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It’s an accepted fact that data management is an important requirement to be able to run accurate segmentation and targeting for marketing campaigns. Dirty data can cause chaos in your Eloqua instance. Establishing a suitable Data Cleansing Program and then maintaining it becomes ever more challenging with organizations that includes multiple data entry points and several teams actively involved in data entry.

 

Data cleansing has been a common pain point for those in the sales and marketing forefront. This could impact every aspect of the daily job. The concept of the Contact Washing Machine (CWM) has existed for some time, however and with the evolution of marketing automation, a Data Cleansing Program becomes ever more necessary in leveraging valuable marketing efforts such as lead scoring, reporting, advanced segmentation, as well as dynamic content.

 

 

The Common Marketing Challenge

 

Incomplete, inconsistent, decayed and a non-standardised database means obtaining key marketing metrics becomes challenging. These includes email deliverability, addressable contacts, and the volume of the target audience. Moreover, this could potentially directly impact the lead scoring module in place.

 

Larger organizations with complex integrations with CRMs, such as Salesforce.com, presents wider a challenge. It is important to understand your integration setup and the flow of data.

 

 

Goals

 

  • To identify incorrect data. Understand the root cause of the data health problem. Develop a plan for ensuring the health of data and future benchmarking on a quarterly basis.
  • Reduce the amount of bad inbound data on forms and lists, while enhancing new data added to the database.
  • Implementation of tools that reduce manual inspection and programming efforts and to streamline the process.
  • Increase the overall opportunity to leverage tactics such as progressive profiling and to strengthen automated decision making to the current lead scoring model through data cleaning.

 

 

Documenting the Current State for Future Benchmarking

 

Data Quality Reports

 

Eloqua provides reporting tools which will assess the health and status of your database. Some of the reports are mentioned below. Note that these reports should be used before and after the change. The most important goal is to reduce the number of blank fields and to correct the incorrect values.

 

  1. Contact Field Value. Report shows the percentage of contacts with different values
  2. Contact Field Completeness. Reports show how complete each field is (by %)
  3. Fields & Views section. This is important to start building lookup tables for the update rules to overwrite wrong values or fill the blank fields

 

 

Achieving Data Quality Through Eloqua: Implementation Steps

1.0 Building the Contact Washing Machine

 

Data cleansing through Eloqua’s CWM continually monitors Contacts and initiates cleaning if it encounters erroneous contact data.The CWM is connected through the Program Canvas and/or Builder, an automated workflow that allows you to integrate data tools to wash data. Connector applications include, but are not limited to:

 

  1. Look-up Tables
  2. Update Rules
  3. Cloud Connectors

 

The below considers the wider scope of the CWM. It is advised to start small and gradually expand its functionality.

 

Do not forget to think about other, integrated, databases that might play a role in data management. If you clean up your field in one system but the other system overwrites those values, you could be adding unneeded complexity to the process or simply wasting your efforts.

 

Process steps:

 

Look-up Tables

Lookup Tables are a two-column table created as a Custom Data Object of associated data values; one column in which a look up can be performed, and a second column holding a corresponding, associated value.

 

  • Standardise Data: Building Lookup tables helps to standardize data and keep the values consistent.
    • For example, replace dirty (existing) values with the normalized (new) value. Look up values like “USA” or “U.S” or “U.S.A” and replace with a standard value such as United States. The same process can be used for any other field required to clean in your database such as company value.

 

  • Validate Data: Lookup Tables can be used as a Find and Replace functionality.
    • For example, look up values like “Test” or “123” and blank them out or replace them with a standard value. (Useful for Progressive Profiling tactics).

 

  • Populate Data: Populate data with lookup tables.
    • For example, assign a lead to a particular salesperson based on a contact's region.

 

      • Creating a Lookup Table:
        1. Navigate to Audience > Tools > Data Tools
        2. Click the Data Tools menu > select > New Lookup Table
        3. Enter an appropriate display name, for example Normalize Country
        4. Enter an appropriate description (optional).
        5. Enter a lookup value column name
          • This is the column name for the original field values that you are looking up to replace, for example, Country
        6. Enter a replacement value column name
          • This is the column name for the field values that will replace the original field values, for example, Normalized Country
        7. Check or clear the Values are case-sensitive field, depending on the state of the data you are looking up
        8. Click Save
        9. Add values to the lookup table manually by entering the lookup value, the replacement value, and then click Add.
        10. Multiple entries can be uploaded from an existing file by going to Manage Entries > Upload Lookup Table Entries (.CSV)
        11. Follow Wizard > (1) Data Source, > (2) upload Data source > (3) Field Mapping > (4) Summery > (5) Finish

 

  • Update Rules
    • An update Rule is a definition of criteria used to update field value(s) in Contact, Account, or Custom Object fields. Each Update Rule defines a field to update, as well as an update action to take against the field value.
    • An Update Rule Set is a collection of Update Rules to be run together in sequential order.
      • In a Contact Washing Machine, Update Rules act on the information provided in the Lookup Tables.
    • Update Rules allows the process of manipulating information WITHOUT having to manually oversee the process.

 

      • Creating an Update Rule:
        1. Navigate to Audience > Tools > Data Tools
        2. Click the Data Tools menu > select Update Rule Set
        3. Enter an appropriate update rule set name
        4. Give name of entity type > for example: Contacts
        5. Click > Add Update rule
        6. Select a field to update > search > make selection > Ok
        7. Edit update Rule by selecting the field to update:
          1. Select an update action. Options include:
            1. Append set value to field -  Append a specific value into a field
            2. Apply date stamp – (Consider this for GDPR)
            3. Overwrite value form Lookup Table Field
            4. Overwrite value from other Field - Take value from field A and overwrite it to field B
            5. Set to value - Allows you to write a hard coded value into a specific field
          2. Select a lookup field by searching it via the Entity Field Search
          3. Select Lookup Table (This of course must be created and uploaded beforehand)
          4. Apply > Save

 

    • Note: Just be sure to analyze and scope the current values within your database. Use Eloqua Data Quality Reports to analyze. Moreover, then consider using OpenRefine (formerly Google Refine) which is a powerful tool for working with messy data to explore large data sets with ease. 

 

  • Cloud Connectors: Data Cleansing in the Cloud
    • Cloud applications help to process and clean data.
    • Very similar to Lookup tables but with no need to build a table, it allows the normalisation of data in a given field in a number of already maintained MASTER lookup tables inside of Eloqua.
    • Note: You will first need to install the CWM app and go through the configuration steps. 

 

          Use Cloud Connectors

 

      • Contact Data Normalizer: Allow mass normalization of common fields

Example below:

            • Title is VP of Marketing
            • Job Level is Executive/C-Level

 

      • String Manipulation: Allows the use of regular expressions or trim functions

Example: Jon smith – smith is in lowercase.

            • After String Manipulation:
            • First Name = John, Last Name = Smith - Smith becomes Uppercase.

 

Other Advance FIND and REPLACE functions include:

            • Trim extra spaces

 

Update Rule Vs. Standardization Action (CWM App)

The key difference between using an Update Rule vs the lookup action of the CWM app is the level of detail and customization.

 

2.0 Database Checklist

 

Useful Database Checklist prior to automating the Contact Washing Machine. Did you:

 

  1. Create new Contact fields to store normalized Data?
  2. Ensure Cloud Connector setup and access is enabled for the database?
  3. Ensure user account is configured with API user security access?
  4. Ensure the account is created on cloudmarketplace.oracle.com?
  5. Create Lookup Tables based on needs?
  6. Create a Contact Filter to find dirty Contacts?

 

3.0 Automating the Contact Washing Machine

 

Program Canvas is used to create automated workflow's or program builder that can be used to carry out various marketing functions and to cleanse Contact Data. Depending on your requirements, these can be simple or complex workflow's. Below are the elements that are utilized within the Program Canvas for the CWM:

 

  1. Add and Configure Segment(s): Use element to configure entry for all contacts that feed into your program.
    • The two available options to add contacts to a program are:
      • Listener: This program step examines the Eloqua database for changes in real-time, and then pulls the contacts into the program based on the changes. You can pull either new contacts or old contacts that have been updated with a new lead score. Alternatively, you can configure other Eloqua elements to push contacts to the listener step. These sources include: segments, forms, campaigns, programs, or custom objects.
      • Segment Members: This program step pulls and adds contacts from an existing or a new segment to the program. You can also set the frequency of evaluation of this step.
  2. Add and Configure Update Rule(s): Use element to move contacts through a rule set in order to update contact fields or custom object records.
  3. Add and Configure Contact Washing Machine App: Use element for cleansing of contact fields. You are able to define one or more contact fields as inputs, then run actions such as trim, concatenate, adjust case (propercase or lowercase), and perform lookups to populate fields. The data can then be mapped back to that same field or a separate field.
  4. Add and configure the Add to Program: If needed, add any additional processing steps (For example: You may want to route the updated contacts to your CRM integration program or maybe add them to a shared list.)

 

 

Conclusion

 

A Data Cleansing Program is a worthwhile initiative, but only if it leads to a healthier pipeline. The goal should never be just to have clean data, but rather to take action once that data is clean. The CWM has the potential to tremendously improve the segmentation and targeting capability and its overall effectiveness. It could be very difficult to score leads without normalized fields. This is especially true for a lead’s profile score. The program reinforces an automated cycle, ensuring leads from data entry points such as web forms are consistently clean. Other beneficial impacts include:

 

  • Reporting - Increased reporting capabilities on leads or contacts, which will help make decisions on where to invest in the lead generation efforts.

 

  • Strategic persona-based campaigns through better segmentation. Increased capabilities to draw from these personas will drive the way segments are conducted on a database and thus interact with clients or prospects with the goal of increasing engagement and driving more sales.

 

  • Dynamic Content - If you have implemented nurturing campaigns, you understand the importance of dynamic content.

 

  • Routing - When a lead finally hits your scoring threshold, or raises their hand via a high value form-fill, you'll want them to be routed to the correct sales team or person.

 

 

Helpful Marketing Cloud Courses and Blogs

 

  • B2B Targeting
    • B2B: Advanced Segmentation
    • B2B: Data Cleansing
    • B2B: Web Profiling
    • B2B: Custom Subscription Management
  • RPM: Effective Nurturing
  • RPM: Lead Quality
  • RPM: Targeting & Segmentation
  • B2B: Fundamentals of Segmentation
  • Blog Post:

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