Data Clean House

Every marketer knows that an inaccurate, inconsistent or out-of-date database decreases campaign effectiveness, but solving the problem is no simple matter. This award recognizes organizations that have made clean and accurate data a strategic priority – and have seen that investment pay off with higher conversion rates, more opportunities, bigger deals and increased ROI.

Blue Coat Systems Data Clean House (2013)

Bluecoat’s data restructuring effort showcases how sound intelligence is a pillar supporting not only operational initiatives but the broader corporate vision. Relentless and focused attention on data, transformed Eloqua into a more efficient and scalable data engine enhancing lead conversion rates and increasing sales productivity by 20%. Setting up Eloqua and its ecosystem to work optimally, has helped in increasing the marketing qualified leads volume by 25% which as a result has helped in increased marketing sourced pipeline. With 85% contact profile completeness, the centralized and standardized marketing database is invaluable to Blue Coat’s ability to exceed defined targets. Blue Coat recently acquired three companies, bringing in data from different platforms but the solid data framework enabled us to seamlessly integrate this information surge in record time.

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Domo Data Clean House (2013)

As a business intelligence company, Domo values data. However, bad data plagued and hindered our marketing and sales efforts, specifically a new education nurture campaign that was dependent on reliable data and field completeness. With a renewed commitment to clean our database, marketing and sales rolled up our sleeves, identified and deleted junk data from Eloqua and Salesforce.com, built an entirely new contact washing machine, standardized field values, decreased blank fields, and established a lasting process for better data management at Domo.

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inContact Data Clean House (2013)

Data quality is at the heart of any One View of the Truth program for collaborative business intelligence between Marketing and Sales.  To ensure the integrity of its program, inContact carried out a data cleansing overhaul.  The project involved aligning goals between Marketing and Sales, leveraging the expertise of Eloqua’s Expert Services, and utilizing sophisticated application of Eloqua’s program builder and Cloud Connector Apps.  The project resulted in 47% increase in data quality, 73% reduction in lead qualification times, and 75% more opportunities.

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Snagajob Data Clean House (2013)

Prior to getting our Eloqua instance up and running, we worked to clean up our CRM database in order to ensure that we were putting only clean data into the Eloqua database once we were implemented. Additionally, we created rules and processes around what information could be added either directly into Eloqua or into our CRM. This has dramatically helped us ensure that we maintain our CRM and Eloqua databases, and provides us a “clean in, clean out” philosophy for our data entry.

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Ariba, an SAP Company Data Clean House (2012)

Data is the foundation of all Ariba’s marketing and sales processes. Our bad data was costing us significantly, resulting in poor productivity, misaligned marketing and sales teams, lost leads, broken trust, and lower conversions and response rates. Our commitment to better data management and cleanliness enabled us to not only improve these areas,  but to also instantly generate hundreds of new MQLs and make an impact on driving net new subscription software pipeline, thereby proving the importance of maintaining a clean database. We also achieved our end goals of implementing a new Sales and Marketing funnel, Lead Scoring, and Lead Management process.

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Iron Mountain Inc. Data Clean House (2012)

Consolidated data into Eloqua from 4 different data sources saving over $125,000/year in maintenance and support and making Eloqua the system of record for all Marketing data.  Eloqua data now links Marketing, Sales, and Billing information in one place to get a 360 degree view of customers and allows more focused segmentation.

In addition to “typical” data washing machine programs, we  implemented a real-time D&B integration to dynamically cleanse and enhance records as they enter Eloqua, a zip code normalization cloud connector to allow for state validation and real time territory mappings.  The increased usage of internal data also generated additional savings of $40,000/year versus purchasing lists from external vendors.  Better utilization of current data has also increased our response rates by 2% overall.

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Motorola Solutions Data Clean House (2012)

Motorola Solutions put significant effort into data clean up this year through implementing several in-house developed Eloqua contact washing machines. Although our marketing communications are focused on specific Industries, Job Functions and Organization Levels, many of these fields had incomplete and non-standardized values. The contact washing machines standardized values and decreased blank and “Other” values from 46% to 34% for Industry, 85% to 68% for Job Function, 85% to 41% for Organization Level and decreased blanks for country from 68% to 29%. The more complete and standardized data allows for more accurate lead scoring and better segmentation for nurturing programs.  After efforts to clean up data, we have seen a 31% increase in qualified leads passed to the sales team and 85% increase in pipeline value.

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Synopsys, Inc. Data Clean House (2012)

Synopsys has been using Eloqua for over 4 years, and in that amount of time any database would become polluted with bad lead and contact data as well as inactive legacy programs, filters, groups and lists. Combine that with multiple people who control the database with different strategies going in and out of the role, you get a very messy, almost unusable database. To correct this we understood that we had to start from the foundation up and take care of the basics at the database level, removing old and unneeded fields, creating a naming and organization structure for email, list, and asset names, archiving old emails, and archiving and removing old programs. Also we revised our strategy on our database management by including a contact washing machine that allows leads to get clean and normalized even before getting into Eloqua.

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Autotask Corporation Data Clean House (2011)

For years we used Eloqua as a blunt instrument of torture for our customers and prospects: we sent everything to everyone, over and over again. And, thanks to the law of large numbers, we were seeing results – but it simply wasn’t sustainable, it wasn’t an effective use of the tool, and we were eroding the value of the contact database we’d worked years to build. Not because we wanted to, but because we weren’t spending the time we needed to ensure we had the good, clean, actionable data required to target, segment and pace our communications to match the needs and interest of our contacts. In early 2011, we recommitted ourselves to understanding the power of Eloqua and how we could better use it to deliver more meaningful messages to the people who wanted to receive them, where and when they’d be most effective. And, while it took a little pre-work and education, the results have been outstanding on every level.

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McAfee Data Clean House (2011)

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!

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National Instruments Data Clean House (2011)

Email activity filters have played a huge role in our ability to clean up our contact lists.  We were excited to be able to utilize the new Eloqua activity filters throughout this pilot.  We knew that this would be the beginning of establishing a best practice of tracking our engaged contacts, via our email channel, and developing nurturing paths to help reengage them before they drop off.  We also knew our limitations with contact preferences on our site, and hoped that we could get our prospects to update their user profile (the main CTA) so we could provide them more relevant information.  And, this would hopefully reveal important data points to help support the business case for more robust contact preferences. Regardless, this would be a massive clean-up effort for our inactive prospects via email, giving us greater visibility of the performance of our projects.  Without Eloqua activity filters, Blind Forms, Contact Groups, and Program Builder, we would not have been able to implement this strategy.

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New Hope Natural Media, a division of Penton Media Data Clean House (2011)

In less than a year Eloqua has helped this division revitalize its email database and position it to rapidly move forward.  Our audience is more engaged with targeted communications and content and the investment in Eloqua and implementing automation is already paying off.

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