The Gong Goats: How Demandbase Grew Its Market Presence and Hiked Win Rates
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Gong
Tech Stack
- Salesforce.com
- Slack
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Revenue Growth
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Functions
- Sales & Marketing
Use Cases
- Predictive Quality Analytics
- Predictive Replenishment
Services
- Data Science Services
- System Integration
About The Customer
Demandbase is a marketing technology company headquartered in San Francisco, California. Founded in 2006, the company has grown to over 815 employees. The company's main goal is to ensure that its field organization is equipped with the intelligence it needs to have better conversations with prospects and customers, ultimately winning more deals, renewing customers, and increasing win rates. The company's CEO, Gabe Rogol, is focused on capitalizing on the vast opportunities in the marketplace. Demandbase has also absorbed three new companies in recent years, integrating their functionality into the current product.
The Challenge
Demandbase, a marketing technology company, was aware of the vast marketplace opportunities available but lacked a reliable method to uncover them. They needed a solution grounded in reality that could identify areas for improvement and growth to generate more revenue. The company was also facing the challenge of integrating the functionality of three new companies it had recently absorbed. This required a collaborative approach and the identification of data that could help increase their Average Contract Value (ACV).
The Solution
Demandbase implemented Gong to gain full visibility into its teams' performance and market opportunities. Gong's competitive trackers provided automated notifications when competitors were mentioned, which types of questions customers or prospects asked, and which objections they presented. This intelligence helped Demandbase build out objection handling responses and scale them out to the rest of the team. Gong also allowed Demandbase to identify its star performers and leverage their approaches to train the rest of the field, a technique referred to as 'cloning the A-players'. Furthermore, Demandbase used Gong's Deal Boards to pinpoint where conversations were happening or where there was a lack of activity, providing opportunities for learning and improvement. The company also created a Gong-specific Slack channel where sales development reps (SDRs) and reps could share Gong call snippets and use them as learning opportunities.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
IoT Data Analytics Case Study - Packaging Films Manufacturer
The company manufactures packaging films on made to order or configure to order basis. Every order has a different set of requirements from the product characteristics perspective and hence requires machine’s settings to be adjusted accordingly. If the film quality does not meet the required standards, the degraded quality impacts customer delivery causes customer dissatisfaction and results in lower margins. The biggest challenge was to identify the real root cause and devise a remedy for that.
Case Study
Prevent Process Inefficiencies with Automated Root Cause Analysis
Manufacturers mostly rely on on-site expert knowledge for root cause analysis. When the defective product is sent to lab for analysis, it is laborious and always a post-mortem one. Manufacturers that collect data from IT and OT also need a comprehensive understanding of a variety of professionals to make sense of it. This is not only time consuming, but also inefficiencient.
Case Study
Digitalising QC records
Ready-mix concrete batching plant with seasonal demand 6,000 to 12,000 cu.metre per month.Batch-cycle records for each truck is stored in paper format. 1000 to 2000 truck loads per month, generating ~2000 to 6000 paper records.QC anomaly detection in chemical batch-mixing is manual & time consuming.
Case Study
Automotive manufacturer increases productivity for cylinder-head production by 2
Daimler AG was looking for a way to maximize the number of flawlessly produced cylinder-heads at its Stuttgart factory by making targeted process adjustments. The company also wanted to increase productivity and shorten the ramp-up phase of its complex manufacturing process.
Case Study
CleanTelligent Enhances Janitorial Software Solutions with Infor Birst
CleanTelligent Software, a company that aids in-house and contracted janitorial teams in streamlining communication and improving quality control, faced a significant challenge. Their clients were demanding a more dynamic way to present reporting data. The company's software was primarily used to analyze and summarize a custodial team's performance, replacing a highly manual, paper-driven process. However, the initial differences between service providers in the janitorial industry are often unclear, and the cost of switching is comparatively low. This situation led to high client turnover, with a janitorial company's customer lifetime averaging four years or less. CleanTelligent needed to improve the customer experience with dynamic dashboards and reporting, retain customers through predictive analysis, capitalize on advanced analytics capabilities to build market differentiation, and improve client retention rates.
Case Study
Digitization of Pharmaceutical Packaging Machines: A Case Study of CVC Technologies
CVC Technologies, a leading manufacturer of pharmaceutical packaging machines, was seeking an end-to-end IoT solution to fully digitize their pharmaceutical liquid filling and capping machines. The company aimed to enhance the safety of their equipment, introduce digital maintenance capabilities, and gain visibility into machine status from anywhere at any time. The challenge was to find a solution that could provide real-time visibility into the machine's status, deliver direct cloud connectivity and digital services, and simplify all aspects of the machine's lifecycle, from engineering to maintenance.
