What is JS Analytics?
Nov 4, 2025
When I started JS Analytics, I'd just spent 7 years bouncing between startups and Fortune 500 companies, watching the same pattern repeat: technically sophisticated, well-funded companies failing to operationalize their data.
In almost every case, these companies checked off the people and technology side of the equation. They had teams of smart, highly-credentialed data people, and access to the most robust tools on the market.
Eventually I realized the problem wasn’t a lack of tools or technology – there was a fundamental gap between data and operations. These companies were buying complexity when they needed clarity.
What We Actually Do
JS Analytics builds data and analytics infrastructure for early-stage startups that aren't ready for a full-time data hire but can't afford to fly blind.
Just like it would be risky driving your car without a dashboard, operating your business without an objective view into what’s happening behind the scenes is a recipe for disaster.
You should have visibility into what’s happening in your business, how customers are using your products and services, and where the biggest gaps are, without spending hours distracted from your day-to-day manually wrangling data.
The problem is, data professionals tend to specialize in one part of the data lifecycle (data engineers are good at building integrations, but often bad at business analytics), and quality, full-time data specialists are expensive.
Even if you happen to come across a data generalist who checks all the boxes (s/o analytics engineers), the fact of the matter is most early-stage companies don’t have enough work to justify hiring full-time.
And if you do, well, there’s a good chance you’re spending time on low ROI data activities like building advanced analytics before you really need them.
Obviously there are exceptions. But I’d wager that most full-time data teams within early-stage companies are cost centers.
Our goal at JS Analytics is to bridge that gap by focusing on what we call “zero-to-one analytics”. That is, building the core data and analytics assets that companies actually need in their early stages to answer critical questions and identify their biggest bottlenecks impeding growth. All of this while ensuring that what we’re building is scalable for when you do graduate from the zero-to-one phase.
The Hidden Cost of Operating Blind
Every day you do business in a sub-optimal way, you’re losing money. Inefficiencies and bottlenecks in your business mean there’s some profit not being realized or some factor weighing down your growth.
When you don’t have visibility into your data, you’re less likely to spot these inefficiencies and bottlenecks, and more likely to prioritize lower-value activities over the higher-impact growth levers you should be pulling.
I once signed up for a digital fitness coaching service. Completed registration, filled out an onboarding questionnaire, and then…nothing. I reached out to the company only to find out that part of their onboarding automation was broken and their systems never registered my completion of the questionnaire which would have triggered the next step in the process.
If this seems like an edge case, you’d be surprised how often these types of things happen with early-stage companies.
Monitoring the right metrics and setting up the right data-driven alerts helps you prevent situations like this turning into costly issues.
Who We Work With
JS Analytics is built specifically for early-stage companies with:
5-30 employees (that awkward size where you need infrastructure and insights but can't justify full-time hires)
An upcoming fundraise that requires investor-ready metrics
Engineers spending too much time on analytics instead of product
Previous bad experiences with freelancers who only solved part of the problem
We're here to build practical systems that answer real questions without breaking the bank. We’re also here as a partner to ensure those systems are actually used by your teams to help you operate more efficiently and grow your business.
Early-Stage Reality vs. Enterprise Best Practices
A lot of data advice is written for Series B+ companies. They'll tell you about machine learning, real-time streaming pipelines, semantic layers, and data contracts.
Here's what early-stage companies actually need:
Basic KPI dashboards
To ensure you’re headed in the right direction
To spot big gaps and inefficiencies
Basic operational analytics
To automate or augment time-consuming, manual processes
To streamline and improve daily decision-making
Basic data and analytics literacy
To ensure you’re building systems that will produce high-quality, usable data
To effectively leverage the data you do have (via #1 and 2)
We focus on meeting companies where they’re at. Not building expensive, advanced systems to accommodate some future world. Clarity > complexity.
Our Approach After 20+ Implementations
Tools don't solve problems, processes do: We use modern and affordable tools, but the real value is in how we structure your data and work with your teams to implement analytics into their daily workflows.
Ship and iterate quickly: We don’t develop in a vacuum. The best solutions are built collaboratively with business users, every step of the way.
Build for the handoff from day one: We document every system obsessively. When you're ready for a full-time hire, the transition is seamless. We’ll even help interview and onboard candidates.
The Typical Engagement Timeline
Month 1, Foundation: Connect all your data sources (CRM, product database, payment systems, etc.) into a central location. Clean and transform raw data into reusable models. First dashboards go live. This is when clients usually have their first "I had no idea that was happening" moment.
Month 2, Expansion: Iterate on and refine core dashboards to make sure you have visibility into what matters. Set up new reports, dashboards, and alerts that help teams optimize their daily operations and prevent things from slipping through the cracks.
Month 3, Optimization: Deeper dives into your data to answer questions you didn’t know you had. Complete documentation and training. Ensure foundations are set up to scale and handoff.
Month 4+, Maintenance: Ongoing support and maintenance. Metric reviews and strategy sessions. Continued development and ad-hoc analyses as needed. Transition support when you’re ready for someone internal to take over.
Moving Forward
If your team is wasting time on manual reports, scrambling for metrics before investor meetings, or making decisions without clear visibility, we should talk.
We’ll be honest if you're too early for our help or if there’s a cheaper, off-the-shelf solution that can solve your needs. But if you're at that inflection point where lack of visibility is holding you back, we can probably help.
Next steps if interested: Book a 30-minute discovery call with Josh (JS Analytics’ founder) or DM him on LinkedIn.
Thanks for reading!
