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frameworks and manuals, no hidden sales
π§ Prospecting, π£ Marketing, π€ Sales Enablement,π CRM, and π BI tools for the post-investment, growth-stage startup.
Use this list to research the tech stack you are building.
TLDR: Overanalysis = Missed Opportunities
Three frameworks for rational business decisions with incomplete data.
We summarize 3 genuinely awesome books into short, clear, actionable steps, that you can download, print, stick on the wall and win boldly while others drown in details.
-- Work In Progress --
TLDR: This is OUR One-Page Customer Development Interview framework
This interview is designed to validate a lot of our hypothesis about our clients. It evolves - as yours should too - as we are getting into deeper and deeper layers of our ICP mind.
Steal it, adapt it, use it. There's no free lunch though, you got to learn the underlying principles to get good at this. Read the books, or at least spend a few days researching and cross-referencing the concepts in them.
Troubleshooting guides for Marketing, Sales, support, and C-level:
Troubleshooting guides for Marketing, Sales, support, and C-level:
confusing and conflicting figures
confusing and conflicting figures
You need a data engineer to set up data quality checks in your pipeline, review data sources and calculations, and an analyst to ensure a single source of truth, even if your teams use their own independent data.
laborious data entry and reporting
laborious data entry and reporting
As your company grows, the data processes that evolved organically are reaching their limits. A data engineer should streamline the pipeline and implement best practices, while an analyst addresses key issues.
missing and inconsistent data
missing and inconsistent data
You need a data engineer to implement quality checks at data entry points and resolve logical errors in the BI pipeline, while an analyst ensures process synchronization and data requirements.
Slow and failing report generation
Slow and failing report generation
A data engineer needs to review the data pipeline and infrastructure systematically, addressing complexity. Industry best practices must compensate the complexity inherent to organizational growth.
teams disagree on basic numbers
teams disagree on basic numbers
You need an analyst to align sales and marketing teams with shared goals and knowledge, while a data engineer ensures accurate, consistent reporting to support collaboration and avoid misalignment.
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