The “Account Engagement” Scorer

What It Is

The Account Engagement Scorer aggregates engagement signals from multiple individuals at the same company to create an account-level buying signal. Instead of treating each lead independently, it recognizes that B2B buying is a team sport—when 4 people from Acme Corp visit your site in the same week, that's a stronger signal than 4 individuals from different companies.

Why It Matters

Enterprise deals involve 6-10 decision makers on average. Individual lead scoring misses the 'swarming' behavior that indicates real evaluation. Account-level scoring catches buying committees in motion and enables sales to engage at the right moment with the right message.

Who It's For

• B2B companies targeting mid-market and enterprise accounts
• ABM teams wanting better prioritization signals
• Sales teams overwhelmed by individual lead notifications
• Companies where deals involve multiple stakeholders

Required Tools

• MadKudu, 6sense, or custom scoring solution
• CRM with account hierarchy (Salesforce, HubSpot)
• Website visitor tracking with company identification
• Marketing automation for engagement tracking

Required Fields/Properties

• Lead-to-account matching logic
• Individual engagement scoring model
• Account aggregation rules
• Alert thresholds and routing

Definitions Required

• Which engagement signals to include
• How to weight different signal types
• Time window for aggregation
• Threshold for sales notification

Slack Alert: Hot Account Detected

🔥 *HOT ACCOUNT ALERT*

*Account:* {{account_name}}
*Score:* {{account_score}} (+{{score_change}} this week)
*ICP Fit:* {{icp_score}}/100

*Engaged Contacts ({{contact_count}}):*
{{#each engaged_contacts}}
• {{name}} ({{title}}) - {{individual_score}} pts
  Last activity: {{last_activity}} - {{last_activity_date}}
{{/each}}

*Top Content Consumed:*
{{#each top_content}}
• {{title}} (viewed {{view_count}}x)
{{/each}}

💡 *Recommended Contact:* {{recommended_contact}}
💡 *Suggested Approach:* {{outreach_suggestion}}

<{{crm_link}}|View Account> | <{{linkedin_link}}|Find on LinkedIn>

Slack Digest: Weekly Hot Accounts

📊 *Weekly Account Engagement Report*

*New Hot Accounts (5):*
{{#each hot_accounts}}
{{rank}}. {{name}} - Score: {{score}} | Contacts: {{contact_count}}
{{/each}}

*Rising Accounts (Score +50%):*
{{#each rising_accounts}}
• {{name}}: {{previous_score}} → {{current_score}}
{{/each}}

*Cooling Accounts (Action Needed):*
{{#each cooling_accounts}}
• {{name}}: No activity in {{days_inactive}} days
{{/each}}

<{{dashboard_link}}|View Full Dashboard>

CRM Field Reference

| CRM Field | Description | Update Frequency |
|-----------|-------------|------------------|
| Account Engagement Score | Aggregated score from all contacts | Real-time |
| Engaged Contact Count | Number of unique contacts with activity | Real-time |
| Score Trend | 30-day trend (Rising/Stable/Cooling) | Daily |
| Last Engagement Date | Most recent activity from any contact | Real-time |
| Primary Interest | Top content category consumed | Weekly |
| Recommended Contact | Best contact for outreach | Weekly |
| Days Since Last Activity | Staleness indicator | Daily |

Account Tier Definitions

| Score Range | Tier | Sales Action | Marketing Action |
|-------------|------|--------------|------------------|
| 100+ | Hot | Immediate outreach (same day) | Pause ads, enable sales |
| 50-99 | Warm | Review and prioritize (24h) | Increase ad frequency |
| 20-49 | Engaged | Monitor, continue nurture | Standard nurture + retargeting |
| 10-19 | Aware | No action, in nurture | Awareness campaigns |
| <10 | Cold | No action | Broad awareness only |

Test Cases Checklist

• 3 people from same account visit pricing page → account score increases significantly
• Account crosses 100 threshold → sales alert fires immediately
• Single person high activity → score increases but not as much as multi-person
• Engagement > 30 days old → score decays appropriately
• Account owner receives alert (not wrong rep)

Common Failure Modes

• Poor lead-to-account matching: If leads aren't properly associated with accounts, scores will be understated. Invest in match quality and manual review processes.
• Score inflation from bots/crawlers: Bot traffic can inflate page view counts. Filter known bots and require minimum engagement depth before counting.
• Threshold too low causing alert fatigue: If alerts fire constantly, sales ignores them. Start with high thresholds and lower based on capacity and conversion data.
• Stale scores misleading sales: An account that was hot 6 months ago but quiet since shouldn't show high score. Ensure time decay is working properly.

Troubleshooting Tips

• If scores seem too low: Check lead-to-account matching and verify all engagement sources are feeding the model
• If alerts aren't actionable: Review what's included in alert—may need more context
• If conversion is low on hot accounts: Validate score components—may be weighting wrong signals
• If sales ignores alerts: Reduce volume, increase quality, add accountability

KPIs to Track

• Hot Account-to-Opportunity Rate: >15% of hot accounts convert to qualified opportunity
• Sales Acceptance Rate: >70% of alerts accepted by sales as legitimate
• Alert-to-Response Time: <4 hours for hot accounts, <24 hours for warm
• Score Accuracy: Hot accounts should close at 2x rate of non-hot
• Pipeline Influenced: Track $$ of pipeline where account score was factor

Suggested Dashboard Widgets

• Account Score Distribution: Histogram showing accounts by score tier
• Hot Accounts List: Real-time list of accounts above threshold
• Score Velocity Trends: Accounts with biggest score changes this week
• Conversion by Score Tier: Win rate analysis by score tier at first touch