Case Study: How an Enterprise Cloud Infrastructure Provider Expanded Market Share by Replacing AI Intent Guesswork with Human-Verified Custom Sourcing

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B2B Demand Generation Case Study

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The Client Profile & Industry Context

The client is an enterprise-tier cloud infrastructure and managed services provider specialising in multi-cloud cost optimisation, and hybrid-cloud regulatory compliance architectures for high-growth SaaS platforms, fintech applications, and digital healthcare networks.

Replace intent guesswork with researched buyer signals

Replace intent guesswork with researched buyer signals

Replace intent guesswork with researched buyer signals

Problem: The Fragility of Intent Data and the Demand Generation Mirage

The enterprise demand generation landscape has run into a distinct challenge. Many growth teams rely on broad, subscription-based intent intelligence platforms to trigger their outbound sales and marketing engines. These automated platforms monitor web traffic, content consumption, and digital signals across the web, grouping accounts into broad “intent surges” when they show interest in a specific topic.

The client set up a comprehensive demand generation push based on these third-party intent signals, targeting companies flagging a surge in keywords like “Cloud Infrastructure Cost” or “AWS Migration.”

However, their campaigns struggled to generate qualified sales pipeline due to three structural data gaps:

  • The “Ghost Account” Echo Chamber: The automated intent platform flagged major organisations showing high digital interest, but it could not identify where that interest originated. The client’s marketing automation system ended up targeting random contacts at those organisations, only to realise the intent signals were generated by entry-level developers or students researching papers, not corporate budget-holders.

  • Lack of Contextual Clarity: The subscription platform flagged companies for “Cloud Security” interest, but it could not tell the client what those firms’ current tech stacks looked like. Sales representatives were frequently booking discovery calls only to find the prospect was locked into long-term contracts with incompatible legacy providers.

  • High Data Decay and Friction: The contact records attached to the intent lists were severely outdated. Outbound email sequences hit hard bounces, sales outreach suffered from dead direct dials, and the demand generation funnel was bogged down by constant manual data cleaning.

The client was wasting valuable marketing spend running programmatic ads and outbound sales plays against a broad, unverified list that failed to convert into actual pipeline value.

The Solution: Replacing Machine Assumptions with Human-Verified Bespoke Sourcing

The client realised that to convert intent into true demand, they needed to replace broad automated lists with high-precision, custom data sourcing. They partnered with Ascentrik Research to function as their agile data research extension, building custom demand generation pipelines from the ground up.


Automated Intent Signal Flowchart


1. Re-Engineering the Ideal Customer Profile (ICP)

Ascentrik’s research team began by shifting the focus from high-level keyword surges to concrete, verifiable corporate triggers. We refined the client’s demand generation filters to isolate companies undergoing major infrastructure transitions:

  • The Scale Trigger: Companies that had recently closed a fresh funding round or expanded their digital footprint, indicating an imminent need for infrastructure scaling.

  • The Compliance Variable: Organisations operating in heavily regulated spaces (like fintech or healthtech) facing newly introduced regional data localisation mandates.

2. Triangulating Real Intent via Secondary Research

Instead of guessing intent based on background web traffic, Ascentrik’s full-time research analysts tracked active, public corporate indicators. Our teams monitored engineering job boards to see which target companies were actively recruiting for specialised cloud architects, audited localised technology patent applications, and reviewed public technical stack disclosures. This human-led approach allowed us to identify businesses facing active operational challenges that the client’s platform could solve.

3. Granular Infrastructure Mapping

To ensure the client’s sales messaging landed with maximum impact, our researchers manually mapped the specific cloud setups of each target account. We identified whether an organisation was running a single public cloud provider or a complex hybrid system. This deep technographic enrichment allowed the client’s marketing team to move past generic “Optimise Your Cloud” headlines and speak directly to the prospect’s actual setup.

4. Precision Mapping of the Core Buying Committee

With a highly accurate, intent-validated account list secured, Ascentrik mapped the internal buying committees. We bypassed general IT department listings to identify the precise executives with the operational mandate to sign off on major infrastructure investments. Our researchers manually sourced direct-dial corporate phone lines, corporate mobile numbers, and verified email addresses for hard-to-find roles such as Director of Cloud FinOps, VP of Infrastructure Engineering, and Head of DevOps Automation.

The Strategic Outcome

Transitioning from automated intent guessing to a custom, human-verified data partnership with Ascentrik completely transformed the client’s demand generation metrics:

  • Exceptional Top-of-Funnel Efficiency: With outbound sequences targeted precisely at buyers experiencing real operational triggers, the client’s email open rates rose to 48%, while response rates on account-based LinkedIn outreach quadrupled.

  • Significant Drop in Lead Friction: By removing unverified records and catch-all email domains, the client’s campaign hard bounce rate dropped to under 0.5%, completely safeguarding their corporate domain reputation.

  • Substantial Increase in Conversion Rates: Sales Development Representatives (SDRs) no longer wasted hours sorting through messy data. Equipped with direct dials and granular infrastructure context, the client achieved a 65% increase in lead-to-opportunity conversions quarter-over-quarter.

  • Streamlined Pipeline Velocity: Because Ascentrik formatted and pre-categorised all data points to match the client’s exact Salesforce configurations, internal data processing time dropped to zero. This enabled their growth teams to act on high-intent target lists the moment they were delivered.


Transform Your Demand Generation Engine

Are you struggling to convert broad, automated intent signals into actual sales opportunities?

Stop chasing automated guesswork and start fueling your demand generation engine with precision-built, human-verified business intelligence.

Contact Ascentrik Research Today to Design a Custom Target Sourcing Strategy Tailored to Your Specific Demand Gen Metrics

Turn verified buying signals into stronger sales opportunities

Turn verified buying signals into stronger sales opportunities