Apollo's database has ~40% staleness. This workflow uses live LinkedIn data to refresh Apollo contacts, drop bounce rates below 10%, and surface job changes automatically.
Quick answer
The Apollo → LinkedIn enrichment workflow fixes Apollo's staleness problem. Export your Apollo list as CSV, upload to Scrupp, and Scrupp cross-references each row against live LinkedIn profiles — refreshing job titles, companies, and emails. Rows where the person has changed jobs get flagged; their new company and new email replace the stale Apollo data. Typical result: bounce rate drops from 30-40% to under 10%, and 15-20% of rows get routed to a "moved on" list for re-enrichment in the new company context.
The workflow
6 steps · est. 1-2 hours for a 5,000-row refresh (mostly waiting for Scrupp to process)
In Apollo, filter to your active segment. Export as CSV. Include LinkedIn URL column (critical for matching).
In Scrupp, click "Bulk enrichment". Upload the Apollo CSV. Scrupp auto-detects LinkedIn URL and name columns.
Toggle "Refresh against live LinkedIn". Scrupp re-scrapes each LinkedIn profile, pulls current title + company, and flags mismatches with Apollo data.
For each row, Scrupp runs the multi-provider email waterfall + SMTP verification. If the person moved jobs, the old email is flagged stale and the new email is generated.
Output has a "status" column: unchanged (~60%), updated (~25%, new title/company/email), not found (~15%). Route each segment differently in your CRM.
For "unchanged" rows: just re-sync. For "updated" rows: update existing contact. For "moved on" rows: create a new record at the new company + mark the old record inactive.
Tool stack
All the tools involved in this workflow.
Source of original contact list. Keep for database breadth.
Live LinkedIn cross-enrichment + email re-verification. Pay-as-you-go.
Intermediate for segmenting the refreshed output.
Destination CRM.
Total cost: $50-100 for a 5,000-row cross-enrichment pass. Re-runs monthly are the best ROI.
FAQ
Apollo maintains a static database updated on their cycle. LinkedIn is updated in real-time by users. For people-level data (jobs, titles), LinkedIn will always be fresher.
Monthly is the sweet spot. 15-20% of B2B roles change per year — monthly refreshes catch most of the churn early. Quarterly is minimum.
Not for discovery and sequencing — those are Apollo strengths. For data quality, this refresh workflow supplements Apollo with LinkedIn freshness.
Typical: 30-40% Apollo bounces drop to under 10% after Scrupp cross-enrichment. Some specific segments (old SaaS) see 50%+ → 5% improvement.
Related guides
Keep exploring: Apollo Alternative · Apollo Scraper · Scrupp + Clay + HubSpot workflow · B2B Data Enrichment · Export Apollo to CSV
Free Chrome extension · Pay only for successful enrichments · No credit card.