Oceanos for Salesforce (Beta)

Oceanos ListOptimizer supports quarterly batch updates to account, contact, and lead records.
Oceanos ListOptimizer supports quarterly batch updates to account, contact, and lead records.

Contact data management vendor Oceanos is working with Datarista to bring an SFDC-based contact service to the market.  The Oceanos ListOptimizer service, currently in in beta, will be generally available in Q1.  Sales Operations can run counts, perform company and contact searches, and ensure ongoing data integrity.

The service supports standard company and contact list building with running counts as variables are selected.  New execs may be added as lead records or accounts and contacts.  Duplicate checking is performed.

Batch Salesforce updates are performed quarterly.  In 2018, the updates will run every other month with contact changes updated weekly.

Oceanos offers best-in-class contact records from over a dozen vendors.  When records are deployed to customers, they are subject to real-time reverification against FreshAddress, FullContact, and Pipl.

Contact management services are purchased on a credit basis with custom pricing plans based upon volume and intended usage.

In other news, Oceanos recently inked a deal to deliver its ContactAPI to The Big Willow intent data platform. “Targeting prospects before the market even knows they exist provides our customers a first mover advantage,” said Big Willow CEO Charlie Tarzian.  “With the Oceanos ContactAPI, we provide our users targeted contacts for intent-qualified opportunities that accelerates engagement.  With 15 years in the space, they’ve earned a stellar reputation and we’re thrilled to take this next step in our partnership.”

Along with connectors and APIs, Oceanos offers free data health checks and a team of data consultants to assist with data hygiene and analytics initiatives.

Data Science and Competitive Advantage

GlassDoor Tech Salaries

Social media job site Glassdoor recently published its second annual ranking of the top jobs in America and, of the top twenty-five jobs, ten were in technology.  The top ranked position was data scientist which jumped from ninth last year.  Other high ranked positions were Solutions Architect (#3), Mobile Developer (#5), and Product Manager (#8).  Glassdoor bases their rankings on three variables: the number of job openings, salary, and career opportunities rating.

The Median Base Salary for a data scientist is $116,840.  Other tech base salaries can be seen in the above graphic.

When Network World interviewed data scientists about their position, they noted the pleasure of discovery as a key benefit.  A common complaint amongst data scientists was the headache involved with data preparation.  “At times, munging [parsing] through data can get tedious,” said data scientist Jeff Baumes at Kitware. “The worst times are when I realize the quality, quantity, or other aspect of the data simply prevents me from gaining the level of insight that I hoped to gain from the data.”

The McKinsey Global Institute found there is a growing shortage of analytics talent in the United States.  By 2018, they projected a shortfall of 140,000 to 180,000 professionals with analytical expertise.  They also projected a deficit of 1.5 million analytics trained managers and analysts.

Data scientist talent acquisition and retention are a significant problem for organizations, particularly amongst firms looking to initially establish data science capabilities.  In an article in the MIT Sloan Management Review, Ransbotham, Kiron and Kirk Prentice found that 55% of analytically challenged firms had a problem recruiting and retaining analytical talent while firms described as innovators had much less difficulty.  Only 29% of innovators reported difficulty recruiting with 24% reporting difficulty retaining.  Innovators also are much more confident that they have the appropriate skill levels in house.  While 74% of Innovators believe they have hired the appropriate analytics talent, only 17% of the analytically challenged felt the same.

One advantage of partnering with sales predictive analytics companies such as Lattice Engines or Leadspace is the ability to bypass hiring of in-house data scientists and instead work with their resources and tools.  While it is still important to understand the results and train staff in data interpretation, much of the complexity is removed.

Furthermore, the strategic advantage accruing to analytics capabilities is declining as more firms develop such capabilities.  In 2012, 67% of surveyed respondents believed analytics capabilities conveyed a strategic advantage.  By 2014, the percentage had dropped to 61%.  The authors posited two reasons for the decline: an increase in the number of firms investing in analytics and a difficulty in converting analytical insights into business action.  Half the respondents noted difficulty in translating insight to action.

“Technology is no longer the main barrier to creating business value from data: The bigger barrier is a shortage of appropriate skills,” said Ransbotham et al.  “Companies with appropriate analytical skills are far more likely to say that analytics is creating a competitive advantage in their organization than are other organizations.”