Differentiate Buyer Intent Analysis with Advanced Analytics

Advanced statistical analysis enables market research organizations to derive meaningful insights into key market trends, demystifying buyer intent.

Aberdeen defines “advanced statistical analysis” (also referred to as “advanced analytics”) as a set of technologies that enable organizations to analyze data to uncover hidden trends, make forecasts, and glean actionable insights.

In a recent report, How Advanced Statistical Analysis Can Benefit Market Research Firms, Aberdeen’s VP and Principal Analyst of Contact Center and Customer Experience Management Omer Minkara explores the benefits that market research firms achieve by incorporating tools for advanced statistical analysis into their operations.

Minkara’s research shows that firms using advanced analytics tools outperform other organizations in the space by shocking margins. Companies that report using advanced analytics, for example:

• Achieve 22.1% annual improvement in operations costs (compared to 1.2% worsening of organizations not using advanced analytics)
• Achieve 5.2x greater employee engagement rates than non-users
• Achieve 9.2% annual improvement in their profit margin per research program (compared to 1.8% worsening by non-users)

To contextualize the last data point, which calls out the 11% profit margin gap between users and non-users of advanced analytics, consider Minkara’s example: A market research firm that generates $5M in profit annually and uses advanced analytics would see $550,000 greater profit than a market research firm that generates $5M in profits and does not use advanced analytics. Over the course of five years, the firm using advanced analytics would observe $2.75M more by improving the profit margins of its research programs than the firm that does not use advanced analytics.

Market research firms cannot retain clients without satisfying their customers, demystifying buying behavior, and gleaning actionable insights from their own research programs, which explains another key finding from Minkara’s report: The 10.7% gap in customer retention rates of firms using advanced analytics and firms not using advanced analytics (7.8% improvement vs. 2.9% worsening).

Demystifying Buyer Intent with Advanced Analytics

Do the outcomes of Minkara’s research also apply to buyer intent data?

“Demystifying buyer behavior” sounds a lot like something Aberdeen’s teams (and analytics) excel at, and it is logical that the AI-powered ABM solutions in the B2B market also rely on heavy-duty, advanced analytics to execute programs and produce actionable insights.

“Demystified” buyer intent data is not a commodity that teams can share via zipped folder sent over Slack. It requires major algorithmic power to parse and synthesize the vast volumes of purchase intent signals and contextual data.

“Demystified buyer behavior,” however, as the output of the advanced analysis of intent data, is indeed something that can be easily shared outside the proverbial walls of the analytics suite. For example, Aberdeen regularly publishes blog posts containing insights into specific marketspaces, such as Benefits Insights and Analytics software.

The above blog post is, at face value, a 100-word article containing a chart. You probably suspect that a content team copy edited, proofread, and built the post — but have you considered who wrote the post, who collected the multitude of data points taken from 200+ B2B sectors, or who synthesized all of those factors spanning buyer demand, buyer selection preferences, buyer perception of vendors, market share, buying intent signals, and end-user behavior?

If you guessed “advanced analytics, natural language processing, machine learning, and Aberdeen’s Marketspace platform,” you’re correct! The teams at Aberdeen are hard-working and smart, but analyzing massive sets of buyer behavioral data and providing real-time market insights is a job for advanced analytics.

If a provider of market intelligence isn’t using advanced statistical analysis to synthesize their volumes of buyer intent data, the organization can’t be considered a true provider of actionable market insights. If an ABM platform provider isn’t using advanced analytics to parse their troves of purchase intent signals and contact data, the accounts they’re basing their automated marketing on probably are not the best fits for their clients.

To provide the most accurate, insightful, and real-time market insights, any market intelligence provider should do like the top performers in Minkara’s research and start using advanced analytics.

Access How Advanced Statistical Analysis Can Benefit Market Research Firms here.