How Cognism Drove 5x More Qualified Opportunities with AI Signals
Cognism
INDUSTRY
Sales Intelligence Software
HQ
London, UK
SIZE
500+ Employees
#Challenges
1. Difficulty identifying high-intent enterprise accounts before they raise their hand
Cognism’s enterprise prospects, especially in the US, tend to conduct research independently before raising their hand. While these accounts were actively engaging with content, they avoided forms and demo requests, leaving Liam’s team unable to identify or act on them. Despite strong inbound performance, high-intent enterprise accounts were slipping away. Cognism needed to spot intent signals earlier, before competitors got there first.
2. No clear system to prioritize and engage high-intent accounts
Identifying high-intent accounts was just one part of the puzzle. Cognism needed a way to efficiently prioritize and engage these early-stage accounts across marketing and sales efforts to support their enterprise growth strategy. Without a clear system to rank accounts by engagement, the team struggled to know how to allocate resources or align marketing with sales outreach.
3. Unreliable and unscalable attribution reporting
Cognism’s previous custom reporting attribution tool couldn’t handle the complexity of reporting across regions, segments, products, etc. Liam’s team had to build endless custom reports each month, a heavy lift that often resulted in broken dashboards and unreliable data. Reporting frequently broke at critical moments, forcing the team to spend hours patching reports. As Cognism shifted towards an “allbound” strategy, they needed a reliable reporting foundation to prove marketing’s influence on revenue.
“Enterprises are notoriously hard to reach; they want to conduct their own research. We weren’t surfacing the accounts that were engaging with us before they became MQLs.”
Liam Collins, VP of Paid Acquisition at Cognism
“We had to create lots of custom reports just to keep up with monthly reporting, and that was a heavy lift on the team. Every time reporting rolled around, the tool would break, and the reports were unreliable.”
Liam Collins, VP of Paid Acquisition at Cognism
#Solution
1. AI Signals
With Dreamdata, Cognism automatically unifies all their go-to-market (GTM) data into a complete B2B customer journey map. Dreamdata Signals uses AI to scan all Cognism’s GTM data and surface previously untracked signals that correlate with pipeline. The AI engine can toggle between early, mid, and late funnel stages to find the signals that relate to each stage of the buying journey.
“The AI engine surfaced 30 or 40 new signals we hadn’t tracked before. We started introducing them one at a time, measuring their impact on the engagement score, and testing what moved the needle. It’s like pulling levers to see what affects the customer journey.”
Liam Collins, VP of Paid Acquisition at Cognism
2. Custom Engagement Score + Audience Hub
Cognism uses Dreamdata’s Engagement Score to prioritize and engage high-intent accounts. They choose which AI-identified signals feed into a custom engagement score, then integrate that score into Salesforce alongside other data sources to build an account prioritization score.
With Dreamdata’s Audience Hub, Liam’s team builds segmented audiences based on their engagement score, grouping accounts into high, medium, and low levels of engagement. They then automatically sync these audiences to ad platforms like LinkedIn, Google, and Meta.
3. Customizable out-of-the-box reporting
Dreamdata provided Cognism with stable, reliable reporting that eliminated the technical hurdles of their previous custom solution. Cognism’s marketing team can easily customize reports using CRM property filters to answer any question without relying on engineering. The intuitive interface made it easy to get accurate, trusted reports, replacing the buggy dashboards they struggled with before. This flexible setup freed the team from patching broken reports.
#Results
40
New intent signals surfaced by AI
5x
Increase in qualified opportunities
1. Record-breaking enterprise revenue
Armed with early intent signals, Cognism’s sales team began proactively engaging enterprise accounts well before form-fills or demo requests. The impact was immediate: Q1 2025 marked their best-ever enterprise revenue quarter.
2. 5x increase in MQL to Meeting Booked conversion rate
Cognism achieved a 5x improvement in conversion rate from MQL to Meeting Booked by prioritizing high-intent accounts earlier in the buying journey with Dreamdata AI Signals. This resulted in more meetings with high-value accounts, faster.
By syncing high-intent audiences daily to ad platforms, Liam’s team tailored budget and messaging to match each account’s level of engagement. Integrating the engagement score into Salesforce gave sales teams a cherry-picked list of warm leads, aligning marketing and sales efforts, and supporting Cognism’s “allbound” strategy.
3. Scalable and accurate reporting that everyone trusts
Dreamdata replaced Cognism’s unreliable custom reporting setup with a stable, scalable platform that the entire marketing team and leadership could trust. Monthly reporting no longer involves fixing broken dashboards or building custom reports from scratch. As a result, Liam’s team can demonstrate their influence on pipeline and revenue, aligning perfectly with Cognism’s allbound approach.
CognismCognism
Cognism is a European B2B data and sales intelligence company. Cognism aims to provide transformative solutions to help revenue teams drive predictable lead generation and improve conversions across sales engagements.
Liam Collins, VP of Paid Acquisition at Cognism, leads paid media. He focuses on driving MQL volume, optimizing full-funnel metrics such as pipeline and closed-won revenue, and using data to identify and engage high-intent accounts.
