Getting Started with Commerce Intelligence

Welcome everyone, and thank you for joining us today for the Getting Started with Adobe Commerce Intelligence webinar. I’m Webster Love and I’ll be your host for today. Joining me is the presenter for your session today, Deepak Kumar. We’re from the Product Analyst team for Adobe Commerce Intelligence, formerly known as MBI. Before we dive in, we have a couple technical notes. For audio issues, audio is through Adobe Connect, so your speakers or headphones must be unmuted and then ensure the speaker icon is on at the top of the Connect room. We don’t currently have an option for calling in via phone. Adobe Connect doesn’t always work well with Bluetooth headphones, so if you’re using those, you can try switching to wired headphones. You can also try logging out of the room and back in, or switching to the desktop app instead of the browser version. Throughout the webinar, if you face any technical issues with audio or the screen share, or if you have questions related to the functionality of Adobe Commerce Intelligence, or to the content that’s being presented, please feel free to put those questions in the Q&A pod at the left of your screen, as we’ll be monitoring that while the recording of today’s content plays. We will try to answer those questions either right away through chat, or during our Q&A segment at the end of the webinar. We’ll also be sending out a link to a recording of the webinar afterward. Now I’ll hand it over to Deepak. Thank you for joining. This webinar will be a good starting point for our audience who are new to Adobe Commerce Intelligence. We will start with a brief introduction of Commerce Intelligence, a coverage of basic dashboard features, a quick walkthrough of our insightful out-of-the-box dashboards. We will then create a new dashboard from scratch with a few reports so our audience can learn the report builder features. For users who play an administrator role, we have a section each for managing data and managing account in Commerce Intelligence. To ensure users are able to find information they are looking for and stay connected with Adobe Support, we have a help and support section included. We will wrap up our session with a Q&A. Let us take a quick look at our ecosystem. Adobe Commerce Intelligence is a full stack data warehousing and business intelligence solution that comes pre-integrated with Adobe Commerce. Our interaction starts with our customer success and technical advisory teams who take care of onboarding you with a Commerce Intelligence account. Configure it to suit your business needs and guide you for any license upgrades. A user with administrator role will have full control of the data warehouse by setting up integrations with your databases or third-party SaaS applications. Create and export data using built-in Commerce Intelligence API. Establish relationships across tables in your data warehouse using column path. Manage data warehouse tables, columns, data update cycles, etc. Create data warehouse views to consolidate similar but disparate tables together. Standardize the way data is consumed for your reporting requirements using filters and metrics. Ensure key stakeholders receive automated reports in the form of email summaries. Administrators can double up as a data analyst by creating reports and dashboards. Once the administrator is done with most of these settings, our merchants and enterprises can rest assured their Commerce Intelligence is running in an autopilot mode, except for any new users, dashboards, or setting changes here and there. Data analysts with standard role will be able to create dashboards and share with other users. Read-only users will be able to only view the dashboards shared with them. Development can be obtained by launching our product user guide. It also contains quick tutorials wherever applicable. A dedicated Commerce Intelligence community can be referred for frequently asked questions. In case of any issue with the product, you can create a support ticket where our dedicated team can guide you towards resolution of the issue. Commerce Intelligence customers can make use of the out-of-the-box dashboards from day one if Adobe Commerce is part of their license. This is a great way to start most important reports required for businesses. The analysis contained in these packages will let you check on the health of essential metrics such as lifetime revenue, number of repeat purchases, and more, thus creating a solid foundation for future exploration. There are four dashboards, namely Customers, Executive Summary, Orders, and Products. Overall, there are around 60 plus reports across all of these dashboards. We recommend our users to save a copy before deleting any dashboard or report. Let us navigate through various features within dashboards. Search allows you to quickly find the dashboard you are looking for based on keywords from its title. You can notice dashboard groups could be created. This is an effective way to manage a long list of dashboards with similar business objectives together under a suitable name. There is an option to create a new dashboard by clicking this green button. We will create a custom dashboard inside a dashboard group in a short while. The wheel icon adjacent to the dashboard name allows you to perform certain housekeeping activities like dashboard title changes, make this dashboard a default whenever the dashboard menu is clicked above. You can make a copy of the current dashboard to a new one and rename the new dashboard based on need. If you are the owner of this dashboard, you can delete by using this option. Create a new dashboard and browse dashboards perform the same action as the options shown in the dashboards dropdown earlier. We will be using this option to create a new dashboard in a short while. Next, we have an option to share the current dashboard with users in our organization. Commerce intelligence keeps all your newly created dashboards local to you unless you decide to share with other users. If the list is too long, you can find users based on search. The building icon indicates an admin user and others are standard and read only users. You can apply changes one shot using select dropdown for all users or none and apply suitable permissions to allow access to selected users. You can notice the current dashboard already has a few users with edit access and others with none. You can notice the current dashboard may already have a few users with edit or none based on the previous settings. Based on your business needs, you can make selections to selected users and hit save to apply changes. Add layout element can be used to add a separate line typically to group logical reports together. Add header gives a provision to add a title within the dashboard. Add report option allows you to create a report inside this dashboard from scratch or search from existing reports to add from. Instead of creating the layout element or a report at a default position within the dashboard, it could be a good idea to hover the mouse around the specific area you are looking to add these elements or insert a new or existing report. On the top right corner, we have options to filter the dashboard based on date range or store. There is a flexibility given to filter the dashboard based on moving date range or specific date range. I am going to select this year and group the data by month. After applying changes, we can notice that it takes a few seconds to refresh the entire dashboard as the underlying queries are being re-executed with the new date range. The time taken is proportional to count of reports within the dashboard. In order to refresh the dashboard with default date filter, navigate to the dropdown again and select restore defaults. The store filter displays a list of storefronts you may have configured in Adobe Commerce. Based on the selection, the dashboard refreshes its reports with data related to specific store. Let us now focus at the features related to individual reports within dashboards. Broadly there are three types of reports in Commerce Intelligence. Once we hover the mouse pointer over a given report, we can see the wheel icon specific to that report. Edit option launches the report in edit mode for further changes. Enlarge zooms the report to full screen for a better view. It is applicable to charts and tables. In this mode, you can go back to dashboard by using this handle on the right top corner. Save as allows a duplicate copy of the report to be saved. Remove from dashboard can be used to remove the selected report from the dashboard. Please note, this report still exists in the Commerce Intelligence unless it is being deleted from managed data menu. There is a provision to export the report data to CSV or XLS format. Raw data export can be initiated using this option to export the report data in CSV format. Please note, this option works for reports that make use of a single table as source. The mouse pointer becomes a four headed arrow while we point at the title of the report. We can press and drag the report to reposition it wherever required. Hovering over a report highlights its resize handle which can be dragged to resize based on the dashboard requirements.

Hovering over the chart data highlights the chart item and also shows a quick pool tip with specific metric data. We can toggle between show and hide by clicking the legend items for a clearer view of the chart. Within a given chart, you can select a portion by dragging the mouse to zoom into it. To go back, you can click on reset zoom. For each report, we can see a small information icon to view information related to it. The pop-up shows a list of tables, metrics, filters being used to build this report. There is a small description box to view description entered earlier for this report. It is a good practice by the creator of reports to enter suitable description for other users so that they can understand what the report was made for. There is a provision to save changes if required. This completes our walkthrough of dashboard features. Now let us take a look at a few out of the box reports that can be very insightful for your business. Let us check out a few out of the box reports that could be very insightful for your business. Customers dashboard helps data analysts derive insights on customers, their purchase behaviors and accordingly optimize retention of such customers. As per the market trends, it is observed that it is cheaper to retain existing customers than to acquire new ones. Subsequent order probability report helps the merchants to figure out the likelihood that customers who have placed an order places another one. Upon hovering on the chart for first order, we can see that a customer who placed one order has only 38% chances of coming back and placing the second one. Similarly, a customer who placed two orders has 60% chances of coming back and placing third order and so on. The gap seems to be reducing for the third, fourth and fifth orders. They can identify the diminishing rate of drop-off in this case. The drop-off rate from first order to second order is much higher than the repeat orders from customers lifecycle, which is a challenge to merchants. Hence considering the higher drop-off rate for first order conversion, stronger retention campaigns could be run to bring back those customers to the storefront. The second challenge is when to reach out to such customers. The solution to this challenge is this report called Time Between Orders. It shows average and median time between subsequent orders. For example, comparing the average time and mean time for the first order to the second order is a range of 3 to 6 months. Hence this would be a strategy followed to launch a retention campaign. The third challenge is identifying the best customers to target for a reactivation campaign. The solution to this challenge is a report called One-Time Customers who bought 3 to 6 months ago. Using this, we can quickly identify a list of customers for whom an email campaign could be launched, segmenting them based on the revenue they have brought for us. Let us move to the Orders dashboard. We will cover a business challenge of identifying which days and hours are the least fruitful ones in terms of order count. Order per hour report gives an hourly pattern of orders placed on a 24-hour clock in the form of a heat map. Usually it is easier to identify the orders count by looking at the intensity of color. We see that Tuesday first half in particular seems to have the least orders. Accordingly, an ad campaign could be launched for an exclusive discount to attract more orders during that time. This chart gives an overall percentage of order statuses on a one-month timeline. The merchant has a business challenge where he wants to identify reasons for low customer satisfaction ratings due to the delay in processing orders. As a solution, he can refer to this report to analyze the peaks in purple for status processing. Some of the peaks in this area chart explains which were those time periods. Looks like the 5th of November has had a high percentage of orders in processing status. Accordingly, the root cause could be analyzed whether there were any external or internal factors during that time which may have impacted delays in processing orders. Similarly, there could be other use cases where a merchant may want to understand the high amounts of cancellation during a time period to analyze what may have gone wrong. Another use case could be to identify the logistics issues by filtering the report with in-between statuses like picked and picking. So 28th of October seems to be the date when the issues with logistics occurred. This covers the section related to a few reports that can help solve business challenges. In this section, we will recreate the report we saw a while ago that was percentage orders by status. While I walk you through the steps of creating this report, you will understand the features and appreciate the ease with which you can create powerful reports for your business. Let us start creating a fresh dashboard called Webinar Demo. To do this, click on Create Dashboard. Give a suitable name. Associate it with existing dashboard group called Demo. And click on the Create button. So our brand new dashboard is created now with a blank page prompting us to add a report to it. If the report you are looking to add already exists, you can select it from the list or search and add it to the dashboard. We want to create a fresh report. So let us click on Create Report. This page gives us an option to create a report either by using a visual report builder or SQL report builder. SQL report builder is a great way to quickly create reports using graphical user interface within a few clicks. SQL report builder helps you to create reports for more complex scenarios that an advanced data analyst would like to work on. For example, we have a few commerce intelligence clients who run almost 500 lines of SQL code for a single report to meet their business requirements. For more information on SQL report builder, you can visit experienceleague.adobe.com and search for Ask an Expert Webinar. For this webinar, we will focus on visual report builder. Let us go ahead with Create Report. The system prompts us to start with selection of a metric first. Click on Add metric dropdown. These are the list of existing out of the box metrics in sorted order. You can switch to the other tab by table to view the list of metrics grouped by the corresponding table name. If the list of the metrics is too long, you can quickly search the metric by typing the metric name. I am looking for orders. Create the metric. Now we see the visual report builder populating the orders metric I just chose. Let us cover the different sections of this interface. On the left, we have this panel with list of metrics added to the report. Within each metric, we can see the metric name, which can be edited based on your requirement, and the metric scalar value. This will refresh based on any data or time filter you apply. Clicking on the details section expands the area to show metric details and filter. At any time, you can click on this context sensitive help to launch the online user guide for more information. We can remove a chosen metric from the report using delete. Create a copy of this metric to new one to apply any additional calculations. Filters help you to apply additional logic to the metric. For example, if I want to focus on all orders with completed status, I can select the field, give it a condition like this. For users who create SQL statements, this is analogous to a where clause perspective helps us to view the report with a standard or cumulative view or an amount change or percentage like month on month, year on year, etc. Time options lets you configure the report based on timeline. On the right, we have a view of the equivalent chart and tabular view of data meeting the condition from the metrics on the left. By default, the visual report builder creates the chart with a metric trend line, a timeline on the x axis grouped by month and a metric on y axis. The chart type could be changed based on your requirement. We will select area chart for our requirement. The tabular view on the bottom reflects the underlying data behind the chart with metric and timeline. Using this transpose option, we can interchange the rows and columns of the table. We can sort the data based on a given column by clicking the column header if required. On the right top corner, we have the date filter. It works similar to what we saw in the dashboard section earlier. Our requirement is to view the chart for last 30 days as per a moving date range for each day. So I will choose custom moving range specified from as 31 days to as one day. Select time interval as day and click on save. Our requirement is to view the report for orders based on status. To do that, we can use this group by option here. These are all the available dimensions from orders table based on which we can group the data. I will select status and ensure we cover all the order statuses. As a result, the chart section now started showing legends for each status group like complete, pending, etc. You can highlight or choose a given legend to view its corresponding trend. The time interval visualization is grouped by day on x axis and metric data visualization is grouped by status here. Right now what we see here is a count of orders. We want to compare these order counts with their total for that day. To do that, I will add the same orders metric again. I can do so by choosing the add metric dropdown or simply select duplicate from my existing orders metric. Let me rename this metric as total orders. The chart area reflects an additional y axis for total orders. I want to combine these two metrics on the same y axis. So let me deselect multiple y axis option. If we notice both the metrics are broken down by status based on group by. We actually want the total orders alone to be shown in the chart broken down by their order status. To do that, let us edit our group by using this edit icon to open dimension editor pop-up. Here we can select the independent option for total orders and click on apply. Our objective is to show percentage of orders based on their status, which is nothing but orders divided by total orders multiplied with 100. So let us add another metric to our chart which applies this formula. For this, let us click on add formula. We can consider the first metric orders as A and second metric total orders as B in the given order. So let us apply the formula A by B and choose select format as percentage. Let us name this metric as percentage of orders by status. We can restrict viewing only the newly created metric in our chart and tabular format. So we can hide the first two metrics by clicking on hide. Let us give our report a name percentage of orders by status for 30 days. While saving this report to the dashboard, we have a provision to specify whether we would like to consider the scalar or chart or tabular format. I am selecting chart. Then select the dashboard inside which you would like to show this report. I am selecting our newly created webinar demo dashboard. Once saved, you can go to the dashboard. Our newly created report can be seen here. We can resize it as per our requirement. So we are done with our very first report inside our webinar demo dashboard. Let us create another report that demonstrates how to create a scatterplot chart. Reports using scatterplot charts allow us to compare two seemingly unrelated variables and determine the relationship between them. While many statistical graphs only allow you to record and interpret linear data, scatterplots can display curved or irregular data points. Today, we will create a scatterplot chart to find a relationship between revenue, orders, and customers based on their billing region and the type of business they represent. Let us create the report by adding our first metric revenue. We can see the visual report builder interface with y-axis covering revenue metric. In Commerce Intelligence, you can make use of a maximum of three metrics and two dimensions. Now let us quickly add our additional metric, orders. Now let us add unique customers. We see all these metrics occupy the y-axis. Let us select Group by with billing region code. We do not need the time interval here, so let us select Date filter on the top right corner and set the interval to None. Now switch the chart type to scatterplot. The x-axis is now covered by revenue, y-axis by orders, and the bubbles indicate the relationship between revenue and orders placed by unique customers from various billing regions. On the top right corner, we can make out that customers from Florida are the frontrunners with this much of revenue and orders count, followed by Arkansas. It acts like a magic quadrant used by research organizations, where the bubbles on the top right corner indicate the leaders in the given segment along with the relative size of the bubble, whereas the ones on the bottom left corner are the ones lagging behind that need attention from the decision makers. Our requirement is to also compare the customer groups. To do that, let us add a group by using Add another option. Select Customers group code. Now we can see our scatterplot chart showing many more bubbles with different colors, representing the legends shown. Our objective is to compare the B2B customers with General, which in our case represents the B2C customers. So let us deselect all the others from the list of legends. Overall, we can analyze and derive from the chart that B2C business is doing well as compared to B2B. Within the B2B business segment, these regions on the top right corner are the best performers and these are the lagers based on the bottom left corner. And within B2C segment, these regions are the best performers and these are the lagers. Accordingly, the marketing and sales team in your organization can take the necessary business decision. Let us save this report to our dashboard. Here we are with the two strategic reports for business. This completes the creation of dashboards and reports in Commerce Intelligence. Let us move to our next section Managing Data for Commerce Intelligence Administrators. Broadly, the menu options cover data sources where we can configure the database and SaaS integrations, uploading data using CSV files. Manage data helps our administrators to configure metrics, filter sets, column paths, data warehouse options, etc. Export data helps manage the export of data in the form of API integration for downstream systems, raw data export and configure email summary. Integrations displays a list of existing integrations and an option to add new integration. Click on the green Add integration button. Additional integrations show a list of free integrations. Available for upgrade section has five of these integrations that are available for Commerce Intelligence Pro license. Additional integration may add to your invoice. Premium integrations are additionally chargeable integrations. We strongly recommend you to connect with our customer success team as the subscriptions are subject to change. Let us move to the metrics section. In Commerce Intelligence, you can use metrics to create charts. In SQL and database structures, a metric acts like a stored query over a variable period. When used in reports, metrics can be analyzed over a specified time period and filtered or segmented by different categories. With Commerce Intelligence, we can leverage on 20 plus out of the box metrics. This page gives a list of all metrics. In this page, an administrator can edit, clone or delete an existing metric from the list by clicking on the wheel icon. Enter the view by unused metrics or a complete list of metrics using this switch. Expand a given metric to see more information by clicking on the plus icon. Add or remove the dimensions from the list of metrics using these buttons. Let us go ahead create a metric. I want to create a metric to obtain account of customers for whom an email ID is captured. This can help an analyst to understand what would be the size of an upcoming email campaign. So I am going to name this metric as total unique emails. In order to define my metric, I will select customer entity table. Email for column name. Count distinct so that the duplicate emails are ignored. Created add new to order the metric. I want to add a filter condition to consider all customers whose email field is not blank. In case you want to remove the filter, you can do it using remove filters button or the cross icon here. Optionally, you can specify the dimensions by which this metric could be grouped. This would be helpful during creation of reports. For now, I am leaving it as it is. Also you can specify users who can access this metric and their corresponding reports. We can always come back to edit this metric and make changes. Once the metric is defined, we are ready to create this metric by clicking on save. The newly created metric now can be seen under its corresponding table name. Now let us cover the filter sets feature. Clients often face challenges in implementing standard filter conditions that need to be followed globally. Also whenever there is a change in filter conditions in future, there will be a need to minimize the rework and impact. Filter sets in commerce intelligence could be a one stop solution to these challenges. It allows standard conditions to be specified once and reused across metrics, reports, dashboards and email summaries. Let us take a look at it. The right pane shows a list of filter sets grouped by table name. For a fresh implementation of commerce intelligence, we can see few placeholders created with names such as registered accounts vcount, orders vcount, etc. Click on the plus icon next to a given filter set to expand and view its details. Clicking on link gives more information on the impacted areas. Click on the minus icon to collapse it. In order to create a new filter set, you can click on this green button. During creation, we need to specify the fields like table and its filter condition. My requirement is to create a filter set to view sales with status as complete and billing address confined to United States. So I am going to select sales order table. Give a name to this filter set. Orders completed in US. Click on add filter. Select status equal to completed. Click on add filter again. Select billing address country equal to US. There are a standard set of logical operators to specify the conditional statements. These are fairly self explanatory. In case you have more than one conditions in the filter set, like the example above, you might want to ensure whether all or few conditional statements need to be satisfied by commerce intelligence. By specifying and or or in this text field. I am going to save this filter set by clicking on save. I can see the newly created filter set orders completed in US in the list here. Please note, any changes made to a filter set will have an impact on commerce intelligence. The way it filters data differently from then on. Some of this impact can be immediately felt in commerce intelligence, whereas others can be realized after a full update cycle. Now let us cover the data warehouse section. Using the data warehouse manager, you can manage table and column sync settings. Drill down into a table’s schema and create calculated columns to use in reports. For more information, please refer to experienceleague.adobe.com and search for our webinar, Optimize your Commerce Intelligence Data Warehouse. Email summaries are a powerful communication tool that you can use to share the status and trends of your business with key stakeholders. Let us create a new email summary to send automated emails containing the reports we created today during our webinar. Inside the choose content section, click on select report dropdown to choose a report. You can search based on keywords. I am selecting percentage orders by status. Click on add another report in case you like to add more number of reports to the email summary. I am going to add another report called bubble chart we created today. If we notice, after selection of report, commerce intelligence provides option for the user to select between available representation of the report like chart or tabular format. Use the cross icon for a given report to drop it from email summary based on your requirement. On the bottom right corner, we can see a counter to see how many reports are added. The maximum reports supported by email summary is 10. Send email to me option helps the logged in user to receive a copy of the email summary if required. Use the add email recipient box to type in a list of email recipients. A maximum of 100 recipients are allowed. This dropdown lets you schedule the email summary to manual, once or repeating based on your requirement. You can make use of the short description on the right panel if you need any help with email summaries. I am going to choose repeating option to schedule this monthly email summary at 9 am till the end of this year. Please remember the email will be triggered based on the time zone that is set up for a given commerce intelligence implementation. Let us give it a name, webinar demo, email summary. We are done with configuring our email summary. Click on send now if you wish to test the email summary right away. Let me check my inbox to see whether I received the email summary. Here it is with an email subject same as the email summary name. This email summary has the two charts we created today. Going back to the main page, the list of saved email summaries page gives a list of email summaries we created so far. The plus icon helps viewing all the settings related to a given summary. The wheel icon helps in triggering the email now. Open the email summary in edit mode. Activate or pause the email summary and delete. This concludes the manage data section. Let us move to manage account. I am currently logged in as an administrator. We can verify it by viewing the dropdown from the company name on the right top corner. On this list of options, a standard or read only user can only edit his profile and change his account password. Starting with account settings, the administrator can change the company, currency indicator, hour of the day when the data update cycles should not happen, hours of the day when the data update cycles should happen forcefully, send email summaries even though the data update cycles fail and allow data update cycles to run. Manage users allows the administrator to view a list of commerce intelligence users, select a given user to change the role between admin, standard and read only, specify metrics and shared dashboards they have access to. Update settings confirms the changes being made to this user. Select a user option allows the name and email of the new user to be specified along with an associated role. An invitation mail is sent to the user using which he can log in for the first time to commerce intelligence. In case administrator has access to multiple commerce intelligence accounts, he can switch between them using the list here. Now let us move to the help and support section. Help and support is just a click away for all our commerce intelligence users. Using visit the help center, they can launch a complete user guide covering all the features along with tips, tricks, tutorials, usage of API documentation, etc. In case of any frequently asked questions, our users can make use of ask a question in our forum that launches our community forum with different topics, questions and answers. Any new questions will be answered by our product team within a stipulated time. In case of any issues or questions regarding commerce intelligence, our users can submit a support ticket so our support team can get in touch with you and help you resolve it. This completes the agenda for today. I hand over the rest of the session to our host. Thank you. All right. Great. Thank you for that great demo. Let’s get info there. All right. We’re going to move on to the Q&A portion. Please submit any additional questions that you may have in the Q&A pod on the left side of your screen. Also please submit your feedback in the poll questions that are now showing on your screen. These are helpful for us to improve our content in the future. If you have questions after the webinar or if we don’t get to your question during the Q&A, please do send us an email to mvi-webinaratadobe.com. We’ll be able to receive questions there for about the next week. A reminder that you will get a follow-up email in the next day or so with a link to a recording of this webinar and a link to the recordings of our other webinars on Experience League as well as the email address that I just mentioned. All right. So we’ve got a few questions here. First one says, how far back does Adobe Commerce Intelligence go when syncing data? Is there a limit on how much historical data we can ingest? So for example, if I have e-commerce data going back to 2010, can all that data be brought into Commerce Intelligence? Yeah, that’s a great question. There is no limit on how much historical data you can sync to your Commerce Intelligence account. Commerce Intelligence replicates the full set of records from each selected table. So if your full set of historical data is saved in your database, then you can replicate it to Commerce Intelligence. All right. Thanks. Next question is, what are the places we can apply a filter set in Commerce Intelligence? So this is a filter set as opposed to just a filter, which is available in a lot of places. Yeah. Filter sets are available when creating metrics and calculated columns. Great. Yeah. So, I would add to that, if you want to use a filter set and you don’t see it available in the location in the UI that you’re currently in, then basically try backing up a step. If it’s a filter set that you really need and that’s critical to your use case, so for example, standardizing across various metrics, then the place that you really need it is on that metric. So that’s why it’s available to be defined there. All right. Our next question is, what are the different capabilities of an admin user versus a standard user? Yeah. As an admin user, the user will be… I mean, he can do all the actions we covered today and a standard user is much more restricted. For example, standard users can view things like metrics, filter sets, dashboards that are shared with them, but they won’t be able to edit the given edit positions until they are given the edit permissions. So standard users can create their own reports and dashboards, but not metrics or filter sets.

Okay, great. And we actually have one other question about user capabilities. Can we have more than one admin user for a Commerce Intelligence account and is that advisable? Yeah, I think this is a practical scenario many customers have faced. So yes, the Commerce Intelligence does allow more than one admin user. As for whether it is advisable or not, you will have to make the decision in your organization. It can definitely be handy if one of your admin users leaves the organization since you will still have your domain access. So the possible trade-off is that the admin user can have a lot of power over the account in terms of editing or sharing any existing assets.

Okay, great. Well, we know folks are busy these days running from one meeting to the next, so we are about out of time for today’s webinar. Once again, everybody, thank you very much for joining us. We hope you got some really good useful information out of today’s session and have a good rest of your day.