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3 Unique Ways to Improve Your Demand Gen Using Big Data

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A NOTE FROM THE EDITOR

Data enrichment is on my mind since in a couple of weeks I’m hosting the Data Upfronts with my friend Rich Sobel. As you know, good data is key in B2B marketing. So as my worlds collide I thought I’d share some best practices for the ways data can elevate your demand gen game.

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3 Ways to Improve Your Demand Gen Using Big Data

As B2B marketers, we know that data is a driving force behind successful demand generation programs. While there are straightforward use cases for data in B2B demand generation (e.g., audience segmentation, analytics, etc.), there are a few more subtle and complex applications of data that can greatly improve your demand generation game.

Over the years I have implemented these approaches across a slew of B2B brands in various sectors driving demand generation outcomes (sales-ready leads / pipeline) by at least 300%.

Application #1: Content Intent Index™

I’ve discussed this a bit before, but building custom content intent index from consumption patterns can provide you an actionable dimension to intent data. In fact, while there are many providers of syndicated intent data, there is a tremendous opportunity to use content consumption data of your owned and operated properties to really understand the intent of your audience at scale.

In particular, by developing your own compound index of intent leveraging both 3rd party and 1st party insight, you are able to develop a much more predictive pipeline in the sales readiness of leads. Simply put, by building a custom content consumption scoring methodology and applying it to customer and prospect profiles alike drives insight, brand favorability, lead activation. The business outcome is two fold: better qualified leads and higher ACV in your revenue pipeline.

Data Enrichment Planning Process - The B2B Buzz

Application #2: Programmatic Data Enrichment

The second tactic using Data to elevate your demand generation focuses on data enrichment. There are many B2B marketers that lack the acumen to build sophisticated data enrichment management policies and processes to ensure the right information is informing your marketing technology systems. The result: incomplete information for marketing, sales and customer service activities. Leading to many missed opportunities to improve your demand generation, communication customization and so much more.

I would encourage all B2B marketers to develop a sophisticated data enrichment management excellence initiative internally. Above is the process I use to develop data enrichment management excellence for clients to ensure the right data is in the right place to support various go to market efforts. Delivering a comprehensive profile of individual audience members across your sales, marketing and customer service systems is essential to deliver a well-informed and holistic customer experience.

Application #3: Better Performance Metrics

As many of you know, tracking performance metrics (e.g., response rates, conversion rates, and so forth) are part of any successful demand gen campaign. But there are more sophisticated approaches to operational demand metrics that require significant data insight to get at.

One example, is to use acceleration scoring where time is the denominator for analysis to understand the Pace of Performance. That is to say, it's not just the results of this email campaign delivering a tactical outcome, but identifying the acceleration of that performance by segment using time-based analysis. This is an important distinction since Pace of Performance is a more predictive indicator of future performance than just plain performance. Why? This is the application of the theory of Behavioral Momentum in practice. In essence, demand generation efforts are asking people to change their behavior (e.g., fill out a form or watch a video, etc.). Pace of Performance can identify those inflection points where change is most acceptable by your audience. Data is a needed element to make this analysis.

What are your thoughts on the uses of Data in Demand Generation? Share your thoughts on The Buzz Community.

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