Case Study
Overcoming Backlogs and Swiftly Identifying Former Customers in Salesforce.
Pain Point
Designating customers as "x-customer" required a time-consuming manual procedure that involved multiple steps in modifying the account and all related records impacted by the change in status.
Despite dedicating substantial resources to managing this process, the considerable data size and the labor-intensive nature of the procedure often led to frequent backlogs, resulting in an outdated database. Consequently, multiple departments relying on Salesforce's data functioned with incorrect information.
Path to Resolution
- Engaged with the team to gain a first-hand understanding of the steps taken, the reasons behind them, and the order of execution.
- Identified a reliable and accessible database source of truth that displays the status of customer relationships with the company.
- Presented a proposed build to our client, ensuring a transparent and mutually agreed-upon solution process.
- Implemented an end-to-end automated process that eliminated the need for manual intervention, utilizing standard Salesforce automation features. Additionally, we introduced a manual override fail-safe feature, allowing authorized system users to reverse any erroneous customer relationship updates quickly.
- Upon preparing the build for go-live, we coordinated with internal stakeholders to conduct a User Acceptance Testing (UAT) session, incorporated feedback, provided knowledge transfer of the system process, created pre-deployment communications, and established post-go-live monitoring and support plans.
Success Metrics
The transition from a time-consuming process to a fully automated system with minimal human intervention yielded significant positive business results. Instant data updates guarantee that every dependent department always has access to the most current client information. This continuous availability of real-time data strengthens interdepartmental cooperation and data-driven decision-making, resulting in improved business management and well-informed strategies.
The project brought enhanced operational efficiency, optimal resource allocation, and superior data quality, ultimately boosting overall productivity without increasing operating costs.
