Case Study: BoardEx

How a 14-year data business more than doubled its active users and contributed directly to an $87.3M acquisition, using the team, technology, and data it already had

17K → 41K

Active users more
than doubled

300%

Increase in
tablet users

$87M

Acquired by Euromoney
at 3.5x revenue

Client: BoardEx (TheStreet, Inc.)

Industry: Business intelligence and executive relationship mapping (14-year track record)

Product: Global platform profiling over one million senior business leaders, used by banks, law firms, consultancies, executive search firms, and PE firms for business development and relationship mapping

Engagement: Product Diagnostics and Fixes: customer research, customer segmentation, product strategy, product redesign, development oversight

Timeline: 15 months end to end: 3 months of Product Diagnostics followed by 12 months of Product Fixes

Headline result: More than doubled active users from 17,406 to 40,805 a month (after two years of flat growth), drove a 300% increase in tablet adoption, and contributed directly to the commercial profile that led to an $87.3 million acquisition by Euromoney

The Situation

BoardEx was the gold standard for executive intelligence. For 14 years, its database of board directors, C-suite leaders, and senior management across the world's biggest companies had been the tool that banks, law firms, and consultancies relied on for business development and relationship mapping. One customer described it as "LinkedIn for grown-ups" because the profiles were built from publicly disclosed, verified information rather than self-reported data. The quality was unmatched.

The product had never had customer-focused product leadership, and after 14 years it showed. Product decisions had been made by the technical team and a product manager, producing a platform that looked like an Excel spreadsheet: tiny fonts, complex labelling, deeply nested information, and no intuitive structure for finding things. It worked if you already knew how to use it. Learning how to use it was the hard part.

Onboarding a new customer took anywhere from 45 minutes to an hour and a half. Those sessions often had to be repeated. Customers regularly described forgetting where to find things between sessions. Senior people within client organisations (partners, directors, people who understood the value of the data) had gone to the trouble of learning the tool and stuck with it. But the associates and junior teams who were actually tasked with using it day-to-day found it painful. They had hundreds of applications available to them and gravitated to whichever was easiest to use.

While all of that was playing out inside the client base, startup competitors were entering the market with modern, well-designed products. The data quality wasn't comparable, but the experience was dramatically better. Junior staff were starting to prefer these alternatives, creating tension within client organisations between senior people who valued BoardEx's data and younger teams who wanted something they could actually use without a training session.

Active user numbers had been flat for two years: around 20,000, no meaningful growth, not much drop-off either. Renewals were getting harder to close. Onboarding new users inside client organisations was a grind, and paid licences that never converted to active usage were becoming difficult to justify. The business had the data, the market position, and the client relationships to grow. The product was the thing in the way.

A new president had been brought in to optimise the service and grow the user base. He showed the platform to people outside the company. Their reaction was consistent: the experience was terrible, and the business needed real product expertise to fix it. That was where we came in. Mandated from the top, with a clear brief: understand what was actually happening, and build a strategy to turn it around.

Phase 1: Product Diagnostics

We started where we always start: understanding the problem before trying to fix it. Phase 1 runs our Dual Lens approach (Customer Intelligence and Product Efficiency) to build a complete picture before any product decisions are made.

The core insight: The product had been built by technologists for 14 years without ever systematically understanding how different types of customer actually used it, what they needed from it, or the real-world context in which they worked. Every feature was technically functional. Almost none of them were designed around how people actually did their jobs.

Lens 1: Customer Intelligence

This is where Customer Intelligence does the work that analytics can't: speaking directly to real-world customers to understand the why behind the numbers. Analytics can tell you what's happening inside the product. They can't tell you what's happening around it: what customers are actually trying to achieve, who they're answering to, what a good day looks like, where this product sits in a working life full of competing tools and pressures.

We spoke to approximately 40 users across London and New York: researchers, partners, associates, business development teams, and internal champions across banking, law, professional services, executive search, and asset management. These weren't standard interviews. They were structured, in-depth conversations designed to draw out how each person actually worked: the decisions they were making, the pressures they were under, the other tools competing for their attention, and where this product needed to fit into a working day that didn't have much room for friction.

The 45-minute problem: In the big consultancy and accountancy firms, business development teams were spending 45 minutes to an hour trying to explain to senior partners what the data on the screen actually meant. Partners needed to understand how they connected to a target company, which boards their contacts sat on, which relationships could open doors. The product made this information available but nearly impossible to interpret without someone walking you through it
Senior vs. junior divide: Senior users valued the data quality and had invested the time to learn the tool. Junior associates, the people actually tasked with using it daily, described it as "old school" and said simplicity was key. With hundreds of applications available to them, they spent their time on the ones that were easiest to use. The product was losing the next generation of users
Competitors winning on experience, not data: Customers could articulate the difference in data quality when asked directly, but that wasn't what drove their daily behaviour. Junior staff defaulted to whichever tool was easiest to open and use. The competitive threat wasn't better data. It was less friction.
Five distinct customer types, one product: The customer base cut across multiple sectors, but the research revealed five consistent groups that transcended industry lines: senior partners looking to map relationships to target companies; researchers pulling large data sets; associates juggling hundreds of tools and defaulting to whichever was simplest; business development teams supporting partners with relationship intelligence; and internal champions who loved the data and drove adoption within their organisations. Each had fundamentally different needs, workflows, and expectations from the same platform
Management flying blind on segmentation: The senior management team acknowledged they didn't understand how to segment their customer base, who to focus on, who to listen to. Feedback came from all directions, including a loud sales team pushing for features. Without a clear segmentation, the product had become a sprawling attempt to serve everyone, serving nobody particularly well

None of this was visible from usage data or internal feedback alone. It only became clear by going deep with customers across two continents, understanding their working patterns and the real-world context in which they needed this tool to perform.

Lens 2: Product Efficiency

The second lens runs alongside the first and turns the camera on the product itself: how it's structured, how it's labelled, how it guides people through tasks, how its layouts hold up under real use, and where the design is creating unnecessary friction.

It's a structured expert review rather than an opinion piece. We worked through the platform systematically, looking at navigation, information structure, labelling, interaction patterns, and page-level design, identifying the specific points where the product was helping, getting in the way, or silently losing revenue, conversion, or time. What we found:

Spreadsheet experience: The platform looked and felt like a complex Excel spreadsheet. Tiny font sizes, dense data tables, no visual hierarchy, no modern web patterns that would give a new user any intuition about how to navigate or interact with the product
Deeply nested structure: Information was buried behind multiple clicks and nested layers. Users described a "click here, then go here, then go there" pattern just to find basic information. Seven structural categories when the content could be logically organised into four
No responsive capability: Executive search teams and senior partners were accessing the platform on tablets and finding it nearly impossible to use. Touch targets were too small, typography was unreadable, and the layout didn't adapt to different screen sizes. This wasn't a niche use case. Senior decision-makers were trying to access intelligence on the move
Labelling in the wrong language: Navigation labels and content groupings reflected internal business logic rather than how customers actually thought about and described the information they were looking for. Categories made sense to the team that built the product, not to the people using it
Board data buried in tables: One of the platform's most valuable features (understanding which boards an executive sat on and how those board memberships connected companies) was presented as a dense data table. The information that partners needed most for relationship mapping required someone else to interpret it for them
Data export frustrations: Users found it challenging to get data out of the platform. They needed to sort and filter results to exclude irrelevant data before exporting, but the tools didn't support this. List management was also a major gap: some users wanted to track prospects and be notified when those individuals made board moves, but there was no way to do this within the product
Alerts gone stale: Users had signed up for email alerts to track board moves and executive changes. Over time, the alerts became generic and repetitive, burying the updates that actually mattered to each user beneath noise they'd stopped reading.

Neither lens alone would have been enough. Together, they gave the business something it hadn't had before: the five customer types defined by what each actually needed from the product, and exactly where it was helping, falling short, or silently losing revenue, all in one view.

Phase 2: Product Fixes

The conclusion was unambiguous: a world-class data asset trapped inside a product that was actively preventing growth. The product needed to be redesigned around how its five distinct customer types actually worked, using their language, matching their expectations, and performing in the real-world contexts where they needed it.

The five-segment framework became the foundation for every decision, cutting through the noise of competing internal opinions and sales-driven feature requests. The strategy translated into specific, evidence-backed product decisions:

Board table visualisation: The dense spreadsheet of board members was transformed into a visual board table, with members arranged around the table, clickable to reveal the other boards each director sat on. This single change turned a 45-minute partner briefing into a two-to-five-minute visual conversation. It became the most celebrated feature across the client base
Structure and navigation reorganised: Seven historical categories reduced to four, restructured around how customers actually described their tasks and the information they were looking for, not how the business had organised its data internally. Labels were rewritten using customer vocabulary, and the resulting groupings made the platform navigable for the first time, removing the "I never remember where to find this" problem that had plagued even experienced users
Profile pages reimagined: Individual and company profiles redesigned using familiar patterns from modern platforms: entity information anchored on the left, content flowing to the right. Customers could orient themselves immediately without training because the structure matched patterns they already understood from other tools
Search rebuilt for real tasks: Search redesigned around how researchers actually worked: building prospect lists, filtering by sector or seniority, sorting results by the criteria that mattered to each research task. For the first time, users could get from a question to a usable shortlist without exporting to Excel.
Home page developed: A new landing page built to orient both new and returning users, showing what was included in the platform, the number and types of profiles available for both individuals and businesses, and integrating a live feed of recent board moves with deep links straight into the relevant profiles. This gave users an immediate reason to engage rather than arriving at a blank search screen
Onboarding built into the product: Rather than relying on hour-long training sessions, we embedded onboarding within the platform itself, accessible at any point. Customer research revealed where datasets fell short of actual user requirements, which we fed back to the senior team to improve the underlying data. Where the data still required explanation, we developed contextual cues that users could access without interrupting their workflow
Typography and visual design modernised: Colour contrast improved, page layouts simplified to be scannable at a glance, and labels rewritten using the vocabulary customers actually used when describing their tasks and the data they needed
Responsive design implemented: A responsive experience across desktop and tablet. Font sizes increased, touch targets enlarged, layouts reconfigured for smaller screens. Executive search teams and partners who had been struggling on tablets could now use the platform naturally, whether at a desk or on the move

Before anything went into development, we prototyped and tested with customers drawn from the same segments the diagnostics had identified. This confirmed the strategy was working, surfaced improvements we could make before committing to development, and gave internal teams confidence that the changes would land well.

None of these decisions came out of thin air. Every one of them traced back to a specific finding from the diagnostics: a customer type whose needs hadn't been understood, a workflow that didn't match how people actually worked, a piece of language that meant nothing to the people using it. Working alongside the internal team, we paired that Customer Intelligence with deep experience of how modern platforms succeed. That meant the patterns customers expect, the conventions that make a product feel familiar from the first click, and the design choices that separate a credible enterprise tool from a clunky one. Together, that combination produced decisions both sides could stand behind, grounded in evidence and informed by experience.

And we did it with the team, the technology, and the data the business already had. No new hires. No platform change. No extra budget. What changed was what the business knew about its customers, and what it did with that knowledge.

The Results

17K → 41K active users

More than doubled after two years of flat growth

300% tablet increase

Tablet usage tripled after responsive design implementation

Continued to 60K

Active users continued growing to 60,000 after the engagement ended

$87.3M acquisition

Acquired by Euromoney at 3.5x revenue

After two years of flat usage, the user base more than doubled from 17,406 to 40,805 active users a month, with growth continuing to 60,000 after the engagement ended. The product went from being a barrier to sales conversations to a growth driver. Renewals that had been getting increasingly difficult became straightforward when the product experience matched the quality of the data.

The commercial profile that emerged from this work didn't go unnoticed. Euromoney Institutional Investor acquired BoardEx (along with The Deal) from parent company TheStreet for $87.3 million in cash, approximately 3.5x revenues. The acquisition was strategic: Euromoney was building its "People Intelligence" pillar, and BoardEx's combination of world-class data and a modern, growing platform made it the centrepiece of that strategy. BoardEx was later folded into Altrata alongside Wealth-X, RelSci, WealthEngine, and Boardroom Insiders. Euromoney itself was subsequently acquired by a private equity consortium of Astorg and Epiris for £1.7 billion.

“Jeff actually joined us with BoardEx, which was the very start of our People Intelligence journey... the extraordinary value that there is in that business and the wonderful work that the team are doing.”

Andrew Rashbass, CEO, Euromoney Institutional Investor
People Intelligence Investor & Analyst Teach-In, March 2022

What This Means for PE-Backed Tech

It's a pattern we see repeatedly in PE-backed technology businesses. The data is strong, the team is working hard, investment continues, but the product metrics don't move. The instinct is usually to build more features, hire more developers, or commission a redesign. None of those fix the underlying problem. The underlying problem is a knowledge gap. Nobody is combining the quantitative data with the qualitative customer intelligence needed to untangle which customer segments actually matter, what each one needs, and why the numbers aren't moving. And nobody is pairing that diagnostic with the hands-on product judgement needed to turn findings into decisions.

The Pattern

The insight is half the job. Phase 1 surfaces what each customer segment actually needs and exactly where investment will produce the highest commercial return. Phase 2 turns those findings into decisions the team can ship. BoardEx needed both. It didn't need new data or a new platform. It needed that bridge.

This applies to any asset-rich technology business where product experience is an underused lever in the value creation plan.

BoardEx illustrates the Product Diagnostics and Fixes methodology at full stretch: a stalled subscription business returned to growth, active usage more than doubled within the engagement, and grew to 60,000 after handover. The commercial profile that emerged from that work contributed directly to a 3.5x revenue exit. None of it required new technology, new hires, or new data. We're now applying the same approach with PE-backed tech portfolio companies: a focused intervention sized to deliver a clear commercial multiplier within the hold period, working alongside operating partners and management teams to turn asset-rich tech businesses into product-led ones before exit.

About: Building Great Tech is a two-person consultancy bringing 30+ years of combined product and technology experience to a single PE-focused practice. This case study describes work led during a product consultancy engagement with BoardEx (predating BGT as a vehicle), and illustrates the Product Diagnostics and Fixes methodology we now apply with PE-backed tech portfolio companies.

Building Great Tech | BoardEx Case Study