Many companies that experience tremendous growth have data that describes their customer behavior spread across multiple disparate systems. This lack of visibility into the behavior of their customers impedes their ability to improve customer satisfaction, increase their renewal rates, and upsell existing customers. It is critical for a SaaS business to have a successful upsell strategy as dollar for dollar, upsell sales tend to be significantly more profitable than new business sales.
An example of this problem was presented to Proximous by one of the fastest growing SaaS software companies in the world. Sales executives did not have visibility into customers, and when they went to upsell them they ran into “surprises” that impeded their progress. Customer Success reps did not have a holistic view of their customers and this negatively affected their renewal rates. Executives at the company did not have the necessary 360 degree insights into their customers to truly understand customer behavior. Finally, the organization used Salesforce as their CRM and the sales reps spent all of their time in the CRM, so any solution had to be embedded in Salesforce to maintain workflow continuity.
Another problem was that Salesforce’s built in reporting capabilities provided limited visibility based on only the Salesforce data. In addition, the Salesforce data provided visibility that was constrained to a snapshot in time. The reporting that was required needed time based data that could support a sequence of events. This was desirable for the company to support their objective of deriving predictive analytics from customer data.
As the company had been growing aggressively, they had deployed a number of systems that housed a variety of data that they needed to aggregate to enable a single view into their customers. To achieve the goal, a requirement was to source and integrate data from a few disparate systems including:
- Salesforce – Sales, Leads & Orders Data
- Zendesk – Customer service Data
- Gainsight – Customer Predictive Scoring Data
- Product Logs – Product Usage Data
Proximous assisted in the design of a solution that ingests the data from Salesforce, Zendesk, Gainsight and Product Logs directly into a Data Lake that was housed in Snowflake database. The data was then prepped (integration, quality checks, unification and aggregation). Once the data was prepped, it was ready to be consumed for visualization and analysis leveraging Tableau.