Previously in DM News, I wrote about a familiar scenario of steadilyá
declining online lead quality and the five easy steps you couldá
immediately take to turn your campaign around: use targeting; revampá
creative; add a qualifying checkbox; change to real-time dataá
delivery; and send triggered e-mail.
Here are five advanced changes that you can make right now to improveá
lead quality. If you don’t have the expertise in-house, sophisticatedá
network partners should be able to help you implement these steps free.
Use auto-scrub. Automatically exclude leads who incorrectly answerá
key qualifying questions in your offer form. For example, if youá
require consumers to have allergies and they indicate in your offerá
form that they do not, then you should not receive or be required toá
pay for those leads. Scrubbing bad leads upfront saves you the timeá
and effort of contacting consumers who have expressed interest but doá
not qualify for your services.
Add dynamic fields. This versatile feature allows you to customize aá
field in your offer form based on the answer provided in the previousá
field. For example, if a consumer indicates he or she lives in a ZIPá
code where you offer only certain services, then customize the nextá
field with those services only. Don’t give consumers options thatá
aren’t available to them.
Customize validation. Beyond standard data validation like physicalá
address, e-mail and phone, consider customizing validation to yourá
offer form. For example, if you require a certain loan-to-propertyá
value percentage for a mortgage offer, then create the logic toá
calculate that percentage upon submission and reject the lead if itá
Share conversion data. The best targeting methods incorporate yourá
conversion data into a custom model that is continuously adjustedá
according to your offer’s performance on the back end. Your providerá
should be able to accept data from your positive customer leads andá
create a custom look-alike target that identifies and targets theá
offer to consumers most likely to convert based on similar data iná
Determine credit worthiness via predictive modeling. If your criteriaá
for lead quality hinge on a consumer’s credit worthiness orá
likelihood to pay for your service on the back end, predictiveá
modeling can be particularly effective. The process combinesá
demographic information with transaction data to create custom modelsá
that target consumers with similar characteristics to those who meetá
your lead-quality standards.
These suggestions, and the others in my last column, are by no meansá
the only steps you can take to improve lead quality. Talk to yourá
provider before proceeding to determine which are right for yourá
campaign and if there are other actions you can take to reverseá
declining lead quality for good.