“The experience of using Basedash for the first time is pretty magical.”

Ordinal is a social media management platform that helps teams draft, plan, collaborate on, and schedule posts across channels like LinkedIn, Twitter, and Instagram. With a heavy self-serve customer base and a growing mountain of social media data, co-founder Jeffrey Zhao needed a way to go from question to insight without pulling engineers off the product.

Before Basedash, the team was flying partially blind. They had PostHog for event-based analytics and Stripe’s native reporting, but nothing that could handle deeper, database-level questions — or bring all their data sources together in one place.

“We were looking for a way to get those kinds of queries more directly, and also aggregate different sources of truth — PostHog event data, database data, Stripe data — all in one centralized place.”

Scattered tools, scattered insights

Ordinal’s analytics stack was split across multiple tools. PostHog handled event sequences well, but its SQL product wasn’t mature enough for the kinds of ad-hoc queries the team needed. Stripe gave them billing data in isolation. The production database had everything else, but getting answers out of it required engineering time.

The team even considered building something in-house. But the real cost wasn’t just the engineering effort — it was the constant friction of moving between different tools and never having a unified picture of what was happening across the business.

Why Basedash

Jeffrey found Basedash through a social post about automated weekly reporting — specifically, the idea of setting up customized reports that run on a schedule and surface insights about what’s working and what isn’t.

“Getting to just natural language query a question I have as a more non-technical person and not have to bother our engineering team is amazing. And getting this stylized chart back that I can then just send a screenshot or share with the rest of the team is really awesome.”

The team connected their Supabase production database, their PostHog analytics, and their Basedash Warehouse — bringing everything into a single conversational interface. Within days, they had dashboards covering product usage, acquisition metrics, and conversion analysis, plus a weekly automated report delivering insights directly to Slack.

Unlocking PLG onboarding insights

For a company where most customers are self-serve, understanding what drives activation is critical — but also easy to deprioritize. Without someone actively checking the data, onboarding insights tend to get lost in the noise.

With Basedash, Ordinal set up automated reporting to passively surface behavioral patterns: which actions correlate with conversion, what early user behaviors predict long-term retention, and where the self-serve funnel breaks down.

“The self-serve onboarding stuff is one of those hidden things that’s always easy to deprioritize because you’re not tangibly hearing from customers about it. Having this sort of passively happen is actually a huge value add.”

Instead of manually checking PostHog dashboards or filing one-off data requests, the team now gets a regular, structured view of onboarding health — delivered automatically.

Powering Ordinal Data Labs

One of the most interesting ways Ordinal uses Basedash goes beyond internal analytics. The team sits on a massive dataset of social media posts across LinkedIn, Twitter, and other platforms. Social media is notoriously opaque — platforms don’t explain their algorithms, and the space is full of unverified rumors about what works and what doesn’t.

Ordinal launched Data Labs, a content series that uses their data to answer questions the platforms themselves won’t. Does including a link in a LinkedIn post actually hurt reach? Do different reaction types affect performance? The team uses Basedash to query their production data, generate charts, and turn statistically significant findings into blog posts and social content.

“We actually have statistically significant data and can tell you what the real impact is. We’re creating a series of content based on all of this data as a top-of-funnel marketing motion — which is a really interesting use case for Basedash.”

What started as an internal analytics tool has become a core part of Ordinal’s content strategy — turning proprietary data into published research that drives awareness and trust.

Impact

Since adopting Basedash, Ordinal has gone from scattered, tool-by-tool analytics to a unified data layer the entire team can use:

• Three data sources — production database, PostHog, and data warehouse — connected and queryable through a single interface
• Dashboards covering product usage, acquisition, and conversion built without engineering involvement
• Automated weekly reports delivering onboarding and activation insights to Slack
• A non-technical co-founder self-serving data questions that previously required engineering time
• Proprietary social media data turned into published research through Ordinal Data Labs

“The experience of using Basedash for the first time is pretty magical. Getting to just ask a question and get a stylized chart back — that’s really awesome.”