Suppose that there are more than 10,000 unique job titles across more than 200 departments, 25 broad disciplines and 20 position-levels as your target. That makes finding the right decision-maker for a particular offer one of the biggest challenges we face as b-to-b marketers. Adding to this pain, the number of different ways the same job title can be spelled (IT director, IT dir, dir IT, info tech dir, etc.) and a rising-cost environment make it even more critical to ensure every piece of mail counts. Many marketers are therefore turning to more sophisticated ways of selecting prospects and leads for new-customer acquisition by leveraging job title as a supplement to RFM and model selections in identifying those most likely to respond.
The process begins with an understanding of which professional titles are most likely to respond to your offer. While this sounds simple, most marketers struggle to capture this information and lack a universal standard for aggregating data to facilitate analysis across numerous outside lists. Due to differing title formats and data-capture practices, one title can be spelled dozens of different ways on a single mail file.
Using a mail file example, 428 prospects holding the title “Vice President of Direct Marketing” were identified as being addressed in 56 distinct (and often misspelled) ways including 36 titled “dir mktg VP,” three as “vice president of direct marke,” one “VP dir mrkt” and a “direcy mktg VP.” In a typical campaign, each recipient would be targeted with these poor titles printed on the actual offer that (hopefully) reaches their desks. While marketers strive to improve personalization and avoid having solicitations discarded as junk mail, the goal is to correct these awkward and unprofessional misspellings with their true, “beautified” title. In the above example, this would be “vice president of direct marketing.”
The next step after linking many different raw titles to a single, standardized title is to categorize each decision-maker by their department, discipline and position level. Using a smart key on mail files for each segment allows mailers to easily analyze response by title (vice president of direct marketing), department (direct marketing), discipline (marketing) or position level (vice president) after the campaign. This allows marketers to gain insights into which offers and price points may be of interest to each type of decision-maker and improve their upfront name selection.
A backend response analysis on a high-tech promotion with a 2% response rate shows how different titles reflecting different types of decision-makers generate different results relative to the campaign's overall performance. Examples ranged from 2.64% for prospects holding a title of “director of information technology” and 2.19% for “information technology manager” to a below-average 1.37% for “senior vice president” and just 0.32% for “shipping manager.”
Another benefit to leveraging standardized titles is to increase deductions on net name list rental agreements. When targeted title screens are applied to rented lists to select/omit by specific job titles, marketers can identify which names do not meet the list rental agreement criteria, leading to documented deductions against net name agreements. A mailer renting 25 million names annually at an average rental cost of $225/M could save more than $250,000 by removing fewer than 5% of the rented names as unqualified. Marketers can use that savings to replace less-qualified leads with more relevant, targeted prospects for higher response and campaign ROI.
To summarize, from a direct mail perspective, the top four ways to leverage classification and correction of job titles are:
* Replace poorly formatted raw titles on mail files with the correct “beautified” titles.
* Use a smart key strategy to facilitate backend response analysis by title for greater insight into best responders.
* Incorporate standardized titles, departments, disciplines and position levels back into your marketing database to improve targeting and analysis.
* Increase penetration into better performing segments when renting outside lists.
Few service bureaus specialize in the special needs of b-to-b marketers, but there are tools available from a select few that can enable this more sophisticated strategy. With the use of title classification and correction systems, marketers achieve higher returns on their campaigns through both improved targeting and better quality presentation at a lower total cost. The result is a higher return on investment and faster customer database growth.
Thomas Berger is CEO of Cross Country Computer (www.crosscountrycomputer.com), a provider of b-to-b data management services. He can be reached at [email protected] countrycomputer.com.