It’s no secret that nowadays data plays a pivotal role in how organizations plan their strategies, get to know their audience, and ensure their success. Processing your data cannot be more crucial, as with great amounts of data come great amounts of challenges: the multiple number of sources, the possibilities of spam or junk data, incomplete or inaccurate data and so on. Therefore, your data may lack purpose if left in its raw form and can only gain value if it’s coupled with other significant data, and if the extraction methods are connected to your final purpose.

The responsibility that comes with data

Basically, data is an entity which, if interpreted correctly, brings a lot of benefits to the table, and that is because data shouldn’t simply reside in a silo, but must be paired with powerful tools that will get the best out of it. Some of these benefits include: enabling you to set up strategies with the ultimate purpose of customer satisfaction; the possibility of personalizing your products and services so they meet your customers’ needs; the ability of improved sight – you can see the causes of past miscalculations and foresee obstacles before they occur.

Data cleanliness is not optional

One of the methods for achieving interpretable data is data cleansing. It consists of identifying and removing information from your database which proves to be irrelevant, unnecessary, in the wrong format, or simply incorrect. Along with other best-practice methods, data cleansing ensures accuracy and consistency in your data preparing process and gives your marketing efforts the necessary cohesiveness to ensure customer satisfaction.

You can get creative while setting up your process, as long as you define clear and efficient steps that every member of your team is aligned to. Once every person who works on your data cleansing processes understands the final target and is up to date with the relevant particularities in your database, you can start reaping the fruit of your labor:

• build powerful personalized content based on clean data;
• better control multiple data sources;
• reduce the risk of errors;
• report on relevant data only without having to filter out the junk information every time you want to analyze your marketing efforts, thus making perfectly educated decisions.

On the other hand, the consequences of incoherent data funnels are not to be neglected:

• Inaccurate data which leads to marketing inefficiency;
• The inability to report on relevant data, therefore the impossibility of trustworthy decision making;
• You become paralyzed in a state where you fight for the survival of your database;
• Ultimately, customer dissatisfaction and loss of revenue.

In order to ensure data coherence, applying some ground rules is a must and these regulations need to be configured as soon as you start setting your database up. Some of these rules might include:

• 1. Setting the type for your form fields so they reflect the accuracy of the data required. For example, the Country field could be a picklist out of which the persons who fill in the form can pick a predefined value, instead of going for the free text field type which increases the risk of unstandardized values. The said risk is a great one as this way of capturing data makes further targeting very complicated. I.e. whenever you will try to send a communication to people located in the United States, you might have to struggle with sorting out people who filled in their country as US, U.S., United States of America, and so on.
• 2. Properly mapping the Field Names between your database and the sources where you’re importing the data from.

How to – the Eloqua way

While regulations like those mentioned above are mandatory for a healthy database, dirty data might still find its way in, especially if you’re dealing with many data sources. CRM integration, for example, is a common relationship found in MA databases, and the data that comes in this way isn’t always 100% predictable.

For this kind of situation, having a data cleansing program set up allows you to breathe easy, knowing that whatever comes in will be looked upon by this program and will further be triaged accordingly.

Curious to see what a data cleansing program would look like? I will show you how to set one up in Oracle Eloqua, one of the most powerful marketing automation platforms to date.

1. First, open the Programs tab, and create a new program:

2. Next, add the required elements to the canvas:

While there are only two elements on this canvas, this is what most of the data cleansing processes can be narrowed down to in Eloqua.

3. Configure your elements:

a. Set your Listener step to listen to newly created contacts. This way, whenever a contact is being created in your database, it will enter this program. This means that you do not need to schedule your program to run at a specific time, because the Listener step will serve as a trigger point which will keep feeding contacts to the program as long as it is activated.

b. For the Update Rules step, you will first need to configure two data tools: a lookup table and an update rule.

i. From the Audience tab, go to Tools, then Data Tools

ii. Then, create a new lookup table:

iii. Fill in the required details:

iv. Finally, upload an Excel file containing two columns: one for the erroneous values, and one with blank values, as our purpose is to delete any anomaly, as below:Finally, upload an Excel file containing two columns: one for the erroneous values, and one with blank values, as our purpose is to delete any anomaly, as below:

Our goal here is to check any new contacts against the first column of the lookup table. In case the field that we are performing the check on is found in this column, it will be replaced with the corresponding value from the second column (it will be deleted). But for us to be able to employ this lookup table, we need to create an update rule that will put it to action.

v. From the same tab, create a new update rule:

vi. Give it a name and set the conditions on which it will run. In our case, it needs to look like this:

4. Now that our two elements are ready, you can configure the Update Rules step on the canvas, link it to the Listener step, then activate the Program:

Tip 1: Use the Contact Washing Machine cloud app to expand the possibilities of your efforts. Among other options, you can use its RegEx capabilities to better target the anomalies in your database. For example, you can use this functionality to find First Name values that contain any number characters or any repetitive characters of 3 or more:

Tip 2: While the above method is designed to cleanse any anomaly found in the new contacts, you also need to approach the already existing ones. For this, constantly auditing your database is necessary. You can build a segment aiming to find all the non-standard values within certain fields in your database, as shown below:

Next, you can add an update rule that will set these contacts’ Country values to blank:

For all the Marketo enthusiasts

Similarly, a data cleansing program can be created in Adobe Marketo, one of the most popular marketing automation tools, and we’ll show you how in just a few easy steps:

1. After logging into your instance, access Marketing Activities, navigate to the folder where you want to have the program created, and create a Default Program.

2. Under this program, create a Smart Campaign, then go to the Smart List and add the Person is Created criteria so every newly created person goes through the program:

3. Next, go to the Flow tab, choose the Change Data Value step, and configure it according to the fields that need to be reviewed:

*In my example, I am targeting non-standard Company Name values, and I am setting the matching ones to blank. Feel free to either add multiple steps for different fields that you wish to interrogate. 

4. Finally, go to the Schedule tab to activate the campaign. Since it’s a trigger smart campaign, it will start any time someone qualifies for the smart list criteria.

5. If you wish to do this for the already existing contacts, there are multiple options out of which you can choose, thus you can get really creative. A simple one implies targeting people whos’ field values are not blank, and then apply the same flow step.

What's left after there remains nothing to clean?

As soon as the unnecessary data has been cleansed, you can further fill in the gaps with relevant, corrected information. The perfect way to do this is by automating solid processes which eliminate the human risk and aim for data completeness. Such processes could include:

1. Enrichment programs – you can use your existing data to fill in related information. E.g. you might be able to determine the State value if you know the City of a contact.

2. Progressive profiling – If you’re sending out a form to be filled in by contacts who already submitted it before, try to include different form fields instead of the ones that they already submitted so you find out more information about that person.

3. Nurture campaigns – target the contacts with missing information in a series of scheduled emails with the purpose of filling in the cleansed data.

Final Thoughts

In the competitive landscape of digital marketing, data is a key asset that can either propel a business forward or hold it back. Data cleansing is essential for ensuring that the data used in marketing automation is accurate, relevant, and reliable.

Pair data cleansing with other methods such as data standardization, normalization, and enrichment to level up your database to its true potential, relying on the true power of quality rather than the appeal of quantity.

Lastly, use powerful reporting tools such as Eloqua Insight to have a sound perspective on your data’s performance and stay at the top of your game by making educated, customer-oriented choices.

If you believe your data could benefit from this approach, contact us. Our expertise will save you time and help you maximize the benefits of marketing automation without the hassle.