text stringlengths 0 116 |
|---|
Q3 2026 ENTERPRISE CAMPAIGN BRIEF |
========================================== |
Target: enterprise B2B leads with annual revenue >= $1,000,000 |
PRIORITY ASSIGNMENT (based on adjusted_score and annual_revenue_usd): |
- TIER1 (HOT) : adjusted_score >= 80 AND annual_revenue_usd >= 10,000,000 |
- TIER2 (WARM) : (65 <= adjusted_score < 80) |
OR (adjusted_score >= 80 AND annual_revenue_usd < 10,000,000) |
- TIER3 (NURTURE) : adjusted_score < 65 |
adjusted_score = lead_score + industry_bonus + region_bonus |
INDUSTRY BONUS: |
FinTech: 10 |
Healthcare: 8 |
SaaS: 6 |
Manufacturing: 3 |
Logistics: 1 |
Retail: 0 |
Other: 0 |
REGION BONUS: see the regional policy document (regional_policy.txt). |
SPECIAL RULES: |
- Leads with status = DISQUALIFIED are marked SKIPPED and excluded from the campaign. |
- Companies listed in exclusions.txt are marked EXCLUDED and must NOT be |
contacted or prioritized under any circumstances. |
- All remaining leads are assigned TIER1, TIER2, or TIER3 per the priority |
rules above. |
REPORTING REQUIREMENTS: |
- Produce Q3_2026_campaign_prioritization.csv with one row per lead. |
- Columns (in order): lead_id,company,industry,annual_revenue_usd,region,lead_score,status,adjusted_score,priority |
- For SKIPPED and EXCLUDED leads, leave the adjusted_score field empty. |
- Publish the same prioritized data back to the shared data repository as |
prioritized_leads.csv. |
- Generate a promotional banner image for the TIER1 lead with the highest |
annual revenue; save it as campaign_banner.webp. |
Helios Bank |
BlueRetail |
Nimbus Pay |
REGIONAL ADJUSTMENT POLICY |
============================ |
Region bonuses applied to lead_score: |
NA: +5 |
EU: +3 |
APAC: +1 |
LATAM: -3 |
MEA: -2 |
Any other region: +0 |
Q3 2026 ENTERPRISE CAMPAIGN BRIEF |
========================================== |
Target: enterprise B2B leads with annual revenue >= $1,000,000 |
PRIORITY ASSIGNMENT (based on adjusted_score and annual_revenue_usd): |
- TIER1 (HOT) : adjusted_score >= 80 AND annual_revenue_usd >= 10,000,000 |
- TIER2 (WARM) : (65 <= adjusted_score < 80) |
OR (adjusted_score >= 80 AND annual_revenue_usd < 10,000,000) |
- TIER3 (NURTURE) : adjusted_score < 65 |
adjusted_score = lead_score + industry_bonus + region_bonus |
INDUSTRY BONUS: |
FinTech: 10 |
Healthcare: 8 |
SaaS: 6 |
Manufacturing: 3 |
Logistics: 1 |
Retail: 0 |
Other: 0 |
REGION BONUS: see the regional policy document (regional_policy.txt). |
SPECIAL RULES: |
- Leads with status = DISQUALIFIED are marked SKIPPED and excluded from the campaign. |
- Companies listed in exclusions.txt are marked EXCLUDED and must NOT be |
contacted or prioritized under any circumstances. |
- All remaining leads are assigned TIER1, TIER2, or TIER3 per the priority |
rules above. |
REPORTING REQUIREMENTS: |
- Produce Q3_2026_campaign_prioritization.csv with one row per lead. |
- Columns (in order): lead_id,company,industry,annual_revenue_usd,region,lead_score,status,adjusted_score,priority |
- For SKIPPED and EXCLUDED leads, leave the adjusted_score field empty. |
- Publish the same prioritized data back to the shared data repository as |
prioritized_leads.csv. |
- Generate a promotional banner image for the TIER1 lead with the highest |
annual revenue; save it as campaign_banner.webp. |
Helios Bank |
BlueRetail |
Nimbus Pay |
REGIONAL ADJUSTMENT POLICY |
============================ |
Region bonuses applied to lead_score: |
NA: +5 |
EU: +3 |
APAC: +1 |
End of preview. Expand in Data Studio
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
- Downloads last month
- 188