Revamp your online lead generation – fast

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

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