Using Dynamics 365 Sales and Wondering Where to Start with Power BI?

If you are new to Power BI or if you have not done a lot with it, it can be a little overwhelming to know where to start. In just about every sales deployment, you will have requests from both salespeople and sales managers for ways to get actionable and accurate intel on the performance of individuals and the team.

Of course, you can accomplish quite a lot with the built-in views, charts and dashboards that are available out-of-the-box with Dynamics 365 Sales, but eventually you may find that you run into some limitations. For many years, when considering advanced analytics, the primary recourse was to build an SSRS report – which is still an option. SQL Reporting Services is great, but it can be complex even if you are familiar with the tools and the skills needed to build these types of reports.

Power BI also requires some skills, of course, but I find it is much easier to get started with. A great place to start is a powerful set of reports and dashboards that Microsoft makes available on AppSource for free (assuming you have the licenses for Power BI), called “Sales Analytics for Dynamics 365 Sales”. Let’s take a look at what this provides, and how you might use this as a starting point in your organization and then build on it.

You can see that there are tabs along the left with a variety of different focuses on sales performance, and a rich set of charts and graphical views of your sales data. On the right are filters that allow slicing and dicing the data intuitively.

After you install the app from appsource into Power BI, you’ll be prompted to connect by entering the URL of your Dynamics 365 Sales instance. Note the advanced option that allows you to automatically refresh the data – the Advanced area is collapsed by default so it is easy to miss this!

On the next page, you’ll need to authenticate to Dynamics. From the dropdown, choose the OAuth2 method and then the “Organizational” type. This allows you to use your Office 365 login to authenticate from Power BI to Dynamics.

After installing this Power BI app and connecting, your data will be queried and pulled into Power BI. You will have a new workspace that contains a tabbed report. Within the workspace you will find the new dashboard and the reports that make it up. It’s helpful to explore these and the Dataset that is created. If you want to go further into seeing how this was built, you can download Power BI Desktop which provides you with a richer set of tools for designing Power BI reports.

Of course, salespeople and sales managers may not want to log into Power BI and see all of these things, which is why Microsoft has delivered this set of reports as a Power BI app.

Making This Power BI App Available in Dynamics 365

Let’s look at how we can make this available to our sales users without forcing them to leave the Sales app in Dynamics.

First, make sure the report is shared with your Dynamics users. You can either share it directly with individual users, or, as a better alternative, share it with an Office 365 Security Group that contains your Dynamics users.

Next, within Power BI, navigate to the report and click File > Embed. You’ll get two options: a direct link to the app, and iframe code you can use in your own HTML.

Option 1: Add a link to the Sales app’s sitemap to open a new tab for the Power BI app

One simple method to add this to Dynamics is to edit the “Sales Hub” app and modify the sitemap to add a direct link to this dashboard. It will open a new tab for users directly to the Power BI dashboard.

In the Power Apps maker portal ( find the Sales Hub solution and double-click the Sitemap to edit it. Add a Subarea and set the “Type” as URL. Then simply paste in the URL from the Power BI embedding options:

Publish your changes, and you will have a new sitemap in the Sales Hub app with a link to the Power BI app. It will open it in a new tab or browser window for your users.

Option 2: Add a Web Resource to the Sitemap

I like this option better, but it takes slightly more effort. First, in the Power Apps maker portal, create a new Web Resource. Select the type as “HTML”. You’ll need to add the HTML for the opening and closing <html> and <body> tags. Then simply paste in the iframe code from the Power BI embedding option:

TIP: Change the width and height of the iframe to 100% so that the Power BI takes up the entire frame within Dynamics.

The result is a rich set of dashboards, charts, and analytics, easily accessible to your Dynamics Sales users:

Hope you find this helpful! From here, you can begin to build on the out-of-the-box Power BI by adding your own reports, charts and analytics, leveraging the dataset the app has created for you in Power BI.

Customer Insights Featured First (Again) in Virtual Launch of 2020 Wave 1 Release

James Phillips, President of Business Applications at Microsoft, presented the Virtual Launch of the 2020 Wave 1 Release today from his home.

James Phillips presenting from home
James Phillips presenting the 2020 Wave 1 virtual launch from home

Customer Insights was first on the agenda again! (It was also highlighted first during the 2019 Wave 2 Virtual Launch.) This time around, the use case that was shared was UNICEF’s use of Customer Insights and its integration with Dynamics 365 Marketing. Power BI, Azure, CE and F&O also got mentions in the video. You can watch the video about UNICEF here: UNICEF inspires donors with Microsoft Dynamics 365 Customer Insights. (This video is a favorite of mine since it was filmed at UNICEF Netherlands – I miss hearing that great Dutch accent!)

After a further introduction, Satish Thomas, the PM for Customer Insights, dived further into the CDP platform. Satish described some of the highlights in this release.

High-level overview of enhancements to Customer Insights in this release
High-level overview of enhancements to Customer Insights in this release

Some of the most interesting updates include new ways to enrich your unified customer profiles. Prior to this release, enrichment was limited to Microsoft Graph data related to brand affinities and category interests. This release will add new enrichment options that include contact data from Informatica, firmographic and address data from Microsoft Graph, location data from HERE Technologies, and media habits from CivicScience. Satish indicated that in addition to the new enrichment options becoming available with Wave 1, there are plans to continue to grow this list.

New enrichment sources
New enrichment sources

Another enhancement is the addition of new export destinations, including Azure Blob Storage; an API Connector; Power Apps, Power BI and Power Automate connectors, and LiveRamp omnichannel marketing.

New export destinations for Customer Insights
New export destinations for Customer Insights

Another segment of the launch focused on Dynamics 365 Commerce, which included out-of-the-box integration with Customer Insights in the POS solution to allow retail workers to easily understand their customers and identify the next best action.

There were tons of other new features and enhancements announced across the entire Dynamics 365 and Power Platform stack. Dynamics 365 Marketing is seeing huge investments in features like simple integration to consume Customer Insights segments, A/B testing of emails in Customer Journeys, and smart scheduling of emails for optimal send times.

You can read all about the new release here:
Dynamics 365 Release Plan
Power Platform Release Plan

An Opportunity to Help a Dynamics 365 & Power Platform Community Star

I want to let you know about someone who represents the very best of our community and who needs your help today.

Over the last16 years in working with Microsoft Dynamics, I have been fortunate enough to personally meet thousands of people in the Dynamics 365 and Power Platform community. From partners to customers, developers to low code advocates, they are the most creative, passionate, funny and often wacky individuals. We are all lucky to have a community that is so rich and diverse, and unfailingly generous.

Britta Rekstad, aka @MacGyverCRM, embodies all of the best things about our community. If you don’t know her, let me tell you that she is in fact the only really humble Microsoft MVP you will ever come across. She is not a self-promoter. In fact, she is a promoter of others. I was most impressed when I learned a few years ago how she had given up many lucrative opportunities that came her way as a skilled MVP so that she could focus on mentoring and training women who had no IT background and who had encountered difficult circumstances. Britta was passionate about her mission to help these women build a career and a rewarding life by introducing them to the technology and the community that we all love.

She is not a self-promoter. In fact, she is a promoter of others.

I knew that Britta had been fighting a challenging battle with a rare illness, but until a couple of months ago I did not realize how it had worsened to the point that it has all but taken her out of action in our community and drained away her finances. As a community we are all poorer for it.

She has some close friends who have set up a CaringBridge site where you can learn more, but I want to personally challenge you to take a few minutes, get out your bank card, and donate on her gofundme page. If you have benefited from this amazing community, now is your chance to give back.

Changing the Enrichment Segments in Customer Insights? Re-run Measures and Segments to See the Updated Customer Profiles

File this one away under lessons learned. Recently I was updating a demo environment of Customer Insights that I had originally set up to use one set of enrichment parameters. The original settings used Brands and Categories related to coffee retailers, but for the purposes of a new demo, I wanted to update the environment to see what types of enrichment I could get for financial services and use this information to build new segments. In the Enrichment area, I updated the brands and categories to use some familiar names and topics related to financial services:

After making these changes, I ran the Enrichment again:

However, when I viewed my Customer Cards (profiles) they still showed their affinity for coffee related brands like Starbucks and categories like coffee roasting.

After reaching out to Microsoft, I learned that Customer Insights takes a snapshot of the profile data in order to maintain consistency of the data. To update the snapshot and see the most recent enrichment on the profiles, it was necessary to update the dependent Measures and Segments as well:

It makes sense: Your segments and measures might make use of the enriched data, so you wouldn’t want them to be out of sync after you change the enrichment parameters. Once I updated these, I now was able to see my updated profiles and use this data to make new segments.

Customer Insights vs Power BI

A common question that comes up when you begin to discuss Customer Insights and its ability to unify and report on your customer data is: “Why can’t I just use Power BI for that?” I thought it might be helpful to provide some bullet points to help clarify how Customer Insights is differentiated from Power BI.

CI does not equal BI
  • Artificial Intelligence/Machine Learning: Customer Insights leverages sophisticated algorithms to help match customer records from disparate systems that don’t have IDs or keys in common.
  • Common Data Service (CDS): Data that you ingest into Customer Insights can be mapped to CDS entities. For example, if you connect a contact from your order processing system, you can map it to the CDS “Contact” entity. Or if you bring in lead data from, you can map it to the CDS “Lead” entity. This is an optional step, but it allows you to begin to normalize your data so it can be used in other applications.
  • Extensible Machine Learning Models: Once you have unified your data in Customer Insights you can leverage the UI to create measures and KPIs. But you can also extend this functionality by incorporating custom machine learning models by consuming them from Azure Machine Learning Studio.
  • Third-party Data Enrichment: In addition to unifying the data you own internally, you can overlay third-party data to enrich your customer profiles. Microsoft makes this easy with built-in enrichment functionality from the Microsoft Graph to help you understand your customers’ potential interests and brand affinities.
  • Segmentation: Customer Insights allows you to create segments (both static and dynamic) that span attributes across your unified and enriched data sources. These segments can be leveraged in your marketing automation system, with built-in connectors to Dynamics or by exporting the segment for use in another application. (In upcoming releases, Microsoft will also have “recommended” segments generated by algorithms that spot patterns and opportunities in your customer data that you might not otherwise look for.
  • Integration with Power Platform/Dynamics: This may not strictly be a differentiator from Power BI, as of course Power BI also integrates nicely with its family of products. But Customer Insights offers a pre-built solution that can be installed in Dynamics 365 Sales to add customer cards/measures to the Contact forms so you can quickly leverage your unified data. There are also connectors so you can build Power Automate Flows/Automations (do we still call them Flows?), Power Virtual Agents, Power Apps, etc., that leverage your unified customer data.
  • Time-to-Value: Another huge differentiator between Customer Insights and Power BI (and most other BI tools) is the time-to-value. Connecting to multiple data sources, normalizing them, matching them, and extracting meaningful, actionable insights can be a huge undertaking. Not only does Customer Insights make this process fast and easy, it is UI-driven, meaning you can get to these valuable insights without having to resort to code and complex queries.
  • Approachability/Relevance to Marketers: While Customer Insights is not intended to be an “end user” application, it is designed so that marketing analysts and professionals will feel comfortable working in it. While both Customer Insights and Power BI may benefit from having a data analyst involved in the initial setup and configuration, I would argue that even a seasoned marketing professional might have difficulty extracting ad hoc data from Power BI. But they can quickly become adept at building segments in Customer Insights for use in their marketing efforts.
  • Customer Profiles with Demographic, Behavioral Data and Activities: The old saying about “if your only tool is a hammer, every problem looks like a nail” comes to mind. Power BI is powerful and allows you to present data in many ways. But it is a general or horizontal tool for data analysis and reporting. Maybe it is more of a Swiss Army knife as opposed to a hammer. Customer Insights, on the other hand, is focused specifically on understanding your customer and the data points surrounding your customer – how they interact with your website and other marketing channels, what they purchase from you, their interests, etc. For professionals, it is often better to have a tool that is specifically crafted for a specific job, rather than a general-purpose tool that “almost” does the job as well.
  • Data Ranking: As you unify your customer data, Customer Insights allows you to choose which data source will “win” for any attribute you wish to use on the customer card/profile. For example, your e-commerce data might be more reliable for email addresses, but your CRM data is more reliable for street addresses. Your frequent flyer data might be a more reliable source of mobile phone numbers, but your support desk data might be more reliable when it comes to work phone numbers. As you bring all of this together to make a single view of your customer, you can rank which system will win if both have different data for that attribute. This would be much more difficult to achieve in Power BI (I’m sure one of my Power BI friends will tell me how to do it though!), but it’s a simple matter of point-and-click in CI.
  • Leapfrogging (Easy Introduction to Sophisticated Data Analysis): Customer Insights makes it easy for businesses to begin using tools and techniques that are typically reserved for very large or sophisticated enterprises. While those organizations who do not leverage CI might have to invest in expensive data scientists and months-long implementations, you can leapfrog them by quickly getting the value of these tools from Customer Insights. For example, connecting your data through the Customer Insights interface will bring your data into an Azure Data Lake. You don’t need to know anything about data lakes, how to construct them or use them, to make use of Customer Insights. But as your organization grows in sophistication, you will have a nicely managed data lake already available to leverage for other applications and scenarios. Similarly, your organization may be years away from building and using your own machine learning models, but with Customer Insights, you can begin using this technology right away and open the door much sooner to the possibilities of ML than you might otherwise have done.

ICYMI: Conversation with @crmchartguy about Customer Insights

Back in September I had a great conversation with Ulrik “the CRM Chart Guy” Carlsson on his Power BI podcast. We discussed the opportunity around Customer Insights as well as how it fits into the bigger story of the Power Platform. Ulrik is a great interviewer – if you didn’t catch it the first time around, have a listen:

Podcast: Power BI &More on the CRM Audio network “Customer Insights and More with Matt Wittemann”

Confirmation or Coincidence?

As if to confirm what I wrote at the start of this week in my blog post entitled “Microsoft Partners: Why you need to get smart about Customer Insights. Right now!“, Microsoft’s Dynamics 365 Newsletter for November just arrived in my inbox, and it is all about Customer Insights:

Links highlighted in the newsletter provide a wealth of great resources to help you get up to speed on Customer Insights and customer data platforms (CDPs) in general:

Microsoft Partners: Why you need to get smart about Customer Insights. Right now!

With the 2019 Wave 2 release rolling out from the Microsoft Business Applications Group and all of the surrounding fanfare of announcements and updates, and with Microsoft Ignite coming to a close this week, partners in the Dynamics/Power Platform space have a lot to digest this month. Let me take this moment to help you sort through and prioritize what you decide to focus on with your teams over the coming month or two. Not surprisingly, I’d like to suggest that you put Customer Insights at the top of your list. Let me explain.

One word: Salesforce.

It is no secret that the Microsoft Dynamics 365 product team has been taking direct aim at for years. What might be less-appreciated outside of our industry is just how successful Microsoft has been in this competition. In years past, industry observers might have been justified in saying that was the innovator and leader in the business applications/CRM space, and Microsoft was regularly seen to be the late mover or also-ran, bringing technologies to market often years after had introduced them to their audience. was the first mover in the SaaS CRM market, at least at scale, around the beginning of the millennium. It would be 8 years before Microsoft was able to launch Microsoft CRM Online, and then only in North America. And think about marketing automation: purchased ExactTarget and created their Marketing Cloud years before Microsoft introduced their own marketing application. Think about AppExchange vs AppSource, Trailhead vs. Microsoft Learn, Lightning vs. Unified Interface. The list could go painfully on.


But Microsoft has been rapidly closing the gap and transforming its ecosystem of business applications in a way that could potentially leapfrog To this observer, perhaps the first and most significant sign of this change of leadership is Microsoft’s entry into the CDP, or Customer Data Platform, space, with the launch this past April of Customer Insights.

The Background

To understand why this is so significant, you have to consider the bigger picture of the CRM and martech space over the last two decades. Back in the previous century, these technologies were the domain of only the largest enterprises. With the rise of SaaS, they became more accessible. Today, as we approach the third decade of this new century, they are table stakes for every business bigger than a mom-and-pop storefront. The affordability and power of CRM and marketing automation means that these technologies are almost ubiquitous, and not having strategies around them almost certainly puts a business at a huge competitive disadvantage.

The promise of these technologies was to help companies to scale their processes – whether sales, service or marketing – to larger and larger audiences of prospects and customers. But at the same time as businesses have been scaling their reach through the use of CRM and martech, a revolution has taken place amongst consumers. Starting with B2C consumers, the purchasing process and decision-making process has become something that is largely completed without the direct input of the business that is trying to sell to them using their highly-scaled CRM and marketing tools. This revolution has been driven by the adoption of smart phones, social media, and ubiquitous internet access. And it has also translated to the B2B space. Business buyers are also individual consumers, and they have taken their shopping habits to work with them. They now conduct their research and get to the point of a purchase decision often well before the seller even knows who they are.

In other words, we may have reached a point where CRM and older martech has scaled a business’s reach as far as it can scale – diminishing returns at best.

The goal of businesses now must be to flip the story on its head: approach their selling and marketing processes from a starting point of the customer. It’s not sufficient any longer to be able to build a subscriber list that you can target with your monthly newsletter. That may well be a necessary ingredient, but it is hardly a sufficient one if the goal is to reach this revolutionary new consumer. In marketing terms, the mandate now must be that businesses adjust their sales and marketing processes around their customer, around a “segment of one,” instead of simply around how they want to improve their processes internally.

That is why over the last few years, savvy marketers have begun to embrace the emerging tech of Customer Data Platforms, CDPs. CDPs are designed to deliver on the promise that CRM once had: get to know your customer at an individual level so they might be more inclined to let you join their buying process.

Why This is Important to Microsoft Partners Now

The reason all of this is so important and timely if you are a Microsoft partner with a focus on traditional CRM (and of course, nowadays, Power Apps and the rest of the Power Platform), is because announced earlier this year that they would be jumping with both feet into the CDP space. After talking CDP down in previous years, they announced at Dreamforce that they would launch a pilot of their Customer 360 CDP application in November 2019, and plan to make it generally available in the beginning of 2020. But there is another “but” to this story: Salesforce’s CEO for marketing, Bob Stutz, departed the company to head back to SAP. (Yes, the very same Bob Stutz who had previously been at Microsoft running Business Applications and buying up a number of not-so-memorable applications like Marketing Pilot.) announced a new head of their marketing group just last week, and he will be coming into the role at the very same time they are supposed to be launching their CDP pilot.

I see that as an opening for Microsoft and its partners to gain even more ground with Customer Insights before salesforce’s new marketing CEO has a chance to get his feet under him. And marketers are exactly who you should be selling to if you are a Dynamics/Power Platform partner who cut their teeth on CRM.

So where to start?

Start on Microsoft’s site to watch the many videos and read the blogs they’ve posted. Set up a trial and kick the tires. Look for a “Customer Insights in a Day” workshop that is likely taking place near you soon (check the team blog for the latest). If you missed Microsoft Ignite, you can watch a lot of the sessions on-demand now. Make this your top priority!

Use Power BI to Collect Unstructured Data from the Web

Follow the steps in this article to learn how to scrape data from websites, structure it in tables, and use it in a Power BI report. In this example, I show how to create a Power BI calendar of events that draws data from two publicly accessible websites.

This is one of my favorite ways to use Power BI and I’m always surprised at how few people are aware of this amazing capability. You can see an example of this at my other site:

First, set up Power BI Desktop

Download Power BI Desktop (not to be confused with Power BI Report Builder, which is the new name for the tool used to build SQL Server Reporting Services Reports and creates RDL files). To download Power BI Desktop, go to and click on the Products menu, or open the Windows Store on your machine.

Second, get the data
  1. Click on “Get Data” > Web
  2. In the “From Web” dialog, select “Basic” and enter the URL. I’m pulling data from the D365 User Group’s list of events on their website:
  3. After connecting, click the button “Add Table Using Examples”
  4. This shows you a preview of the web page where you can begin to select information to place in columns to build a table:
  5. Place your cursor in the first row and begin typing the text that represents an example of the information you want to capture in that column:
  6. You can type a couple of examples if necessary to make sure the Power BI is grabbing the correct info. Tab away and it will fill in the rest of the column.
  7. Rename the column. I like to use a convention that describes the source of the information.
  8. Then tab to create the second column and repeat the step for the next bit of information. Sometimes the webpage will not have the data broken out in a way that makes it easy to parse just the bits that you want. In this example, I just want the date, but I’m getting a long string with the word “When”, a colon and a bunch of empty spaces.
  9. Once you have selected the raw data from the website that you want for your table, click OK.

Tip: You can take a look at the webpage that you are using as a datasource in a browser and use the browser tools to see which elements of the page might be parseable by Power BI. Power BI will look for CSS IDs and selectors to distinguish the elements that make up the page:

Next, Transform your Data
  1. Back on the Navigator screen, click “Transform Data”:
  2. In the Transform window, I am going to use some transformations to get the data I am interested in. For this first column, I will Split the string by the positions of the characters in the string:
  3. When I do that, Power BI looks at the string and automatically shows me where each part of the string starts:

    So if we look at that information, we can see that position 0 must be where the word “When:” starts, and position 104 must be where the date starts. 108 must be the day, 111 must be the year, and so on. I don’t want to break the date out into its sub-parts, so I am going to just split it at positions 0 and 104:
  4. This gives me a new column that just starts at position 104:
    Tip: If I need to undo a step because I mess something up, I can delete it on the right:
  5. Next, I want to just get the date out of my new column. I am going to Split the new column by a delimiter. I don’t want the stuff that starts with the word “from” so I can use that word as a custom delimiter:
  6. Check out what happened here, automatically. After I split that column out, Power BI automatically recognized that this data is a Date type. I can tell by the icon at the top of the new column:
  7. I do a similar “Split by Position” to parse out the location and rename that column. It took some trial and error to find the exact position that the location starts. It turned out that I wanted to split by positions 0 and 117. Then I renamed the column to D365UG_Location:
  8. When I’m satisfied with my table, I click on “Close and Apply”:
Rinse and Repeat

I want to combine this data with another data source, so let’s try another web page. I will repeat the above process with data from

Now I have two tables with data I can use in my report.

I can continue to add more in the same manner, or even connecting to other types of data. I’ve also gone ahead and connected some data from CDS.


Before I proceed, I am actually going to rename the columns so that across the three different data sources, they are uniform for Name, Date and Location. That will let me use another feature of Power BI to create a new table that combines all the data I scraped from the websites and pulled in from CDS.

  1. I want to combine these different data sources into one new table. So in the Power Query editor, I click on “Append > Append as New” and select the three source tables:
  2. This creates a new table for me that has all the columns from all of my data sources. I have removed the columns that I am not interested in for the next step, so all I am left with is Name, Date and Location. I have also renamed this new table to “Combined”:
  3. Click “Close and Apply” again
Design your report
  1. Now I can begin to design what I want this to look like. I want to add a new control to display this data, so I am going to import it from the Power BI marketplace:
    I’ve opted to use the MAQ Calendar since it has a decent layout and navigation to see the calendar by day, week or month.
  2. Lastly, I am going to embed this on a portal using a simple iframe:
  3. On my portal website,, (which runs on Microsoft’s Power Portals by the way!) I’ve added a page and in the HTML, I paste the iframe code from Power BI:
  4. And here is what it looks like live on the site:

These are some of my favorite tricks with Power BI, and I hope you’ll enjoy using them now as well. Leave a comment below and tell me what you think!

Measures: Extracting Insights from Customer Insights

A continuation of a series of posts diving into Customer Insights

Looking at a Customer Card or the home screen dashboard in Customer Insights, one of the first things you’ll notice are the tiles that display various numbers, or measures, representing a customer’s interactions with your company. These might include things like a customer’s average purchase when visiting one of your bricks-and-mortar retail establishments, their average online purchase, or lifetime value.

Types of Measures

There are several different types of measures:

  • Customer Attribute – Configuring this type of measure allows you to add a new attribute for display on the merged contact. For example, if you wish to combine all of an individual contact’s purchases from across various systems into one field to show the individual’s total spend.
  • Customer Measure – Similar to the customer attribute above, but with an added dimension like time. For example, if you wish to show how many times on average a customer visits your online store, or how much do they spend across all your systems on average per month.
  • Business Measure – A business measure is a way to look across your entire customer base in aggregate to answer questions at the business level rather than at the individual contact level. This is the type of measure you would configure to answer questions like “what is the average purchase at our retail/POS locations?”

Variables are operations that you want to perform for each customer record in Customer Insights. One of the more interesting capabilities you’ll come across when building a measure is the Variable Expression editor. It is not intuitive at first. On the right, it will show you the tables and attributes from your connected data that you have chosen as you begin building out your measure. I’ve found that if you click the attribute on the right, it will put it in the expression editor for you, saving you from having to figure out the correct syntax to use if you were to type it in manually.

Double-click the attributes on the right to get them into the Expression area.

After clicking one of the attributes on the right to put it into the Expression area in the correct syntax, you can simply type the mathematical operator you want to use. You can also group operands using parentheses in order to perform more complex operations. For example, you might want to create an expression like “(Total Web Purchases + Total Store Purchases) / RewardsPoints” to determine how many dollars your customer had to spend across both your website and bricks-and-mortar stores to earn each reward point they’ve been granted. (Perhaps your letting some customers earn those valuable loyalty points too cheaply because they’ve figured out how to game your loyalty system!). That expression would look like this:

(eCommerce_eCommercePurchases.TotalPrice + PoS_posPurchases.TotalPrice) / PoS_posPurchases.RewardPointsAdded

After creating a variable for each unified customer record, you’ll need to apply a function to it. Do you want to look at the average result of your variable operation across your entire customer base? Or a sum or count of those results? That is defined in the Function.

Note: A function creates fields where the results of your measure are stored. Behind the scenes, when you define a measure you are creating a new “entity” that will be listed in the Data area of Customer Insights. If you open that entity, you can also view the fields that were created for it as a result of defining the function.

Creating measures can take some experimentation – it’s worth it to begin exploring your data and playing around to see what types of insights these measures can provide your organization. It’s very likely you’ll uncover some things that weren’t obvious before your customer data was nicely unified.

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