Optimize Demand Generation Through A/B Testing
Sales and marketing leaders have come to appreciate the positive impact that modern digital marketing has made on lead generation. But somewhere along the line marketers became hyper focused on click metrics. Far too often the science of A/B Testing has been lost in the late 1990’s along with your VHS Tape of the movie Braveheart. The discipline of testing was abandoned for the new romance of digital click metrics that finally closed the loop on tracking. The capability loss of formal testing has left marketers with limited ability to fine tune programs through a reliable approach.
Why A/B Testing is Crucial to Demand Generation Success
Lead Generation teams work to drive inquiries into the top of the funnel. Optimization is often performed primarily through click metrics. Click-through rates, conversion rates, and cost per lead are commonly used as fine tuning points. This is short-sighted for two reasons:
- The ultimate success metric should be focused on the cost to generate Sales Ready Leads viewed in context of their conversion to qualified Opportunities for the sales force. The Lead Gen developed Opportunties should be tracked on through to Wins. All other metrics are interesting, but not primary. The goal is not to drive the cheapest leads, but rather the efficient production of qualified leads that drive revenue. It's all about net new logos and upsell to existing customers --- forget the clicks as the focus. Demand Generation teams should focus on these metrics:
- cost per qualified Sales Ready Lead
- conversion rate of Lead to Opportunity segmented by source or mode (Email, direct mail, social media, field event, etc.)
- lead generation contribution of revenue as a % of the sales funnel, and as a % of wins
- Secondly, A/B Testing methodology is used to improve response and conversion rates. Too many marketers take a one dimensional look at click metric performance without an understanding that the performance has not yet been optimized.
Demand Generation teams that don’t leverage A/B Testing are making a tremendous mistake. Challenge your team to get back to the basics of continuous improvement. Embrace the methodology of Demand Generation A/B Testing.
Methodology of A/B Testing
Let’s start with definitions of basic testing terminology:
- Control – Most successful previously used effort
- Test Cell – Segment receiving a different approach
- Roll-out – Continuation of demand generation efforts
- Statistically Valid Sample – Adequate quantity to ensure predictability of test
A/B Testing is simply the run-off between two versions to declare a winner. The ‘A’ version is the Control that represents the most successful previous effort. The ‘B’ version is the new alternative that is identical with the exception of a single variable. This discipline of a single variable produces a clear winner with an undeniable cause and effect.
The following is a visual grid of a demand generation campaign with A/B Testing with email and direct mail: Download a PDF
Initial testing is performed with Test Cells of smaller list or audience segments to decrease risk (Note: See the bottom of this blog post for advanced direction to calculate statistically valid sample size). Webinars and high-value tactics that are used in low quantity shouldn't be ignored. Testing should still be performed to capture trends that can be used as qualitative experiences to optimize.
A series of smaller tests make possible test results across multiple variables to provide feedback on a variety of options. The end result is a fine-tuned demand generation effort.
The aspects of demand generation that should be tested include:
- List or source
- Offer (White paper vs. Webinar)
- Format (Email text vs. HTML, Direct Mail self-mailer vs. envelop)
- Message and Creative
Once testing has been completed, a Roll Out occurs with the metrics of success fully optimized.
Anatomy of a Best in Class Demand Generation
Best in Class demand generation efforts are executed from a strategic marketing plan. The plan includes:
- Campaign - series of marketing programs that support an overarching marketing objective.
- Programs – marketing activities that are grouped together to achieve a specific objective
- Activities – specific marketing tactics that deliver an offer, communicate a message or build awareness.
In summary, challenge your lead gen team to embrace A/B testing. This approach will drive sound discipline that increases the efficiency of acquiring Sales Ready Leads.
Are you seeking additional ways to drive continous improvement? Demo SBI's Sales Productivity Benchmark reports:
APPENDIX: Advanced Demand Generation – Statistically Valid Sample Size
The size of a Test Cell requires a Statistically Valid Sample. There is conventional thinking that 10% is a good rule of thumb for a test cell. This is simply not true as the validity depends on the response rate anticipated, the confidence level desired, and the total size of the audience. When working with sufficient quantities, the following test can be performed:
(Confidence)2 x (Estimated Response) x (1 – Estimate Response) / (Sampling Error)2
90% = 1.64 standard deviations
95% = 1.96 standard deviations
99.73% = 3.0 standard deviations