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So far Dominique Beaudin has created 4 blog entries.

Renovate Your Tableau CRM Dashboard: Create a Custom Toggle in 3 Steps

Ever wondered how you can optimize real estate in your Tableau CRM Dashboard? A great option is using toggles. 

There are several types of toggles. You can select a single field from a dataset when you have the values in one field. Or, you can create a custom toggle that lets you change views and other attributes dynamically. 

You can go from this:

Graphical user interface, application

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To this:

Graphical user interface, application, table, Excel

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What is a toggle?

A toggle is a widget that lets you quickly jump from view to view and show your dashboard users what their options are. You can use them to change groupings, column names and even metrics used. 

In this example, we will keep it simple.

Step 1: Create the visual.

In our example, we are using the Pardot Prospects dataset. We drag a chart filter onto the Canvas and group by Country.

Chart, bar chart

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Step 2: Create the toggle.

Next, we drag a toggle widget onto the canvas. With your toggle on the canvas, you’ll:

1. Click on the toggle.

2. Select “Change data source” (top right).

3. Select “Create Custom Query” (bottom left).

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4. Add a name for the column (the name will display in the toggle).

5. Select “+ Add Column” and select “Dimension.”

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6. Select the “Pardot Prospects” Dataset.

7. Add Country.

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8. Repeat for all dimensions you want to use. Click “Done.”

9. Click on the toggle and change the query properties to “Single Selection (required).” Application

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Step 3: Bind the toggle.

1. Click on the chart you created earlier and select “Advanced Editor” in the right-hand panel.

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2. Click on “Select Query” on the left-hand side.

3. Select the name of the Toggle you created (In this case, it’s “Select Group”).

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4. Select the Back arrow by choosing a query to return to the main screen.

5. Under “Source Data” click on “Choose data.”

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6. Use the dropdowns to select “column” and select the column with the Dimensions you selected. Use the back arrow next to “Select Data” to return to the main screen

7. Change the interaction type to “selection” and the “Data Serialization Functions” to “asObject”

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Note that the Interaction result shows you the value that is created by your string. Click on the “Copy” button to save the interaction code to your clipboard

8. Find the “groups” area and replace the “Country” group with the code you just created (see below). Make sure you keep the Quotes on each side.

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9. Click on the “Widget” Link at the top. Use the Find function to find the “column map” section.

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10. Change the value from this:

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To this:

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Why do we need to remove the column map?

We remove the column map because we are dictating with our Binding what the columns will be and removing Tableau CRM’s static mappings.

Happy toggling with Tableau CRM!

That’s it! You can now use the toggle to select any of the views you created.

As you play around with this feature, you can get very fancy. You can use bindings to change just about anything in your chart dynamically.

When you’re finished playing around, here’s another solution you can use to customize your Tableau CRM reporting tables and keep it going.

Happy toggling!

How fancy are you gonna get with your custom toggling in Tableau? Tell us about it in the comments or send us a message to chat.

Original article: Renovate Your Tableau CRM Dashboard: Create a Custom Toggle in 3 Steps

©2022 The Spot for Pardot. All Rights Reserved.

The post Renovate Your Tableau CRM Dashboard: Create a Custom Toggle in 3 Steps appeared first on The Spot for Pardot.

By |2022-04-07T18:03:00+00:00April 7th, 2022|Categories: Analytics & Reporting, Pro Tips|

How to Use Flags in Tableau CRM to Create Many-to-One Relationships

Ever wished you could facet, filter and do other magic on a dataset that also had aggregated data from a summary table in Tableau CRM?  

There is a way!

For example, you want to look at all the scores in the Pardot engagement history object, but also would like to use the same report to show summarized campaign information.

The dilemma?

When you bring in the summarized data and join it by Campaign, each Activity row will contain the data for the entire campaign. While it will make your campaign numbers look spectacular, it will also be spectacularly wrong!

What to do?

Use a flag to differentiate summarized data

Tableau CRM has an AMAZING feature that lets you create a row number that you can use as a flag to differentiate between summarized and detailed data.  

How? You can use the flag in your dashboard widgets to summarize or exclude data as needed.

Here’s how it works:

  1. Join your data as usual. Here we are joining on ActivityCampaignID in Pardot Engagement history to the ID in the Campaign table after we aggregate the metrics we want from Campaigns (leads, cost $ and opps $).
  2. Use a transform in your recipe to create the “flag” / unique identifier.
  •   Select Add transformation.
  •   Select Multiple row formula at the top.

The multiple row indicator allows Tableau CRM to “partition” the data so you can look at groups of data within the data and apply metrics to the specific group. 

In this instance, we are grouping by the CampaignID to assign a row number for each instance of the campaign (starting from 1).

  1. Select Row Number.
  2.  Select the field you wish to create row numbers from.
  3. Select numeric.
  4. Give it a name and save.
  5. Complete your recipe and run!

You now  have a “flag” that can be used in your recipe.  Each #1 in the row can be used to reflect the “unique” campaign aggregate.

The flag gives you access to accurate data

Now you can use this flag in metrics and KPI widgets where you want to see the campaign metrics. 

Example

By adding the flag we created to the filter for summary statistics around Campaigns, we are able to limit the  distinct Campaigns for our KPI/top level summary. But we are still able to see the row-level detail for non-aggregated data (like score).

Why is this great?  Now you can use the SAME filters, toggles and other interaction features to see detail AND the summary.

Using a single dataset, we can now view the Campaign stats (which we aggregated) and all the activity details our marketing teams crave!

Have a fun use case for this solution? Tell us about it in the comments.

The post How to Use Flags in Tableau CRM to Create Many-to-One Relationships appeared first on The Spot for Pardot.

By |2022-02-18T18:30:44+00:00February 18th, 2022|Categories: Analytics & Reporting, Data Management, Pro Tips, revive|

Recipe for success: Pardot B2BMA columns to rows

Change your data columns to rows in Pardot B2B Marketing Analytics/Tableau CRM

Has this ever happened to you? You wish you could change your Pardot B2BMA data from columns to rows.

You have all the Pardot B2B Marketing Analytics data you want in a single column, but you need to create B2BMA reports that show the data as rows.

For Example:

Your data looks like this.

B2BMA Columns to Rows 1

But you want the data to look like this.

B2BMA Columns to Rows 2

So you can make visuals like this!

B2BMA Columns to Rows 2

And you want to do this without using a complicated query on the front end of your dashboard that could limit the ability to filter and sort the data…

There are many ways to accomplish this. But one of the simplest and most manageable methods is through a data recipe using the Append (UNION) and transform filters. This approach allows you to tweak your rules and data without code on the front end so you can keep your dashboard creation options flexible.

Changing Pardot B2BMA Data Columns to Rows

Step 1: Figure out what fields and filters to add.

The first step is to identify the rules.

  • What determines each type?
  • Which fields are needed for the data visual?
  • What filters do you want to include?

In our example, we know the MQL (Marketing Qualified stage) has been reached if the “Date__Qualified” date is greater than 1971-01-01’. Each stage has its own rules.

To create our dataset, we need to determine what fields and filter to add:

  • MQL Status (rules fields) and MQL Date
  • SQL Status (rules fields) and SQL Date
  • SAL Status (rules fields) and SAL Date

Filters: Country, Account name

When creating your dataset, be sure to document what fields are needed. Keep the field list as small as possible (you can always add more fields later if needed). Less is more for performance and useability in this case.

Step 2: Choose the fields you need.

Open your data recipe and select the dataset. Choose only the fields you need. This will keep the dataset manageable. You should pick all the fields needed to create the rules and the fields you will use to filter. Document everything you select as you will be repeating this process for each row type.

LeadsCompleteSercante

Step 3: Attach a transform to the dataset.

In this next step, you’re going to attach a transform to the dataset. Select the ‘custom formula option.’

In our example, anywhere the qualified data is after ‘1971-01-01’ we flag the type as MQL, otherwise we leave it blank.

Attach a transform to the dataset

Step 4: Add your rule and create a new field.

Use the “CASE” function to add your rule and create a new field. This will create a new field (BusinessStage) that will indicate ‘MQL’ where the qualified data is valid. Set the field type as text and Make sure to rename the field

Code Sample:

case 
when Date_QualifiedMQL__c >’1971-01-01′
then ‘MQL’
else ‘’
end

Add your rule

Step 5: Attach another transform.

Attach another transform

Attach another transform to populate the correct date using the custom formula. We are essentially creating a date field that will be the “main” date for our dataset and allow the aggregate on the dashboard.

Code Sample:

case
when Date_QualifiedMQL__c >’1971-01-01′
then Date_QualifiedMQL__c
else Date_QualifiedMQL__c
end

Step 6: Add a filter.

Add a filter to whittle your dataset down to just the “MQL” data.

Filter
B2BMA Columns to Rows 2

Now your dataset looks like this with “SQL” as a FunnelStatus and the SQL Date as the FunnelDate. 

B2BMA Columns to Rows 2

Step 7: Repeat steps 1 through 6.

Repeat steps 1 through 6 to create the next row type. For each, make sure your CASE statement reflects your rules.

Repeat Steps

Step 8: Append the dataflows.

Append the two dataflows together with the Append connector. Each dataset must have identical rows to connect them as one (unioned) dataset.

Append the dataflows

Now your dataset looks like this. Your SALs and MQLs have gone from columns to rows!

B2BMA Columns to Rows 2

For each remaining variable, repeat steps 1-7 with correct transformation rules and add append to the dataset as you go.

B2BMA Columns to Rows 2

Step 9: Create an output object.

Once you have added all your types in filtered “sub” datasets, create an output object.

Once you run the data flow, you will be able to use the FunnelStage and FunnelDate to do summaries without complex code. If the rules change for creating the FunnelGroups, change the Transforms in the recipe or add new ones.

Now you can use your new dataset to create visuals by date and type or create a summary table. 

Further considerations for reformatting Pardot B2BMA data

Here are a few things to keep in mind as you’re getting started.

  • You can use joins to add other datasets to your recipe – note they have to exist for all “streams”
  • Verify all desired variables have been accounted for (in our example after you filter SQL, SAL and MQL are there rows that are not brought in that you might need in your analysis? )
  • You can bring in as many columns as you need for filtering. Since we are turning each “column’ into its own row, each new column can contain the same data it had before, making all filters in the original dataset available.
  • Make sure you do a reality check on the data including:
    • Expected row counts
    • Expected amount totals
    • Missing values
  • Note that when you create rows from columns, you need to decide if you want ALL data converted or just the data that meets the rules you set. If in doubt, create an additional data stream that filters out all records that don’t meet any of the criteria and make sure to review those. What’s not there might be important too!

Further reading:

The post Recipe for success: Pardot B2BMA columns to rows appeared first on The Spot For Pardot.

By |2021-07-09T14:46:43+00:00July 9th, 2021|Categories: b2bma, Data Management, Pardot B2B Marketing Analytics|