Scrut Automation achieved 8x faster analytics and saved 80 engineering days by partnering with Optiblack for a unified, cost-efficient analytics infrastructure.
Client: Scrut Automation | B2B SaaS Platform for Governance & Compliance
Challenge: 1,000+ customers with fragmented data across multiple sources, preventing cohort analysis and usage-based insights
Solution: Unified analytics infrastructure with multi-source data integration, built on existing tech stack (AWS + Metabase)
Results:
Scrut Automation is a leading B2B SaaS platform that helps companies achieve and maintain their first set of compliance certifications including SOC 2, ISO 27001, GDPR, and HIPAA. As a fast-growing governance and compliance solution, Scrut serves organizations looking to streamline their GRC processes.
With over 1,000 customers and rapid market expansion, Scrut reached a critical inflection point: they had rich customer data but couldn't make sense of it fast enough to drive product-led growth.
As Scrut's Head of Product describes it, the company was operating "in the dark" when it came to customer intelligence. "We had more than 1,000 customers, but we couldn't understand the different cohorts, overlaps, and usage patterns. We needed to make sense out of analytics from various sources of data and solve all of them together."
1. Fragmented Multi-Source Data
Customer data was scattered across multiple systems with no unified way to collate information. Each analytics question required manual data gathering from various sources—a time-consuming and error-prone process.
2. No Cohort Analysis or Segmentation
Without unified analytics, Scrut couldn't segment customers based on various parameters:
The analytics they could generate were "miniscule" compared to what they needed to drive strategic decisions.
3. Engineering Bottleneck
Every analytics request required engineering resources to pull data, create queries, and generate reports. This dependency meant:
"There was an obvious gap," recalls the Head of Product. "We wanted to be data-driven and move fast, but we couldn't. If nothing had changed, we would have spent 5x the amount of time just to get data. We might have stopped at the first try, gotten wrong analytics, and our entire analytics charter would have been at risk."
The implications were severe:
The cost of inaction was clear: Scrut would remain in the dark about their own customers, unable to execute on their growth ambitions.
Scrut considered building analytics infrastructure in-house but recognized critical barriers:
The Reality Check:
1. Speed to Value: Weeks, Not Quarters
"Optiblack got it done in weeks instead of taking a quarter or two. We needed the ability to get this up and running fast."
2. Cost Efficiency: Fraction of Internal Build Cost
"We could do it at a fraction of the cost compared to building in-house. It was higher quality and more efficient than if we had done it ourselves."
3. Expertise & Consulting Partnership
"This was the first time we were doing something like this. We needed someone who had done this before—who brought credibility and could understand the nuances from both a data and consulting perspective. Optiblack was the reason we finally did this instead of continuing to put it off."
The partnership allowed Scrut to treat analytics infrastructure as a minimal-cost experiment with an experienced partner, removing the primary barrier that had prevented them from tackling this challenge.
What differentiated Optiblack's approach wasn't just technical execution—it was the consulting partnership model that emerged.
Blue-Sky Planning, Not Just Requirements
"We didn't confine discussions from a requirements point of view. We went broad and very long—having blue-sky discussions about where we wanted to be in 1 year. We looked at our entire analytics charter together."
Build-Operate-Transfer (BOT) Model
Optiblack didn't just build and hand off a system. They:
Fair and Transparent Pricing
"The cost was reasonable—they weren't overcharging us. That trust made the partnership work."
Architecture: Built on Existing Infrastructure
Rather than introducing new SaaS vendors, Optiblack leveraged Scrut's existing stack:
This approach meant:
Key Capabilities Delivered
1. Unified Data Pipeline
2. Module Usage Analytics
3. Self-Service Analytics
4. Investor-Ready Reporting
8x Faster Analytics Turnaround
"The turnaround time to do analytics that I actually got done within a week would have taken a month before—about 1/8th the time."
Engineering Resource Savings
Self-Sufficiency Achieved
"Our dependency on the engineering team went away completely. We were able to get complex analytics—understanding best vs worst customers—without needing to involve engineering."
"Rich Eyes and Ears" on Customer Behavior
"The business now had rich eyes and ears into what customers wanted to say through their usage. We moved from darkness to being well-lit—able to make sense out of our data."
Data-Driven Product Decisions
The analytics revealed critical insights that shaped Scrut's roadmap:
Investor Credibility
"We're now able to give data to investors proactively—what they ask for and what we want to highlight. The credibility this brings to the organization is invaluable."
Two Worries Eliminated
"We never had to worry about two critical items: the design of the analytics and the quality of the analysis. Optiblack handled both expertly."
This confidence allowed the product team to focus on interpreting insights and making decisions rather than questioning data quality or methodology.
"Optiblack got it done in weeks instead of taking a quarter or two. It was higher quality and more efficient, delivered at a fraction of the cost."
"We didn't confine ourselves to just requirements—we had blue-sky discussions about our entire analytics charter. Optiblack wore a consulting hat, giving us inputs as a collaborative partner. They brought the credibility of 'who has done this before' while understanding our unique nuances."
"The business now has rich eyes and ears into what customers are saying through their usage. We moved from darkness to being well-lit. Without this, we would have made biased decisions based on incomplete information."
"The turnaround time went from a month to a week—about 8x faster. And we saved 80 engineering days, equivalent to 2 full-time engineers. Our dependency on engineering for analytics went away completely."
"We never had to worry about the design of the analytics or the quality of the analysis. The output was more than worth it."
— Head of Product, Scrut Automation
Reflecting on the engagement, Scrut's Head of Product shared valuable insights:
1. Broad Approach Over Narrow Metrics
"From an execution point of view, we initially thought about a couple of metrics, but we went broad instead. That was the right call—it gave us a comprehensive view rather than just point solutions."
2. Trusting the Partnership
"The collaborative partnership model worked perfectly. Having someone who had done this before and could guide us was invaluable."
Go Even Faster
"If I had to do it again, I would have taken more bandwidth full-time and gotten even more from Optiblack, not less. We could have moved faster if we'd dedicated more resources on our side."
Start Earlier
"The only regret is that we didn't do this sooner. Optiblack was the reason we finally tackled this—we had been putting it off because it seemed too complex and expensive. They proved both assumptions wrong."
For fast-growing SaaS companies like Scrut, speed of insight translates directly to competitive advantage:
Before Optiblack:
After Optiblack:
This transformation happened in weeks, not quarters—a critical differentiator in competitive markets where customer intelligence drives product-market fit and growth efficiency.
Scrut's journey offers valuable lessons for scaling SaaS companies:
1. Speed is a Feature
In fast-moving markets, 8x faster insights mean 8x faster iteration on product decisions. The team that learns fastest wins.
2. Don't Let Perfect Be the Enemy of Done
Scrut could have spent 6+ months building the "perfect" internal solution. Instead, they got a working solution in weeks and started learning immediately.
3. Partnership > Vendor Relationship
The consulting partnership model—where Optiblack collaborated on strategy rather than just executing requirements—delivered far more value than a traditional vendor engagement.
4. Leverage Existing Infrastructure
By building on Scrut's existing tech stack (AWS + Metabase), Optiblack eliminated procurement friction and reduced time-to-value.
5. Measure Opportunity Cost
The 80 engineering days saved weren't just a cost reduction—they enabled 2 engineers to build customer-facing features instead of internal tools.
6. Go Broad, Not Narrow
Starting with a comprehensive analytics charter rather than point solutions created a foundation for long-term growth rather than tactical quick wins.
7. Credibility Compounds
The ability to proactively share data-driven insights with investors didn't just answer questions—it established credibility that compounds over time.
With the foundation in place, Scrut continues to expand its analytics capabilities with Optiblack's ongoing support:
The partnership has evolved from a tactical project to a strategic relationship, with Optiblack serving as Scrut's extended data and analytics team.
Optiblack is a digital transformation partner specializing in data services, product analytics, and AI solutions. We help fast-growing companies build the analytics infrastructure they need to scale—in weeks, not quarters.
Unlike traditional consulting or pure outsourcing, we partner with clients through a collaborative BOT model:
✓ Speed: Deliver in weeks what would take internal teams quarters
✓ Cost efficiency: Fraction of the cost of building in-house teams
✓ Consulting expertise: "Done this before" credibility + your unique context
✓ No vendor lock-in: Built on your existing infrastructure
✓ Collaborative partnership: We don't just build—we guide your strategy
If you're operating in the dark when it comes to customer intelligence—if analytics requests take weeks instead of days, if your engineering team is bottlenecked by data requests, if you're making product decisions based on intuition rather than evidence—let's talk.
We'll help you achieve what Scrut achieved: 8x faster insights, zero engineering dependency, and rich eyes and ears on your customers.
Book a consultation: book here
This case study was developed in partnership with Scrut Automation. All metrics and outcomes have been verified by the customer. October 2025
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