Presentation Transcript

1. Data Quality: Better Segment Your Data for Optimising Reach Tejneet Chowdhury, Eloqua
2. What are we going to cover? Why data quality is important? Practices to keep your data consistent Contact Washing Machine Data Append w/ Cloud Connectors Final Thoughts Questions
3. Why is data quality important?
4. Why is data quality important? “ 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 ”
5. Why data quality is important? Poor data quality affects every part of the organization not just Sales and Marketing Data is everyone’s responsibility and should be treated as a corporate asset to achieve better business results and marketing effectiveness
6. Question The Data Warehousing Institute research program found poor data quality was costing US businesses how many dollars? $600 billion
7. How can poor data affect the business? Marketing Productivity Marketing & Sales Alignment Customer Analysis Lost Trust (with the prospect/customer) Bad Reporting
8. Practices to keep your data consistent
9. Preventionis better than cure. 1 - 10 –100 rule €1 to verify record at source €10 to cleanse & de-dupe later €100 if nothing is done
10. “ A strategy that solves conflicts at the source can lead to a 25% increase in converting inquiries to marketing-qualified leads. ” -Sirius Decisions
11. Practices to keep your data consistent Standardized Data Sets define and document a standardized data set where master systems of record are clearly identified and all stakeholders agree work with IT to establish a data field dictionary
12. Practices to keep your data consistent Forms Drop-Down Menu, Radio Buttons or Check Box limit the use of free text fields free form text cannot be reported on, scored on or used for segmentation in a consistent manner this will ensure data consistency
13. Practices to keep your data consistent Validation Rules on Forms set form fields that are primarily used for segmentation as required fields phone numbers, postal code, account ids etc… can be set to have a specific number of characters
14. Practices to keep your data consistent Try Social Sign On! Capture better data Capture more data Provide simple sign on option Build social identity Use social ID to track your prospects across social channels Is Social Sign on appropriate for your audience?
15. Practices to keep your data consistent Use pre-populated form fields to validate and confirm data that you may already have on an individual. Note: it is not a best practice to pre-populate based on cookie alone Leverage a Progressive Profiling approach or a Preferences Management center with forms to obtain valuable new data and achieve profile completes.
16. Eloqua Markies Winner 2011 – Clean House “Getting leads to the CRM system with dirty, unusable or incomplete data is like eliminating lead scoring and lead nurturing all together –because there is no sowing to the marketing seed. But with a few data cleansing processes, McAfee was able to impact the number of leads we sent to sales. Even more importantly, we saw in increase in the number of leads sales accepted. Cleaner data can earn you bigger money!”
17. Contact Washing Machine
18. Contact Washing Machine – what is it? Adata cleanliness program that standardizes and normalizes data within a B2B marketing platform Any new contacts should be added to this program first before being sent to your CRM system
19. Contact Washing Machine – what can it do? Standardize Title to allow it to be used for Segmentation or Scoring Standardize Country to a 3-letter or 2-letter code Map to sales (or field marketing) territory Validate physical address (if you'll be using this)
20. Contact Washing Machine – what can it do? Match company to existing company list (or use a standard code such as DUNS) Map industry to SIC (Standard Industrial Classification), NAICS or other industry code (if this is important for you) Any other data standards or fields that are key to your business
21. Contact Washing Machine - tools Update Rules examine your data using the ‘view field population details’ based on this information create a list to match and update to a standardized value e.g. Title - "Chief Operating Officer" to have a normalized title of "COO”
22. Contact Washing Machine - tools You can use wild cards in Update Rules to standardize your data e.g. Chief Op* or *manager*
23. Contact Washing Machine - tools Lookup Tables ability to upload a 2 column data set to match against and update field values e.g. If State/Province was missing from a contact record we could use the postal code to lookup against a data set to fill the gap Lookup Tables are called from an Update Rule Upload values using a CSV file
24. Question How many different job titles did Eloqua have in its system before we standardized? Of these 15,000 how many were unique? 13,000
25. Data Append w/ Cloud Connectors
26. Data Append w/ In order to complete a profile, and have a high quality database, you need to add missing data to any incomplete records. And missing data comes from a variety of sources – 3rd party, internal sources or from the contacts themselves.
27. Data Append w/ Cloud Connectors - apps that exchange data with another application and integrate with Eloqua passing data into the application. it can be called from Program Builder and Campaign Canvas
28. Centralized market of apps available to Eloqua clients Resources to find information and app installation instructions
29. Data Append w/ Examples!
30. Data Append w/ Examples!
31. Eloqua Markies Winner 2011 – Connecting in the AppCloud “Progress Software has struggled with the overall quality of data on new leads for some time. Incorrect lead assignments and the time involved to accept highly qualified leads have impacted how quickly we can connect to new prospects. The Eloqua D&B Cloud Integration program allows for us to append new records with relevant, trusted data from D&B and not have to solely rely on raw form submission data and lists. This data has enabled us to more accurately score records and set thresholds in our integration with SFDC so that our salespeople are focused on the most important and highly qualified leads first. In a two-month period we recognized a 12% increase in number opportunities, a 36% increase in total opportunity value, all while decreasing the number of leads created by 20%.”
32. Final Thoughts
33. Final Thoughts Keeping clean and consistent data: improves targeting with more accurate, robust segmentation filters perform more accurate lead scoring to improve the quality of leads improve your response rates with better personalization and getting the right message to your recipients reduce operating costs with improved customer data
34. Last quiz, I promise! Who owns responsibility for data quality? IT Marketing Ops Sales Ops Governance Council All of the above
35. Thank you for being a part of the community!