In-App Benchmarking + PostPilot AI Recommendations

In the benchmarking section of the PostPilot App, PostPilot AI analyzes your performance compared to your peer group and makes recommendations around potential areas of improvement.

All PostPilot AI analysis is based on all-time data, refreshed monthly.

What Are Company Benchmarks?

Company benchmarks are the statistical yardsticks we use to show where your direct mail results land compared to other brands like yours.

Metrics Currently Used in Benchmarking

Efficacy: ROAS, Incremental ROAS (iROAS)
Conversion: Conversion rate (CVR), Cost per conversion (CPC)
Value: AOV across all campaign types
Investment allocation: Spend % for retention and retargeting
Revenue attribution: % of revenue from direct mail

How PostPilot AI Benchmarks Your Performance vs. Your Peers

PostPilot AI compares your KPIs to a dynamic peer range and flags your standing with clear zones:

🌟 Excellent: Above the peer range (above the upper confidence interval)
✅ Good: Within the peer range
📈 Fair: Below the peer range (below the lower confidence interval)

Defining your peer group

Brands are grouped using Revenue, AOV, and Industry Category, so you’re compared to genuinely similar businesses.

🤓 For data nerds: PostPilot AI uses multivariate clustering analysis.

Ensuring data quality and accuracy

Confidence intervals keep things statistically sound
Outliers are handled so one unicorn doesn’t set your goals
“Lower-is-better” metrics (like CPC) are scored accordingly
Peer groups and benchmarks are recalculated monthly

What to Do With This Data

We’re putting PostPilot AI to work to help you put your current performance in proper perspective and give you signals for how you might improve your performance

⭐ Important Note: PostPilot AI is not providing a “grading” system. Rather, it’s generating a roadmap for additional success with direct mail and how to scale your program further.

Performance Summaries

PostPilot AI translates your benchmarks into quick takeaways.

You’ll get an overall evaluation of your metrical performance, the areas that are working, and the areas that can be improved.

For instance, PostPilot AI will:

Flag KPIs in Excellent / Good / Fair zones vs. your peers
Surface opportunities: E.g., Automations to scale, untapped strategies that peers use,
Lean on peer adoption rates and spending patterns to suggest next, highest‑leverage moves

How Summaries Are Generated

PostPilot AI uses a wide array of data points for its recommendation engine:

Overview:

Core performance metrics: Peer group averages for all KPIs, average peer discount amounts, top-performing peer strategies
Campaign data: Campaign status, automation vs. one-off performance, creative sizes
Strategic implementation data: Retention strategies, VIP segments, automation adoption vs. peers
Other peer comparison metrics and performance thresholds: Ranging from peer spending levels to AOV/CVR tiers.

The full list:

Core Performance Metrics
1. PostPilotAI has visibility into comprehensive performance data across all campaign types:
  1. Return Metrics: ROAS (Return on Ad Spend), Incremental ROAS (iROAS)
  2. Conversion Performance: Conversion rates (CVR), Cost per conversion (CPC)
  3. Customer Value: Average order values (AOV) across all campaign types
  4. Investment Allocation: Spend percentages for retention and retargeting
  5. Revenue Attribution: Direct mail revenue percentages
Campaign-Level Intelligence
1. To get specific with recommendations, PostPilotAI analyzes:
  1. Campaign status (active, stopped, paused)
  2. Automation vs. one-off performance scores
  3. Spend limits and actual spend levels
  4. Funding status (insufficient funds flags)
  5. Coupon availability (insufficient coupons flags)
  6. Top performing campaigns by ROAS and iROAS
  7. Creative sizes used (4x6, 6x9, 6x11 postcards)
  8. Average discount amounts offered
  9. Minimum purchase requirements
  10. Campaign segmentation approaches
Strategic Implementation Data
1. PostPilotAI understands which strategies you've deployed:
  1. Retention Strategies: Winback, Reactivation, Bounceback
  2. VIP Segmentation: Use of VIP (Number of Orders > 3) customer segments
  3. Last Order Date (LOD) Ranges: Recent vs. furthest targeting
  4. Retargeting Strategies: Abandoned Browse/Cart (ABC), MM, SM
  5. Automation Adoption: Count of automated campaigns vs. peers
Peer Comparison Metrics
1. Peer group averages for all performance indicators
2. Peer group statistical confidence intervals (upper and lower bounds of range)
3. Peer spending levels
4. Peer automation counts
5. Peer strategy (Winback, Birthday Campaigns, MailMatch etc) adoption rates
6. Top performing peer strategies (Winback, Birthday Campaigns, MailMatch etc)
7. Average peer discount amounts (For UCCs ONLY)
Performance Thresholds
1. PostPilot AI enhances recommendations by analyzing your baseline input metrics:
  1. AOV Tiers:
    1. Retention: High (≥$200), Medium (≥$100), Low (<$100)
    2. Retargeting: High (≥$150), Medium (≥$75), Low (<$75)
    3. Overall: High (≥$200), Medium (≥$100), Low (<$100)
  2. CVR Tiers (all campaign types):
    1. High (≥15%)
    2. Medium (≥5%)
    3. Low (<5%)
  3. Performance against confidence intervals: Excellent, Good, Fair

What data does PostPilot AI not use (yet)?

Static coupon offer details
Actual designs on mailers
Connectivity between campaigns that is not explicitly clear in-app
1. Example: If you did not use the “automate” button on a one-off campaign and instead created a new automation, PostPilot AI does not know that you automated that campaign and may suggest that you automate it.

Additional Questions?

For more information about how AI recommendations are generated or to discuss your specific insights, please contact your account manager.