Part 1 of a 2 Part Series
Oceanos was founded twelve years ago to add a strategic layer to a model that was heavily transactional. It was different and better model which enabled Oceanos to take root. Over the next decade, we watched new data vendors hit the stage and others disappear. The infusion of technology changed the market and many companies simply could not adapt. From the marketer’s side, the common theme continued to be the pursuit of that “new” data provider that would live up to all its promises. Well, that white horse has yet to arrive.
For years we have used the metaphor of stock investing when coaching clients on how to design a contact discovery strategy. Below you will find part one of a two part series, where we first outline the key points to overview our model, and will then dive deeper into the strategy as a follow up.
A successful contact discovery plan includes three pieces and each is equally important.
- Audience Definition – think about the “buying team” and define each group (e.g. Influencers, Decision Makers & End Users). The audience definition goes beyond job title and business demographics to include roles, responsibilities, interests, skills, certifications, group memberships and a like. With a great amount of detail, the audience definition serves as the foundation of your contact discovery plan.
- Contact Gap Analysis – an application that takes the audience definition and provides visibility into the contacts you have and those missing within your house database. It reveals the “gaps”; the target contacts missing at each account. It also highlights if a third party contact record is available or if custom discovery is required to close the gap.
- Data Strategy – armed with the Audience Definition and Gap Analysis results, you are now in a position to craft the contact discovery plan. The most common approach is to focus on finding contacts to close the most important “gaps” (e.g. account and job title combinations). So, how do you do this? It requires a multi-source approach including third party databases, social media research, and other advanced web discovery techniques. This methodology will not only increase reach, but it provides cross validation which increases overall data quality.
Within my next blog post, I’ll take a deeper dive into “how” you execute a contact discovery plan and share specific real word examples.
To find out how smarter data can lead to a better marketing automation system and more revenue for your organization, contact Brian P. Hession, President & Founder at firstname.lastname@example.org