CHALLENGE:
Eight critical contract data points that were causing revenue loss
Over time, the company had accumulated more than 15,000 customer contracts in its Docusign contract management system. To stay on top of these documents and access key details like renewal dates or licensing charges, the team had to invest significant manpower and hours. Over time, they had identified eight critical data points that needed to be tracked across contracts:
- Late payment fees
- Early termination fees owed by the customer
- Third-party pass-through price increases
- Penalties for invoice timeliness
- Penalties for late response time
- Annual rate escalations for labor and/or staffing
- Fees owed by the customer to relocate equipment
- Rate escalations for equipment and/or maintenance services
As tracking became increasingly complex, the company began losing revenue. Missed penalties, untracked escalations, and overlooked fees increased the risk of leaving money on the table. The leadership team worried about the financial blind spots hidden in thousands of contracts. With every missed data point, they risked not just revenue loss but also reduced profitability and weakened customer accountability. The fear of missing out on rightful earnings became a pressing concern, and the company retained Spaulding Ridge to find a smarter, scalable solution.
SOLUTION:
Extracting data points from contracts using advanced AI techniques
Spaulding Ridge approached the problem with one goal: to deliver the data the client needed in the simplest way possible. We took a two-level approach—one that made it easy to filter data, and another that enabled users to group and view relevant data in one place.
Using Docusign AI, we built eight models for each data point that allowed users to quickly search documents using contract-based terminologies. A user could now enter “early termination fees” into the system and instantly receive a list of documents containing that data point.
Recognizing that not all contracts use identical phrasing, we applied advanced AI techniques such as latent semantic indexing, complex keyword matching, and exclusion logic. This ensured that variations in terminology didn’t prevent relevant documents from surfacing. This extra layer of intelligence helped guarantee that no contracts were lost in the mix.
To build the second layer of data confidence, we developed real-time BI dashboards that automatically updated and summarized the number of contracts containing each data point. This gave the client a clear view of potential revenue tied to specific clauses in one place.
As we delivered the models, the company requested visibility into one additional data point: Contracts containing an equipment relocation with no cost clause. We fulfilled the request in under a week by leveraging existing models and advanced search techniques. The quick response addressed an immediate need in the project and ensured the solution was delivered within the agreed timeline.
Given that the success of any tool depends on user adoption, we conducted training sessions and created tailored presentations to onboard the team. These sessions ensured users could confidently navigate the tool, interpret the dashboards, and extract insights independently. By empowering the team with hands-on knowledge, we ensured they had complete visibility into their systems and could optimize the solution to its highest potential.
RESULTS:
Nine AI models scanning 15,000 contracts for lost revenue opportunities
The company asked Spaulding Ridge for a solution that would have required major human oversight without AI. With over 15,000 documents to review, tracking payment cycles and identifying costly contract clauses became unmanageable. The overwhelming volume, coupled with fatigue and human error, created significant room for mistakes.
What Spaulding Ridge built using Docusign Insights went far beyond basic data point retrieval. It enabled the company not only to identify documents with specific labels but also to detect variations in wording and return relevant results. From a business perspective, this has translated into significant revenue savings by reducing manual labor and recovering revenue that previously slipped through the cracks.
