How to Use an Index to Measure Page Testing Success
This session debunks the old adage, "select and test just one measure of success." Specific to B2B marketing, it's not that simple - multiple touch points and long sales cycles mean "success" can't accurately be captured by just one metric. The answer? An index that gives a differing value point to each conversion point. See how one marketer has realized great success from this system in both paid and organic search campaigns.
* Tami Dalley, Director, User Experience Optimization, ROI Labs
26. 7/9/2010 21 What Is It? Assigning value to behaviors for “assists.” Home Runs: 18 Home Runs: 15 Runs Batted In: 66 Runs Batted In: 103 Which player is more valuable to you? *
42. 7/9/2010 32 The Process Step 1:Identify online behaviors that reflect engagement (and correlate with leads or sales) Step 2:Confirm correlation, assign value and calculate the weighted metric Step 3:Optimizeusing this weighted metric “point” system
Incrementally improve campaigns that have already been optimized using a single measure
Incrementally improve campaigns that have already been optimized using a single measure
Vacation exampleTrue for landing pages - a LP needs to do so many things. Not just for internal stakeholders but for consumers at totally different point in the shopping cycle. So who’s right? Well everyone is… but how do you address the problem?
Balanced View of Success – not one dimensionalhttp://www.istockphoto.com/stock-photo-11846527-balancing-stones.php
Better optimize for multiple desired outcomeshttp://www.istockphoto.com/stock-photo-3470760-blank-signpost.php
Incrementally improve campaigns that have already been optimized using a single measureAston Martin DB9 - $289K. Pretty good street car – “how can we make it better?” There is always more you can do…
Long Sales CyclesConsidered purchasesEducation goals?
Multiple possible outcomes from a single path
Integrate offline data or data from other sourceshttp://www.istockphoto.com/stock-photo-713960-bridge.php
These are obvious online examples
Ideal - (Omniture GENESIS integration w/sales force. Call tracking integration - Need a unique identifierOffline SalesCRM Call centreValidation:Contact correctInterestDecision 1:Option 1) Tie secondary conversion to offline salesOption 2) Tie to online leads
Ideal - (Omniture GENESIS integration w/sales force. Call tracking integration - Need a unique identifierOffline SalesCRM Call centreValidation:Contact correctInterestDecision 1:Option 1) Tie secondary conversion to offline salesOption 2) Tie to online leads
Ideal - (Omniture GENESIS integration w/sales force. Call tracking integration - Need a unique identifierOffline SalesCRM Call centreValidation:Contact correctInterestDecision 1:Option 1) Tie secondary conversion to offline salesOption 2) Tie to online leads
Look at least at 2 rounds of screeningShit lead or good leadCalled/contacted and lead was interested
Following example is assuming you have no access to offline data
Now, if you HAVE integration of offline data – this step is not necessary. Because you clearly know the relationship between the online engagement behaviours and ultimate conversion
Use same arithmetic on each of the behaviors
Limitation of GWO (can use some GA to get at the details) plus stat sign calculatorUse revenue filed in T&T