How A-LIGN cut research costs by 83% and generated millions in pipeline

A-LIGN's first Clay project replaced their manual researcher with an automated workflow that delivered 15x more useful information at lower cost and faster speeds.

The build: Instead of checking boxes for compliance services, they searched for whether companies used 15 specific services, why they used them, and which competitors were providing them. The workflow ran through 2,000 accounts and delivered 1M+ data points.

The timeline: Clay deployed March 20, 2025. All competitive displacement data was live in Salesforce by May 22, 2025—a two-month build that would have taken six months manually.

The cost: The Clay contract cost $10K less than the manual research contract. They saved money while getting 15x more data.

The revenue impact: A-LIGN tracked results through a "Displacement SPIFF" program where reps flagged opportunities as displacement deals. From March 20 through December 12 (6.5 months of live data):

• $6.8M in total pipeline generated or identified ($4.2M created, $2.6M tagged)
• $5.7M in qualified (Stage 2+) pipeline ($3.6M created, $2.1M tagged)
• $3.3M closed revenue ($2.2M created, $1.1M tagged)

For context, A-LIGN's total pipeline generation improved dramatically during this period. Comparing March-December 2025 to the same period in 2024:

• Total pipeline: $185M (up from $132M in 2024, +40%)
• Qualified pipeline: $83M (up from $57M in 2024, +46%)

The displacement research directly contributed to this growth while representing a small fraction of total pipeline, proving its efficiency as a targeted outbound strategy.

One key design choice made this work. Instead of telling reps "this company uses compliance services," the system showed them which specific service the company used and why they needed it.

"We searched for 15 services as well as the justification behind the services and the competitors playing in the space," Arthur Lorente, A-LIGN's Director of GTM Operations

This context changed how reps opened conversations because they could reference specific needs rather than making generic pitches.

When A-LIGN planned regional in-person events, they ran into the same problem every events team faces: contact data from providers relies on stale information from email signatures. People move cities but don't update their email signatures for months.

The build: Starting with 11,000 target contacts, they used Clay to:

• Find LinkedIn URLs for contacts where standard providers came up empty
• Pull current city locations directly from LinkedIn profiles
• Compare provider data against LinkedIn data

The data quality impact: Clay found 4,500 new LinkedIn URLs that standard providers missed (41% lift). More surprisingly, Clay identified that 1,500 of the 6,500 existing records had wrong locations. That meant 23% of their "known good" data was actually incorrect.

The revenue impact: Those corrected and enriched contacts drove $9.3M in influenced pipeline, $8.4M in last-touch pipeline, and $558K in closed revenue. Arthur notes many of these were existing customers, but the precise targeting made these events far more effective than previous attempts.

The speed: Arthur estimates the entire enrichment workflow took about 20 minutes to build.

This doesn't show up in pipeline reports, but it transformed how A-LIGN's RevOps team works.

The old workflow: Any Salesforce data operation required a multi-step handoff. Marketing would send data to sales ops, sales ops would prepare a CSV and submit a ticket to the Salesforce admin team, admins would process it, sales ops would verify, then confirm back to the original requester. Typical cycle time: 48 hours.

The new workflow: Sales ops receives the request, processes the data in Clay, pushes directly to Salesforce, verifies, and confirms. Typical cycle time: 2 hours.

That's a 24x speed improvement. With at least one major upload per week, A-LIGN saves roughly 46 hours weekly. Their ops team now spends that time on strategic projects rather than administrative work.

"Clay removes that barrier. It's literally manipulating your CRM as a CSV. I can have people that are not technical, that don't have Salesforce permissions, do anything," said Dimitrios Gatsos, an analyst on Arthur’s team at A-LIGN.