How do most marketers create a database? Do they go off and order a big pull of account based marketing data or purchase a list and hope that yummy target accounts are represented? Simply loading the sales funnel with target accounts is actually an easier task than hoping you’ll get lucky and find them when buying a database.
Why not create databases that exclusively contain the target accounts? There is no excuse for marketing to companies that you don’t want. Instead of using the pray and spray method, where specific keywords are purchased in the hopes that they will attract top prospects doing searches, ask the sales and marketing teams to compile a list of the actual companies the team wants to penetrate. There are two parts to this marketing strategy, but they should not be thought of as daunting. Creating a database is really a non-mystical exercise. It simply requires hard work and methodical research. It goes like this:
- Once the list of top prospect companies is drawn up, the next step is to match those company names with the companies listed in larger databases. Matching is a skill that takes both good account based marketing tools and careful, manual labor. When a tool identifies a VP of Sales’ jotting of the name “ARM,” it has to figure out if the person meant the brand Arm and Hammer, the stock symbol for American Airlines, Fidelity Investments, or American Medical Response, or whether they simply misspelled the target account. This scenario often comes down to a judgment call, as good technology can get you part of the way there, but name matching often involves a human element ̶ a live person looking at possible matches and choosing what they feel the author really meant. It requires having some knowledge of target marketing and an understanding that American Airlines would process a lot of credit cards, making it a likely candidate. Once the list is matched and the accounts are updated with their correct spelling, address, website URL, etc., then the next step is to populate the account’s listing in the database with key contacts.
- Building contacts (also known as “contact discovery”) is a specialized discipline that, again, isn’t very mysterious. It just takes hard work. The old-fashioned way is often the best: call into the account and talk to real people and capture names by title or by role. It isn’t very exciting work, but it is the only way to ensure you get the name of the person who has responsibility in the target area. You need skilled researchers who will call the target account and get someone (or multiple people) to confirm the person’s name, spelling, title, role, email, etc. This method can achieve >95% accuracy.
What can make this process easier?
If you already have some names in that target account, you can leverage them to get other names. When your research teams go hunting for contacts, they can invoke the names they already have to establish enough credibility to get someone in the organization to yield new names.
Beware of sources that use “web scraping,” another technique for automatic contact building. They often get names that would be described as “good enough.” For many marketers, “good enough” meets their budget constraints. In reality, using “good enough” names can compromise the delivery of your marketing message. Imagine sending an email where the contact name is spelled wrong, their title is wrong, or the message doesn’t really resonate with their role or responsibilities. Or the email bounces, never to be delivered, and the outbound effort is wasted on a bad email.
Creating a database specifically for the purposes of advanced lead generation (particularly in target accounts) is hard. Turning target accounts into top prospects is hard. Getting specific executives in target companies into your sales funnel is hard. But creating a database with the goal of achieving high accuracy is easy…and, again, not mystical. It is simply all about hard work and methodical research. A super high-accuracy database means that all the marketing programs that leverage those names will not fail based on bad data. They may fail for other reasons (more on that in other blogs), but at least the account based marketing data will not be one of the usual suspects.