Apollo.io Product Pivot Process

Leading a Product Pivot: A Customer Success Manager turned Innovation Leader

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Build for differentiation in an extremely saturated Revenue Tech market.

Apollo.io was a YC-backed, series A Data-First Sales Intelligence software company with a powerful, complex product. It was easy to sell but not easy to retain clients. And, there was no moving upstream. I was tasked with discovering what Apollo.io’s future product should solve for to add differentiated, pain killer value in a saturated competitive landscape that would retain customers. Here’s an overview of my process in discovering and documenting that solution, anonymized for security.

The Story:

I was hired as employee #5 as the second customer success and support manager. I got to build our customer success and support playbooks, platforms, processes, team, and collateral from scratch. 3 years later, I was promoted to Head of Innovation to lead the company’s strategic pivot. I was chosen for that role given my in-depth knowledge of the customers’ go-to sales tech stacks and operations, common issues, and unresolved pain points. Previously, I’d unearthed underserved needs and designed our stickiest solutions as a customer success leader.

Given my product intuition and design background, I had the skills needed to conduct market research, validate a problem spec, validate a solution spec, and work with a team to build that solution.

“Customer Experience is the Product before the Product is the Product.”

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1. Build Lean Canvas Business Models

First, we had a quarterly meeting and discussed potential product directions with all leaders in the company to be sure we were not leaving any explorations on the table. We ended up with 7 viable problems spaces to explore and validate.

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2. Write Research Scripts: Problem Space Validation

For each of the aforementioned business model canvases, I wrote and ranked the top issues I assumed would be associated with these problem spaces. I then wrote out a call script that would allow me to schedule calls with prospective customers in my target market and target personas to validate that the issues we intend to solve for each problem space are 1) real and 2) very important, important enough for the customer to want to talk again and eventually pay for a solution to fix.

These scripts were used to standardize every conversation I had with prospective customers so results were reliable. I also scrambled the order in which I asked customers problem-importance-ranking questions so as to not skew the results. I wanted to be able to reliably report the relative importance and rank of the problems in the problem space resulting from my interviews.

I interviewed 20+ qualified prospective clients per Lean Canvas Business Model. And, those results were added into a spreadsheet where they were quantified.

 

Validate and Build Iteratively

3. Following validating the problem landscape and prioritizing top valued problems to solve, we knew what we had to build.

With a validated strategic direction, we wrote a master product requirements doc for the new product to be built and began iteratively validating solutions with users who agreed to stay in touch from earlier problem validation interviews. We rolled new product changes out slowly over old, existing product.

Master PRD product areas graphic from master PRD.

This is a barebones wireframe of the new product’s core feature, the Playbook Builder.

Anonymized for security, this is a screenshot of one product area’s PRD, the Playbook Builder, and a list of features and behaviors for the new product.

Anonymized for security, this is a screenshot of one product area’s PRD, the Playbook Builder, and a list of features and behaviors for the new product.

This new product is still under development, being phased into production piece by piece by the Apollo team. However, this case study is here for you to get a gist for the general innovation process I designed to validate a new problem space to design solutions for, accurately prioritize and validate problems to solve and their solutions, validate those solutions, and work with designers and engineers to roll out the new, highly technical Sales Intelligence product iteratively.

Thank you for reading – feel free to contact me with more questions!

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