Analyzing the Data

Transcript

Thanks for having me. I’m Jennifer Workmeister and I’m a senior product manager for Adobe Analytics. Ashok just walked you through the basics of the user interface and now I’m going to show you how to uncover actionable insights. First a little about me. I’ve been a product manager at Adobe for three years, but I’ve been focused on delivering data-driven insights for almost a decade now. I joined Adobe after getting my MBA from UC Berkeley, which is when I moved to Salt Lake City. My hobbies include almost anything outdoors, but I especially enjoy trail running, gardening, and painting landscapes. I’ll be here for a live Q&A after the session, so if you have any questions, go ahead and just drop them in the chat. Before we jump in, there’s a quote I want to share with you. One accurate measurement is worth a thousand expert opinions. We know that timely, data-driven insights are essential to business success, so I’m going to show you how Adobe Analytics is here to make it easy to uncover those actionable insights. I’m going to show you how to build a freeform table, how to create date ranges, apply segments, and lastly, we’re going to explore some panels that can speed your discovery of those actionable insights. Before we dive into analyzing our data, let’s first define some of the foundational metrics that we may want to use in our analysis. These three metrics form the foundation of analysis and workspace. First, a visitor. So this is going to be a single user, a single person. A visitor may have multiple visits, and a visitor KPI might be called something like people, users, devices, etc. Second is a visit. So a visitor may have more than one visit to a page during a single sitting. That sitting is referred to as a visit or a session.

A visit is always tied to a time period, so the most common way that a session ends is if the user has been inactive for more than 30 minutes. Lastly, a page view is counted for each server call that is sent. In the analytics world, you may also hear this referred to as a hit. As mentioned, there will be multiple page views associated with a single visit or session. So let’s recap with an example. If I visit my favorite retail website, I will be counted as a single visitor. When I visit that site, I’m going to browse through several different pages looking at items I’d like to buy. I’m still counted as a single visitor with a single visit, but the page view count increases with each page I visit.

Now, if I return to that website the next day, I am still only counted as a single visitor. But now the number of visits associated with me has increased to two, and the number of page views will again increase by the number of pages I visit in that second day. Now that you understand the foundational metrics that we’ll be using, I’m going to show you how to build a freeform table. A freeform table is one of the easiest and most flexible ways to get answers from your data. Let’s start by creating a new blank project and workspace. From the landing page that Ashok shared with you, click Create New Project and select Blank Project.

A blank project typically opens with an empty freeform table. If you need to add a freeform table, you can navigate over to the left rail and select the panel icon and then drag and drop the table over into your workspace. The first thing you’ll want to do is select your date range from the calendar in the upper right hand corner. Now we’ll select a metric to create what’s called a time series or trended table. I’m dropping in unique visitors. As you can see, the freeform table automatically adds the data dimension to complete my table.

If I go to the top, I can control how many rows I want to view at one time. I can also use the arrows to go back and forth between paginations so I can skip between different data points.

Now to swap out a dimension, all I need to do is drag and drop a new dimension over into the column header.

To create a breakdown, I can drag and drop another dimension into the table. Or I can right click on a dimension and create a breakdown from the list or by searching for it. Each time you create a freeform table, think about these three key requirements. When, what, and how many. When is going to be your date range. What you are analyzing is going to be your dimension. And how many is going to be your metric. Second, think about what you want your finished table to look like. Typically, you want the metrics to appear as your columns and the dimensions to be your rows. So when you drag and drop, drag and drop your metrics over to the right half of the table and your dimensions over to the left.

Let’s try what we just learned with an exercise. Let’s think about how we would answer the following question. What page was the most visited in the month of April? The when is the date range from April 1st to April 30th. The what is the page name dimension. And how many is the metric visits? Putting it together in my data set, I get a table that looks like this. I have a row for each page and I can see how many visits each page received in April. It looks like my home page was the most visited page. Let’s try another example question. Which browser did your visits originate from in the month of March? The when or the date range is the month of March. The what or the dimension item is the browser type. And the how many or the metric is the visits.

And here is what that table would look like with my data set. Now that we’ve mastered building our table, I’d like to point out some tips.

You may have noticed the blue prompts show up as we built our table. These are drop zone guides and they will pop up and help you as you build your freeform table. The add guide, like what is shown here, will help you find the right spot to drop a metric or a dimension. The replace guide will appear when you are dropping a dimension over another dimension.

And the breakdown guide will appear when you break down one or more dimension items by another dimension. Lastly, the filter by guide will appear when you filter the table by segments, which we’re going to go over in just a little bit. In this example, online revenue will be filtered by new visitors so that only revenue from new visitors will show up in the table. Now let’s talk about date ranges. While choosing our date range from the calendar in the last example was pretty simple, there are several flexible and powerful options for creating just the right date range for your analysis.

The calendar analysis workspace lets you select a date range from a calendar or from a drop down menu of presets.

When you select a date range, it applies only to the panel you’re working with. But you also have the option to apply the date range you’ve just selected to all the panels within the workspace project. If you don’t specify a date range, workspace will default to a current month.

Dates don’t have to be limited to a panel. You can also drag and drop dates and time dimensions into a workspace project. For example, in our first example project, unique visitors were broken down by the day dimension.

Lastly, rolling dates allow you to create reports based on when you ran the report. For example, you can have a report that always gives the data for the last 30 days. You can select preset rolling dates or create your own. Date ranges can be provided by Adobe or can be custom created. They can be applied in the panel calendar or created using the date range builder. You can find pre-created date ranges in the calendar in the left on the component rail. You’ll notice various date components in a separate date range section in the left rail. You can drag and drop these date ranges into a workspace project. You can also create your own custom date range that will show up in the calendar as well as the date range section of the left rail. Let’s talk a little bit more about those next. You can create a new date range either by going to the components menu and selecting create date range or by clicking the plus button next to the date range components in the left rail.

Let’s create a custom date range with a rolling time period of one month, two months ago. To do that, select the one month, two months ago and then select use rolling dates. Open the details to make sure it’s set up exactly the way you want. You can use the date math to add or subtract the number of months, weeks or days that you need for exactly the perfect date.

Hit apply.

Now all you need to do is name it and save it. Now the date range will show up on the left rail where you can drag and drop it into your analysis. A common use of date range components is when you want to compare a metric over two different time periods. Analysis workspace lets you compare metrics year over year, quarter over quarter, month over month, week over week, etc. Or between any two custom date ranges. It also has a date comparison feature that automatically includes a different column which shows you the percentage change between two time periods.

To try this, head on over to the freeform table. Here I have visits for pages during the month of May.

Right click on the metric column to navigate to compare time periods.

The three options that show up depend on the table’s date range. You’ll notice that workspace creates the date comparison by adding another column with visits and filtering that by a custom date range of the previous month. Also, a new column with the percentage change between the two metrics is auto created. This feature can quickly help you with comparing any metric over time for your analysis. Here’s an example. If you want to know the percentage change in revenue for each of your products between May and April, you’d start with a freeform table with your product dimension and revenue metric and set your date range to May. Then you would right click the revenue column and choose the time period comparison prior month to this date range.

Now let’s talk about applying segments. Adobe Analytics lets you build, manage, share, and apply powerful focused audience segments to your reports. Using analytics capabilities, the Adobe Experience Cloud, Adobe Target, and other integrated Adobe products. In this section, we’re going to learn about how to use these segments in our analysis. Segments allow you to identify subsets of visitors based on characteristics or website interactions.

They’re designed as codified audience insights that you can build in for your specific needs, and then verify, edit, and share with other team members or use in other Adobe products.

Segments can be loosely grouped into four major types. You can segment visitors based on attributes, so that’s browser type, device, country. You can segment visitors also based on interactions. That describes how they interact with your touchpoint, so campaign, keyword search, or search engine.

You can also segment visitors based on entry and exit, which define where they are entering your website from, where they land, the last page they were at before they exit your website, and then lastly, you can segment visitors around custom variables like product ID, form field, etc. You can find segments in workspace in the left with your other components. They can be dragged and dropped into any panel you may be working on. The segments will filter the data in your tables and visualizations, and can be used with dimensions to compare against metrics. You can also break down dimensions by segments. So that’s a lot of power and flexibility. Let’s see some examples. There are a couple ways that you can use segments to filter data in your panel. The first is to apply this segment globally, so it applies to all the data in the panel.

Here I have a freeform table, and I’m going to pick my segment and drop it into the segment drop zone at the top.

As I’m adding these segments, you’ll notice that the data in the table is dynamically changing, and is being filtered by the segment applied.

I can add more segments here too, and stack them so that they will filter down to only the data that exists in all of the segments at the top of the panel. Another way to apply segments is to apply them at a metric or a column level. This is helpful when you’re trying to compare a metric filtered by some condition against the same metric without the filter. So let’s say I want to compare my visits against all my pages from the mobile phone, to visits against all my pages from not a mobile phone. I’m going to start with my freeform table here, with pages as the dimension and visits as the metric.

Now I’m going to search for a segment I’ve already created, visits from mobile phone.

I’m going to drag and drop it over here to the metric column.

Now I’m going to add another column of visits. Now that I have that, I can search for my other segment, visits from non-mobile phone, and drag that over to the new column. Now I can easily compare and contrast for every page, the visits that I have from a mobile phone, and the visits that I have from not a mobile phone. Another really great way to use segments is to use them as dimensions. I have a table here with visits and page views.

I’m going to go ahead and search for my segment. Now I’m going to replace the page dimension with that segment. Now it’s been replaced, but I want to see a few more segments in the list. I’m going to pull over visits from social, and another visits. As I drop segments into the header, it adds another row, allowing me to easily compare visits and page views across the segments I choose. So let’s try another example.

How would we use segments to find the most popular page visited in the United States from a mobile device in July 2021? So I’m going to start with a freeform table, and the date range is of course set to July 2021.

Visits is my metric, and page is my dimensions.

Now I’m going to stack the two segments to get the answer that I need. Drag and drop the segments’ visits from mobile devices and the segment USA to find the most popular page visited in the United States from a mobile device.

All right, let’s try one that’s a little harder. Let’s find the month-over-month change in visits and page views from visits from search engines between June and July.

To get this table, we’d start with a freeform table with visits and page views as the metrics and July as the date range. Use the segment Visits from search engines as the dimension. Then you’re going to use the Compare Time Period feature twice, once for the Visits metric and once for the Page View metric. This is going to give you a great month-over-month view of visits and page views from visits from search engines, and you’ll see that it’s created two columns. One’s going to show you the visits from June, and one is going to show you the visits from July. We talked at length about the most popular panel in Workspace, the freeform table, but there are several more that can help provide insights. We’re going to explore two more today that are particularly helpful. First, I want to introduce you to the Quick Insights panel. It’s specifically built to answer business questions quickly, and it’s a great tool for beginners.

Clicking on the panels icon in the left will open up the panels menu. Then you can drag and drop the Quick Insights panel from the left to start using it.

When you first start using Analysis Workspace, you might wonder what visualizations are the most useful, which dimensions and metrics are the most useful, and where to drag and drop your items.

Quick Insights can help with all of this. It uses an algorithm to show you the most relevant dimensions, metrics, segments, and date ranges based on your company’s usage. In fact, you’ll see dimensions, metrics, and segments tagged as popular in the dropdown list.

Quick Insights is great for helping you properly build a table and an accompanying visualization. It’s also great for learning the terminology and vocabulary for basic components. It’ll help you to do simple breakdowns, add multiple metrics, or compare segments easily within a table. It’s also great for trying out new visualizations. You can change the visualization type to help you see which ones work best with your data. When you first start out, go through the short tutorial that teaches you some of the Quick Insights panel basics, but I’ll take you through it right now.

In the Quick Insights panel, you’ll start by selecting your building blocks, or the components. These should be the same components that we just used to build our freeform table. You must select at least one dimension and one metric for the table to be built automatically. You can drag and drop your components from the left rail, like we did in the freeform table. Or, you can use the dropdown. Notice that these first dimensions are labeled popular, indicating that others in my company have been using them also.

You can also search for a dimension right from the dropdown menu.

If you know what you’re looking for, just start typing, and Quick Insights will fill in the blanks for you.

When you’ve added at least one dimension and one metric, the following will be created. You’ll get the freeform table with the dimension, here it’s marketing channel, and the metric, here it’s bounce rate. And you’ll notice the segment, iOS, has also been applied to the metric.

You’ll also get an accompanying visualization, in this case the bar chart. The visualization that’s generated for you is based on the type of data you added to the table. Any time-based data, such as visits per day or month, defaults to a line chart. And any non-time-based data, such as visits per device, defaults to a bar chart. You can change the type of visualization by clicking on the dropdown arrow next to the visualization type.

Quick Insights can also make breakdowns easier. To get a breakdown, just click on the Add Breakdown option below your dimension to select what you want to break it down by.

You can use up to three levels of breakdowns and dimensions to drill down to exactly the data that you need.

You can also add more metrics. You can add up to two more metrics by clicking Add Metric. You can also add up to two more segments and choose to either combine those segments or to compare them in the table. The second panel we’re going to explore is the Attribution panel. So, a given customer journey isn’t linear and it’s often unpredictable.

Each customer proceeds at their own pace and they often double back, stall, restart, or engage in other non-linear behavior. These actions make it really difficult to know the impact of marketing efforts across the customer journey. And it also hampers efforts to tie multiple channels of data together.

Attribution gives analysts the ability to customize how dimension items get credit for success events. So, an example would be a visitor to your site clicks a paid search link to one of your product pages. They then add the product to the cart, but they don’t check out yet. The next day, they see a social media post from one of their friends, click the link, and then they complete their purchase. Attribution gives analysts the ability to customize how those marketing efforts get credit for the success event completing a purchase. The Attribution panel is an easy way to build an analysis comparing different attribution models. It uses Attribution IQ to give you a dedicated workspace to use and compare models. To start, click the panel icon on the left and drag the Attribution panel into your analysis workspace project.

First, you’re going to want to add a metric that you want to attribute. Then, add any dimension to attribute against. So, an example would be marketing channels or any custom dimensions such as internal promotions.

Then, select the attribution models that you want to use. The model describes the distribution of conversions to the hits. For example, first touch or last touch. Next, select a lookback window. The lookback window describes which groupings of hits are considered for each model. It should be the amount of time before a conversion in which you want to look at the touch points. As you can imagine, attribution models that give more credit to the first interactions see larger differences when viewing different lookback windows.

Once you’ve chosen your inputs, click Build. The Attribution panel lets you look across the different models of attribution to see what dimension is making the biggest difference in your conversion event. The top of the panel returns your total metric value, in this case revenue, and a visualization. In this example, I can see that whether I look at it from a first touch, linear, or algorithmic attribution, the display ads are the biggest contributor to revenue, followed by email. Below the visualization, there’s a table that’s going to help you better compare and contrast the results for the various attribution models selected in the panel.

That wraps up the Analyze section of today’s session. I hope it helps give you a sense of how easy it is to get answers for business questions when you have the power of Analysis Workspace. I’m going to be sticking around for the Q&A, so if you haven’t already, go ahead and drop your questions in the chat and we’ll do our best to answer them.

Great. Thank you, Jennifer. I appreciate you doing that presentation for us. Welcome to the Q&A session. Are you emotionally psyched for this session? Of course, I always am.

I knew it. I knew it. We’ve got a lot of questions coming in, so we want to dig in here a little bit. The first one is a doozy. It’s from Simon. It says, how does the Adobe SDK upgrade improve analytics performance and are there new workspace features, dimensions, segments, tools, etc.? Coming in hot. Great question, Simon. Unfortunately, that’s a little bit outside of my knowledge range. Doug, do you have any color to add to that? Yeah, like you said, a little outside the scope of this call, but I don’t want to leave you hanging on this one.

First of all, Simon, I’m going to assume for a minute, I hope this is a good assumption, cross fingers, that you mean the Adobe Web SDK. And it does improve analytics performance as far as page performance, let me say that, because it combines libraries, you know, if you have analytics, target, audience manager, those kinds of things. It combines those JavaScript libraries to help page performance. It wouldn’t really help analytics reporting performance.

And then you asked, are there new workspace features, dimensions, segments, tools, etc.? So again, if you’re talking about the Web SDK, since it is data collection, it doesn’t affect the features available in workspace. I hope I got that right. If I didn’t, I’m sorry. And you can, you know, go to the community. We’ll talk about that later on.

So let’s jump into the next one. What is the best metric to use if we want to report on the number of times a specific page has been viewed within a date range? Good question. So you’re going to want to set the date range that you’re interested in in the upper part of your panel. And then in terms of the metric, you should have a page views metric. If you want to be more specific about how you want to define a page view, you can also explore some other metrics such as visits or sessions. And then of course, if you just align that to your page dimension, that should get you what you’re wanting.

Great. Great. Yeah, good. Kind of the one of the, what we sometimes call one of the big three with page views, visits, and visitors. Okay. We have a question from Abby or Avi. What if you look at monthly data, but then decide afterwards, let’s see, decide afterwards you want to look at a month-over-month comparison? For example, not just look at April, but look at January, February, March, April, etc.? Yeah, that’s a really good question. Playing with date ranges and configuring your table exactly how you want it is really the basis of what makes Workspace great because it is really flexible. So if you’re looking at a single month and you want that month-over-month comparison, you can actually do a right-click on your metric and you can choose from that menu for a month-over-month comparison. If you want multiple months like January, February, March, April, I would recommend using the month dimension and then maybe having a breakdown underneath that. You can also grab specific months from your month dimension and line them up so that they’re on top of your metric columns.

Those are a couple of great ideas. Thank you. Good ways to compare months. Okay, Logan coming in with a question. What is the best or simplest way to differentiate between a hit or visit-based metric when creating a story? Oh, good one with creating a story. Yeah, that’s a really good question. So most metrics should, you should have some clue about whether they’re hit or visit-based based on what they’re titled. But a lot of calculated metrics actually allow you to look inside them if you click on the little info icon and see how they’re built. So calculated metrics give you the option to look at it at a hit level or a visit level. And so it should indicate that in the information of how that metric was built. Cool. Yeah, great. Lots of flexibility there. Okay, next question. What is the Adobe metric for unique page views in Google Analytics? So unique page views is number of sessions during which the specific page was viewed at least once. Let’s see, number of sessions. Got it. So in that case, you could probably look at just your page and use sessions as your metric. But if you wanted to get even more specific than that, you could create a calculated metric looking at sessions and then count distinct pages. So, and when you say sessions in Adobe Analytics, visits, right? So a session and visit is defined a little bit separately, and I’m assuming by the way the question is phrased, that they have some knowledge and understanding of what a session is. But they’re very, very similar. And I think for the scope of this conversation, it’s probably not worth getting into the details because that’s something that you can configure in your initial analytics setup. Great. Thanks. Thanks for making that distinction. Okay, next one. Can we create a monthly goal to track progress of a particular metric, for example, for revenue in Adobe Analytics? Well, questioner, you are in good company. Goals is something that we’ve been asked quite a bit about. Right now, there is no way to create a goal natively within Workspace. You can upload metrics and kind of use those as goals, but I know that’s not what a lot of people are looking for. The exciting news is that the analytics Workspace team is specifically working on goals and targets right now. So hopefully there will be something exciting around that maybe in the next year.

Cool. Cool. It’s good to know that they, yeah, like you said, they’re in good company. Other people ask that as well.

Okay. All righty. If you create a rolling time period, for example, one year ago, does your overall date range in the right hand corner have to reflect that period? So I think I understand the question. So the date range that you have in your upper right hand corner of your panel, that is the date range that is applied to your entire panel. And so if you go into that date range and you set that as a rolling date period of one year ago based on today, it will always update itself so that depending on whatever today is, it’ll be that rolling period of one year ago. As I touched on a little bit in the presentation, you can also use date maps. So if you always want to see aggregated views for like all of last year, regardless of whether it’s March or September of this year, you can also do that with your rolling periods. Cool. Cool. Very flexible. Okay. Kellen, is there a good resource for learning how to create segments? Yes. So we actually have a lot of really great resources over on Adobe Experience League. That’s… Doug, help me get this right. I think it’s adobe.experienceleague.com. It is. It’s so close. You’re so close. Yeah. Thanks for teeing me up on that one. It is experienceleague.adobe.com. Yeah. Okay. That’s right. Yeah, yeah, yeah. Just go there and you can go to the tutorials, you know, up in the, you know, learn tutorials up in the navigation and go to analytics. And yeah, there’s a folder full of segment videos and there’s a course actually for segmentation as well. Yeah. I just want to double down on what Doug was talking about there. I still go to Experience League all the time, even though I have been with the company and with Adobe for about three years now. There’s incredible resources and self-paced courses on everything from very beginner activities to more advanced things that I’m still looking up now. It’s wonderful. Great. Okay. All right. Next. What is the quickest and easiest way to show year-to-date percentage progress towards an annual goal or target? Yeah, a little bit there from before as well. If 12 month goal is X, how can I visualize the percent achievement year-to-date? Yeah. Again, a great question. I am going to have to defer to my earlier answer and that’s exactly something that the Workspace team is working on right now. And that’s goals and targets. So hopefully there shall be more exciting features there in the near future.

Cool. Thank you. Okay. Kristin asks, when do you use hits versus visits when creating a segment? That’s a really good question and a really important question. So I’m trying to come up with an example. I’m not sure what kind of segment that you’re talking about, but basically you would want to use a visit if you were looking at a longer time period. So for example, if you wanted to create a segment with people that had visited a certain page maybe five times, and you say that that’s a really good indicator that they want to buy something, but you don’t want it to be a hit. So what you want to see is that they’re coming back separately like five different times instead of just navigating back to the page five times in a sitting. So that’s when you might make the distinguish. You might want to distinguish between hits and visits. And it really depends on what you’re trying to achieve and whether you’re thinking about basically individual page views or an action taken on a page, or if you’re wanting to count just a single sitting and the action that is taken then. Nice. Yeah. Thanks. That’s a big important question when you’re building segments, of course, the bucket there. Okay, cool. Thank you.

I hope I get this right from Jiyoti. How to make best use of attribution models? What are your, he has a pretty broad question there, but do you have any hints for making the best use of the attribution models? Yeah, absolutely. I think it really comes back to what is it specifically that you’re trying to do? So if I’m trying to understand if an email campaign has helped sales in some regard, I want to think very carefully about am I really most concerned about what the last touches with the first touches or whether they were exposed to the email at all during a certain time period. And you’re going to want to use the different models according to what it is that you’re trying to show. And sometimes, as I showed in the example, it’s worth looking across a couple models to kind of understand what is happening.

A really great resource, again, is Experience League. There is an excellent table that shows all of the different models that you can use in the attribution panel, what exactly it is that they’re doing, and when is the best time to use them. There’s actually like a specific little when to use box that helps explain when this is going to be most advantageous. Nice. I’m assuming that’s in the documentation for the attribution. Is that right? Yeah, you’ll find it under attribution IQ under the workspace. Okay, cool. Great. Okay, Tracy has our next question. Is it possible to compare results for different date ranges? We have events that are in August last year and October this year. So they want to compare those. Yeah, absolutely.

So assuming that your metrics and your dimensions are the same and the only thing you’re doing is comparing date ranges, it’s very easy to turn a date range into basically a segment. So what you’re going to want to do is have your panel covering a much wider date range that covers the entire period that you’re looking at. Then you can actually create date range components. Those will show up in purple on your left-hand rail in your components bar. So you can create the date ranges that you specifically want to look at and compare. Very common use cases like Thanksgiving this year versus Thanksgiving last year because those dates kind of move. Then you just drag them in on top of your metric columns and then it’s very easy to compare your metrics over those two date ranges.

Nice. Nice. Okay, we get lots of questions from stakeholders about quote undefined traffic like in the mobile device versus non-mobile device. There’s always undefined traffic. How do we explain that traffic to our stakeholders? Yeah, that is a really great question and a constant plague, I think, of analysts.

So I think we as analysts understand that undefined is just data that is showing up that doesn’t have a defined value for what it is that you’re looking at, whatever that is in your dimension. There’s always a lot of it. If you’re concerned about explaining it to your stakeholders, there’s actually a checkbox. If you go under the filter for your dimension, you can check and uncheck whether you want to show those undefined or unspecified values. That’s great. You can get that filtered out.

Okay, Grant has our next question. How does the page dimension get classified? Is it Adobe? Let’s see. Is it Adobe that determines that or the organization itself? When you say classified, I’m assuming how you’re defining the page name. Doug, is that how you understood that question? Yeah, I think so too. Yeah. How does the page dimension get classified? How does that dimension set like the page? Yeah, so that’s a great question. That is something that you can set within your organization, but you don’t have to necessarily go in and manually set every page name. Adobe is also pretty smart and can pull the page name from the URL. Yeah, and in a lot of cases, I would say it depends on the implementation at your organization if they’re using kind of the out of the box page dimension or another one. So maybe talk to your implementation team about how they’ve done that. Yeah, cool.

Are there ways to automate the month over month, also known as the mom percentage is my favorite.

Are there ways to automate the month over month change and the month over month volume change calculations once I update the date ranges for two months? Once you update the date ranges for two months, I don’t quite understand the last part of that question, but is there an easy way to automate that month over month change? The answer is yes, absolutely. We saw a quick example earlier of how you can right click on a metric and have that month over month comparison. Again, Workspace is pretty smart. When you do that, it doesn’t just generate the next month column, sorry, the previous month column, but it gives you another column that gives that percentage change. So if you have that set as one month to another month, that’ll automatically update.

Awesome. Well, those are great questions and we have more, but that’s what we have time for today. Again, I’ll talk a little bit later about where you can get some more questions answered, but basically, you know, I just want to thank you, Jennifer, for being here to answer all these questions for all of our viewers. Yeah, of course, Doug. I love this.