Oceanos began as a list broker back in 2002, but has since evolved into a B2B contact aggregator and data refinery. The firm aggregates 97 million active US contact records and retains millions of inactive names and emails to assist with hygiene. Data is aggregated from eleven vendors and includes social data from FullContact and Pipl. Oceanos provides data enrichment, TAM analysis, net-new contacts, and a set of data specialists to assist with projects.
Oceanos is self-funded and based in Marshfield, MA. Annual revenue is around $5 million and is derived from data hygiene services, contact matching, and API-based data licensing.
Each record is assigned a data quality score based upon eleven signals including dead email addresses, drops between files, email naming conventions, and social data verification. Thus, customers and partners can employ data quality score cutoffs when licensing data. Data quality scores are also employed as part of a free Data Health Check for customers.
Contacts are mapped to 12 Job Functions, 109 Sub-functions, and 7 Job Levels. Granularity to the sub-function level assists with strategic targeting. For example, marketing is mapped to 18 job functions including brand, corporate communications, events, public relations, search engine, and social media.
The Data Health Check report does not directly validate emails and other fields, but employs the Data Quality Scores to provide an overall Data Quality Score and a data accuracy histogram. The service also provides proposed before and after fill rates across twenty biographic and firmographic variables including address fields, direct and corporate phone, employees, revenue, industry, and major social handles. The final element of the Data Health Check report is a set of segmentation charts by job level, function, specialty, domain extension, industry, sizing variables, and country.
At the end of the report, there is a data health recommendation where they contrast their Account Based Marketing approach to traditional database augmentation services:
With 0ther health checks, this is the section where they tell you that they have a plethora of contacts for you to purchase, all matching your data profile. First, the point of this analysis is not to assume that the accounts and contacts currently in your database represent the optimal mix. In many cases the results demonstrate that there is a percent of bad and misaligned data. Second, it’s important to note that this is not a quantity game. In fact the more-the-merrier mindset is the root of many database problems.
We recommend a three step process to effectively cleanse, complete, and grow your database. This is the ideal approach, but we understand that timing and budget do not always permit the perfect solution. That being the case, we suggest a conversation to review the health check results and to determine the best prescription based on your needs and goals.
The Cleanse and Complete stages purge bad data, standardize and validate data, and enrich the client’s database. Cleansing processes the file against FreshAddress, Clickback, internal tables, Whitepages, Pipl and FullContact. Only once the current data quality issues are addressed does the firm recommend a Contact Gap Analysis for populating accounts with missing strategic contacts. The analysis also identifies the percentage of contacts that match the target audience criteria (Ideal Customer Profile). Oceanos contends that best-in-class firms have at least 70% of contacts within their target audience.
The Contact Gap Analysis also provides a greenfield (net-new contact analysis) by job function and sub-function and an analysis of Total Addressable Market (TAM) coverage between House and Greenfield contacts.
Integration services include a partner API, used by ReachForce, Engagio, and Integrate, and MAP connectors for Marketo and Eloqua Cleanse and Append
Oceanos President Brian P. Hession identified their differentiators as their unique blend of technology, professional services, and data quality. With data quality being critical to ABM sales and marketing initiatives, the inclusion of real world project fulfillment through their program specialists provides Oceanos with data quality insights that are used to continuously inform and enhance the data quality processes. “We apply both technology and real-world insights to ensure the highest quality of data before we are releasing it. We are incorporating a continuous stream of data quality insights into our code to address the many nuances that a program specialist encounters manually on a dataset,” said Hession. “The way that Oceanos is going to be successful in the future is if we can assemble an internal contact database that is of the highest quality in the industry. So there’s been a lot of focus on putting models on top of our contact data.”