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We have had a lead scoring program running in program builder for several years now that was built in our previous E9 instance.  It seems to run smoothly, however the criteria is a bit lax and sales has told us that a majority of the leads that are being sent over are still too early in the buying cycle. After DNB made it through the transition to E10 in December of 2013, we wanted to revisit the criteria and utilize the E10 lead scoring module to see how it compared, both in terms of ease and reporting. We were able to do this, but <spoiler alert> this story is still doesn't have a complete ending just yet.  However, we have gained enough insight into our database to prove our point.


Below is a report of our lead score distribution as it is from the program builder program. We are hoping that by revisiting the criteria and recreating our model in the new module, we will reduce the number of contacts in the upper left quadrants (A1, B1, A2, B2, etc) so that we can continue to nurture those that are still making their way through the funnel.

After careful review of our business requirements, we decided to make a few changes to our scoring criteria in order to simplify from our existing program builder program. We removed criteria that checked to see if the account included a current customer or is in an existing agreement.  We also deemed it unnecessary to have a field that checked whether the contact’s role matched their title (i.e., the decision maker was a director or above).  We kept the basic metrics for title and our other criteria, but did have to make small updates based on the way the calculations are done in the new module; i.e., the scoring for titles were given a per cent of the weight instead of a certain number of points.  We also had to change the way we accounted for some of the titles within the model.  For instance, in order to not discount any of the multiple C-suite titles that are appearing today, we changed "contains" "CEO, CTO, CFO..." to "matches wildcard pattern" "C?O"


We have four main segments in our business, each with different sets of criteria that have been built into our program builder program (sales and marketing, risk, supply and general).  The biggest shift in our design for the E10 module is that we originally wanted to keep utilizing one model which would include all four segments.  However the main difference in criteria between each segment is the weights and % of the available score that we attribute to titles. In the new module, we are unable to assign different scores to the same title for different segments within a model, so after consultation with our account manager, we decided it best to build four different models.


I took the "Eloqua 10: Lead scoring" class in Eloqua University for the second time as a refresher right before I started this initiative. With the help of this class, I built all 4 models in the module with no hesitation. The class taught all of aspects of both best practices of lead scoring as well as configuration.  Once all the requirements were agreed upon, it took me hardly any time at all to construct all four modules.


Based on the insight reporting after activation, the new scoring module and criteria has greatly decreased the number of high scoring contacts!   A1’s went from 481 contacts to 71 and B1 from 705 to 176!  Below is an insight report of our main model for comparison.

But, as I said our story doesn’t have a true ending.  While we were in the process of building this out, our company hired a new CMO and at this time, our models are being reviewed to ensure sales, marketing, and our c-suite is in alignment.  Therefore, we have not set up the final integration with SFDC for these contacts to be sent to sales.

Despite not having true closure, we are optimistic that we will be able to move forward. After reviewing the contacts in the reports, they appear to be high quality leads.  We hope to test it by sending over the A1’s from this report to a team in sales to determine the lead quality.

So we can wait on the edge of our seats for the final conclusion…da Da DA


Marketing needed to prove their value to sales and drive enough "Qualified Leads" by tracking and presenting analytics and KPI's on a monthly basis. The task was to increase qualified leads or MQL and report on key analytics by using Eloqua (E10), as well as developing and maintaining an agreement between marketing/sales for MQL, SAL, SQL and lead scoring.



To reach revenue targets with Eloqua by hitting a preset amount of qualified leads as well as gaining the ability to predict the amount of qualified leads that can be driven that will be attributed as lead source to marketing originated.  Predicting qualified lead and revenue with Eloqua can help marketing request more budget and improving marketing spend - meanwhile keeping sales happy.


Benchmark or document current state:

We needed to define what Qualified lead was for each of our lead stages. We used revenue, lead source original to see lead originating from marketing,opens, clicks, form submissions, and explicit feedback from sales.


Strategic Initiatives:


1) By using best practices taught by Eloqua University to score implicit and explicit information in prospects, we setup lead scoring in Eloqua with a low of ZERO and max of 100.  Marketing Qualified Lead (MQL) was at 40.  Marketing collaborated with sales on what are the key determinants in making a sales lead ready. Once lead scoring was set in Eloqua, we used Eloqua's Closed Loop Reporting and Analytics to prove Marketing Value and Display Key Performance Indicator's on a regular basis.


Lead source original and lead source most recent was used to track were leads originated from and calculate Cost Per Lead MQL to see which marketing channels were performing best.


KPI's =

  • Revenue
  • MQL, Cost Per Lead per MQL
  • Lead velocity model of drop of each lead stage to stage (IE MQL to OPP, MQL to close, MQL to SAL)
  • Conversion rates
  • Lead score
  • Funnel Metrics by Marketing Channel


Tools used to collect and report on KPI's =

  • Eloqua + Analyzer License
  • Salesforce
  • Google Analytics
  • Excel
  • SQL
  • Eloqua University Training


2) Our main strategy was having interesting or great content backed by the core channel of driving it with Eloqua's Email Marketing—since Email Marketing is the lowest cost to reengage your prospects at best value to your website.  Eloqua's Closed Loop Reporting (CLR) and Eloqua advanced prospect tracking methods were used to track a buyer’s long journey.


3) Because sales would complain that leads were being routed wrong or are duplicates, we setup standards for importing data in Eloqua and cleaned up our current database as well as improved data quality.   Another step we took in tackling this challenge and per Eloqua University’s tip’s is to stop buying lists, data normalization and much more.


We focused on having topics or content that the buyer would be interested in hearing early stage focusing on informational content. This was taught in the Eloqua University RPM courses, which taught demand generation best practices.


Key Take Aways

  • Email Marketing and great content is the best way to drive qualified leads at lowest cost on your current database.
  • Eloqua is not just for emails, but a good way to prove marketing value to sales and predict revenue / qualified leads.
  • Data Quality is important and Sirius Decisions says companies with strong data quality drive 7x qualified leads.
  • Proving marketing value to sales and the c-suite is important and Eloqua provides KPI tracking that will show marketing value.
  • Lead scoring should be setup to have both implicit/explicit and minimum / maximum to keep scores from becoming inflated.
  • Eloqua is only as good as the people and processes that use it.


Key Impacts or Results

We were able to track and show how many MQLs marketing generated based on a month-to-month or quarter-to-quarter segmented metrics. Money spent per channel now had ROI tracking, enabling us to stop spending money and increase accordingly. Having strong data quality standards and processes facilitated the ability to gain clear insight into our reporting.




Things we would have done differently


  • Building Engagement Streams of recycled or inactive leads.
  • Stronger standard on data import into Eloqua to ensure good data is being imported with a system of check and balances.
  • Set SLAs with sales on how long things take to be done to manage their expectations. IE event list upload, ad hoc campaign runs.


Helpful Eloqua University Classes

These classes below were helpful in learning about best practices of demand generation and of setting up Eloqua.

Eloqua 10 Lead Scoring

Eloqua 10: Closed-Loop Reporting

RPM: Introduction (WBT)

RPM: Targeting & Segmentation

RPM: Lead Quality

RPM: Effective Nurturing




Was a great help when looking for ad hoc information when running into day to day challenges of administrating Eloqua. And finding documentation on Best Practices. And how to integrate Eloqua with Webex (webinar tool) and other apps.



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