Skip to main content

Understanding Recommendations

Learn how Hero Marketer AI provides actionable optimization recommendations and helps you implement them safely.

John avatar
Written by John
Updated over a week ago

How Recommendations Work

Recommendations in Hero Marketer are data-driven suggestions focused on sustainable B2B SaaS growth. Each recommendation includes:

  • Clear pattern evidence across timeframes

  • Expected impact on CAC and efficiency

  • Implementation type (AI-assisted or manual)

  • Specific action steps with context

Implementing Recommendations

AI Assisted Implementation

When you choose AI-assisted implementation, Hero Marketer handles the technical execution while you maintain full control:

  1. Review Process

    • See the specific pattern identified

    • View affected campaign elements

    • Understand current vs. target state

    • Review expected CAC impact

  2. Safety Checks

    • Multi-timeframe evidence shown

    • B2B sales cycle considerations

    • Risk level assessment

    • Implementation prerequisites

  3. Implementation Flow

    • Type "implement" to start

    • Review the proposed changes

    • Confirm to proceed

    • Get real-time execution updates

    • See confirmation when complete

Manual Implementation

For marketers who prefer hands-on control, manual implementation provides detailed guidance:

  1. Step-by-Step Instructions

    • Precise Google Ads navigation

    • Exact values and settings

    • Required order of changes

    • Validation checkpoints

  2. Implementation Support

    • B2B-specific considerations

    • Common pitfall warnings

    • Performance impact context

    • Ask questions anytime

  3. Progress Tracking

    • Report completed changes

    • Monitor implementation

    • Note any adjustments

    • Track performance impact

Best Practices

  1. Review Impact Estimates

    • Check expected performance changes

    • Consider budget implications

    • Review historical data support

  2. Implementation Order

    • Start with high-impact, low-risk changes

    • Group related recommendations

    • Follow prerequisite order

    • Allow time between major changes

  3. Track Results

    • Monitor performance after changes

    • Compare with predicted impact

    • Adjust future optimizations

    • Document successful patterns

Safety Features

  • All changes require explicit user confirmation

  • Recommendations based on consistent patterns, not single-period variance

  • Impact predictions use multi-timeframe analysis

  • Clear distinction between structural vs. performance changes

  • Built-in B2B sales cycle awareness

Getting Help

If you're unsure about a recommendation:

  • Type "why" to understand the reasoning and evidence behind it

  • Ask for specific details about any part of the recommendation

  • Request clarification about expected impact or risks

  • Ask about alternative approaches that might work better for your needs

Did this answer your question?