Technical Product Research Before Product Management Interviews
- Harshal
- 16 hours ago
- 6 min read
Deep-Dive Using My Directus Product Memo Example in 2025
In earlier posts, I shared a framework to write a case study or product memo when preparing for Product Management interviews.
Here, I show an example I did for Directus a few months ago when I interviewed with them. All the information I share here was from my own analysis. Since this doesn’t have Directus employee inputs, the information may not be accurate, but I hope it gives you ideas on the approach.
I spent 60 minutes writing this after a few hours of research. You need 6 minutes to read this.
Related:
Tips For Your Product Memos
Writing a product memo forced me to structure findings, test assumptions, and explain insights clearly. This made my interviews stronger and my evaluation of the company more grounded. With most companies I spoke to, my research process could identify the red flags these employers wanted to hide and the green flags they wanted to highlight.
Tips:
Create your own artifacts (scrape forums, test the product, etc.) instead of citing third-party blogs.
Talk to actual users or similar personas.
Test the product hands-on within a small budget.
Use frameworks like SWOT or Business Model Canvas to structure your thinking.
Read more in Cracking Startup PM Interviews By Doing A Case Study.
1 - Context, Goal
Goal:
Drive product leadership in a company looking to grow into the CMS and Backend-as-a-Service (BaaS) categories.
Increase developer adoption, convert open-source users into paying enterprise customers, and enable both: a) community-driven innovation and b) commercial growth.
Desired Outcome:
Improve time-to-value for both developers and non-technical users building internal tools.
Some questions I tried to answer:
Should the company focus on community-requested features or enterprise-requested ones?
Should the company prioritize Directus Cloud or the self-hosted platform?
How do enterprise leads find this product? If it's through community, then community is the base / first contact.
What is the customer journey map for an enterprise user? What's the path for a community user? Is the community user becomingan enterprise user? What's the conversion at each step?
2 - Identify The Users
Target Users
Developers and technical teams needing backend scaffolding (auth, API, CRUD, permissions) without building from scratch
Data engineers or ops teams needing a visual layer for SQL data
Internal tool builders at startups and mid-sized enterprises
Citizen developers managing data workflows
Not Target Users
Marketing teams looking for WYSIWYG editors
CMS-focused content creators
Analytics-only users expecting BI functionality
3 - Identify User Needs
The product serves several distinct user types, each with its own set of needs and frustrations.
Developers want an instant backend on top of SQL. They care about having full control, API-first access, and no vendor lock-in. Their expectation is a backend-as-a-service that behaves like a headless CMS but keeps developer autonomy intact.
Data analysts and operations teams need a unified view across multiple SQL sources. They struggle with siloed data, manual exports, and repetitive work when connecting data from different databases. They look for an open data platform that simplifies access and transformation.
Open-source users want a clear roadmap and transparency in decision-making. They are often frustrated by unpredictable release cycles and lack of visibility into how community feedback influences the product.
4a - Notes From Product Test Drive
I took the product for a test drive and wrote some notes with the goal of finding areas of improvement.
Areas of Excellence
Data Modeling Flexibility: Product offers strong schema creation with advanced field types, AI-suggested data models, and JavaScript examples.
Integration Paths: Built-in REST API, Data Studio, and Appsmith integration.
Automatic API Generation: Instantly generates REST endpoints for all collections.
Areas for Improvement: Onboarding
Password Security: Sends passwords in plain-text emails instead of one-time secrets.
Unclear Starting Points: Default templates don’t align with user needs.
Slow Setup: Long project creation delays and unclear status updates.
Localization Issues: Sandbox interface switching languages unexpectedly.
No First-Step Guidance: New users often feel lost without guided onboarding.
Frontend Options: Lacks clarity on how to create public-facing apps from data.
Areas for Improvement: UX
Navigation Confusion: Hard to find data models or switch between content and schema.
Hidden Functionality: Important actions buried in “three dots” menus.
Poor Feedback Loops: Icon searches show no loading or empty-state cues.
Side Navigation: Non-expandable, making section names hard to read.
Broken Links: Documentation occasionally 404s.
Context Switching: Difficult to move between related views (data ↔ content).
Areas for Improvement: Functionality
API Clarity: No built-in API playground or hierarchy visualization.
Bulk Operations: Missing multi-create or multi-import flows.
Import/Export: Manual and multi-step, lacks field mapping tools.
Frontend Bridge: No clear path from backend data to frontend delivery.
4b - Competitive Summary
Headless CMS competitors:
Sanity, Contentful, Strapi, Storyblok, Hygraph. Strengths: strong visual editing, templates, cloud-native hosting
BaaS competitors:
Supabase, Firebase, Hasura. Strengths: developer-first, integrated auth, strong SDKs
Low-code data platforms:
Retool, Appsmith, Metabase. Strengths: rapid internal app development, BI integrations
The product is between a developer-first backend and a visual data platform. Each direction offers growth but demands trade-offs. There could be a way to make both work, but it sounds like a hard path.
Competitors increasingly embed AI to assist users. For example, PostHog, Supabase, Lovable, n8n, and Metabase.
AI-powered onboarding, schema suggestions, and query generation can help Directus shorten time-to-value for new users.
5 - Identify Feature Improvements
I focused on opportunities that complement the product strengths while addressing gaps:
Complementary product strategy: Build a path from free open-source use to paid enterprise features. That will help find upsell opportunities.
AI onboarding: Help users auto-generate schemas or sample dashboards.
Template library: Use-case templates for internal tools or content models.
Business user handoff: Provide preview modes or shareable environments for non-developers to enable handoff from developers.
6 - Execution Plan
Although I usually prefer to write this section, I did not have a lot of new details to add here that I can also show externally. So, I am showing you that usually we should have this section, but not showing you the details here.
7 - Go-To-Market Plan
Directus’s growth has relied heavily on word of mouth within the developer community. Strengthening that engine remains key.
In the discovery stage, individual developers find Directus through templates, GitHub auto-deploy options, and search visibility. The goal is to make it effortless for them to spin up a project and see value within minutes.
During the community stage, users engage in forums, Q&A threads, and discussions where they share use cases. Growth here depends on strong showcases, gamified engagement, and well-maintained example templates that inspire experimentation.
At the evangelism stage, a satisfied user begins proposing Directus internally at their company. “Pitch Directus” kits and ready-to-use internal templates can help advocates make the case to their teams.
In the decision-making stage, company stakeholders review proofs of concept and compare feature sets. Usage analytics, ROI estimation tools, and well-timed upgrade prompts can highlight business value.
The conversion stage follows when the company purchases a license. Smooth paid-plan onboarding, SSO setup, enterprise support, and team billing tools help increase customer usage of the product.
To continue the flywheel, In the expansion stage, more teams within the company start using Directus. Training programs, certification, usage dashboards, and expansion-tier pricing encourage organization-wide rollout and long-term retention.
8 - Metrics And Counter-Metrics
To measure success, Directus should track product and user engagement metrics along with counter-metrics to maintain balance.
Cloud activation rate:
The cloud activation rate should increase as more signups create active projects. Whereas, a rising number of users abandoning the setup flow would signal onboarding issues that need attention.
Time to value:
The time to first internal tool built should fall below one day, showing faster time to value. Whereas, a surge in setup-related support tickets would indicate that complexity still exists.
Upgrade:
Free-to-enterprise conversion is another key measure, tracking how many open-source users adopt the paid tier. If the open-source roadmap becomes overcomplicated or overly commercialized, it may harm trust.
User Persona:
Tracking the ratio of developer to non-developer users shows how the product broadens its audience. Yet if both personas find the interface confusing, that ratio loses meaning.
Feature Adoption:
Finally, feature adoption for advanced capabilities like RBAC or WebSockets should reach meaningful use within a few months. Overbuilding features that few users adopt would show misplaced effort.
9 - Evaluate Risks And Trade-Offs
CMS vs Data platform:
The company is positioning itself as both a CMS and a data platform. The dual branding can create confusion. If the team can communicate the differentiation well, then it will be in a unique spot.
Self-hosted vs Cloud:
A fragmented roadmap between the self-hosted and cloud products could slow innovation. Aligning both is necessary but can make delivery slower.
Dev vs Business users:
Improving user experience may not benefit developer-first users who prefer flexibility and control. Yet ignoring UX limits wider organizational adoption.
Reflection
This exercise helped me practice evaluating product-market fit, competitive differentiation, and execution trade-offs under ambiguity. It made my interview conversations sharper and helped me see how product direction choices affect long-term strategy.
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