by Marie Carino Jimenez, Data and Systems Specialist, Sales-Link Inc.
Most people in sales and marketing are familiar with the term “lead generation,” but often don’t understand what it entails, and seldom consider the work that goes on “behind-the-scenes.” Lead-generation refers to the process of identifying potential customers with the purpose of initiating and cultivating consumer interest for specific products or services. These potential customers are referred to as “leads,” or “contacts,” and in marketing, leads are collected in a database for list building, e-newsletter list acquisition or for other targeted sales opportunities. But how exactly are these lists created and maintained? How are they kept current with up-to-date information?
The answer is that lead generation databases are mined and maintained by an army of people like me, behind the scenes. My title at Sales-Link Inc. is Data and Systems Specialist, a title that may seem broad and specific at the same time. Broad, because it encompasses so many different details within the database; specific, because it refers to systems, in which I mostly send data as uploads.
There are many steps involved in preparing to upload a file of contacts into a database. The data within each file needs to be researched and verified prior to upload. Our system, Pharma BDI (Pharmaceutical Business Development Information), includes the names, titles, places of employment, contact information, and other important, pertinent information for over 500,000 industry Pharma, Biotech, and Diagnostics professionals. When our clients purchase licensing to our system, so they can search for potential targets to connect with, they rightfully expect a current list with correct information.
Cleaning a mined file can be a daunting process, depending on the number of prospects in the file. Smaller files, in the 50-count range, are easily eyeballed. Larger files, in the hundreds-range and upward, need to be run through an Excel chart that has Macros embedded, in order to weed-out useless and unimportant information.
Once the file is uploaded, the system outputs two reports: a “matched” file and an “unmatched” file. A matched file contains prospects that the system identifies as possible duplicates, that may already be entered in the system. Since the system is correct only about 60 % of the time, the other 40% must be processed by our staff manually.
The second report, the unmatched file, is a list of prospects that are technically reported as new, although not necessarily. Some of the prospects on this list may already exist in our system, but are showing as “unmatched” for some reason, such as, a relocation to a new company. Of course, these discoveries, and consequent corrections, need to be addressed manually, as well.
To further illustrate our process, I’ve included a graphic (see above) we refer to as “The Factory”. Yes, my team often feel similar to factory workers that are performing tasks on factory lines. We often laugh about the “I Love Lucy” episode where Lucy and Ethel are on the chocolate factory line and the conveyor belt speeds up to the point where Lucy and Ethel start stuffing chocolates in their mouths and hats in an attempt to keep up with the process. Hysterical!
Luckily, we stay well-paced at Sales-Link by balancing the manual processes with automation.
Uploading into our system, is just one of many processes my team and I perform for Pharma BDI. Once the new data is entered, the real fun begins. Our lead generators use the data for email campaigns, our call center uses the information for phone calls, and both reach out to contacts via LinkedIn.
We’ve been using automation to enhance the manual work that we do for quite some time, but in an effort to continuously enhance our clients’ experiences with our system, we are now working on incorporating machine learning into Pharma BDI, as well. The science of algorithms and statistical models is a fascinating one, and this subset of artificial intelligence, in which computer systems use patterns and inference, instead of explicit instructions from human handlers to continuously tweak and improve systems, is positioned to advance lead generation capabilities in a big way.
In the near future, machine learning will be supporting our clients (sales and marketing groups in the pharma/biotech industry) by identifying new potential customers for them. The Pharma BDI system will be asking the user if they want to contact other leads with the same title, working for similar companies, that have similar pipelines.This system is already used as a planning tool, a network, and a sales platform, in addition to being an intelligence and methodology for lead-generation. Soon, it will have even more impressive capabilities, and I am thrilled to be a part of these giant strides behind the scenes of our industry.
( If interested, you can find more information about our powerful CRM system here: Pharma BDI )