantage of the funnels is the possibility of breaking down various sequences of customer actions into steps to see the transitions between them.
## Business benefits
---
- Increase conversion rate by delivering messages adjusted to the preferences of individual customers.
- Predict sales volume as you see how many customers move to the next stage.
- Identify problem areas by tracing the step in the funnel they often leave.
- Funnels facilitate analyses of universal processes which let you focus on examining occurrences such as cart abandonment, cart recovery, message flows, and many more.
-
## Contents
# Creating Sankey Diagrams
Sankey Diagrams in Synerise allow the users to reconstruct the flow of customer actions before or after an occurrence of a particular event. Using an event as a reference point, users create charts that present steps to get the answers to questions such as "how much?" and "how is it connected with each other?".
## Requirements
---
You must have a [user role](/docs/settings/identity-access-management/permissions) with the following permissions:
- [access the Decision Hub](/docs/settings/identity-access-management/permissions/analytics-permissions#access-the-decision-hub)
- [view analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#view-analyses)
- [create analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#create-analyses)
- [edit analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#edit-analyses)
- [preview results](/docs/settings/identity-access-management/permissions/analytics-permissions#preview-results)
- To collect the events on your website, you need to paste the [tracking code](/docs/settings/tool/tracking_codes) into the source of your website.
## Creating a Sankey Diagram
---
and choose a number from the dropdown list.
5. Choose the number of paths that come from each step. To do so, click the
and choose a number from the dropdown list.
6. Define the type of event occurrences.
- **Unique occurrences** - It means that only the first occurrence of the event is counted in the analysis. Every subsequent occurrence of the same event will be ignored in the analysis. This way you can count the number of customers who are in the flow.
- **All occurrences** - It means that if a customer repeated a series of actions, each of them will be counted in the analysis. This way you can count the number of the flow repetitions.
7. By selecting one of two following options, choose the reference point of the analysis:
- **After event** - The system will analyze the flow of customers' actions after the occurrence of a particular event.
- **Before event** - The system will analyze the flow of customers' actions before the occurrence of a particular event.
8. Choose an event that is the basis of the analysis. Depending on the option you have selected in step 4, the system generates a chart with the customer actions before or after the event you choose.
9. To narrow down the scope of the analyzed event, click the [Enable filter](/docs/analytics/i_profile-filter) button. Confirm the settings in the filter by clicking the **Apply** button.
10. If you want to exclude the occurrence of particular events from the analysis, click the **Add event** button. These events will not be considered in the analysis at all.
10. To define the time range for data analysis, click the calendar icon. Confirm the dates by clicking the **Apply** button.
11. To complete the process, click the **Save** button. When you save the chart, you can find it on the list of the Sankey charts.
# Creating geoanalytics
If you want to group your customers according to the actions performed in a specific location, create an analysis on the basis of location.
## Requirements
---
You must have a [user role](/docs/settings/identity-access-management/permissions) with the following permissions:
- [access the Decision Hub](/docs/settings/identity-access-management/permissions/analytics-permissions#access-the-decision-hub)
- [view analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#view-analyses)
- [create analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#create-analyses)
- [edit analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#edit-analyses)
- [preview results](/docs/settings/identity-access-management/permissions/analytics-permissions#preview-results)
- A tracking code implemented into the website.
## Creating a geoanalysis
---
1. Go to
5. Enter the name of the segmentation.
6. Optionally, you can write a short description of the analysis.
**Result**: The first step is already done for you - a `session.start` event with the geographical coordinates are already selected. The system selects the group of customers which performed this event in the location you selected. Out of the group selected this way, you can select customers who meet your conditions specified in the further steps.
8. To create the next step in the segmentation, click the **Add funnel step** button.
9. To select an event, click the **Choose event** button.
10. If needed, specify the [event parameters](/docs/analytics/i_events-parameter-value) by clicking the **Where** button.
11. If you want to add a condition to the segmentation, click the **Choose filter** button.
12. Specify the dependency between the conditions by choosing the **AND** or **OR** operator.
- **OR** - Only one condition needs to be met.
- **AND** - Both conditions need to be met.
13. To set the time needed to complete all steps in the segmentation, click the clock icon.
To be included in the segmentation, a customer must complete the steps in the specified order and time.
14. To determine the time range from which the data will be analyzed, click the [calendar](/docs/analytics/i_date-filters) icon.
15. You can create several segmentations in one and compare them in one preview. To create another segmentation, click the
button.
15. To complete the process, click the **Save** button.
**Result**: When you save the segmentation based on geoanalytics, you can find it on the list of segmentations under the given name.
1. Go to 

1. Go to 






button, set **First** as the type of the aggregate result (this configures the aggregate to show the first value of the event parameter in the time range selected in the analysis).
4. From the **Choose event** dropdown list, select the **page.visit** event.
5. From the **Choose parameter** dropdown list, select **og:image**.
6. Click the **+ where** button.
7. From the **Choose parameter** dropdown list, select the **utm_campaign**.
8. Select the **Equal** logical operator.
9. Next to the logical operator, in the text field, enter the name of the UTM campaign.
10. By default, the date range for the analysis is set to the last 30 days. To change the date range, click the calendar icon. Confirm the changes with the **Apply** button.
11. Save the aggregate by clicking **Save**.
**Result**: The aggregate uses the image of the product and returns the first product viewed in the UTM campaign.
icon.
4. From the **Choose event** dropdown list, select the **Bought product** event.
5. Start creating the formula of the expression by clicking the **Select** button.
**Result**: A dropdown list appears.
6. From the dropdown list, select **Event attribute**.
**Result**: The **Unnamed** event attribute appears.
7. Click the attribute.
8. From the **Choose parameter** dropdown list, select **$quantity**.
9. Click the plus button.
**Result**: Another **event attribute** appears.
10. Click the attribute.
11. From the **Choose parameter** dropdown list, select **$finalUnitPrice**.
12. Multiply those two attributes, by selecting the multiplication sign between two event attributes.
**Result**:
button, set **First** as the type of the aggregate result (then the aggregate result shows the first value of the event parameter in the time range selected in the analysis).
4. From the **Choose event** dropdown list, select the **page.visit** event.
5. From the **Choose parameter** dropdown list, select the **og:image**.
6. Click the **+ where** button.
7. From the **Choose parameter** dropdown list, select **utm_campaign**.
8. Select the **Equal** logical operator.
9. Click the icon next to the logic operator and keep clicking until you get
button, set **First** as the type of the aggregate result (this configures the aggregate to show the first value of the event parameter in the time range selected in the analysis).
4. From the **Choose event** dropdown list, select the **page.visit** event.
5. From the **Choose parameter** dropdown list, select **Specials**.
6. From the list, select **TIMESTAMP**.
6. Click the **+ where** button.
7. From the **Choose parameter** dropdown list, select **utm_campaign**.
8. Select the **Equal** logical operator.
9. Click the icon next to the logic operator and keep clicking until you get
button, set **Last Multi** as the type of the aggregate result (this configures the aggregate to show the defined number of results of the event parameter in the time range selected in the analysis).
4. In the **Size** field, select the number of results of the aggregate.
4. From the **Choose event** dropdown list, select the **product.buy** event.
5. From the **Choose parameter** dropdown list, select **$orderId**.
6. Click the **+ where** button.
7. From the **Choose parameter** dropdown list, select **$image**.
8. Select the **Equal** logical operator.
9. Click the icon next to the logic operator and keep clicking until you get
## Contents
# Creating formula metrics
Compared to simple metrics, formula metrics let you perform more complex mathematical and logical operations on events and customer attributes. The result is always a number.
You can use metrics in [histograms](/docs/analytics/histograms/introduction-to-histograms) and [reports](/docs/analytics/reports/introduction-to-reports). Before proceeding, familiarize yourself with the limits and constraints that apply to metrics used in these analyses:
- [Allowed metrics in histograms](/docs/analytics/histograms/creating-histograms#allowed-metrics)
- [Allowed metrics in reports](/docs/analytics/reports/creating-reports#allowed-metrics)
## Requirements
---
You must have a [user role](/docs/settings/identity-access-management/permissions) with the following permissions:
- [access the Decision Hub](/docs/settings/identity-access-management/permissions/analytics-permissions#access-the-decision-hub)
- [view analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#view-analyses)
- [create analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#create-analyses)
- [edit analyses](/docs/settings/identity-access-management/permissions/analytics-permissions#edit-analyses)
- [preview results](/docs/settings/identity-access-management/permissions/analytics-permissions#preview-results)
- A tracking code implemented into your website.
## Creating a formula metric
---
1. Go to






| Property name | Available in | Description |
|---|---|---|
| Visualization type | All types of analyses apart from a metric and an expression | Select a chart type an analysis is going to be presented in. |
| Appearance | All types of analyses | Define the unit of results and their accuracy (decimal places). |
| Layout | All types of analyses apart from a metric, aggregate and an expression | Select a horizontal or vertical layout of a chart. |
| Axes | All types of analyses apart from a metric, aggregate and an expression |
|
| Axes titles | All type of analyses apart from a metric, aggregate and an expression | Enter titles for X and Y axes. |
| Legend | All type of analyses apart from a metric, aggregate and an expression | Define the position and alignment of a chart legend. |
| Colorize | All type of analyses apart from a metric, aggregate and an expression |
|
| Color palette | All type of analyses apart from a metric, aggregate and an expression | Select colors of chart elements. |
| Text | A metric, aggregate and an expression |
|
| Icon | A metric, aggregate and an expression | Select an icon and its color. The icon is displayed above the title of the widget. |
| Goal colors | A metric, aggregate and an expression | Define the color of the lowest and the highest result. |



1. Go to
- To go back to editing the segment, scroll up the screen and click **Show conditions**
- To include a customer in more than one segment, if the customer met conditions, in the preview of the segmentation, switch the [**Multi-match**](/docs/analytics/segmentations/creating-segmentations#multi-match) toggle on.
- To see the percentage distribution, scroll down the page.
- To preview the list of customers that meet the requirements of the segmentation, click the column/slice of a pie chart that represents a segment and select **Show records**.
- To print out the preview of the segmentation, in the **Preview** section, click 


## Contents
# Exporting reports to a file
You can export a report into a CSV file.
## Report export limits
A report can contain up to 250,000 records. If your report exceeds this limit, you must divide it into smaller parts. You can do this in the settings of a metric used in a report.
For example, when you want to request a list of bestselling items and, you can:
1. Create simple metrics for item categories, for example summer, autumn, winter, spring.
2. Create a report and add one of the metrics to it.
3. Export the report.
4. Change the report to another metric and export it.
5. Repeat until you export all the data you need.
Alternatively, you can also create separate reports for each category.
## Procedure
1. Go to
## Contents
---
# Removing metrics
When you do not need an analysis any longer, you can delete it from the system.

























The screen below presents a segmentation that groups profiles in terms of their date of birth. The conditions of the segmentation uses the Custom logical operator to define the date range for the birth date attribute.









{
"clientId": 6855607997,
"email": "default_unique_71fa217a-4c72-4224-89d0-780b7fdfda16@anonymous.invalid",
...
"agreements": {
...
},
"attributes": {
"exampleCustomAttribute": "2023-08-03T11:30:00",
},
"tags": []
}
{
"time": "2023-08-04T14:08:33.990Z",
"action": "docs.read",
"client": {
"id": 6855607997,
"email": "default_unique_71fa217a-4c72-4224-89d0-780b7fdfda16@anonymous.invalid",
"uuid": "eb73d1c7-c9de-491a-a7bf-992a7167311c"
},
"params": {
"exampleCustomParam": "2023-08-03T11:30:00"
}
}





