A recent Eloqua blog feature by Jennifer Horton criticises the use of ‘vanity' performance metrics by sales and marketing professionals. She argues these metrics lead to complacency, since although they are non-actionable they may provide a misplaced feeling of purpose, worth and job security.
Commenting that the only performance metrics worth considering are those that drive business results and real revenue performance, the feature then defines types of ‘vanity' metrics to beware of. These include:
- Metrics taken out of context - For example, a statistic of 50,000 web visitors to a website in a single month is meaningless unless that figure is put in context. There may have been more visitors the site in the previous month, and there is no data on either the source of those visitors or whether those visitors became customers.
- Metrics that emphasize volume - It is argued that volume as an absolute can be very misleading in terms of getting to actionable intelligence, with ‘Total Influenced Revenue' metrics being singled out in particular.
- Metrics that are easy to report, yet provide no worth - Ignoring important metrics because internal process changes are required or because they would take time to implement could cause the loss of potential opportunities. Sales and marketing professionals should ignore these ‘easy to report' metrics in favour of working towards measuring metrics that matter.
The feature concludes with a strategy for attaining ‘actionable' performance metrics at the expense of ‘vanity'-driven metrics. In this context of providing bona fide, actionable metrics,
Prospectvision's sophisticated Behavioral Inference Engine (BIE) provides an ideal tool, enabling unique insight into the visitors to a website - who they are, and what they are looking at. Effectively, the Prospectvision tool identifies and separates 'serious' potential customers from casual website visitors, allowing targeted action then to be taken.
There are four strands to the strategy for attaining ‘actionable' performance metrics:
(1) Problem: the problem should be articulated in the form of a question. Instead of saying - We didn't hit our sales-accepted lead target this quarter, consider - Why didn't we hit our sales-accepted lead target this quarter?
(2) Context: Identify relevant metrics that help complete the story. There should be analysis on conversion and acceleration by campaign and campaign type, etc, as well as analysis on scoring program model and output.
(3) Hypothesis: Propose a possible answer. Downloads of customer case studies is not a high-value buyer behavior.
(4) Test: Document how to prove or disprove. Run a pilot of an adjustment to your scoring model with a sales team to determine impact to sales acceptance rate and sales-accepted lead volume next quarter.
It is concluded that sales and marketing professionals are not in the business of measuring campaign and funnel performance to make themselves ‘feel good day in and day out'. Instead, they are in the business of identifying and moving the levers that drive revenue and business results - resulting in true Revenue Performance Management.
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