Small and medium-size businesses can find it hard initially to make the transition to business-to-business (B2B) selling when they’re used to selling to consumers.

An excellent example is small banks and credit unions that have well-trained staff for consumer lending, checking, card, and savings products. Unfortunately, these staffs are often “homegrown” in the consumer selling space, but don’t have much experience when it comes to dealing with business. They quickly find themselves in trouble when they are asked to talk with businesses about loans for carrying inventory, payroll lines of credit, and loans for commercial construction projects.

They solve the problem by teaming with a larger bank or credit union that has a business lending and sales division, but the problem doesn’t end there. These institutions also have to identify business prospects they can sell to. This is where big data screening and analytics enter.

How Radius Intelligence tracks and edits big data for SMBs

“We track 30 million small and medium sized businesses in the US, store them in a database, and refresh this data weekly,” said Adrian Druzgalski, CTO and cofounder of Radius Intelligence. “The service is especially useful for financial services companies that want direct mailing lists.”

Since SMBs come and go, what makes the service valuable (and less wasteful) for smaller financial institutions and companies in other industry sectors is that the SMB contact information is likely to be far more accurate than what they could get with any other kind of SMB database they could put together in-house.

“The business records that we accumulate come in from multiple services,” explained Druzgalski. From there, duplicates of businesses are eliminated, and data is “cleansed” before it ever enters the database.

This big data editing exercise is critical, because SMBs leave their footprints all over the internet. If you don’t know how to consolidate them, you can risk inaccuracies and also the expense of additional mailers.

Because the volume of “raw” big data that comes in from websites, social media, and other sources can be large, unpredictable, and difficult to manage, companies like Radius use a “discovery” process that is organized around a set of data attributes that the analytics utilize. The process is dependent upon big data processing on platforms such as Hadoop and MapReduce.

To simplify this need for multiple big data solutions “under the hood” of its operations, Radius uses a big data software framework called Cascading, which arches over all of these different big data processing resources so internal big data operations can be simplified. The result is faster time-to-market with valuable SMB data that Radius delivers to clients.

“Our clients come from financial services and other industries, and many of their needs are custom,” said Druzgalski. “An over-arching solution like Cascading enables us to write a custom application quickly, without having to worry about the technical details of interfacing with different big data systems and hardware.”

Beneficiaries of the resulting analytics are also insulated from the data science and mechanics that are required in the big data “engine room.”

Does it make a difference?

For companies in the B2B selling space, it certainly can make a difference, because cleaner data and outreach efforts assist them in reducing churn and adding new customers. For those entering the B2B selling space, they have the peace of mind that someone else can already deliver accurate business marketing information. All they need to do is focus on developing staff so they are properly trained to sell to business.