Data is what gets you in the door with your customers. Getting to know your buyers’ needs will
allow you to segment users and personalize your marketing campaigns.
However, it’ll be difficult to analyze and manage data if your information is disorganized or outdated.
To be successful at demand generation you’ll need a strong focus on data quality and cleansing data management.
As you interact with prospects over long periods of time you’ll want to ensure you data is clean and up to date.
“An organization with a strong commitment to data quality can produce nearly 70% more
revenue than a company with only average data-quality procedures.” Sirius Decisions
Benefits of Sparkling Clean Data
Why is clean data so important? Here are several benefits:
• Clean data lets you understand your prospects and customers better
• It paves the way for easy reporting of analytics and business intelligence
• It gives you simple segmentation, paving the way for better cohort analysis
• It enables personalization, boosts response rates and improves your communication overall
• It lets you serve up personalized and dynamic content
• It allows you to push back normalized data to Salesforce
• It increase revenue and productivity
“Research found that employing consistent data hygiene will generate 7x
the number of inquiries and 4x the number of leads” Report on State of Marketing Data Quality
The 1st step is to look at where your data comes from and how do you manage the data.
Benchmark your Data Health
Netprospex has researched into hundreds of companies looking at their databases and data.
Effective Data Management
When managing data, you have to make sure the information you have meets the 3 C’s of Data Quality which are:
• Consistent– Are your processes systematic?
Are all marketing automation admin doing best practices and do you have documentation about procedures
• Complete - Are all pieces in prospect database field out?
• Correct - How do I identify incorrect data?
Communication Management
You also need to handle any gaps in communication, such as:
• Bounce backs - how you handle this?
• Subscribed / unsubscribed – through subscription management center
• Active / Inactive - IE 20%+ active open rate. Less than 10% open rate inactive
Marketing and B2B Demand Generation go hand in hand, this study shows data quality is one of the bigger challenges
The Marketing Automation is owned by marketing and Salesforce or CRM most often by the sales team, this makes a
bigger task to normalize data for marketing when sales see no benefit for themselves in hindsight.
Owning the entire data quality and management to create a strong data quality culture is marketing task primarily.
How to Handle Missing Data
Don’t upload entries with missing data to your marketing automation database.
Missing data in lists from trade shows, paid marketing, partners, bought lists,
and data mining should be upgraded before being entered in to the system.
To avoid dealing with too much missing information, set your marketing goals well before you start collecting data.
For example, if you’re looking to personalize your online campaigns, then you’ll need the user’s name,
email, job title, industry and content of interest. On the other hand, if you’re planning to do direct mailing,
you will have to add each user’s street address to your forms and data collection procedures.
To make things easier,consider hiring an outsourced team to upgrade data or capture / append
data from 3rd party applications or you can do progressive profiling (to ask incremental questions
on missing data in forms). When doing manual uploads into Eloqua make sure complete data is imported.
There is a Progressive Profiling class in Eloqua University.
Problems Caused by Dupe Leads
Duplicate leads can build up over time in your instance of Eloqua and Salesforce.
1) Inaccurate lead scoring. Causing you to miscalculate your Marketing Qualified Leads (MQL).
And for your sales team to never receive some leads that are MQL, since they don’t hit the score
threshold to be assigned to salesforce.
Hot leads will be left behind in Eloqua and theywill not be followed up by sales,
which will make you miss revenue on people that you “could have” closed.
This (duped) lead will never be seen by the sales team.
Lead 1A: 20 points
Lead 1B: 15 points
IE MQL = 40 with 0 min and 100 max.
2)Inaccurate Analytics Minor skewed open rates making them slightly lower.
3)Paying more for Eloqua as you keep adding up bad contacts.
(Eloqua charges by # of contacts in the system at different levels)
Normalizing Data
You can’t score, segment, or route leads if you don’t normalize or standardize your data so be sure
to take the steps to do so. For instance, when dealing with the data point “Job Title,” you may encounter
up to 15 choices; if you don’t normalize that data, you might end up with over a thousand job titles
in your Eloqua database and encounter difficulties in segmenting users.
Examples of data that you need to standardize include:
•Geographic- Country, Zip, City, State, Region
Documentation to Improve Data Quality
This documentation will help you remain consistent and help other Marketing Automation stick to the best practices.
• Lead Routing Doc
• List Upload Doc
• Field Mapping / Field Views Doc
• Standardized Data Set Doc
• Naming Convention Doc
• Lead Scoring Doc
• Data Dictionary Doc- all data you plan to collect and utilize as a company
etc
Conclusion
By taking these steps, you’ll be able to ensure that your data remains clean.
This, in turn, will improve your marketing ROI and help meet your company’s goals.
“It takes $1 to verify a record as it’s entered, $10 to cleanse and de-dupe it and $100 if nothing is done,
as the ramifications of the mistakes are felt over and over again.” SiriusDecisions
Additional Resources:
Example Standardized Data Value and Set Template
Eloqua Topliners Normalization Forums Section
Eloqua Topliners Contact Washing Machine Section
Eloqua University
RPM: Targeting & Segmentation (3 Hour Webinar)