Eightball
Year:
2024
Service:
AI-Powered Analytics
Industry:
Marketing
Size:
5–10 employees
Client Website:
Eightball's analysts were drowning in data cleanup while million-dollar campaigns ran blind. Source built a self-healing analytics pipeline that cut data latency by 90% — turning their team from data janitors into strategic advisors.
Introduction
Eightball sells marketing intelligence to enterprise brands — the kind of clients who spend seven figures on a single campaign and expect real-time visibility into every dollar.
The promise was simple: connect all your marketing data, get instant insights, optimize on the fly.
The reality was messier.
Behind Eightball's polished dashboards was duct tape and manual labor. Data flowed in from 30+ sources — Google Ads, Meta, LinkedIn, Salesforce, custom tracking pixels, third-party attribution tools. Each had its own schema, its own quirks, its own way of randomly breaking at 3am.
When a client asked "how's our campaign performing?" the answer should have been instant. Instead, it required an analyst to:
Check if all data sources synced correctly (they usually hadn't)
Manually reconcile discrepancies between platforms
Apply transformation rules that lived in someone's head, not documentation
Generate a report that was outdated by the time it reached the client
Eightball's analysts weren't analyzing. They were babysitting data pipelines.
Challenge
The problem compounded with every new client.
A typical week at Eightball:
Monday: Facebook API changes without warning, breaking three client dashboards
Tuesday: Analyst spends four hours tracking down why conversion numbers don't match between platforms
Wednesday: Client launches $2M campaign, asks for hourly performance updates
Thursday: Same client's data is 6 hours behind because a sync failed overnight
Friday: Emergency meeting about why insights are always "too late to be useful"
The technical issues were obvious:
Fragmented data sources with incompatible formats
Frequent API changes requiring constant manual fixes
No data quality control — garbage in, garbage out
Hours of latency between campaign actions and visible results
But the strategic problem was worse: Eightball was selling proactive intelligence while delivering reactive reporting.
Clients weren't paying for pretty charts. They were paying for the ability to make faster, smarter decisions than their competitors. And Eightball couldn't deliver because their own infrastructure was too slow.
Solution
Source didn't just fix Eightball's data pipelines — we made them intelligent.
We built a self-healing analytics infrastructure that treated data quality as a continuous process, not a one-time cleanup.
The new system:
Adaptive connectors for 30+ data sources that automatically adjusted when APIs changed
AI-powered anomaly detection that caught data issues before they reached dashboards — duplicate records, missing fields, suspicious spikes all flagged and corrected automatically
Real-time normalization transforming disparate data formats into a unified schema on ingestion
Intelligent retry logic that handled transient failures without human intervention
Continuous validation running automated quality checks across every data point
But the real innovation was making it all self-documenting and transparent. When the system made a correction, it logged why. When data looked suspicious, it showed its reasoning. Analysts could trust the automation because they could see its work.
Result
Two months after launch, Eightball looked like a different company:
90% reduction in data latency (hours → minutes)
60% less time spent on pipeline maintenance and data cleanup
40% faster campaign optimization cycles — clients could test, learn, and iterate in the same day
Zero manual interventions required for routine data issues
But the transformation went deeper than metrics.
Analysts' roles fundamentally changed. They stopped spending their days fixing broken syncs and started identifying patterns in client behavior. They moved from reactive problem-solving to proactive strategy — spotting opportunities before clients even asked.
Client conversations changed too. Instead of "here's what happened last week," it became "here's what's happening right now, and here's what we recommend for the next three hours."
Eightball's Head of Analytics described it perfectly: "We used to deliver hindsight. Now we deliver foresight."
The platform didn't just clean data faster — it got smarter over time. Every anomaly it caught improved its detection algorithms. Every API change it adapted to made it more resilient. What started as a data infrastructure project became Eightball's core competitive advantage.
Today, when enterprise brands evaluate marketing analytics platforms, they're not just comparing features. They're comparing speed of insight. And Eightball is consistently hours ahead of the competition — not because they have more data, but because they can actually use it in real time.
