The State of Artificial Intelligence in B2B Marketing

By September 18, 2018
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Artificial Intelligence (AI) is more than just a buzzword these days, it’s the standard operating procedure for many businesses. We’re hearing it everywhere from sales and marketing, to finance and banking, HR and recruiting, and even the retail supply chain. In almost every industry, whenever someone says “artificial intelligence,” heads are turning and ears are raising.

According to The State of AI in B2B Marketing report, 63% of marketers are not using AI in their tech stack. There is definitely a huge appetite for it, but there’s also quite a bit of confusion around what exactly it could be used for in sales and marketing.

A majority of sales and marketing professionals believe that AI will impact the way they do business and in doing so, they’ll be much more efficient and effective in their work. But there are very few companies out there that can actually do it.

For example, here at EverString, we think about AI in regards to how company contact data is collected because so many data providers use human beings to collect and validate data they sell in order to ensure it has high levels of accuracy. This yields smaller datasets for marketers to purchase, although the data is very accurate. Compared to data collection done by AI systems that have large datasets with much lower accuracy and out-of-date information.

Human review usually involves gathering information on a prospective company starting with their website, and then visiting LinkedIn to find who owns what roles within an organization. The human reviewer uses their best judgment to determine who does and does not constitute a good account to call on, and they will eliminate the unnecessary information.

From the beginning, our mission has been to take that gut-feel decision-making process that was validated by, or even driven by, humans and scale it. No organization has had sales development representatives (SDRs) browse through the Internet to find their entire potential customer base and then make efficient decisions based upon what they’ve found. There are too many times those leads aren’t a good fit or aren’t even in the market for the organization’s product. But this is the way data collection has been done for years.

Until now.

How EverString Uses Artificial Intelligence for Data Gathering

The way the EverString system works is to use machine learning to build our discovery system based on your sales team’s initial research and decision making processes. It builds upon the past successes and failures and better mimics your humans’ decision-making process so you can harness an entire army’s worth of humans all in a single algorithm to do your Internet research and contact discovery.

“By analyzing the companies you sold to, and the companies who weren’t interested in you, we can determine which companies constitute a good business to go after.”

This helps avoid problems associated with senior leadership holding all that prior institutional knowledge of companies and contacts, or the specialized knowledge of a few human researchers, and brings it all to life through data and intelligence.

By analyzing the companies you sold to, and the companies who weren’t interested in you, we can determine which companies constitute a good business to go after. We’ll do all that leg work for you and just give you back high-probability results with a good fit score so you can target only those accounts where you actually have a good chance of closing the sale.

With a cohesive and effective system that combines machine learning and decision making, combined with a human’s eye for judgment and verification, not to mention a system of checks and balances to confirm accuracy, you can be assured that the dataset of potential leads you get are skewed in favor of your success.

Interested to learn what marketers are saying about AI? Download The State of AI in B2B Marketing report from Heinz Marketing and EverString.

To learn more about how we use artificial intelligence and human confirmation in finding and validating our data, ask to see how the data collection and confirmation process works.

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