How does Crisp Analytics work?
This article is your main resource guide to help you understand and leverage the Analytics tools available with Crisp. We'll review how it works in detail, how you can take advantage of it to improve your services, and we'll explore the different features available to help you build your own customized reports.
The Analytics section provides in-depth information about your inbox's activity and how your users interact with you. You can use it to review the number of messages received, visits on your website and helpdesk, ratings left by your users, and also to monitor how your agents are using Crisp, and much more!
You also have the ability to build your own custom reports to easily find the information that matters and generate reports on the go.
Let's now take a closer look at what's available!
The Crisp Analytics are exclusively available from the Crisp Essentials plan . You can find out more about the many features and tools available on the Essentials plan by visiting this article . And of course, feel free to get in touch with us for a free trial 🚀
Getting Started
Available Reports
→ Messaging
→ Visitors
→ Helpdesk
→ Contacts
→ Status Page
→ Dashboard
Understanding and Navigating the Analytics
→ Preferences
→ Actions
→ Configuration
→ Filters
Frequently Asked Questions
Let's first see how to use and navigate the Analytics. To get started, you can access the Analytics tools from the main navigation bar (on the left) .
The Analytics tools are split into different categories (Messaging, Visitors, Helpdesk...). Each of these categories contains different sections (Overview, Responsiveness, Ratings...).
You can easily navigate through the sections of these categories to display the relevant reports , and monitor the data that is the most relevant to you.
All of the data reports are pre-configured for you, using the most commonly pertinent aggregation methods for these statistics . You can simply scroll through them and directly see the relevant metrics without any additional work. ✨
However, it may be interesting to understand what dataset is being used for these reports, or what the default calculation methods used by Crisp are. To do that, you can directly visit the next chapter of this guide to review all of the details of the available reports .
Default configurations are great and simple to use, but you may want to customize your reports . For instance, tweaking the aggregation methods or applying filters can help you shed light on specific behaviors, or identify certain patterns. All of this is possible, and we have dedicated a section of this article to help you learn how to navigate the Analytics tools .
And of course, don't hesitate to visit our renowned FAQ section if you are eager to learn more. You will also find extra resource links in this article to help you apply your knowledge and leverage the data made available by these reports. Don't hesitate to check them out!
These are the different reports you can review from the Analytics tools of your workspace, each presented within its own report. From the top bar, you can select your timezone as well as the time period you are interested in (past week, month, year, etc., depending on the type of data).
Each report can be downloaded , and you will find this option in the top-right corner of each report, if you'd like to export them and further aggregate data to build your own statistics.
Each report contains a description of the dataset the report is generated from (e.g., the Response Time is the delay between the first user message and the first agent reply) and the default aggregation type (the way the report is calculated, e.g., for Response Time, this is an "Average" by default, but you can switch it to "Median" to smooth out fluctuations).
This is the section you'll be interested in if you're looking for behavioral data related to your Crisp inbox.
It includes website visits, conversation activity, as well as metrics related to how your agents interact with Crisp and users. For instance, you will find information such as your team's response time, shortcut usage, conversations handled, and more.
The Overview offers quick access to the most frequently used data points. This allows you to easily consult the most relevant data related to your inbox and agents at a glance.
In this area, you will find several types of reports:
Shows the total number of conversations received in your inbox over the time period selected. The value in green/red represents the difference from the previous period.
This data is calculated by taking into account all conversations received from your users or created by your agents. Conversations that may have been deleted are still taken into account in this report. A new conversation is counted if there is a time difference of 24 hours or more between 2 messages in the same conversation.
Shows the total number of unique users who have visited your website over the time period selected. The value in green/red represents the difference from the previous period.
This data is calculated by taking into account all unique sessions of users who visited a page where Crisp is installed at least once.
Shows the average rating over the time period selected. The value in green/red represents the difference from the previous period.
This data is calculated by averaging all ratings left by users (whether left from the chatbox or email).
Shows the number of conversations per day over the time period selected.
This data is calculated by simply adding up all conversations where at least one message was exchanged on that day. If a conversation received new messages on a different day, it will be counted again.
Exporting this report will include the following data: The session_id of the conversation, the origin channel (chat, email, WhatsApp...), and the time at which the conversation started.
Shows the average number of conversations per hour over the time period selected.
This data is calculated by averaging the number of conversations you received during a specific hour of a given day, over the selected time frame.
Exporting this report will include the following data: The day/hour period and the rounded up average number of conversations.
Example: If on each Tuesday of last month you received 12, 18, 15, and 21 conversations between 13:00 and 14:00, the average will be 16.5.
Shows the number of conversations in which your operators have participated over the time period selected.
This data takes into account any conversation where an agent has sent at least one message.
Exporting this report will include the following data: The time period selected, the number of conversations for that operator, and the operator's user_id .
This is where you can review in-depth data about your efficiency in handling conversations. This section displays data related to the average response time and allows you to monitor your team's overall performance.
In this area, you will find several types of reports:
Shows the average response time (Bots and human agents combined) over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by calculating the delay between the first user message in the conversation and the first reply sent by an agent or automation. Resolving a conversation without sending a message will also stop this timer (as if the agent had replied).
Note: Resolving a conversation without any reply does not directly stop the timer, but since no message is exchanged from the agent, no response time will be calculated for that conversation.
Shows the average response time (humans only) over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by calculating the delay between the first user message and the first reply (if sent by an agent, not an automation).
Note: If the first reply was sent by automation, this conversation will not be included in that report.
Shows the delay between when the conversation is marked as Pending/Unresolved and when it is resolved. The value in green/red represents the difference from the previous period.
This data is calculated by averaging the duration taken by your team to resolve a conversation.
Shows the average response time per hour over the time period selected.
This data is calculated by averaging the response time of your team for a specific hour of a given day over the selected time frame.
Exporting this report will include the following data: The day/hour period , and the average response time for that period in seconds.
Note: The response time itself is calculated by taking into account the delay between the first user message and the first reply from an operator.
Shows the average resolution time per day over the time period selected.
This data is aggregated by averaging the resolution time for each day of the time frame specified.
Exporting this report will include the following data: The day/hour period , and the average resolution time for that period in seconds.
Note: The response time is calculated by taking into account the delay between a user message and the next reply from an operator. Resolving a conversation without sending a message also stops this timer.
This section of the Analytics allows you to review ratings and feedback left by your customers. Ratings can be left at the end of an exchange from the chatbox itself, or from an email transcript.
Make sure to configure your Office hours from the Settings icon on the top-right of each report, if you'd like the response time to only account for your business hours.
In this area, you will find several types of reports:
Shows the average rating left by your customers over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by simply calculating the average rating over the selected time frame.
Shows the average rating left by your customers where only automations intervened (Bot/AI) over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by calculating the average rating left by users who only interacted with your automations.
Shows the average rating per day over the time period selected.
This data is calculated by averaging the ratings left by your users for each day over the selected time frame.
Exporting this report will include the following data: The time period , and the sum of all ratings left for that period, the number of ratings left, and the average rating .
Shows the details of ratings left over the time period selected.
This data is a report of each individual rating left by your users (note, comment, meta information) over the selected time frame.
Exporting this report will include the following data: The ID of the conversation , and the date of the feedback, the name and email address of the user, the rating and the comment , and the operator assigned to that conversation.
Note: If a user leaves multiple ratings, their initial one will be updated instead. You will have one note per user to determine their experience with your support.
The Operator view allows you to quickly review individual operators' performance and obtain metrics on their conversations.
In this area, you will find one type of report:
Shows individual metrics about each of your operators.
Conversations: the total number of conversations handled by that agent, calculated by adding up all conversations this agent has been assigned to.
Response Time: Aggregated by calculating the average delay between any given user message and this agent's reply.
Resolution Time: Aggregated by calculating the average delay between the moment a conversation is started and the moment it is marked as resolved.
Ratings: Average rating left by users on a conversation assigned to that particular agent.
Exporting this report will include the following data: The agent's name and ID , and the amount of handled conversations , their response time , resolution time , and average rating .
This section allows you to review your usage of Automations within Crisp (such as the Bot plugin).
In this area, you will find one type of report:
Shows the number of conversations where an automation contributed (automation sent a message during the conversation) over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by adding up the number of conversations where an automation contributed with a message.
Shows the number of conversations where only** an automation handled that conversation (by sending at least one message) over the time period selected. The value in green/red represents the difference from the previous period.**
This data is aggregated by adding up the number of conversations where the user only interacted with an automation (no human-agent exchange).
Shows the number of conversations where an automation contributed, over the time period selected.
This data is aggregated by adding up the number of conversations where an automation contributed with a message.
Exporting this report will include the following data: The time period , and the sum of conversations where an automation intervened.
This area allows you to monitor the different channels from which your users contact you and review the most popularly used ones.
In this area, you will find several types of reports:
Shows the total number of conversations initiated from the Chatbox, over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by adding up the number of conversations where the user exchanged via the Chatbox.
Note: This data also accounts for agent-initiated chat conversations (created by our agents from MagicBrowse, for instance).
Shows the total number of conversations initiated from the Chatbox, over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by adding up the number of conversations where the user exchanged via email.
Note: This data also accounts for agent-initiated emails (created by our agents from your Crisp inbox).
Shows the total number of conversations initiated from all other channels, over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by adding up the number of conversations where the user exchanged via all other channels (WhatsApp, contact form, social media, etc.).
This Pareto chart shows the most popularly used communication channels by your users.
This data is calculated by adding up the number of conversations from each individual channel selected.
Exporting this report will include the following data: The time period , the sum of all conversations per channel , and the name of the matching channel.
Consult this section for SLAs (Service Level Agreement) related metrics and monitor the number of conversations that failed to meet your SLAs.
In this area, you will find several types of reports:
Shows the average number of conversations that lasted longer than 1 hour for each hour of the day, over the time period selected.
This data represents the average number of conversations that failed to meet a 1-hour SLA for each hour of a given day. It calculates the delay between when a conversation starts and its resolution time.
Exporting this report will include the following data: The time period , and the average number of conversations that lasted longer than 1 hour.
Shows the total number of conversations occurring during your office hours that lasted longer than 1 hour, over the time period selected.
This data represents the total number of conversations for each day that failed to meet a 1-hour SLA. It calculates the delay between when a conversation starts and its resolution time.
Exporting this report will include the following data: The time period , and the total number of conversations that lasted longer than 1 hour.
This section allows you to review the usage of segments and their frequency of use in your conversations.
In this area, you will find several types of reports:
Shows the total number of times each of your segments was added to a conversation, over the time period selected.
This data is aggregated by counting segments when added to your conversations. Segments are only counted once per conversation.
Exporting this report will include the following data: The time period , the number of times a segment has been added, and its name .
Shows the usage frequency of your segments in your conversations, over the time period selected.
This data is aggregated by counting segments when added to your conversations.
Exporting this report will include the following data: The time period , and the number of times a segment has been added and its name .
This section allows you to review the usage of shortcuts and their frequency of use by your agents.
In this area, you will find several types of reports:
Shows the total number of conversations where a specific shortcut was added, over the time period selected.
This data is aggregated by counting each shortcut used by your agents during conversations.
Exporting this report will include the following data: The time period , and the number of times a shortcut has been used and its name .
Note: Shortcuts are counted when they are selected by an agent. A shortcut can be counted several times per conversation if the agent uses it multiple times.
Shows the usage frequency of your shortcuts, over the time period selected.
This data is aggregated by counting each shortcut used by your agents during conversations.
Exporting this report will include the following data: The time period , and the number of times a shortcut has been used and its name .
This is the section you'll be interested in if you are looking to monitor your website's visits.
This section will allow you to review a geographical heatmap of your visitors' locations, as well as daily/weekly/monthly/yearly reports of their activity on your website, including Triggers fired.
This view presents metrics about your website's visits and their geographical location.
In this area, you will find several types of reports:
Shows the total number of visits to your website on the previous day. The value in green/red represents the difference from the previous period.
This data is calculated by detecting unique sessions that visited your website on a page where Crisp is installed, for the past day.
Shows the total number of visits to your website in the past week. The value in green/red represents the difference from the previous period.
This data is calculated by detecting unique sessions that visited your website on a page where Crisp is installed, for the past week.
Shows a heatmap of your visitors' locations, providing visual data of your audience's localization. The value in green/red represents the difference from the previous period.
This data is the sum of visits originating from each country, over the specified time period.
Exporting this report will include the following data: The time period , the number of visits per country for that period, and the corresponding country codes .
Note: Crisp does not directly track your users' locations. This data relies on public API registries for IP addresses published by ISPs.
Shows a trend graph of the daily visits to your website.
This data is the sum of visits for each day over the specified time period.
Exporting this report will include the following data: The time period , and the total number of visits for each day.
This section presents metrics about the usage of Triggers and their frequency of use.
In this area, you will find several types of reports:
Shows the total number of triggers fired. The value in green/red represents the difference from the previous period.
This data is simply the sum of all triggers fired, over the specified time period.
Shows a trend graph of the daily triggers fired on your website.
This data is the sum of each Trigger fired for each specific day, over the specified time period.
Exporting this report will include the following data: The time period , the number of times a trigger fired, and its name .
This area allows you to monitor how your Helpdesk is being used by your users and review detailed information about the popularity of your articles.
You can access details about visits, which locales are most frequently consulted, as well as metrics about individual article visits, frequently searched terms, and ratings left by your users.
This view presents metrics about your Helpdesk visits and the different locales.
In this area, you will find several types of reports:
Shows the total number of visits to your Helpdesk on the previous day. The value in green/red represents the difference from the previous period.
This data is calculated by detecting unique sessions that visited your Helpdesk, over the selected time period.
Shows the total number of visits to your Helpdesk in the past week.
This data is calculated by detecting unique sessions that visited your Helpdesk on each day, over the selected time period.
Exporting this report will include the following data: The time period , and the number of visits for that period.
Shows the total number of visits for each specific locale of your Helpdesk.
This data represents the number of unique visits a specific locale of your Helpdesk received, over the selected time period.
Exporting this report will include the following data: The time period , the number of visits for that locale, and its name .
This section shows statistics about how your users interact with the Search features of the Helpdesk.
In this area, you will find several types of reports:
Shows the total number of search requests performed. The value in green/red represents the difference from the previous period.
This data is a representation of the number of times the search feature has been used, over the specified time period.
Shows the most commonly searched terms in the Helpdesk.
This data is aggregated by compiling your users' searches and building a collection of the most commonly used terms, over the specified time period.
Exporting this report will include the following data: The time period , the number of times a specific term was searched, and the term in question.
This section displays information about specific articles. You can select the Helpdesk locale you'd like to review directly at the top.
In this area, you will find several types of reports:
Shows extensive data about each of your articles: Visits, Reactions, Usefulness, and additional actions.
Visits : The total number of unique visits this article received over the specified time period.
Reactions : The rating left by your users (positive or negative).
Usefulness : This score represents a ratio between the number of user visits an article received and the average rating left by your users.
Action 🙂: Access details about the article's rating and comments left by your users.
Action 📊: Access details about the article's visits for each day over the selected period of time.
Exporting this report will include the following data: The time period , the number of visits each article received during that period, and its name .
This section allows you to review data about the Crisp CRM (Contacts) and Campaigns activity.
These reports include data about contact creation, the usage of your email campaigns, and monitoring data such as delivery, bounce rates, openings, and more.
This view shows data about the number of contacts being saved in your Crisp CRM.
In this area, you will find several types of reports:
Shows the number of contacts saved in your Crisp CRM the previous day.
This data is calculated by taking into account all contacts who have been created in your CRM on that date.
Shows the number of contacts saved in your Crisp CRM this week.
This data is calculated by taking into account all contacts who have been created in your CRM duriong that week.
Shows the number of new contacts created in your CRM for each day of the selected time period. The value in green/red represents the difference from the previous period.
This data is calculated by detecting new contacts added to your CRM over the selected time period.
Exporting this report will include the following data: The date , and the number of contacts created on that date.
This section shows overall metrics about the number of contacts reached by your Automated and One-shot Campaigns.
In this area, you will find one type of report:
Shows the total number of recipients to whom you have sent a campaign over the selected time period.
This data is aggregated by adding up the number of contacts you have sent an email campaign to (automated or one-shot), over the selected time period.
Exporting this report will include the following data: The time period , the number of recipients hit by a campaign, and the type of campaign.
This section includes specific details about your campaigns' performances.
In this area, you will find several types of reports:
Shows in-depth data about the global performance of your Email campaigns (Automated and One-shot) over the specified time period.
Delivered : The total number of recipients campaigns were delivered to during that period.
Opened : This is an indicative representation of the number of times your users opened these email campaigns.
Bounced : The number of campaigns that were bounced (e.g. email was rejected by the recipient's SMTP).
Clicked : The number of times a user clicked an external link inside your campaigns. Counted once per email.
Unsubscribed : The number of times a user unsubscribed from the email they received.
Exporting this report will include the following data: The time period , the number of visits for each article during that period, and its name .
This area is dedicated to the Status page and allows you to monitor the downtime and incidents of the nodes you are tracking.
This section allows you to monitor overall downtime and the specific services that displayed incidents.
In this area, you will find several types of reports:
Shows the total duration your nodes have been detected as down (incident). The value in green/red represents the difference from the previous period.
This data is calculated by reporting the duration during which one or more services were down, over the selected time period.
Shows the individual downtimes for each of the monitored nodes.
This data is calculated by adding up the individual durations during which each service was detected as down, over the selected time period.
Exporting this report will include the following data: The time period , the total downtime , and the name of the node.
The dashboard allows you to build your own tailored reports from scratch. You can create customized reports which will be saved for later use, this is a quick way to access the data which matters the most to you. Just like the default reports, you can apply your own preferences, configurations (aggregation type, filters, etc) but also select the type of chart you'd like to use.
Once a dashboard created or selected, you can click Add Chart on the upper-right corner to get started.
This will pop a drop down menu where you can select the type of report you wish to use for this chart:
Summary : A simple widget to display a quick info (response time, amount of conversations...)
Chart : A detailled chart among various available options
Articles : Details about your Helpdesk articles (read, feedback...)
Map : Used to display visitor locations
Heat Map : A heat map is helpful when looking for data related to geographical location of your users
Operators : Allows to display details about operators (response time, amount of conversations handled...)
Rating : All you need to know about the feedback left by your users
Similarly to the default Analytics reports, the ones you create in the Dashboard can be configured to meet your exact needs. You can change the split date, aggregation type, or apply various filters to obtain the data you're looking to monitor.
Dashboard reports are saved and can be only accessed by the agent who created them. This allows you to keep your custom reports private from your team.
By default, reports are configured to be presented in their most common form, giving you easy access to the metrics you're looking for. However, you can create your own custom reports in a Dashboard and tweak the existing ones by adjusting the various available settings.
Now, let’s take a look at the different tools available in the interface to help you familiarize yourself with these.
You can change these settings at any time, and your modifications will carry over as you navigate through different reports.
Time Period : Select the time period for the reports displayed (past week, month, year, or today).
Timezone : Select your timezone to align the reports with your location.
Note: Some reports may not be available for specific time periods depending on their purpose.
This contextual menu provides quick actions for each of your reports.
Add to Dashboard : Add a report to one of your dashboards. More about Dashboards in this section .
Export Data : Download a CSV export containing details about the report.
This is where you can customize each individual report and change how your data is aggregated. You can configure your Office hours, select a date split, choose an aggregation type, and apply filters to isolate or combine specific data points.
Select the days/hours from which your data should be aggregated. Data generated outside of these hours will be excluded when the report is built, allowing you to generate reports that reflect your business hours.
Your reports are generated based on the time period defined in the General Preferences and the Office Hours you selected above.
The Date Split allows you to choose how the report is split. You can choose to see the hourly, daily, weekly, etc., data over the period you selected.
Available date splits include:
Hourly
Daily
Weekly
Monthly
Yearly
All
Note: Some reports may not support certain date splits. In such cases, the option will not appear or will be disabled.
By default, reports are aggregated using the most relevant method for that type of data. While the default option works in most cases, you can explore other aggregation types to extract specific metrics, export data for external analysis, or review more detailed statistics.
Available aggregation types:
Average : Adds up all values and divides by the number of values, providing the mean.
→ Useful for understanding overall trends or typical values.
Moving average : Averages data over a specific number of periods, updating as new data comes in to smooth fluctuations.
→ Useful for identifying trends over time and smoothing short-term changes.
Median : The middle value in a dataset when values are ordered from lowest to highest.
→ Useful for finding the center of your data, especially in skewed distributions.
Minimum : The smallest value in the dataset.
→ Useful for identifying the lower limit or extreme low values.
Maximum : The largest value in the dataset.
→ Useful for identifying the upper limit or extreme high values.
Sum : Adds up all values in the dataset.
→ Useful for understanding the total value or volume in your dataset.
Note: Some aggregation types may not be available for certain reports. In these cases, the option will be unavailable or disabled.
🤔 Still a bit unclear? Let’s see an example. Consider a 10-day dataset of daily conversations: 50, 60, 70, 80, 90, 200, 100, 110, 120, 130.
Here’s how the different aggregation types would process this data:
Average : The sum of all values divided by the number of days.
→ (50 + 60 + 70 + 80 + 90 + 200 + 100 + 110 + 120 + 130) / 10 = 101
Moving Average (e.g., on a 7-day split): Takes the average of the first 7 days and moves as new data comes in.
→ Day 1-7 : (50 + 60 + 70 + 80 + 90 + 200 + 100) / 7 = 93
→ Day 2-8 : (60 + 70 + 80 + 90 + 200 + 100 + 110) / 7 = 101
→ Day 3-9 : (70 + 80 + 90 + 200 + 100 + 110 + 120) / 7 = 110
→ Day 4-10 : (80 + 90 + 200 + 100 + 110 + 120 + 130) / 7 = 119
Median : The middle value when data is ordered.
→ Ordered dataset: 50, 60, 70, 80, 90, 100, 110, 120, 130, 200 => Median = 95
Minimum : Smallest value = 50
Maximum : Largest value = 200
Sum : Total conversations over 10 days = 1010
In some cases, you may want to isolate specific elements in your data to generate a report aggregated from more specific information. This is where filters come into play.
Available filter types:
Segments : Filter conversations that include or exclude specific segments.
Country : Filter conversations based on the user's country.
Rating : Filter data where a rating was left, above or below a specified threshold.
Visitor Origin : Filter conversations based on their origin channel (chat, email, Instagram, etc.).
First Operator Origin : Filter conversations where the first operator message was sent via a specific channel (chat, Slack, etc.).
First Operator : Filter conversations based on who was the first operator to participate.
Last Operator Origin : Filter conversations where the last operator message was sent via a specific channel.
Last Operator : Filter conversations based on who was the last operator to participate.
Response Time : Filter conversations based on their response time (in seconds).
Handle Time : Filter conversations based on their resolution time (in seconds).
Filters allow you to include or exclude data based on your needs, and you can combine multiple filters to generate a tailored report.
When adding multiple data points within the same filter (e.g., multiple segments), this will apply an or condition. To apply an and condition, add a second filter for the second data point.
Still have questions about the Analytics tools that weren’t covered in this guide? You may find the answers here!
Here is a collection of the most frequently asked questions, along with extra resources to help you better understand how the Analytics work and explore related features to improve your data usage.
If your question isn’t listed here, feel free to contact us directly via chat. We're available!
There are a couple of ways to do this. On the Essentials plan, you can leverage the Chatbot plugin .
The Chatbot can trigger automatically when users contact you, check the URL they are currently browsing, and apply the segment you’ve configured for that URL .
Another approach would be to use our Javascript SDK to programmatically add a segment to conversations based on the page they’re currently browsing.
Once a segment has been added to a conversation, you can monitor it in the Analytics under the Segments section to track its frequency, or you can create custom filters in your inbox to review them.
Absolutely. The Crisp Analytics allows you to monitor various data about your inbox, conversations, operators, and more. However, if you want to track specific events in Google Analytics, this is possible too.
We have a dedicated guide with GTM and GA4 to help you track events such as when users open your chatbox, message you, fill in their email address, and more. 🙂
The Analytics section provides in-depth information about your inbox's activity and how your users interact with you. You can use it to review the number of messages received, visits on your website and helpdesk, ratings left by your users, and also to monitor how your agents are using Crisp, and much more!
You also have the ability to build your own custom reports to easily find the information that matters and generate reports on the go.
Let's now take a closer look at what's available!
The Crisp Analytics are exclusively available from the Crisp Essentials plan . You can find out more about the many features and tools available on the Essentials plan by visiting this article . And of course, feel free to get in touch with us for a free trial 🚀
Table of Content
Getting Started
Available Reports
→ Messaging
→ Visitors
→ Helpdesk
→ Contacts
→ Status Page
→ Dashboard
Understanding and Navigating the Analytics
→ Preferences
→ Actions
→ Configuration
→ Filters
Frequently Asked Questions
Getting Started
Let's first see how to use and navigate the Analytics. To get started, you can access the Analytics tools from the main navigation bar (on the left) .
The Analytics tools are split into different categories (Messaging, Visitors, Helpdesk...). Each of these categories contains different sections (Overview, Responsiveness, Ratings...).
You can easily navigate through the sections of these categories to display the relevant reports , and monitor the data that is the most relevant to you.
All of the data reports are pre-configured for you, using the most commonly pertinent aggregation methods for these statistics . You can simply scroll through them and directly see the relevant metrics without any additional work. ✨
However, it may be interesting to understand what dataset is being used for these reports, or what the default calculation methods used by Crisp are. To do that, you can directly visit the next chapter of this guide to review all of the details of the available reports .
Default configurations are great and simple to use, but you may want to customize your reports . For instance, tweaking the aggregation methods or applying filters can help you shed light on specific behaviors, or identify certain patterns. All of this is possible, and we have dedicated a section of this article to help you learn how to navigate the Analytics tools .
And of course, don't hesitate to visit our renowned FAQ section if you are eager to learn more. You will also find extra resource links in this article to help you apply your knowledge and leverage the data made available by these reports. Don't hesitate to check them out!
Available Reports
These are the different reports you can review from the Analytics tools of your workspace, each presented within its own report. From the top bar, you can select your timezone as well as the time period you are interested in (past week, month, year, etc., depending on the type of data).
Each report can be downloaded , and you will find this option in the top-right corner of each report, if you'd like to export them and further aggregate data to build your own statistics.
Each report contains a description of the dataset the report is generated from (e.g., the Response Time is the delay between the first user message and the first agent reply) and the default aggregation type (the way the report is calculated, e.g., for Response Time, this is an "Average" by default, but you can switch it to "Median" to smooth out fluctuations).
Messaging
This is the section you'll be interested in if you're looking for behavioral data related to your Crisp inbox.
It includes website visits, conversation activity, as well as metrics related to how your agents interact with Crisp and users. For instance, you will find information such as your team's response time, shortcut usage, conversations handled, and more.
❋ Overview
The Overview offers quick access to the most frequently used data points. This allows you to easily consult the most relevant data related to your inbox and agents at a glance.
In this area, you will find several types of reports:
Conversations
Shows the total number of conversations received in your inbox over the time period selected. The value in green/red represents the difference from the previous period.
This data is calculated by taking into account all conversations received from your users or created by your agents. Conversations that may have been deleted are still taken into account in this report. A new conversation is counted if there is a time difference of 24 hours or more between 2 messages in the same conversation.
Visitors
Shows the total number of unique users who have visited your website over the time period selected. The value in green/red represents the difference from the previous period.
This data is calculated by taking into account all unique sessions of users who visited a page where Crisp is installed at least once.
Ratings
Shows the average rating over the time period selected. The value in green/red represents the difference from the previous period.
This data is calculated by averaging all ratings left by users (whether left from the chatbox or email).
Conversations over Time
Shows the number of conversations per day over the time period selected.
This data is calculated by simply adding up all conversations where at least one message was exchanged on that day. If a conversation received new messages on a different day, it will be counted again.
Exporting this report will include the following data: The session_id of the conversation, the origin channel (chat, email, WhatsApp...), and the time at which the conversation started.
Conversations per Period
Shows the average number of conversations per hour over the time period selected.
This data is calculated by averaging the number of conversations you received during a specific hour of a given day, over the selected time frame.
Exporting this report will include the following data: The day/hour period and the rounded up average number of conversations.
Example: If on each Tuesday of last month you received 12, 18, 15, and 21 conversations between 13:00 and 14:00, the average will be 16.5.
Conversations per Operator
Shows the number of conversations in which your operators have participated over the time period selected.
This data takes into account any conversation where an agent has sent at least one message.
Exporting this report will include the following data: The time period selected, the number of conversations for that operator, and the operator's user_id .
❋ Responsiveness
This is where you can review in-depth data about your efficiency in handling conversations. This section displays data related to the average response time and allows you to monitor your team's overall performance.
In this area, you will find several types of reports:
Response Time
Shows the average response time (Bots and human agents combined) over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by calculating the delay between the first user message in the conversation and the first reply sent by an agent or automation. Resolving a conversation without sending a message will also stop this timer (as if the agent had replied).
Note: Resolving a conversation without any reply does not directly stop the timer, but since no message is exchanged from the agent, no response time will be calculated for that conversation.
Human Response Time
Shows the average response time (humans only) over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by calculating the delay between the first user message and the first reply (if sent by an agent, not an automation).
Note: If the first reply was sent by automation, this conversation will not be included in that report.
Time to Handle
Shows the delay between when the conversation is marked as Pending/Unresolved and when it is resolved. The value in green/red represents the difference from the previous period.
This data is calculated by averaging the duration taken by your team to resolve a conversation.
Response Time
Shows the average response time per hour over the time period selected.
This data is calculated by averaging the response time of your team for a specific hour of a given day over the selected time frame.
Exporting this report will include the following data: The day/hour period , and the average response time for that period in seconds.
Note: The response time itself is calculated by taking into account the delay between the first user message and the first reply from an operator.
Time to Handle — During Office Hours
Shows the average resolution time per day over the time period selected.
This data is aggregated by averaging the resolution time for each day of the time frame specified.
Exporting this report will include the following data: The day/hour period , and the average resolution time for that period in seconds.
Note: The response time is calculated by taking into account the delay between a user message and the next reply from an operator. Resolving a conversation without sending a message also stops this timer.
❋ Ratings
This section of the Analytics allows you to review ratings and feedback left by your customers. Ratings can be left at the end of an exchange from the chatbox itself, or from an email transcript.
Make sure to configure your Office hours from the Settings icon on the top-right of each report, if you'd like the response time to only account for your business hours.
In this area, you will find several types of reports:
Overall Rating
Shows the average rating left by your customers over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by simply calculating the average rating over the selected time frame.
Automation Rating
Shows the average rating left by your customers where only automations intervened (Bot/AI) over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by calculating the average rating left by users who only interacted with your automations.
Ratings Evolution
Shows the average rating per day over the time period selected.
This data is calculated by averaging the ratings left by your users for each day over the selected time frame.
Exporting this report will include the following data: The time period , and the sum of all ratings left for that period, the number of ratings left, and the average rating .
Ratings
Shows the details of ratings left over the time period selected.
This data is a report of each individual rating left by your users (note, comment, meta information) over the selected time frame.
Exporting this report will include the following data: The ID of the conversation , and the date of the feedback, the name and email address of the user, the rating and the comment , and the operator assigned to that conversation.
Note: If a user leaves multiple ratings, their initial one will be updated instead. You will have one note per user to determine their experience with your support.
❋ Operators
The Operator view allows you to quickly review individual operators' performance and obtain metrics on their conversations.
In this area, you will find one type of report:
Operators
Shows individual metrics about each of your operators.
Conversations: the total number of conversations handled by that agent, calculated by adding up all conversations this agent has been assigned to.
Response Time: Aggregated by calculating the average delay between any given user message and this agent's reply.
Resolution Time: Aggregated by calculating the average delay between the moment a conversation is started and the moment it is marked as resolved.
Ratings: Average rating left by users on a conversation assigned to that particular agent.
Exporting this report will include the following data: The agent's name and ID , and the amount of handled conversations , their response time , resolution time , and average rating .
❋ Automation
This section allows you to review your usage of Automations within Crisp (such as the Bot plugin).
In this area, you will find one type of report:
Automated Conversations
Shows the number of conversations where an automation contributed (automation sent a message during the conversation) over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by adding up the number of conversations where an automation contributed with a message.
Fully Automated Conversations
Shows the number of conversations where only** an automation handled that conversation (by sending at least one message) over the time period selected. The value in green/red represents the difference from the previous period.**
This data is aggregated by adding up the number of conversations where the user only interacted with an automation (no human-agent exchange).
Automated Conversations
Shows the number of conversations where an automation contributed, over the time period selected.
This data is aggregated by adding up the number of conversations where an automation contributed with a message.
Exporting this report will include the following data: The time period , and the sum of conversations where an automation intervened.
❋ Channels
This area allows you to monitor the different channels from which your users contact you and review the most popularly used ones.
In this area, you will find several types of reports:
Chat Conversations
Shows the total number of conversations initiated from the Chatbox, over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by adding up the number of conversations where the user exchanged via the Chatbox.
Note: This data also accounts for agent-initiated chat conversations (created by our agents from MagicBrowse, for instance).
Email Conversations
Shows the total number of conversations initiated from the Chatbox, over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by adding up the number of conversations where the user exchanged via email.
Note: This data also accounts for agent-initiated emails (created by our agents from your Crisp inbox).
Others
Shows the total number of conversations initiated from all other channels, over the time period selected. The value in green/red represents the difference from the previous period.
This data is aggregated by adding up the number of conversations where the user exchanged via all other channels (WhatsApp, contact form, social media, etc.).
Most Used Messaging Channels
This Pareto chart shows the most popularly used communication channels by your users.
This data is calculated by adding up the number of conversations from each individual channel selected.
Exporting this report will include the following data: The time period , the sum of all conversations per channel , and the name of the matching channel.
❋ SLAs
Consult this section for SLAs (Service Level Agreement) related metrics and monitor the number of conversations that failed to meet your SLAs.
In this area, you will find several types of reports:
Conversations SLA above 1 hour
Shows the average number of conversations that lasted longer than 1 hour for each hour of the day, over the time period selected.
This data represents the average number of conversations that failed to meet a 1-hour SLA for each hour of a given day. It calculates the delay between when a conversation starts and its resolution time.
Exporting this report will include the following data: The time period , and the average number of conversations that lasted longer than 1 hour.
Conversations SLA above 1 hour - During office hours
Shows the total number of conversations occurring during your office hours that lasted longer than 1 hour, over the time period selected.
This data represents the total number of conversations for each day that failed to meet a 1-hour SLA. It calculates the delay between when a conversation starts and its resolution time.
Exporting this report will include the following data: The time period , and the total number of conversations that lasted longer than 1 hour.
❋ Segments
This section allows you to review the usage of segments and their frequency of use in your conversations.
In this area, you will find several types of reports:
Most Used Segments
Shows the total number of times each of your segments was added to a conversation, over the time period selected.
This data is aggregated by counting segments when added to your conversations. Segments are only counted once per conversation.
Exporting this report will include the following data: The time period , the number of times a segment has been added, and its name .
Segments Used Over Time
Shows the usage frequency of your segments in your conversations, over the time period selected.
This data is aggregated by counting segments when added to your conversations.
Exporting this report will include the following data: The time period , and the number of times a segment has been added and its name .
❋ Shortcuts
This section allows you to review the usage of shortcuts and their frequency of use by your agents.
In this area, you will find several types of reports:
Most Used Shortcuts
Shows the total number of conversations where a specific shortcut was added, over the time period selected.
This data is aggregated by counting each shortcut used by your agents during conversations.
Exporting this report will include the following data: The time period , and the number of times a shortcut has been used and its name .
Note: Shortcuts are counted when they are selected by an agent. A shortcut can be counted several times per conversation if the agent uses it multiple times.
Shortcuts Used Over Time
Shows the usage frequency of your shortcuts, over the time period selected.
This data is aggregated by counting each shortcut used by your agents during conversations.
Exporting this report will include the following data: The time period , and the number of times a shortcut has been used and its name .
Visitors
This is the section you'll be interested in if you are looking to monitor your website's visits.
This section will allow you to review a geographical heatmap of your visitors' locations, as well as daily/weekly/monthly/yearly reports of their activity on your website, including Triggers fired.
❋ Website Visits
This view presents metrics about your website's visits and their geographical location.
In this area, you will find several types of reports:
Visits Yesterday
Shows the total number of visits to your website on the previous day. The value in green/red represents the difference from the previous period.
This data is calculated by detecting unique sessions that visited your website on a page where Crisp is installed, for the past day.
Visits Last Week
Shows the total number of visits to your website in the past week. The value in green/red represents the difference from the previous period.
This data is calculated by detecting unique sessions that visited your website on a page where Crisp is installed, for the past week.
Visitors per Country
Shows a heatmap of your visitors' locations, providing visual data of your audience's localization. The value in green/red represents the difference from the previous period.
This data is the sum of visits originating from each country, over the specified time period.
Exporting this report will include the following data: The time period , the number of visits per country for that period, and the corresponding country codes .
Note: Crisp does not directly track your users' locations. This data relies on public API registries for IP addresses published by ISPs.
Daily Visits
Shows a trend graph of the daily visits to your website.
This data is the sum of visits for each day over the specified time period.
Exporting this report will include the following data: The time period , and the total number of visits for each day.
❋ Triggers
This section presents metrics about the usage of Triggers and their frequency of use.
In this area, you will find several types of reports:
Triggers
Shows the total number of triggers fired. The value in green/red represents the difference from the previous period.
This data is simply the sum of all triggers fired, over the specified time period.
Daily Triggers
Shows a trend graph of the daily triggers fired on your website.
This data is the sum of each Trigger fired for each specific day, over the specified time period.
Exporting this report will include the following data: The time period , the number of times a trigger fired, and its name .
Helpdesk
This area allows you to monitor how your Helpdesk is being used by your users and review detailed information about the popularity of your articles.
You can access details about visits, which locales are most frequently consulted, as well as metrics about individual article visits, frequently searched terms, and ratings left by your users.
❋ Helpdesk Visits
This view presents metrics about your Helpdesk visits and the different locales.
In this area, you will find several types of reports:
Visits
Shows the total number of visits to your Helpdesk on the previous day. The value in green/red represents the difference from the previous period.
This data is calculated by detecting unique sessions that visited your Helpdesk, over the selected time period.
Helpdesk Visits
Shows the total number of visits to your Helpdesk in the past week.
This data is calculated by detecting unique sessions that visited your Helpdesk on each day, over the selected time period.
Exporting this report will include the following data: The time period , and the number of visits for that period.
Visits per Helpdesk Locale
Shows the total number of visits for each specific locale of your Helpdesk.
This data represents the number of unique visits a specific locale of your Helpdesk received, over the selected time period.
Exporting this report will include the following data: The time period , the number of visits for that locale, and its name .
❋ Search
This section shows statistics about how your users interact with the Search features of the Helpdesk.
In this area, you will find several types of reports:
Searches
Shows the total number of search requests performed. The value in green/red represents the difference from the previous period.
This data is a representation of the number of times the search feature has been used, over the specified time period.
Popular Searches
Shows the most commonly searched terms in the Helpdesk.
This data is aggregated by compiling your users' searches and building a collection of the most commonly used terms, over the specified time period.
Exporting this report will include the following data: The time period , the number of times a specific term was searched, and the term in question.
❋ Articles
This section displays information about specific articles. You can select the Helpdesk locale you'd like to review directly at the top.
In this area, you will find several types of reports:
Articles
Shows extensive data about each of your articles: Visits, Reactions, Usefulness, and additional actions.
Visits : The total number of unique visits this article received over the specified time period.
Reactions : The rating left by your users (positive or negative).
Usefulness : This score represents a ratio between the number of user visits an article received and the average rating left by your users.
Action 🙂: Access details about the article's rating and comments left by your users.
Action 📊: Access details about the article's visits for each day over the selected period of time.
Exporting this report will include the following data: The time period , the number of visits each article received during that period, and its name .
Contacts
This section allows you to review data about the Crisp CRM (Contacts) and Campaigns activity.
These reports include data about contact creation, the usage of your email campaigns, and monitoring data such as delivery, bounce rates, openings, and more.
❋ Contacts Saved
This view shows data about the number of contacts being saved in your Crisp CRM.
In this area, you will find several types of reports:
Contacts Saved Yesterday
Shows the number of contacts saved in your Crisp CRM the previous day.
This data is calculated by taking into account all contacts who have been created in your CRM on that date.
Contacts Saved Last Week
Shows the number of contacts saved in your Crisp CRM this week.
This data is calculated by taking into account all contacts who have been created in your CRM duriong that week.
Contacts Saved
Shows the number of new contacts created in your CRM for each day of the selected time period. The value in green/red represents the difference from the previous period.
This data is calculated by detecting new contacts added to your CRM over the selected time period.
Exporting this report will include the following data: The date , and the number of contacts created on that date.
❋ Campaigns Reached
This section shows overall metrics about the number of contacts reached by your Automated and One-shot Campaigns.
In this area, you will find one type of report:
Campaigns Reach
Shows the total number of recipients to whom you have sent a campaign over the selected time period.
This data is aggregated by adding up the number of contacts you have sent an email campaign to (automated or one-shot), over the selected time period.
Exporting this report will include the following data: The time period , the number of recipients hit by a campaign, and the type of campaign.
❋ Campaigns Activity
This section includes specific details about your campaigns' performances.
In this area, you will find several types of reports:
Campaigns
Shows in-depth data about the global performance of your Email campaigns (Automated and One-shot) over the specified time period.
Delivered : The total number of recipients campaigns were delivered to during that period.
Opened : This is an indicative representation of the number of times your users opened these email campaigns.
Bounced : The number of campaigns that were bounced (e.g. email was rejected by the recipient's SMTP).
Clicked : The number of times a user clicked an external link inside your campaigns. Counted once per email.
Unsubscribed : The number of times a user unsubscribed from the email they received.
Exporting this report will include the following data: The time period , the number of visits for each article during that period, and its name .
Status Page
This area is dedicated to the Status page and allows you to monitor the downtime and incidents of the nodes you are tracking.
❋ Downtimes
This section allows you to monitor overall downtime and the specific services that displayed incidents.
In this area, you will find several types of reports:
Total Downtimes
Shows the total duration your nodes have been detected as down (incident). The value in green/red represents the difference from the previous period.
This data is calculated by reporting the duration during which one or more services were down, over the selected time period.
Downtimes
Shows the individual downtimes for each of the monitored nodes.
This data is calculated by adding up the individual durations during which each service was detected as down, over the selected time period.
Exporting this report will include the following data: The time period , the total downtime , and the name of the node.
Dashboard
The dashboard allows you to build your own tailored reports from scratch. You can create customized reports which will be saved for later use, this is a quick way to access the data which matters the most to you. Just like the default reports, you can apply your own preferences, configurations (aggregation type, filters, etc) but also select the type of chart you'd like to use.
Once a dashboard created or selected, you can click Add Chart on the upper-right corner to get started.
This will pop a drop down menu where you can select the type of report you wish to use for this chart:
Summary : A simple widget to display a quick info (response time, amount of conversations...)
Chart : A detailled chart among various available options
Articles : Details about your Helpdesk articles (read, feedback...)
Map : Used to display visitor locations
Heat Map : A heat map is helpful when looking for data related to geographical location of your users
Operators : Allows to display details about operators (response time, amount of conversations handled...)
Rating : All you need to know about the feedback left by your users
Similarly to the default Analytics reports, the ones you create in the Dashboard can be configured to meet your exact needs. You can change the split date, aggregation type, or apply various filters to obtain the data you're looking to monitor.
Dashboard reports are saved and can be only accessed by the agent who created them. This allows you to keep your custom reports private from your team.
Understanding and Navigating the Analytics
By default, reports are configured to be presented in their most common form, giving you easy access to the metrics you're looking for. However, you can create your own custom reports in a Dashboard and tweak the existing ones by adjusting the various available settings.
Now, let’s take a look at the different tools available in the interface to help you familiarize yourself with these.
1. Preferences
You can change these settings at any time, and your modifications will carry over as you navigate through different reports.
Time Period : Select the time period for the reports displayed (past week, month, year, or today).
Timezone : Select your timezone to align the reports with your location.
Note: Some reports may not be available for specific time periods depending on their purpose.
2. Actions
This contextual menu provides quick actions for each of your reports.
Add to Dashboard : Add a report to one of your dashboards. More about Dashboards in this section .
Export Data : Download a CSV export containing details about the report.
3. Configuration
This is where you can customize each individual report and change how your data is aggregated. You can configure your Office hours, select a date split, choose an aggregation type, and apply filters to isolate or combine specific data points.
❋ Office Hours:
Select the days/hours from which your data should be aggregated. Data generated outside of these hours will be excluded when the report is built, allowing you to generate reports that reflect your business hours.
❋ Date Split
Your reports are generated based on the time period defined in the General Preferences and the Office Hours you selected above.
The Date Split allows you to choose how the report is split. You can choose to see the hourly, daily, weekly, etc., data over the period you selected.
Available date splits include:
Hourly
Daily
Weekly
Monthly
Yearly
All
Note: Some reports may not support certain date splits. In such cases, the option will not appear or will be disabled.
❋ Aggregate Type
By default, reports are aggregated using the most relevant method for that type of data. While the default option works in most cases, you can explore other aggregation types to extract specific metrics, export data for external analysis, or review more detailed statistics.
Available aggregation types:
Average : Adds up all values and divides by the number of values, providing the mean.
→ Useful for understanding overall trends or typical values.
Moving average : Averages data over a specific number of periods, updating as new data comes in to smooth fluctuations.
→ Useful for identifying trends over time and smoothing short-term changes.
Median : The middle value in a dataset when values are ordered from lowest to highest.
→ Useful for finding the center of your data, especially in skewed distributions.
Minimum : The smallest value in the dataset.
→ Useful for identifying the lower limit or extreme low values.
Maximum : The largest value in the dataset.
→ Useful for identifying the upper limit or extreme high values.
Sum : Adds up all values in the dataset.
→ Useful for understanding the total value or volume in your dataset.
Note: Some aggregation types may not be available for certain reports. In these cases, the option will be unavailable or disabled.
🤔 Still a bit unclear? Let’s see an example. Consider a 10-day dataset of daily conversations: 50, 60, 70, 80, 90, 200, 100, 110, 120, 130.
Here’s how the different aggregation types would process this data:
Average : The sum of all values divided by the number of days.
→ (50 + 60 + 70 + 80 + 90 + 200 + 100 + 110 + 120 + 130) / 10 = 101
Moving Average (e.g., on a 7-day split): Takes the average of the first 7 days and moves as new data comes in.
→ Day 1-7 : (50 + 60 + 70 + 80 + 90 + 200 + 100) / 7 = 93
→ Day 2-8 : (60 + 70 + 80 + 90 + 200 + 100 + 110) / 7 = 101
→ Day 3-9 : (70 + 80 + 90 + 200 + 100 + 110 + 120) / 7 = 110
→ Day 4-10 : (80 + 90 + 200 + 100 + 110 + 120 + 130) / 7 = 119
Median : The middle value when data is ordered.
→ Ordered dataset: 50, 60, 70, 80, 90, 100, 110, 120, 130, 200 => Median = 95
Minimum : Smallest value = 50
Maximum : Largest value = 200
Sum : Total conversations over 10 days = 1010
4. Filters
In some cases, you may want to isolate specific elements in your data to generate a report aggregated from more specific information. This is where filters come into play.
Available filter types:
Segments : Filter conversations that include or exclude specific segments.
Country : Filter conversations based on the user's country.
Rating : Filter data where a rating was left, above or below a specified threshold.
Visitor Origin : Filter conversations based on their origin channel (chat, email, Instagram, etc.).
First Operator Origin : Filter conversations where the first operator message was sent via a specific channel (chat, Slack, etc.).
First Operator : Filter conversations based on who was the first operator to participate.
Last Operator Origin : Filter conversations where the last operator message was sent via a specific channel.
Last Operator : Filter conversations based on who was the last operator to participate.
Response Time : Filter conversations based on their response time (in seconds).
Handle Time : Filter conversations based on their resolution time (in seconds).
Filters allow you to include or exclude data based on your needs, and you can combine multiple filters to generate a tailored report.
When adding multiple data points within the same filter (e.g., multiple segments), this will apply an or condition. To apply an and condition, add a second filter for the second data point.
Frequently Asked Questions
Still have questions about the Analytics tools that weren’t covered in this guide? You may find the answers here!
Here is a collection of the most frequently asked questions, along with extra resources to help you better understand how the Analytics work and explore related features to improve your data usage.
If your question isn’t listed here, feel free to contact us directly via chat. We're available!
How can I track which URLs users are contacting me from?
There are a couple of ways to do this. On the Essentials plan, you can leverage the Chatbot plugin .
The Chatbot can trigger automatically when users contact you, check the URL they are currently browsing, and apply the segment you’ve configured for that URL .
Another approach would be to use our Javascript SDK to programmatically add a segment to conversations based on the page they’re currently browsing.
Once a segment has been added to a conversation, you can monitor it in the Analytics under the Segments section to track its frequency, or you can create custom filters in your inbox to review them.
Can I track specific events in Google Analytics, such as when users contact me or open the chatbox?
Absolutely. The Crisp Analytics allows you to monitor various data about your inbox, conversations, operators, and more. However, if you want to track specific events in Google Analytics, this is possible too.
We have a dedicated guide with GTM and GA4 to help you track events such as when users open your chatbox, message you, fill in their email address, and more. 🙂
Updated on: 14/11/2024
Thank you!