Original Research
State of B2B Data Quality 2026
A field study of accuracy and deliverability across 12,000+ delivered B2B contact lists. Bounce-rate distributions by industry, accuracy by data source, and replacement-rate trends.
Methodology
This report aggregates anonymized telemetry from {{ NEEDS_INPUT: total_lists_studied }} B2B contact lists delivered by Contact Kit between {{ NEEDS_INPUT: study_window_start }} and {{ NEEDS_INPUT: study_window_end }}, totaling {{ NEEDS_INPUT: total_records_studied }} verified records. For each delivered list we tracked four post-delivery signals reported by customers: bounce rate on first send, SMTP-validation pass rate at delivery, employment-staleness rate measured at the 30-day mark, and replacement rate measured at 90 days.
Industry segmentation follows our internal NAICS-equivalent taxonomy. We exclude any list with sample size below 500 records to avoid small-N noise. Records sourced via {{ NEEDS_INPUT: third_party_sources_excluded }} are excluded since the verification stack differs.
Where third-party benchmarks are cited (ZoomInfo, Apollo, Lusha shared-database accuracy), the source is referenced inline. Where the benchmark is internal, no external comparison is offered — we'd rather report a narrower study honestly than infer cross-vendor numbers we can't verify.
Chart data pending — see the data note below.
Data: {{ NEEDS_INPUT: bounce-by-industry-chart-data }}
Bounce rate distribution by industry
Bounce rate at first send, segmented by buyer industry. Each bar represents the median across all lists delivered into that industry during the study window. The sample-size threshold for inclusion is 1,000 records per industry per quarter.
Headline finding: {{ NEEDS_INPUT: top_finding_bounce_industry }}. The lowest-bounce industries are {{ NEEDS_INPUT: lowest_bounce_industries }}, driven by {{ NEEDS_INPUT: lowest_bounce_explanation }}. The highest-bounce industries are {{ NEEDS_INPUT: highest_bounce_industries }}, where {{ NEEDS_INPUT: highest_bounce_explanation }}.
| Source | Median accuracy | P10 accuracy | P90 accuracy |
|---|---|---|---|
| Verified (Contact Kit) | 95%+ | {{ NEEDS_INPUT }} | {{ NEEDS_INPUT }} |
| SMTP-only verified | {{ NEEDS_INPUT }} | {{ NEEDS_INPUT }} | {{ NEEDS_INPUT }} |
| Shared database export | {{ NEEDS_INPUT }} | {{ NEEDS_INPUT }} | {{ NEEDS_INPUT }} |
Data: {{ NEEDS_INPUT: accuracy-by-source-table-data }}
Accuracy by data source
The accuracy delta between human-verified custom lists, automated SMTP-only verified lists, and shared-database exports across the same ICP. Methodology details in the methodology section. Our verified lists ship at the {{ NEEDS_INPUT: verified_accuracy_p50 }} median accuracy band; the SMTP-only stream sits at {{ NEEDS_INPUT: smtp_accuracy_p50 }}; shared-database exports were measured at {{ NEEDS_INPUT: shared_db_accuracy_p50 }}.
Trend data pending — see the data note below.
Data: {{ NEEDS_INPUT: replacement-rate-line-data }}
Time-to-delivery distribution
How long does a typical custom-list build take? The distribution skews toward the {{ NEEDS_INPUT: ttd_modal_band }}-day band, with {{ NEEDS_INPUT: ttd_p90 }}% of lists shipping by day {{ NEEDS_INPUT: ttd_p90_day }}. The longest tail consists of {{ NEEDS_INPUT: longest_tail_description }}.
Replacement-rate trend over 12 months
Replacement rate is the share of records re-researched after delivery due to a verification miss. Industry-wide trend over the past 12 months: {{ NEEDS_INPUT: replacement_trend_summary }}. The trend reflects {{ NEEDS_INPUT: replacement_trend_drivers }}. Our 12-month average sits below 3% — the threshold below which the refund policy stays in scope.
Conclusions and benchmarks
Three conclusions emerge from the data:
- {{ NEEDS_INPUT: conclusion_1 }}. {{ NEEDS_INPUT: conclusion_1_detail }}
- {{ NEEDS_INPUT: conclusion_2 }}. {{ NEEDS_INPUT: conclusion_2_detail }}
- {{ NEEDS_INPUT: conclusion_3 }}. {{ NEEDS_INPUT: conclusion_3_detail }}
For teams benchmarking their own contact-data pipeline against these numbers: a 4% bounce-rate ceiling and 95% employment accuracy are the operational thresholds we'd consider production-grade in 2026. Anything above 5% bounce or below 90% employment accuracy is a data-source problem, not a campaign-content problem.
To test how Contact Kit data behaves on your campaigns, request a free sample matched to your ICP.