Poggio Labs
I helped companies make the most of their customer data, focusing on how data is configured and how its surfaced in the CRM's core views. Here are a few things I worked on.
Extending the integration setup and configuration
Increasing speed to value by enabling our users to self-serve activation
For each new customer Poggio onboarded, it required work from 3 teams help set them up be cause the product didn't allow for configurations. We also learned from feedback that users refrained from adopting integrations that captured critical customer touch points despite it being crucial for their CRM.
In 1.5 months, we streamlined the setup flow and added configurations so users can self-serve integrations. As a result, existing and future customers could self-serve onboarding without involving customer success, leadership and the integrations engineering team.
Contributions
End-to-end design
Scope alignment
Design system
Hybrid team
CTO (acting Product Manager)
Tech lead
Engineer
Investing in a customer data pipeline
Acquiring more customers by giving users more data
Customers weren't able to leverage their customer data effectively to drive sales motions as the information was rudimentary and hard to consume. Improving data visibility and structure would support Poggio's goal to increase customer acquisition and retention.
To address this, we invested in a pipeline that transformed the way data is shown in the product and created a framework for future data sources. Users can now access 6 categories (~40+ types) of data across the core product areas (accounts, contacts and opportunities), empowering them to make informed decisions and accelerate sales processes.
Contributions
Hybrid team
Front-end engineer
A systems approach to investing in a data pipeline
Categorizing data to scale
Despite a fuzzy Ideal Customer Profile (ICP), I defined data categories commonly used by SMBs and Enterprises. This enabled our team to seamlessly integrate new data into the product.
Defining the quality of data
The type of interactions users have with customers is crucial, but it's the quality that drives organizations' sales strategies. Each data point answers the who, what, when, and where to showcase this interaction quality.
Structuring the data
While data is shared between objects, not all objects are on the same hierarchy. Differentiation is created for the same types of data.
The activity feed and its expanded state in the context of an account when I inherited it.