All leads have different value profiles and predicted profitability. Here are eight variables you can control.
If you're like many online marketers, you're failing to optimize search around lead quality, according to several experts who spoke recently at LeadsCon NYC. According to several people I spoke with at this conference, a common mistake among lead-gen marketers is to just use a simple cost per lead metric for internal efforts as well as when dealing with vendors.
This is a very common mistake, even among some seasoned online marketers (although it's more common for those new to marketing in general or to online marketing). In the same way that all clicks are not equally valuable, all leads have different value profiles and predicted profitability.
Lots of things beyond the keyword can predict high or lower quality leads. We search marketers have control over some of these factors, whereas those we have no control over can still be measured and used to refine our scoring mechanisms. For example, here are some variables we can control and select around, narrowing them when we want to be high up, low down, or not present at all in a SERP (define):
Some variables are predictive of lead quality but we don’t have control over them at the SERP level, so we can’t choose not to receive them as paid clicks. For example:
I mention the additional variables because while they may not be controllable for inbound PPC or organic search traffic, they are indeed variables you may want to consider optimizing with a search retargeting campaign. Why retarget everyone when you can cherry pick (assuming the differences are material and the confidence level of your data is high)?
For example, here’s what Sean Cheyney, VP marketing and business development at AccuQuote, had to say on evaluating the quality of online leads.
Then Sean shared with us how to meet the challenges of lead source diversity.
Later that day, Steve Isaac, the chief executive officer of EducationDynamics, had a specific point of view on lead quality within the education market.
Steve also shared with me how to deal with the diversity of quality of leads.
If you're not sure which of the above variables will dramatically or subtly influence lead quality, then start embedding the above data right into your CRM (define) or business intelligence systems and wait the six to 12 months to regress the data. If you already have some of this data saved in your CRM systems, then get started and move towards a scored-lead environment and away from a lead-is-a-lead environment. So if you haven’t thought long and hard about the differing quality of your leads, perhaps now is the time to do so, both for paid search and for all the marketing you do to capture those most interested and most valuable to you (or your client) - even if it means connecting to back end CRM or business intelligence systems controlled by an IT department.
Kevin Lee, Didit cofounder and executive chairman, has been an acknowledged search engine marketing expert since 1995. His years of SEM expertise provide the foundation for Didit's proprietary Maestro search campaign technology. The company's unparalleled results, custom strategies, and client growth have earned it recognition not only among marketers but also as part of the 2007 Inc 500 (No. 137) as well as three-time Deloitte's Fast 500 placement. Kevin's latest book, "Search Engine Advertising" has been widely praised.
Industry leadership includes being a founding board member of SEMPO and its first elected chairman. "The Wall St. Journal," "BusinessWeek," "The New York Times," Bloomberg, CNET, "USA Today," "San Jose Mercury News," and other press quote Kevin regularly. Kevin lectures at leading industry conferences, plus New York, Columbia, Fordham, and Pace universities. Kevin earned his MBA from the Yale School of Management in 1992 and lives in Manhattan with his wife, a New York psychologist and children.
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