How a Global Pharma Enterprise Replaced Manual Data Sprints with Continuous AI enabled CRM Enrichment

Introduction

A global Pharma enterprise with a large sales and marketing operation had built significant automation capability across their GTM stack. But the foundation those automations relied on - their CRM data - was increasingly unreliable. As the organisation scaled, the gap between the data they had and the data they needed grew wider each quarter.

RevOps engaged Tapistro to solve the underlying problem: not just cleaning the CRM once, but keeping it continuously clean, enriched, and scored - without ongoing manual effort.

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The Challenge

The team's CRM had accumulated significant data decay over time. Records were missing key fields, contact details had gone stale, and bounce rates on outbound campaigns were climbing. Every major campaign required a manual data sprint just to reach a usable baseline.

• Outdated contact records missing job titles, phone numbers, and LinkedIn profiles meant SDRs were prospecting against incomplete data.

• High email bounce rates were damaging sender reputation and reducing deliverability across the organisation's campaigns.

• Lead scores were static, reflecting historical data rather than current buying signals or behavioural changes.

• Each campaign launch triggered a reactive data cleanup sprint, consuming RevOps bandwidth and delaying go-live timelines.

• Marketing had no confidence in CRM data quality, limiting their ability to run targeted, segmented campaigns without manual.

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The Goal & Solution

The objective was to move from reactive data management to a continuously maintained, always-accurate CRM - one that required no manual intervention to stay current.

Tapistro deployed a continuous enrichment layer across the organisation's full CRM dataset:

• Account Enrichment ran automated enrichment cycles continuously across all CRM records not as a one-time fix, but as an ongoing process running in the background at all times.

• Waterfall enrichment chained multiple data sources Apollo, NeverBounce, Wiza, and Tap AI Agents  to maximise coverage and fill gaps no single provider could address alone.

• Missing fields were systematically populated: job title, direct phone, LinkedIn URL, company size, industry classification, and more without any manual data entry.

• Email validation ran before every campaign send, eliminating bounce risk at the source rather than managing the fallout after the fact.

• Lead scores updated dynamically as new behavioural signals arrived including hiring activity, funding events, and engagement data  keeping scores reflective of current account readiness rather than static historical snapshots.

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The Impact

Data Quality Impact

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• CRM records stayed continuously enriched with accurate contact details, firmographics, and technographic data — no manual cleanup required between campaigns.

• Email bounce rates dropped to near-zero, protecting sender reputation and improving deliverability across both sales and marketing sends.

• Missing field rates fell sharply across key contact attributes, giving SDRs complete, actionable records for every account they worked.

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Campaign & Pipeline Impact

• Pre-campaign data sprints were eliminated entirely - RevOps no longer needed to run manual prep cycles before each campaign launch.

• Lead scoring reflected live signals rather than stale snapshots, allowing sales to prioritise accounts at the moment of highest readiness rather than weeks after peak intent.

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Operational Impact

• RevOps bandwidth previously consumed by data sprints was redirected to higher-value orchestration and reporting work.

• The enrichment layer operated fully autonomously no triggers, no tickets, no manual runs -freeing the team from data maintenance entirely.

• Both sales and marketing operated from the same continuously updated data foundation, reducing friction at the handoff and improving alignment across the GTM motion.

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