A leading American multinational cybersecurity company with headquarters in Santa Clara, California. Its core products are a platform that includes advanced firewalls and cloud-based offerings that extend those firewalls to cover other aspects of security.
Though data in Salesforce is mostly structured it can be subject to inconsistencies. These inconsistencies arise due to various reasons – behaviour of users, integrations from other systems, data migration from older CRM’s, organizational changes such as mergers and acquisitions, etc.
Salesforce org accumulated a ton of data and users rely on reports and dashboards to guide their decisions.
SpringML implemented a pipeline management solution combed through Salesforce data to find hidden patterns and trends. This solutions helps answer and highlight things such as:
- What are the main differences between opportunities that won vs those that were lost?
- Do these changes by region or product?
- How reliable is your open pipeline amount?
- How many opportunities have been pushed out consistently to the next quarter?
- How many opportunities have a close date that’s more than a few months out?
Can you realistically count such opportunities in your active pipeline? The solution leveraged history objects in Salesforce or take snapshots if history is unavailable.