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May 14, 2015

Big Data, Giant Return

Dmitry Cherches

Sales drive business. And technology drives sales. The trick is to figure out how to make the two work together. That opportunity arose when a long-term client, National Registered Agents, Inc. (NRAI), determined the time was right to rev up their sales engine.

By way of background, NRAI are in the Registered Agent industry. Their business? In short, any entity conducting business within a state must register to do business in that state, designate and maintain a registered agent, and in some cases have a registered office. NRAI and its competitors sell these corporate and legal services.

NRAI’s sales executives knew the demographics of their best target market. Because every company must register every entity in every state in which they do business, companies with multiple entities, subsidiaries, etc. operating in multiple states represent lots of revenue. That means corporate filings deadlines and legal activities that span across multiple jurisdictions.

NRAI specifically wanted to target companies they knew were related in some way, but weren’t big enough to attract the attention of their competitors. While the competition was focused on really big companies, NRAI’s focus was on families of smaller companies operating in multiple states that on the surface appeared to be individual entities.

Because these companies operated under different names and in a variety of industries, their relationships to each other were both unknown and undefined – and identifying them under a common umbrella was impossible.

We had a long history with NRAI, and had developed a level of trust that enabled us to imagine an innovative solution for them. Recognizing both the complexity of the challenge and the potential for it to be a game-changer for NRAI, we needed to build a custom solution that would automate the discovery of relationships between companies in the short term, and drive an entirely new sales process in the long term.

We knew that prospect data was accessible on public databases on the web and available for purchase from private, third-party sources. But collecting from hundreds of databases each using a unique combination of structured and unstructured data posed major challenges:

  • Individual databases contained only partial data sets, and were usually hiding or missing a critical field;
  • 50 states meant at least 50 different database formats;
  • Some data was old, some was real-time, some was plain, unstructured text and some arrived in a spreadsheet;
  • For databases we were not able to buy, or when the data from a paid subscription was old, wrong, or unsatisfactory, we had to obtain permission to set up an automated scheduled scraping that would not affect site performance.

So we developed a custom, web-scraping technology using Microsoft .NET and SQL Server that would collect, warehouse, and transform disparate data points into a common format.

All incoming data was pumped into a data warehouse and then moved into a data transformation engine that removed outliers and converted distributed databases into a single, easy-to-consume format. All this needed to be optimized and scaled in order to accommodate constantly refreshing data.

On the front end of the solution, we created a web interface that would allow the sales team to query the transformed data from multiple sources and laser focus its efforts on these cherry prospects.

The user interface would also allow updates made by the sales team to feed back into the system, ensuring the data was constantly improving.

A True Business Intelligence Discovery

  • The prospect finder engine, with its massive back-end operation, discovered productive relationships between seemingly unrelated data points and uncovered a treasure of top prospects. Families of businesses could now be grouped and targeted together, and prospects could be ranked by size and clustered by geography.

With the heavy lifting being done by the back end of the prospect finder engine, the easy-to-use front-end interface gave sales executives immediate access to top prospect information they never would have uncovered, no matter how much time, energy, or research had been devoted to finding it.

  • Sales executive could now filter and find thousands of prospects in seconds. They could create new sales strategies by searching for any common attribute. If a group of companies all shared a competitor, they could adjust how they pitched to them. If that competitor had recent trouble, their customers immediately became an NRAI target.

This drastically decreased the selling effort. Deals were larger because NRAI was able to target their sweet spot: families of businesses. And because NRAI had unique intelligence about companies that the competition was ignoring, sales conversions were fast and easy. At only a few hundred dollars per year per entity, making a switch to a new Registered Agent is a low-risk decision.

As a bonus, the accounting and finance teams also leveraged the new information made available. They could now confirm and verify contact information, and go after delinquent accounts.

On the day the system launched, NRAI created a list of several hundred companies that had named NRAI as their Registered Agent – going back over five years – but had never been billed for services. This represented approximately $200,000 per year. NRAI billed immediately and collected more $300,000 in unexpected receivables in a matter of days.

While every industry and every company has unique prospects, this worked for NRAI because they:

  1. understood exactly who their target market was;
  2. knew where they could obtain prospect information;
  3. wanted to create a long-term competitive advantage;
  4. targeted prospects not being actively watched by competitors; and
  5. trusted our expertise and technical innovation.

Not only did NRAI overtake their competitors, they soared to #3 in the nation in an industry filled with a handful of giants and many, many small businesses. Their small investment into Big Data yielded giant returns.

About the author: Dmitry Cherches is CTO for Mind Over Machines, a premiere software and data consultancy located in Owings Mills, MD.

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