Last updated on March 8th, 2016 at 07:38 am
Running a B2B company has its challenges. Competition remains intense, profit margins are too thin and the top line has plateaued. How can B2B find secondary revenue sources? The answer could lie in part within business intelligence (BI) data monetization.
“Data monetization is an increasingly popular trend among B2B enterprises,” says Ramon Chen, chief marketing officer, Reltio, creator of data-driven applications. “And it’s no wonder why, given the vast amounts of data that companies now store.”
But first that data must be analyzed to identify hidden opportunities that have not been exploited before. How can B2B firms accomplish these tasks? Analyzing BI exists beyond the capabilities of normal humans in any substantive way. Powerful computing resources must bear the brunt of the BI data burden to make it available and meaningful.
“While getting there seems daunting, the first steps start with improving reliability and relevance of internal data to improve business operations,” Chen says. “In fact, reliability and relevance are two key areas any enterprise must address to reap the greatest benefits from its data.”
Artificial intelligence sweetener
Artificial intelligence (AI) platforms can pull data signals out from the noise of structured or unstructured data, according to Jana Eggers, CEO, Nara Logics, an enterprise big data platform provider. Among the B2B applications that can benefit from AI, financial services, call centers, e-commerce and talent management rank toward the top.
“Making better business decisions is all about synaptic intelligence (i.e., AI),” Eggers says. “It connects siloed data for better customer recommendations and better employee decisions.”
Aggregating and wrangling data
Even with AI on the job, all that data has to find its way into the analytics engine. However, with BI data sources living in nurture marketing, customer relationship management (CRM), web sites and other B2B repositories, the process exists as an unsurmounted task.
The secret: automate data wrangling and free BI and data science teams, to enable them to focus on drawing inferences, according to Cameron Sim, CEO, Crewspark, provider of automated data ingestion and visualization platforms. In addition, by leveraging ready sources from other B2B organizations, the overhead of data discovery is lightened significantly, he says.
While the power of aggregating B2B data across external organizations exists as potent intelligence, very often a company will wish to look within first. And the closer to the customers the data lives, all the better. Naturally, field marketing and other customer-facing B2B staffers will have the primary sources.
“Recently, we began to aggregate, anonymize and summarize activity data around how field reps operate,” says Mat Brogie, COO, Repsly, a mobile CRM and data collection tool for field teams. “Over time, we will extract more information around activities that various field organizations perform across different demographics and customer types.”
This data establishes field activity benchmarks for customers and the industry so that subsequent performance of field teams can be evaluated. Then organizations can see how their teams’ metrics compare to those of peers within the industry or geographic region, according to Brogie.
“This helps optimize the team structure to provide the best return for its efforts,” he says. “This will help determine if they are over or under investing in field resources—one of the most expensive parts of a company’s organization.”
Account-based marketing and retargeting
As seen in recent coverage, account-based marketing (ABM) remains one of the hottest areas of B2B data analytics. Using leads, buying intent signals, white paper stats and other ABM data, BI scientists can focus on the customer accounts they already know and retarget them with display ads and other paid-for messaging.
“We’ve found that many B2B companies have tremendously rich and underutilized data,” says Patrick Shea, co-founder, AdDaptive Intelligence, an ad tech company. “Whether that’s lead information, CRM data or subscriber info, those are extremely strong signals of business purchase intent. Activating that data is the first step to unlocking value.”
And using that data to run highly targeted digital media campaigns is an extremely effective way to monetize data, according to Shea. Lead retargeting and ABM are great ways to start, he says.
Ideally, B2B practitioners will use this data to learn about users and the companies they represent, then target them and their colleagues with digital ads in coordination with the rest of marketing. With lead retargeting, they’re getting a message in front of a specific user who has shown some interest (e.g., white paper download, form fills).
“Someone who has demonstrated intent in your product and then been exposed to additional messaging about that product is more likely to be receptive to your other marketing efforts,” Shea says. “Or they could convert directly from the digital ad.”
Real-time marketing and sales
In the end, obtaining the data to monetize exists as only half the battle. After marketing hands off the data to sales, they still need to close the deal. For B2B data, speed has become the prime metric.
Thus, the relationship between sales and marketing will hinge on timely delivery of data from one team to the other. B2B marketers need to provide salespeople with the real-time information that allows them to have high-value conversations with prospects when they’re in the best position to buy. Without this data delivered in a timely fashion, close rates drop off or grow stagnant. But this is easier said than done.
“In their study Applying Timely, Targeted and Tailored Insight to Improve the Pipeline, the CMO Council found that only 9 percent of marketing executives felt that their company had competency in real-time delivery of sales intelligence and breaking news,” says Bob Murphy, managing partner, Movéo, a Chicago-based B2B marketing firm. “More than nine in 10 marketing executives felt unprepared to respond to customer intelligence in real time. Today, customers expect real-time engagement from companies with which they do business, and marketing executives need to get up to speed.”