Productboard Spark, AI built for PMs. Now available & free to try in public beta.
Try SparkProductboard Spark, AI built for PMs. Now available & free to try in public beta.
Try Spark
company founded
2013
location
United Kingdom
"The context and insights in there help. The result? Drastically reduced review cycles and higher confidence when presenting to stakeholders."
Lead Product Manager
Productboard Spark
11th March 2026
Software
company founded
2013
location
United Kingdom
"The context and insights in there help. The result? Drastically reduced review cycles and higher confidence when presenting to stakeholders."
Lead Product Manager
As engineering teams begin to accelerate their delivery with AI, product teams are focused on ensuring that speed translates into rapid delivery of customer value. That's exactly what happened at BigChange.
BigChange, part of Simpro Group, is the AI-first operating platform for the trades and field service industry. Moving beyond traditional FSM software, BigChange provides an all-in-one ecosystem that empowers UK-based businesses to transform their operations through practical AI and smart automation.
By centralizing the entire journey—from CRM and intelligent scheduling to real-time tracking, financial management, and compliance—BigChange enables companies to work smarter, grow faster, and reclaim valuable time in a high-pressure, fast-paced market. We don't just manage jobs; we provide the clarity and control needed to turn operational efficiency into unstoppable business performance.
Following BigChange’s acquisition by Simpro Group, the product team gained access to Productboard and was rapidly onboarded into new, more efficient ways of working. By leveraging the platform’s advanced capabilities, the team was able to immediately enhance their product processes and align every decision with real customer feedback and strategic goals.
Following the Simpro Group acquisition, BigChange's product team onboarded to Productboard. The platform transformed how Charlie Thacker and Andy Knight, both Product Managers at BigChange, worked—providing a centralized place for insights, roadmapping capabilities, and multiple stakeholder views that had previously been scattered across Miro boards, emails, and disparate systems.
It was a massive step forward in evolving their product processes, but new challenges emerged quickly.
As BigChange integrated into Simpro Group, the focus shifted toward evolving the product development lifecycle through innovation. With engineering teams beginning to leverage AI-powered tools, the product team recognized a natural opportunity to modernize their own workflows. The goal was to harness these new technologies to synthesize vast amounts of data more effectively, ensuring product strategy remained data-driven and focused on solving the most critical customer problems.
"We were doing product better than we had before," Charlie explained, "and it was taking a while to get things into a product brief, backing it up with insights, and then understanding the impact, the reach."
The team faced a painful irony: their improved product practice was slowing them down. Each product brief required:
These were all the right things to do. But the manual effort was significant, often consuming up to a week per brief.
"We recognized we couldn't become a bottleneck in delivering customer solutions," Andy Knight explained, The team tried exporting Productboard data into Google Gemini to accelerate product brief generation, but generic AI tools didn't understand their product context. "We were taking information outside of Productboard to start generating these briefs," Andy noted. “We were getting all of our prompts in place and had a good way of creating and reviewing our briefs, doing all the hard work."
They were doing extra work to work faster. They needed AI that understood product brief requirements natively.
When BigChange gained access to Productboard Spark during the beta, the difference was immediate and tangible.
Because Spark is built directly into Productboard, it automatically pulled in all the customer insights, features, and feedback their instance was already collecting. The team could easily add their product context once, making it available for everyone to use—no more exporting data, rebuilding context in every conversation, or manually verifying that AI was referencing the right insights.
Spark could answer questions like "What are the top customer pain points related to scheduling features?" and instantly provide specific answers with links back to source insights in Productboard giving the team exactly the context needed for product brief creation.
The team realized this wasn't just faster, it was fundamentally different.
What once consumed days of manual synthesis now takes minutes. Instead of building the data foundation from scratch, product managers now ask Spark to analyze all insights related to a problem space, generate the foundational customer problem statement, and validate the brief references the right customer segments and pain points..
This allows the PM to immediately move past the data analysis and focus on the deeper strategic decisions: evaluating solutions, running customer interviews, aligning cross-functionally, and building the competitive and product-specific context that ultimately defines the brief's success.
And, the team quickly discovered Spark's applications extended far beyond basic product brief generation.
Before sharing plans with engineering or leadership, the team uses Spark as an internal peer review, stress-testing their thinking before formal reviews.
"By the time it gets to the peer review, we're more confident in it," Charlie explained. "We've already addressed a lot of these questions. It’s been through the rock tumbler so to speak."
Andy uses Spark to validate past work too: "Just asking Spark to go back and validate some of the briefs that we did previously. Did I have the right answer? What did I miss? The context and insights in there help."
The result? Drastically reduced review cycles and higher confidence when presenting to stakeholders.
The team took Spark further. Charlie described one prompt example: "Give us a delivery plan based off of the sizing of these features. How do you think we should order that, and what measurements should we take along the way?"
Spark now helps them surface buried patterns across hundreds of customer insights, analyze roadmap trade-offs, identify feature dependencies, and generate release notes.
"The sky's the limit, really, as to what you could use it for," Charlie reflected. "We kind of learned as we went along."
Since adopting Spark, BigChange's product team has experienced fundamental improvements:
"We're in a lot better position to use metrics and qualitative data, like we get from Productboard, to make sure we're prioritizing the right things," Charlie explained.
BigChange's transformation shows how product teams can accelerate their impact by prioritizing customer focus and data while ensuring the Product Manager can dedicate their time to strategic value-add to drive great decisions.
The team is no longer fighting their tools or slowing down development. They're moving at the speed their business demands while making better product decisions through data-backed product briefs, comprehensive feedback analysis, and systematic validation.
Charlie's advice for teams testing Spark: "Just give it a go. Ask it questions, validate assumptions. We started experimenting and learned as we went along."
As BigChange continues scaling, Spark remains essential—handling the heavy lifting so product managers can focus on strategy, customer empathy, and leadership.
In an era where engineering moves faster with AI, product teams need equivalent tools to remain strategic partners, ensuring they are solving the right problems for customers.
Don’t be the bottleneck. Try Productboard Spark and see how your product team can work faster without sacrificing quality.
