Turning Data Exhaust into Profit:

The growing demand for data is forcing many companies to look at what was previously an untapped revenue stream - data exhaust.  That’s where Gulp comes in - helping businesses unearth, appraise, and cash in on their untapped data assets.

Jeremy Bruck, a leader at Gulp, explains their novel approach: "We are doing to data what Zillow does to residential real estate when they're coming up with their Zestimate." By dissecting a company's data attributes, quality, and volume, Gulp can forecast potential revenue and pinpoint profitable commercialization opportunities.

Companies that have never licensed their data before are using that information to licensed their data before are realizing that

From Digital Landfill to Data Goldmine: Transforming Business Byproducts

For many organizations, data has long been viewed as a necessary expense rather than a potential revenue driver. Bruck notes, "Where we've seen the most success is companies that never have viewed their data as their core competency. It's been a cost center, it's been exhaust, and we're helping elevate the perception of the technology function, of the analytics function, to be able to be viewed as a revenue generator or profit center."

This paradigm shift can lead to substantial financial windfalls. By partnering with Gulp, companies are able to:

1. Uncover valuable data assets hiding in plain sight

2. Identify lucrative use cases and target markets for these data assets

3. Craft data products tailored to specific buyer segments

4. Move from exploration to action to revenue 

"We're taking the same underlying dataset, but creating different products that have different use cases or applications for different audiences, and then using that to figure out what's the overall potential of the asset," Bruck explains.

Consider a B2B distributor, for instance. They possess a wealth of information on suppliers, products, and customer transactions. This data can be transformed into valuable insights on supply chain dynamics, logistics efficiency, geospatial analytics, customer buying behavior, demand forecasting, and product preferences across different geographies. Each of these insights can be packaged as distinct data products, catering to various industries and use cases.

The Playbook:

For companies looking to strike it rich with their data exhaust, Bruck offers several key insights:

Capitalize on proprietary first-party data: "We're seeing real interest here because if no one else has access to this data, it could represent an advantage for the first buyers. Buyers are willing to dig in to see the value it can unlock for them”

Explore cross-market opportunities: Unlike some competitors who focus on specific industries, Gulp takes a broader approach. "We're crossing markets. We're trying to take those same raw ingredients and use them to make different recipes, and serve those recipes to the customers / buyer segments where there is demand"

Fast-track time-to-revenue: "Accelerate the path to get the first data monetization dollar in the door...it takes the exercise from theoretical to tangible and enables a company to transition from, 'I think we could monetize our data' to 'We are generating revenue from our data assets"

Lending Against Data: A New Vehicle in Asset-Based Financing

One of Gulp's most innovative offerings is the ability to use data as collateral for loans. This groundbreaking approach opens up new avenues for companies to leverage their data assets beyond traditional monetization strategies.

Bruck explains the process: "For the data assets that we are taking as collateral, we actually go through a daily revaluation process. So we are constantly marking to market the assets that we have collateralized to be able to keep a pulse on what is the value of that collateral, knowing that these markets are changing and changing fairly quickly"

This daily revaluation is crucial, as the value of data can fluctuate based on market demands, seasonality, and other factors. 

However, Bruck emphasizes a conservative approach to this novel form of lending: "We take a conservative approach to our underwriting because this is still a relatively new asset class, and what we're doing is still on the leading edge of the space. We are not trying to overextend the way that we think about the collateralization of data".

Challenges Persist

Despite the immense potential, challenges remain in the data monetization landscape. The process of buying and selling data is still cumbersome, with lengthy sales cycles and complex reporting requirements. Addressing these friction points will be crucial for creating a truly fluid data marketplace.

Bruck identifies two key factors that could accelerate the adoption of data monetization:

1. Normalization of data commercialization: "Having more publicly available case studies, having more companies normalize data commercialization, removing some of the taboos and misconceptions about what it takes to actually commercialize data." This shift in perception can help companies see data monetization as a standard business practice rather than a risky or complex endeavor.

2. Accelerating the path to first revenue: "Doing that takes the exercise from theoretical to tangible and goes from, 'Hey, I think we could monetize our data' to 'We are actually generating revenue from this.'" This tangible success can serve as a catalyst for further data monetization efforts within an organization.

As more companies successfully monetize their data, it creates a virtuous cycle. Bruck explains, "New data providers with valuable, novel datasets are in demand from buyers; those transactions add liquidity to the market and demonstrate the potential revenue streams available with data licensing; those proof points increase the number of data providers / companies that are open to exploring data commercialization.” 

The Road Ahead: Bridging the Gap

The future of data monetization hinges on bridging the gap between data providers and buyers. This involves streamlining the process of data exchange, from discovery to delivery and ongoing management. As the industry matures, we can expect to see innovations that address current pain points, such as:

• Simplified contract negotiations and standardized agreements

• Automated data delivery and integration systems

• Improved tools for data quality assurance and compliance monitoring

• Development of industry-specific data marketplaces and exchanges

As Bruck puts it, "We are in a lot of ways ahead of a wave that has yet to crest." For forward-thinking companies willing to explore the potential of their data assets, a new market is ripe for the taking.The key to success will lie in embracing collaboration, focusing on unique and valuable datasets, and continuously innovating to meet the evolving needs of data buyers across industries.