“Big Data” is gathered from every corner of our digital life, including demographics, geography, spending habits and even lifestyle.  There are thousands of data points collected and used to market and sell goods to us as consumers and this data has spawned entire industries and software companies. 

However, the promise of Big Data in business to business selling and partner recruiting hasn’t always hit the mark.  We at MarketStar have tested all kinds of data sources and predictive software that promises to provide the same magic we have seen in business to consumer data and software.

Some of the difficulty in BtoB is that a company is a collection of people who behave and act in different ways. When those behaviors are compiled, we lose the power of intent to predict outcomes.

A small, targeted list is far better than a big list. 

However, there are a few data and software companies we have recently worked with that are bearing fruit.  I believe that the Big Data industry is making inroads in capturing the intent of a business in three distinct ways:

1. Capturing and aggregating company activity data — What are the employee’s business activities online? What are they reading and commenting on? What blogs they are following?
2. Scraping and capturing traceable domain and software items — What software connections are coming from the company domain? What connections are embedded in website source code?
3. Capturing internet facing device and traffic information — How much bandwidth is going to cloud providers like AWS/Azure versus a data center?

Many Big Data companies combine those methods with old school data gathering methods like desktop research.  Several (what I think are winning companies) layer predictive scoring to make the data actionable.

That being said, we have not found the silver bullet to solve all of our needs.  What we do know is that we’ve been able to use Big Data to more effectivelyrecruit partners, and sell to end customers.  Big Data means going beyond a name, e-mail address, and industry.  We also have learned that a small, targeted list is far better than a big list. 

The ability to triangulate Big Data utilizing analytics is where the magic really happens.

To target partners, we layer advanced analytics to not only score them based on likelihood to sell or buy, but also to understand what to expect in the future. We have a number of analytics we provide, including:

• RFMVT (recent purchases, frequency, monetary value, and variance in trend) modeling – Is a partner a good long-term investment, or a short term gain?
• Cross-sell/up-sell analysis – How much opportunity exists for complimentary services or products?
• Sales Forecasting – What can be expected if things stay the same, or change?
• Revitalization analysis – Voice of customer data that helps mitigate pain points?
• On-point analysis – Who are the optimal customers, and who should be targeted for more support?

The ability to triangulate Big Data utilizing analytics is where the magic really happens. Creating a Big Data/Predictive Analytics practice to guide investment and go-to-market decisions will be one of the greatest competitive advantages companies can invest in for the next 5 years.