/*
=== KDP Core: Dynamic Bid Management ===
Purpose: Scales bid adjustments proportionally based on distance from target ACOS using adaptive timing controls.
Recommended: Change Bid: Set ($) using $target_bid | Daily
*/

// === Core Settings ===
let $blend_profit_min = 6.00;                           // CORE: Minimum blended profit required for reliable ACOS evaluation ($6.00 threshold)
let $bid_min_change = 3%;                               // CORE: Minimum bid adjustment when change is warranted
let $bid_max_change = 10%;                              // CORE: Maximum bid adjustment when ACOS is at or beyond target ACOS thresholds

// === Target ACOS Thresholds ===
// Between buffer and thresholds: bid adjustments scale linearly from min to max change percent
let $t_blend_acos_buffer_min_change = 10%;              // STRATEGY: No-change buffer around target blended ACOS - min changes start outside this zone (Target Blended ACOS ± 10%) [e.g., 100% target = 90-110% no-change zone]
let $t_blend_acos_threshold_max_increase = 50%;         // STRATEGY: Max increase when blended ACOS ≤ (Target Blended ACOS × 50%) [e.g., 100% target = 50% max increase threshold]
let $t_blend_acos_threshold_max_decrease = 200%;        // STRATEGY: Max decrease when blended ACOS ≥ (Target Blended ACOS × 200%) [e.g., 100% target = 200% max decrease threshold]

// === Time Periods ===
let $period_short = 0d..7d;                    // TIME: Primary evaluation period (7 days including today)
let $cooldown_short = 2d;                      // TIME: Wait period after bid change for short data periods

let $period_medium = 0d..14d;                  // TIME: Secondary evaluation period (14 days including today)
let $cooldown_medium = 3d;                     // TIME: Wait period after bid change for medium data periods

let $period_long = 0d..30d;                    // TIME: Tertiary evaluation period (30 days including today)
let $cooldown_long = 5d;                       // TIME: Wait period after bid change for long data periods

let $period_extended = 0d..60d;                // TIME: Final fallback evaluation period (60 days including today)
let $cooldown_extended = 7d;                   // TIME: Wait period after bid change for extended data periods

// === Advanced Settings ===
let $bid_limit_cpc_multiplier = 2.0;          // SAFEGUARD: Max bid = Avg CPC × 2.0 [e.g., $0.50 CPC = $1.00 max]
let $bid_limit_cpc_period = 90d;              // SAFEGUARD: Period for calculating CPC-based bid limits

// === Segment Filters ===
let $include_campaigns = [""];                // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto", "Research"]
let $exclude_campaigns = ["NEVER_MATCH"];     // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test", "Archive"]

// ============================================================================
// === Blueprint Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// Multi-period data selection with extended coverage
let $blend_profit_short = blended profit($period_short);
let $blend_profit_medium = blended profit($period_medium);  
let $blend_profit_long = blended profit($period_long);
let $blend_profit_extended = blended profit($period_extended);

let $evaluation_blend_acos = case(
   $blend_profit_short >= $blend_profit_min => blended acos($period_short),
   $blend_profit_medium >= $blend_profit_min => blended acos($period_medium),
   $blend_profit_long >= $blend_profit_min => blended acos($period_long),
   $blend_profit_extended >= $blend_profit_min => blended acos($period_extended),
   else 99999  // No reliable data
);

// Track which period was used for diagnostics
let $data_quality = case(
   $blend_profit_short >= $blend_profit_min => "High Volume: Short Lookback",
   $blend_profit_medium >= $blend_profit_min => "Med Volume: Medium Lookback",
   $blend_profit_long >= $blend_profit_min => "Low Volume: Long Lookback",
   $blend_profit_extended >= $blend_profit_min => "Very Low Volume: Extended Lookback",
   else "insufficient"
);

// Adaptive cooldown periods based on data source
let $cooldown_cutoff = case(
   $blend_profit_short >= $blend_profit_min => now() - interval($cooldown_short),
   $blend_profit_medium >= $blend_profit_min => now() - interval($cooldown_medium),
   $blend_profit_long >= $blend_profit_min => now() - interval($cooldown_long),
   else now() - interval($cooldown_extended)
);

// Calculate performance ratio with Target Blended ACOS validation
let $blend_acos_ratio = case(
   $evaluation_blend_acos = 99999 => -1,       // No reliable data
   target acos <= 0 => -1,                     // Invalid target blended ACOS
   else $evaluation_blend_acos / target acos   // Performance ratio
);

// Check if within no-change buffer zone
let $within_buffer = case(
   $blend_acos_ratio < 0 => 1,                 // No change if no data or invalid target
   $blend_acos_ratio >= (1 - $t_blend_acos_buffer_min_change) and $blend_acos_ratio <= (1 + $t_blend_acos_buffer_min_change) => 1,
   else 0
);

// Proportional scaling for bid adjustments
let $performance_gap = case(
   $blend_acos_ratio < 0 => 0,                 // No gap if no data
   // Max increase region: ACOS at 50% of target or better
   $blend_acos_ratio <= $t_blend_acos_threshold_max_increase => 1,
   // Scaled increase region: ACOS between 50% and buffer zone (90% of target)
   $blend_acos_ratio < (1 - $t_blend_acos_buffer_min_change) =>
       ((1 - $t_blend_acos_buffer_min_change) - $blend_acos_ratio) /
       ((1 - $t_blend_acos_buffer_min_change) - $t_blend_acos_threshold_max_increase),
   // Max decrease region: ACOS at 200% of target or worse
   $blend_acos_ratio >= $t_blend_acos_threshold_max_decrease => 1,
   // Scaled decrease region: ACOS between buffer zone (110%) and 200% of target
   $blend_acos_ratio > (1 + $t_blend_acos_buffer_min_change) =>
       ($blend_acos_ratio - (1 + $t_blend_acos_buffer_min_change)) /
       ($t_blend_acos_threshold_max_decrease - (1 + $t_blend_acos_buffer_min_change)),
   else 0                                      // Within buffer zone - no adjustment
);

let $adjustment_percent = case(
   $within_buffer = 1 => 0%,                   // No change within buffer zone
   // Increase adjustments for ACOS below target
   $blend_acos_ratio <= $t_blend_acos_threshold_max_increase =>
       $bid_min_change + ($performance_gap * ($bid_max_change - $bid_min_change)),
   $blend_acos_ratio < (1 - $t_blend_acos_buffer_min_change) =>
       $bid_min_change + ($performance_gap * ($bid_max_change - $bid_min_change)),
   // Decrease adjustments for ACOS above target
   $blend_acos_ratio > (1 + $t_blend_acos_buffer_min_change) =>
       -1 * ($bid_min_change + ($performance_gap * ($bid_max_change - $bid_min_change))),
   else 0%
);

// Calculate target bid with CPC-based limits
let $initial_target_bid = bid * (1 + $adjustment_percent);

let $avg_cpc = cpc($bid_limit_cpc_period);
let $dynamic_max = case(
   $avg_cpc > 0 => $avg_cpc * $bid_limit_cpc_multiplier,
   else 999  // No CPC data = no dynamic limit
);

let $target_bid = case(
   $avg_cpc > 0 and $initial_target_bid > $dynamic_max => $dynamic_max,
   else $initial_target_bid
);

// Cooldown validation
let $cooldown_ready = case(
   is_null(last bid change) => 1,
   last bid change < $cooldown_cutoff => 1,
   else 0
);

// Diagnostic properties
let $reason = case(
   target acos <= 0 => "No target blended ACOS set",
   $evaluation_blend_acos = 99999 => "Insufficient blended profit data across all lookback periods",
   $within_buffer = 1 => case(
       $data_quality = "High Volume: Short Lookback" => "[High Volume: Short Lookback] Within target buffer zone",
       $data_quality = "Med Volume: Medium Lookback" => "[Med Volume: Medium Lookback] Within target buffer zone",
       $data_quality = "Low Volume: Long Lookback" => "[Low Volume: Long Lookback] Within target buffer zone",
       $data_quality = "Very Low Volume: Extended Lookback" => "[Very Low Volume: Extended Lookback] Within target buffer zone",
       else "Performance within target buffer zone"
   ),
   $cooldown_ready = 0 => case(
       $data_quality = "High Volume: Short Lookback" => "[High Volume: Short Lookback] Recently changed - cooldown active",
       $data_quality = "Med Volume: Medium Lookback" => "[Med Volume: Medium Lookback] Recently changed - cooldown active",
       $data_quality = "Low Volume: Long Lookback" => "[Low Volume: Long Lookback] Recently changed - cooldown active",
       $data_quality = "Very Low Volume: Extended Lookback" => "[Very Low Volume: Extended Lookback] Recently changed - cooldown active",
       else "Recently changed - cooldown active"
   ),
   $target_bid = bid => "No bid change calculated",
   $avg_cpc > 0 and $initial_target_bid > $dynamic_max => "Limited by CPC-based maximum",
   $adjustment_percent > 0 => case(
       $data_quality = "High Volume: Short Lookback" => "[High Volume: Short Lookback] Blended ACOS below target threshold",
       $data_quality = "Med Volume: Medium Lookback" => "[Med Volume: Medium Lookback] Blended ACOS below target threshold",
       $data_quality = "Low Volume: Long Lookback" => "[Low Volume: Long Lookback] Blended ACOS below target threshold",
       $data_quality = "Very Low Volume: Extended Lookback" => "[Very Low Volume: Extended Lookback] Blended ACOS below target threshold",
       else "Blended ACOS below target threshold"
   ),
   $adjustment_percent < 0 => case(
       $data_quality = "High Volume: Short Lookback" => "[High Volume: Short Lookback] Blended ACOS above target threshold",
       $data_quality = "Med Volume: Medium Lookback" => "[Med Volume: Medium Lookback] Blended ACOS above target threshold",
       $data_quality = "Low Volume: Long Lookback" => "[Low Volume: Long Lookback] Blended ACOS above target threshold",
       $data_quality = "Very Low Volume: Extended Lookback" => "[Very Low Volume: Extended Lookback] Blended ACOS above target threshold",
       else "Blended ACOS above target threshold"
   ),
   else "Performance at target"
);

let $result = case(
   $within_buffer = 0 and $cooldown_ready = 1 and $target_bid != bid => case(
       $adjustment_percent >= $bid_max_change => "Bid Increase: Max",
       $adjustment_percent >= $bid_max_change * 0.5 => "Bid Increase: Upper Range",
       $adjustment_percent > 0 => "Bid Increase: Lower Range",
       $adjustment_percent <= -1 * $bid_max_change => "Bid Decrease: Max",
       $adjustment_percent <= -1 * $bid_max_change * 0.5 => "Bid Decrease: Upper Range",
       $adjustment_percent < 0 => "Bid Decrease: Lower Range",
       else "No action needed"
   ),
   else "No action needed"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $within_buffer = 0
and $target_bid != bid
and $cooldown_ready = 1

/*
=== KDP Core: Adaptive Budget Management ===
Purpose: Prevents budget waste while ensuring adequate spend for data collection and performance scaling.
Recommended: Change Daily Budget | Set ($) using $new_budget | Daily or Multiple Times Daily
*/

// === Core Settings ===
let $high_utilization = 90%;                    // CORE: Daily spend % that indicates budget constraint
let $low_utilization = 50%;                     // CORE: Daily budget utilization % that triggers rightsizing
let $enable_cpc_minimums = 1;                   // ADVANCED: Enable CPC-based budget minimums (1=yes, 0=no)

// === Budget Increases (High Utilization) ===
let $t_blend_acos_threshold_increase = 130%;    // STRATEGY: Increase budget when blended ACOS ≤ (Target Blended ACOS × 130%) [e.g., 100% target = 130% threshold]
let $budget_increase_pct = 20%;                 // STRATEGY: Percentage increase when scaling up
let $blend_profit_min = 12.00;                  // STRATEGY: Minimum blended profit needed for reliable ACOS evaluation ($12.00 threshold)

let $acos_eval_short = 7d;                      // TIME: Recent performance period
let $acos_eval_medium = 14d;                    // TIME: Medium-term performance period
let $acos_eval_long = 30d;                      // TIME: Long-term performance period

// === Budget Rightsizing (Low Utilization) ===
let $spend_buffer = 130%;                       // STRATEGY: Buffer above avg daily spend when rightsizing (budget set to 130% avg daily spend)
let $budget_min = 5.00;                         // STRATEGY: Absolute minimum budget floor for rightsizing

let $cooldown_eval_period = 14d;                // TIME: Period for sustained utilization evaluation
let $cooldown_period = 14d;                     // TIME: Wait period between rightsizing actions

// === CPC-Based Budget Minimums ===
let $min_daily_clicks = 5;                      // ADVANCED: Minimum clicks per day budget should support
let $cpc_eval_period = 60d;                     // ADVANCED: Period for calculating average CPC for minimum budget

// === Segment Filters ===
let $include_campaigns = [""];                  // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto"]
let $exclude_campaigns = ["NEVER_MATCH"];       // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test", "Archive"]

// ============================================================================
// === Blueprint Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// Increase Path: Individual daily budget cap analysis
let $today_spend = spend(0d..0d);
let $yesterday_spend = spend(1d..1d);
let $day2_spend = spend(2d..2d);
let $day3_spend = spend(3d..3d);

let $today_capped = case($today_spend >= budget * $high_utilization => 1, else 0);
let $yesterday_capped = case($yesterday_spend >= budget * $high_utilization => 1, else 0);
let $day2_capped = case($day2_spend >= budget * $high_utilization => 1, else 0);
let $day3_capped = case($day3_spend >= budget * $high_utilization => 1, else 0);

let $any_day_budget_capped = case(
   $today_capped = 1 or $yesterday_capped = 1 or $day2_capped = 1 or $day3_capped = 1 => 1,
   else 0
);

// Increase Path: CPC-based data sufficiency check
let $avg_cpc = cpc($cpc_eval_period);
let $min_budget_for_data = case(
   $enable_cpc_minimums = 1 and $avg_cpc > 0 => $avg_cpc * $min_daily_clicks,
   else 0  // Data minimums disabled or no CPC data
);

let $budget_too_small = case(
   $enable_cpc_minimums = 1 and $avg_cpc > 0 and budget < $min_budget_for_data => 1,
   else 0
);

// Increase Path: Performance evaluation for increases (prioritize recent data)
let $blend_profit_short = blended profit($acos_eval_short);
let $blend_profit_medium = blended profit($acos_eval_medium);
let $blend_profit_long = blended profit($acos_eval_long);

let $performance_blend_acos = case(
   $blend_profit_short >= $blend_profit_min => blended acos($acos_eval_short),
   $blend_profit_medium >= $blend_profit_min => blended acos($acos_eval_medium),
   $blend_profit_long >= $blend_profit_min => blended acos($acos_eval_long),
   else 99999  // No reliable blended ACOS data
);

let $acos_good_for_increase = case(
   $performance_blend_acos = 99999 => 1,  // No blended ACOS data = allow increase
   target acos <= 0 => 0,  // Invalid target
   $performance_blend_acos <= (target acos * $t_blend_acos_threshold_increase) => 1,
   else 0
);

// Rightsizing Path: Sustained utilization analysis
let $total_spend = spend($cooldown_eval_period);
let $days_in_eval = 14;  // Days in 14d period
let $avg_daily_spend = $total_spend / $days_in_eval;
let $avg_utilization_rate = case(
   budget > 0 => $avg_daily_spend / budget,
   else 0
);

// Calculate effective minimum for decreases early
let $effective_min_for_decreases = case(
   $min_budget_for_data > $budget_min => $min_budget_for_data,  // Use CPC minimum if higher
   else $budget_min  // Otherwise use absolute minimum
);

let $rightsizing_cooldown_passed = case(
   is_null(last budget change) => 1,
   last budget change < now() - interval($cooldown_period) => 1,
   else 0
);

// Decision logic by path
let $should_increase = case(
   $budget_too_small = 1 => 1,  // Data-starved campaign
   $any_day_budget_capped = 1 and $acos_good_for_increase = 1 => 1,  // Budget-capped + good performance
   else 0
);

let $should_rightsize = case(
   $rightsizing_cooldown_passed = 0 => 0,  // Cooldown period active
   budget <= $effective_min_for_decreases => 0,  // Already at or below minimum - don't rightsize
   $avg_utilization_rate < $low_utilization => 1,  // Sustained low utilization (including 0% from no spend)
   else 0
);

// Calculate new budget
let $increase_budget = budget * (1 + $budget_increase_pct);

// For rightsizing, calculate based on actual usage plus buffer
let $rightsized_budget = case(
   $avg_daily_spend > 0 => $avg_daily_spend * $spend_buffer,
   else $budget_min  // No spend = use minimum budget
);

let $calculated_budget = case(
   $should_increase = 1 => $increase_budget,
   $should_rightsize = 1 => $rightsized_budget,
   else budget
);

// Apply minimums - different rules for increases vs decreases
let $final_minimum = case(
   $should_rightsize = 1 => case(
       $effective_min_for_decreases > 1.00 => $effective_min_for_decreases,  // Use effective minimum if higher than platform
       else 1.00  // Otherwise platform minimum
   ),
   $should_increase = 1 and $budget_too_small = 1 => case(
       $min_budget_for_data > 1.00 => $min_budget_for_data,  // Use CPC minimum for data generation increases
       else 1.00  // Platform minimum
   ),
   else 1.00  // Platform minimum for budget-capping increases
);

let $new_budget = case(
   $calculated_budget < $final_minimum => $final_minimum,
   else $calculated_budget
);

// Diagnostic properties
let $reason = case(
   target acos <= 0 => "No target blended ACOS set",
   $should_increase = 1 and $budget_too_small = 1 => case(
       $avg_utilization_rate <= 0.10 => "[0-10%] Below CPC minimum threshold",
       $avg_utilization_rate <= 0.30 => "[10-30%] Below CPC minimum threshold",
       $avg_utilization_rate <= 0.50 => "[30-50%] Below CPC minimum threshold",
       $avg_utilization_rate <= 0.70 => "[50-70%] Below CPC minimum threshold",
       $avg_utilization_rate <= 0.90 => "[70-90%] Below CPC minimum threshold",
       else "[90%+] Below CPC minimum threshold"
   ),
   $should_increase = 1 => case(
       $avg_utilization_rate <= 0.70 => "[50-70%] Above high utilization threshold, blended ACOS acceptable",
       $avg_utilization_rate <= 0.90 => "[70-90%] Above high utilization threshold, blended ACOS acceptable",
       else "[90%+] Above high utilization threshold, blended ACOS acceptable"
   ),
   $rightsizing_cooldown_passed = 0 => case(
       $avg_utilization_rate = 0 => "[0%] Below low utilization threshold, cooldown active",
       $avg_utilization_rate <= 0.10 => "[0-10%] Below low utilization threshold, cooldown active",
       $avg_utilization_rate <= 0.30 => "[10-30%] Below low utilization threshold, cooldown active",
       $avg_utilization_rate <= 0.50 => "[30-50%] Below low utilization threshold, cooldown active",
       else "[50%+] Below low utilization threshold, cooldown active"
   ),
   $should_rightsize = 1 => case(
       $avg_utilization_rate = 0 => "[0%] Below low utilization threshold",
       $avg_utilization_rate <= 0.10 => "[0-10%] Below low utilization threshold",
       $avg_utilization_rate <= 0.30 => "[10-30%] Below low utilization threshold",
       $avg_utilization_rate <= 0.50 => "[30-50%] Below low utilization threshold",
       else "[50-70%] Below low utilization threshold"
   ),
   $any_day_budget_capped = 1 and $acos_good_for_increase = 0 => case(
       $avg_utilization_rate <= 0.70 => "[50-70%] Above high utilization threshold, blended ACOS too high",
       $avg_utilization_rate <= 0.90 => "[70-90%] Above high utilization threshold, blended ACOS too high",
       else "[90%+] Above high utilization threshold, blended ACOS too high"
   ),
   budget <= $effective_min_for_decreases => case(
       $avg_utilization_rate = 0 => "[0%] Budget below rightsizing minimum",
       $avg_utilization_rate <= 0.30 => "[0-30%] Budget below rightsizing minimum",
       else "[30-50%] Budget below rightsizing minimum"
   ),
   else case(
       $avg_utilization_rate = 0 => "[0%] Within acceptable utilization",
       $avg_utilization_rate <= 0.10 => "[0-10%] Within acceptable utilization",
       $avg_utilization_rate <= 0.30 => "[10-30%] Within acceptable utilization",
       $avg_utilization_rate <= 0.50 => "[30-50%] Within acceptable utilization",
       $avg_utilization_rate <= 0.70 => "[50-70%] Within acceptable utilization",
       $avg_utilization_rate <= 0.90 => "[70-90%] Within acceptable utilization",
       else "[90%+] Within acceptable utilization"
   )
);

let $result = case(
   $should_increase = 1 and $budget_too_small = 1 => "Budget Increase: CPC Minimum",
   $should_increase = 1 => "Budget Increase: High Utilization",
   $should_rightsize = 1 => "Budget Decrease: Rightsizing",
   else "No Action"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and ($should_increase = 1 or $should_rightsize = 1)
and $new_budget != budget

/*
=== KDP Core: Product Ad Waste Elimination ===
Version: 1.1
Docs: merchjar.com/templates/kdp-core-product-ad-waste-elimination

Purpose: Pause wasteful product ads that have spent enough without efficient results.
Dataset: Product Ads
Recommended: Set State | Daily Schedule
*/

// === Core Settings ===
let $clicks_threshold = 20;                  // CORE: Base clicks required before evaluation
let $spend_threshold = 5.00;                 // CORE: Base spend required before evaluation

// === Safeguards ===
let $safeguard_profit = 50.00;               // SAFEGUARD: Never pause ads with this much blended profit ($) or more
let $safeguard_acos = 400%;                  // SAFEGUARD: Never pause if blended ACOS ≤ (Target × 400%) [e.g., 100% target = 400% threshold]

// === Advanced Settings ===
let $clicks_scaling_per_profit_unit = 20;    // ADVANCED: Additional clicks required per $5 blended profit [e.g., $10 profit = 20 + 40 = 60 clicks]
let $spend_scaling_per_profit_unit = 5.00;   // ADVANCED: Additional spend required per $5 blended profit [e.g., $10 profit = $5 + $10 = $15]

// === Segment Filters ===
let $include_campaigns = [""];               // FILTER: Apply to all campaigns, or specify terms
let $exclude_campaigns = ["NEVER_MATCH"];    // FILTER: Exclude campaigns containing these terms

// ============================================================================
// === Segment Logic ===
// ============================================================================

// Performance metrics
let $lifetime_profit = blended profit(lifetime);
let $lifetime_clicks = clicks(lifetime);
let $lifetime_spend = spend(lifetime);
let $lifetime_acos = blended acos(lifetime);

// Calculate profit units for scaling ($5 = 1 unit)
let $profit_units = case(
   $lifetime_profit > 0 => $lifetime_profit / 5,
   else 0
);

// Scaled thresholds - require more data as profit accumulates
let $clicks_required = $clicks_threshold + ($profit_units * $clicks_scaling_per_profit_unit);
let $spend_required = $spend_threshold + ($profit_units * $spend_scaling_per_profit_unit);

// Data sufficiency
let $sufficient_data = case(
   $lifetime_clicks >= $clicks_required and $lifetime_spend >= $spend_required => 1,
   else 0
);

// Safeguard checks
let $high_profit_protection = case(
   $lifetime_profit >= $safeguard_profit => 1,
   else 0
);

let $acos_protection = case(
   $lifetime_profit > 0 and target acos > 0 and $lifetime_acos <= target acos * $safeguard_acos => 1,
   else 0
);

// === Pausing Paths ===

// Zero-profit waste: sufficient data with no profit
let $zero_profit_candidate = case(
   $lifetime_profit <= 0 and $sufficient_data = 1 => 1,
   else 0
);

// Poor ACOS: has profit, sufficient data, and blended ACOS exceeds threshold
let $poor_acos_candidate = case(
   $lifetime_profit > 0 and $sufficient_data = 1 and target acos > 0 and $lifetime_acos > target acos * $safeguard_acos => 1,
   else 0
);

// Combined pausing candidate
let $pausing_candidate = case(
   $zero_profit_candidate = 1 or $poor_acos_candidate = 1 => 1,
   else 0
);

// === Diagnostics ===
let $reason = case(
   $high_profit_protection = 1 => "Protected - high blended profit",
   $acos_protection = 1 => "Protected - blended ACOS within acceptable range",
   $zero_profit_candidate = 1 => "Zero blended profit with sufficient spend/clicks",
   $poor_acos_candidate = 1 => "Blended ACOS exceeds safeguard threshold",
   $lifetime_profit <= 0 and $lifetime_spend < $spend_required and $lifetime_clicks < $clicks_required => "Insufficient spend and clicks",
   $lifetime_profit <= 0 and $lifetime_spend < $spend_required => "Insufficient spend",
   $lifetime_profit <= 0 => "Insufficient clicks",
   $lifetime_profit > 0 and $sufficient_data = 0 => "Insufficient data for profit level",
   $lifetime_profit > 0 and target acos <= 0 => "No target ACOS set",
   else "Performing within acceptable range"
);

let $result = case(
   $high_profit_protection = 1 => "Protected - No Action",
   $acos_protection = 1 => "Protected - No Action",
   $zero_profit_candidate = 1 => "Pause - Zero Profit",
   $poor_acos_candidate = 1 => "Pause - High Blended ACOS",
   else "No Action"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $pausing_candidate = 1
and $high_profit_protection = 0

/*
=== Core: Product Ad Waste Elimination ===
Version: 1.1
Docs: merchjar.com/templates/core-product-ad-waste-elimination

Purpose: Pause wasteful product ads that have spent enough without efficient results.
Dataset: Product Ads
Recommended: Set State | Daily Schedule
*/

// === Core Settings ===
let $clicks_threshold = 20;                  // CORE: Base clicks required before evaluation
let $spend_threshold = 5.00;                 // CORE: Base spend required before evaluation

// === Safeguards ===
let $safeguard_orders = 10;                  // SAFEGUARD: Never pause ads with this many orders or more
let $safeguard_acos = 400%;                  // SAFEGUARD: Never pause if ACOS ≤ (Target × 400%) [e.g., 30% target = 120% threshold]

// === Advanced Settings ===
let $clicks_scaling_per_order = 20;          // ADVANCED: Additional clicks required per order [e.g., 2 orders = 20 + (2 × 20) = 60 clicks]
let $spend_scaling_per_order = 5.00;         // ADVANCED: Additional spend required per order [e.g., 2 orders = $5 + (2 × $5) = $15]

// === Segment Filters ===
let $include_campaigns = [""];               // FILTER: Apply to all campaigns, or specify terms
let $exclude_campaigns = ["NEVER_MATCH"];    // FILTER: Exclude campaigns containing these terms

// ============================================================================
// === Segment Logic ===
// ============================================================================

// Performance metrics
let $lifetime_orders = orders(lifetime);
let $lifetime_clicks = clicks(lifetime);
let $lifetime_spend = spend(lifetime);
let $lifetime_acos = acos(lifetime);

// Scaled thresholds - require more data as orders accumulate
let $clicks_required = $clicks_threshold + ($lifetime_orders * $clicks_scaling_per_order);
let $spend_required = $spend_threshold + ($lifetime_orders * $spend_scaling_per_order);

// Data sufficiency
let $sufficient_data = case(
   $lifetime_clicks >= $clicks_required and $lifetime_spend >= $spend_required => 1,
   else 0
);

// Safeguard checks
let $high_order_protection = case(
   $lifetime_orders >= $safeguard_orders => 1,
   else 0
);

let $acos_protection = case(
   $lifetime_orders > 0 and target acos > 0 and $lifetime_acos <= target acos * $safeguard_acos => 1,
   else 0
);

// === Pausing Paths ===

// Zero-order waste: sufficient data with no conversions
let $zero_order_candidate = case(
   $lifetime_orders = 0 and $sufficient_data = 1 => 1,
   else 0
);

// Poor ACOS: has orders, sufficient data, and ACOS exceeds threshold
let $poor_acos_candidate = case(
   $lifetime_orders > 0 and $sufficient_data = 1 and target acos > 0 and $lifetime_acos > target acos * $safeguard_acos => 1,
   else 0
);

// Combined pausing candidate
let $pausing_candidate = case(
   $zero_order_candidate = 1 or $poor_acos_candidate = 1 => 1,
   else 0
);

// === Diagnostics ===
let $reason = case(
   $high_order_protection = 1 => "Protected - high order volume",
   $acos_protection = 1 => "Protected - ACOS within acceptable range",
   $zero_order_candidate = 1 => "Zero orders with sufficient spend/clicks",
   $poor_acos_candidate = 1 => "ACOS exceeds safeguard threshold",
   $lifetime_orders = 0 and $lifetime_spend < $spend_required and $lifetime_clicks < $clicks_required => "Insufficient spend and clicks",
   $lifetime_orders = 0 and $lifetime_spend < $spend_required => "Insufficient spend",
   $lifetime_orders = 0 => "Insufficient clicks",
   $lifetime_orders > 0 and $sufficient_data = 0 => "Insufficient data for order volume",
   $lifetime_orders > 0 and target acos <= 0 => "No target ACOS set",
   else "Performing within acceptable range"
);

let $result = case(
   $high_order_protection = 1 => "Protected - No Action",
   $acos_protection = 1 => "Protected - No Action",
   $zero_order_candidate = 1 => "Pause - Zero Orders",
   $poor_acos_candidate = 1 => "Pause - High ACOS",
   else "No Action"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $pausing_candidate = 1
and $high_order_protection = 0

/*
=== Newly Sold Search Terms ===
Purpose: Find search terms with recent orders that have never sold before.
Dataset: Search Terms
Recommended: Export for review | Daily or Weekly
*/

// === Core Settings ===
let $recent_period = 0d..7d;                     // CORE: Recent period for new sales [Change both periods together: 7d recent = 8d.. historical]
let $historical_period = 8d..;                   // CORE: Historical period - must start day after recent ends
let $orders_min_recent = 1;                      // CORE: Minimum orders in recent period to qualify

// === Strategy Settings ===
let $t_acos_threshold = 150%;                    // STRATEGY: Only flag if ACOS ≤ (Target ACOS × 150%) [e.g., 30% target = 45% threshold]
let $orders_min_for_acos_eval = 3;               // STRATEGY: Minimum orders needed for ACOS reliability check

// === Segment Filters ===
let $include_campaigns = [""];                   // FILTER: Apply to all campaigns
let $exclude_campaigns = ["NEVER_MATCH"];        // FILTER: Exclude campaigns containing these terms

// ============================================================================
// === Segment Logic ===
// ============================================================================

// Define time periods for comparison
let $recent_orders = orders($recent_period);
let $historical_orders = orders($historical_period);

// Check if this is truly a "new winner"
let $is_new_winner = case(
   $recent_orders >= $orders_min_recent and $historical_orders = 0 => 1,
   else 0
);

// Performance validation for new winners
let $recent_acos = acos($recent_period);

let $performance_acceptable = case(
   target acos <= 0 => 1,                                              // No target set = accept
   $recent_orders < $orders_min_for_acos_eval => 1,                   // Not enough data for ACOS check
   $recent_acos <= (target acos * $t_acos_threshold) => 1,           // ACOS acceptable
   else 0
);

// Final qualification
let $qualified = case(
   $is_new_winner = 1 and $performance_acceptable = 1 => 1,
   else 0
);

// Diagnostic properties
let $reason = case(
   $recent_orders = 0 => "No recent orders",
   $historical_orders > 0 => "Already has historical sales",
   $recent_orders < $orders_min_recent => "Insufficient recent orders",
   $performance_acceptable = 0 => "Recent ACOS too high",
   $qualified = 1 => "New winner identified",
   else "Not qualified"
);

let $result = case(
   $qualified = 1 and $recent_orders >= 5 => "Strong New Winner",
   $qualified = 1 and $recent_orders >= 3 => "Solid New Winner",
   $qualified = 1 => "Emerging New Winner",
   $is_new_winner = 1 and $performance_acceptable = 0 => "New Sales - Poor ACOS",
   $historical_orders > 0 => "Established Performer",
   else "No Action"
);

// === Final Filter ===
negated = false
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $qualified = 1

/*
=== Anomaly Detection: Spend ===
Purpose: Identifies entities driving spend changes for account-level investigation.
Datasets: Campaigns | Ad Groups | Keywords & Targets | Keywords | Targets | Ads | Search Terms
Recommended: Ad-hoc investigation tool | Change dataset based on investigation depth needed
*/

// === Time Periods ===
let $period_recent = 0d..7d;                    // TIME: Recent spend window (7 days)
let $period_baseline = 8d..35d;                 // TIME: Baseline comparison (28 days)

// === Reliability Thresholds ===
let $spend_min = 5.00;                          // CORE: Minimum baseline spend for reliable analysis [e.g., $5+ spend]
let $impressions_min = 50;                      // CORE: Minimum baseline impressions for meaningful context [e.g., 50+ impressions]
let $clicks_min = 5;                            // CORE: Minimum baseline clicks for reliable spend attribution [e.g., 5+ clicks]

// === Shift Detection ===
let $spend_moderate = 30%;                      // STRATEGY: Moderate spend shift threshold [e.g., 30% = $100 to $130 or $70]
let $spend_severe = 75%;                        // STRATEGY: Severe spend shift threshold [e.g., 75% = $100 to $175 or $25]
let $component_threshold = 25%;                 // STRATEGY: Click/CPC shift to attribute root cause [e.g., 25% shift = meaningful driver]

// === Performance Context ===
let $acos_acceptable_threshold = 120%;          // STRATEGY: ACOS threshold for performance assessment [e.g., 120% = 30% target → 36% acceptable]
let $acos_problem_threshold = 150%;             // STRATEGY: ACOS threshold for problem identification [e.g., 150% = 30% target → 45% problem]

// === Segment Filters ===
let $include_campaigns = [""];                  // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto", "Research"]
let $exclude_campaigns = ["NEVER_MATCH"];       // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test", "Archive"]

// ============================================================================
// === Segment Logic ===
// ============================================================================

// === Baseline & Recent Metrics ===
let $spend_recent = spend($period_recent);
let $spend_baseline = spend($period_baseline);
let $impressions_recent = impressions($period_recent);
let $impressions_baseline = impressions($period_baseline);
let $clicks_recent = clicks($period_recent);
let $clicks_baseline = clicks($period_baseline);
let $cpc_recent = cpc($period_recent);
let $cpc_baseline = cpc($period_baseline);
let $acos_recent = acos($period_recent);
let $acos_baseline = acos($period_baseline);
let $orders_recent = orders($period_recent);
let $orders_baseline = orders($period_baseline);

// === Data Reliability ===
let $sufficient_data = case(
   $spend_baseline >= $spend_min and $impressions_baseline >= $impressions_min and $clicks_baseline >= $clicks_min => 1,
   else 0
);

let $sufficient_for_acos = case(
   $orders_recent >= 1 and $orders_baseline >= 1 => 1,
   else 0
);

// === Calculate Changes ===
// Spend = Clicks × CPC, so analyze these components
let $spend_change = case(
   $spend_baseline > 0 => ($spend_recent - $spend_baseline) / $spend_baseline,
   else 0
);

let $clicks_change = case(
   $clicks_baseline > 0 => ($clicks_recent - $clicks_baseline) / $clicks_baseline,
   else 0
);

let $cpc_change = case(
   $cpc_baseline > 0 => ($cpc_recent - $cpc_baseline) / $cpc_baseline,
   else 0
);

let $acos_change = case(
   $sufficient_for_acos = 1 and $acos_baseline > 0 => ($acos_recent - $acos_baseline) / $acos_baseline,
   else 0
);

// === Severity Assessment ===
let $spend_severity = case(
   $spend_change >= $spend_severe => "severe_increase",
   $spend_change >= $spend_moderate => "moderate_increase",
   $spend_change <= -1 * $spend_severe => "severe_decrease",
   $spend_change <= -1 * $spend_moderate => "moderate_decrease",
   else "normal"
);

let $has_anomaly = case(
   $spend_severity != "normal" => 1,
   else 0
);

// === Root Cause Analysis ===
// Determine if spend change is driven by click volume or cost per click
let $driven_by_clicks = case(
   $clicks_change >= $component_threshold or $clicks_change <= -1 * $component_threshold => 1,
   else 0
);

let $driven_by_cpc = case(
   $cpc_change >= $component_threshold or $cpc_change <= -1 * $component_threshold => 1,
   else 0
);

let $change_driver = case(
   $driven_by_clicks = 1 and $driven_by_cpc = 1 => "clicks_and_cpc",
   $driven_by_clicks = 1 => "click_volume",
   $driven_by_cpc = 1 => "cost_per_click",
   else "minor_shifts"

);

// === Performance Assessment ===
let $performance_status = case(
   $sufficient_for_acos = 0 => "insufficient_data",
   target acos <= 0 => "no_target",
   $acos_recent > target acos * $acos_problem_threshold => "poor_efficiency",
   $acos_recent > target acos * $acos_acceptable_threshold => "acceptable_efficiency",
   $acos_recent > target acos => "near_target",
   else "good_efficiency"
);

// === Spend Impact Assessment ===
let $spend_impact = case(
   $spend_recent >= 50.00 => "high_impact",
   $spend_recent >= 20.00 => "medium_impact",
   $spend_recent >= 5.00 => "low_impact",
   else "minimal_impact"
);

// === Diagnostic Properties ===
let $reason = case(
   $sufficient_data = 0 => "Insufficient spend history",
   $has_anomaly = 0 => "No significant spend shift detected",

   // Severe increases with performance context
   $spend_severity = "severe_increase" and $performance_status = "poor_efficiency" and $change_driver = "click_volume" => "Severe spend increase from click volume growth with poor ACOS",
   $spend_severity = "severe_increase" and $performance_status = "poor_efficiency" and $change_driver = "cost_per_click" => "Severe spend increase from CPC escalation with poor ACOS",
   $spend_severity = "severe_increase" and $performance_status = "poor_efficiency" => "Severe spend increase with poor efficiency",

   $spend_severity = "severe_increase" and $change_driver = "click_volume" => "Severe spend increase driven by click volume growth",
   $spend_severity = "severe_increase" and $change_driver = "cost_per_click" => "Severe spend increase driven by CPC escalation",
   $spend_severity = "severe_increase" and $change_driver = "clicks_and_cpc" => "Severe spend increase from both click volume and CPC rises",
   $spend_severity = "severe_increase" => "Severe spend increase detected",

   // Moderate increases with performance context
   $spend_severity = "moderate_increase" and $performance_status = "poor_efficiency" and $change_driver = "click_volume" => "Moderate spend increase from click volume with poor ACOS",
   $spend_severity = "moderate_increase" and $performance_status = "poor_efficiency" and $change_driver = "cost_per_click" => "Moderate spend increase from CPC rise with poor ACOS",
   $spend_severity = "moderate_increase" and $performance_status = "poor_efficiency" => "Moderate spend increase with poor efficiency",

   $spend_severity = "moderate_increase" and $change_driver = "click_volume" => "Moderate spend increase from click volume growth",
   $spend_severity = "moderate_increase" and $change_driver = "cost_per_click" => "Moderate spend increase from CPC rise",
   $spend_severity = "moderate_increase" and $change_driver = "clicks_and_cpc" => "Moderate spend increase from click volume and CPC",
   $spend_severity = "moderate_increase" => "Moderate spend increase detected",

   // Decreases with performance context
   $spend_severity = "severe_decrease" and $performance_status = "good_efficiency" and $change_driver = "click_volume" => "Severe spend drop from lost clicks despite good ACOS",
   $spend_severity = "severe_decrease" and $change_driver = "click_volume" => "Severe spend drop due to lost clicks",
   $spend_severity = "severe_decrease" and $change_driver = "cost_per_click" => "Severe spend drop due to CPC decrease",
   $spend_severity = "severe_decrease" and $change_driver = "clicks_and_cpc" => "Severe spend drop from both click and CPC declines",
   $spend_severity = "severe_decrease" => "Severe spend decrease detected",

   $spend_severity = "moderate_decrease" and $performance_status = "good_efficiency" and $change_driver = "click_volume" => "Moderate spend drop from reduced clicks despite good ACOS",
   $spend_severity = "moderate_decrease" and $change_driver = "click_volume" => "Moderate spend drop from reduced clicks",
   $spend_severity = "moderate_decrease" and $change_driver = "cost_per_click" => "Moderate spend drop from CPC decrease",
   $spend_severity = "moderate_decrease" and $change_driver = "clicks_and_cpc" => "Moderate spend drop from click and CPC declines",
   $spend_severity = "moderate_decrease" => "Moderate spend decrease detected",

   else "No significant spend pattern change"
);

let $result = case(
   $sufficient_data = 0 => "insufficient_data",
   $has_anomaly = 0 => "insufficient_data",

   // Problem increases (high spend + poor efficiency) - sort to top
   $spend_severity = "severe_increase" and $performance_status = "poor_efficiency" and $spend_impact = "high_impact" => "Problem: Severe Increase + Poor ACOS [High $]",
   $spend_severity = "severe_increase" and $performance_status = "poor_efficiency" => "Problem: Severe Increase + Poor ACOS",
   $spend_severity = "moderate_increase" and $performance_status = "poor_efficiency" and $spend_impact = "high_impact" => "Problem: Moderate Increase + Poor ACOS [High $]",
   $spend_severity = "moderate_increase" and $performance_status = "poor_efficiency" => "Problem: Moderate Increase + Poor ACOS",

   // Neutral/good increases
   $spend_severity = "severe_increase" and $performance_status = "good_efficiency" and $change_driver = "click_volume" => "Scaling: Severe Increase (Clicks) + Good ACOS",
   $spend_severity = "severe_increase" and $change_driver = "click_volume" => "Increase: Severe (Click Volume)",
   $spend_severity = "severe_increase" and $change_driver = "cost_per_click" => "Increase: Severe (CPC Spike)",
   $spend_severity = "severe_increase" and $change_driver = "clicks_and_cpc" => "Increase: Severe (Clicks + CPC)",
   $spend_severity = "severe_increase" => "Increase: Severe",

   $spend_severity = "moderate_increase" and $performance_status = "good_efficiency" and $change_driver = "click_volume" => "Scaling: Moderate Increase (Clicks) + Good ACOS",
   $spend_severity = "moderate_increase" and $change_driver = "click_volume" => "Increase: Moderate (Click Volume)",
   $spend_severity = "moderate_increase" and $change_driver = "cost_per_click" => "Increase: Moderate (CPC)",
   $spend_severity = "moderate_increase" and $change_driver = "clicks_and_cpc" => "Increase: Moderate (Clicks + CPC)",
   $spend_severity = "moderate_increase" => "Increase: Moderate",

   // Opportunity decreases (good performers losing volume)
   $spend_severity = "severe_decrease" and $performance_status = "good_efficiency" and $change_driver = "click_volume" => "Opportunity: Severe Decrease (Clicks) + Good ACOS",
   $spend_severity = "moderate_decrease" and $performance_status = "good_efficiency" and $change_driver = "click_volume" => "Opportunity: Moderate Decrease (Clicks) + Good ACOS",

   // Normal decreases
   $spend_severity = "severe_decrease" and $change_driver = "click_volume" => "Decrease: Severe (Click Loss)",
   $spend_severity = "severe_decrease" and $change_driver = "cost_per_click" => "Decrease: Severe (CPC Drop)",
   $spend_severity = "severe_decrease" and $change_driver = "clicks_and_cpc" => "Decrease: Severe (Clicks + CPC)",
   $spend_severity = "severe_decrease" => "Decrease: Severe",

   $spend_severity = "moderate_decrease" and $change_driver = "click_volume" => "Decrease: Moderate (Click Loss)",
   $spend_severity = "moderate_decrease" and $change_driver = "cost_per_click" => "Decrease: Moderate (CPC Drop)",
   $spend_severity = "moderate_decrease" and $change_driver = "clicks_and_cpc" => "Decrease: Moderate (Clicks + CPC)",
   $spend_severity = "moderate_decrease" => "Decrease: Moderate",

   // Catch-all for any edge cases
   else "insufficient_data"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $sufficient_data = 1
and $has_anomaly = 1
and $result != "insufficient_data"

/*
=== Core: Impression Recovery Boost ===
Purpose: Increases bids for proven performers when impression volume drops significantly.
Recommended: Change Bid: Set ($) using $target_bid | Daily
*/

// === Core Settings ===
let $orders_min_lifetime = 10;                  // CORE: Minimum lifetime orders to qualify as proven performer [e.g., 15+ orders = established winner]
let $orders_min_baseline = 0;                   // CORE: Minimum orders in baseline period for reliable ACOS evaluation [e.g., 2+ orders in 30 days]
let $impression_drop_threshold = 40%;           // CORE: Act when impressions drop at least 40% from baseline [e.g., 40% = from 1000 to 600 daily impressions]
let $bid_change_increase = 10%;                 // CORE: Bid increase amount when conditions are met [e.g., 10% = $1.00 bid increases to $1.10]

// === Strategy Settings ===
let $t_acos_threshold_increase = 120%;          // STRATEGY: Only increase if ACOS ≤ (Target ACOS × 120%) [e.g., 30% target = 36% threshold]
let $impressions_min_daily = 50;                // STRATEGY: Minimum daily impressions for reliable baseline [e.g., 50+ impressions/day = meaningful traffic]
let $cooldown_period = 3d;                      // TIME: Wait 3 days after bid change before adjusting again

// === Time Periods ===
let $period_recent = 7d;                        // TIME: Recent period for drop detection (7 days including today)
let $period_baseline = 90d;                     // TIME: Baseline comparison period (30 days including today)

// === Advanced Settings ===
let $bid_limit_cpc_multiplier = 2.0;            // SAFEGUARD: Max bid = Avg CPC × 2.0 [e.g., $0.50 CPC = $1.00 max]
let $bid_limit_cpc_period = 90d;                // SAFEGUARD: Period for calculating CPC-based bid limits (90 days)

// === Segment Filters ===
let $include_campaigns = [""];                  // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto", "Research"]
let $exclude_campaigns = ["NEVER_MATCH"];       // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test", "Archive"]

// ============================================================================
// === Segment Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// === Impression Analysis ===
let $recent_impressions = impressions($period_recent);
let $baseline_impressions = impressions($period_baseline);

let $recent_days = interval($period_recent) / 86400;
let $baseline_days = interval($period_baseline) / 86400;

let $recent_daily_avg = $recent_impressions / $recent_days;
let $baseline_daily_avg = $baseline_impressions / $baseline_days;

let $impression_drop_ratio = case(
   $baseline_daily_avg > 0 => ($baseline_daily_avg - $recent_daily_avg) / $baseline_daily_avg,
   else 0  // No baseline data = no drop detected
);

// === Performance Protection ===
let $baseline_orders = orders($period_baseline);
let $baseline_acos = acos($period_baseline);
let $acos_acceptable = case(
   target acos > 0 and $baseline_orders >= $orders_min_baseline and $baseline_acos <= (target acos * $t_acos_threshold_increase) => 1,
   else 0
);

// === Bid Calculation ===
let $calculated_target_bid = bid * (1 + $bid_change_increase);

// === Dynamic Bid Cap ===
let $avg_cpc = cpc($bid_limit_cpc_period);
let $dynamic_cap = case(
   $avg_cpc > 0 => $avg_cpc * $bid_limit_cpc_multiplier,
   else 999  // No cap if no CPC history
);

let $target_bid = case(
   $calculated_target_bid > $dynamic_cap => $dynamic_cap,
   $calculated_target_bid < 0.02 => 0.02,
   else $calculated_target_bid
);

// === Cooldown Check ===
let $cooldown_cutoff = now() - interval($cooldown_period);
let $timing_ready = case(
   is_null(last bid change) => 1,
   last bid change < $cooldown_cutoff => 1,
   else 0
);

// === Qualification Logic ===
let $impression_drop_detected = case(
   $impression_drop_ratio >= $impression_drop_threshold => 1,
   else 0
);

let $action_needed = case(
   target acos <= 0 => 0,                       // Invalid target
   orders(lifetime) < $orders_min_lifetime => 0, // Not proven performer
   $baseline_daily_avg < $impressions_min_daily => 0, // Insufficient baseline data
   $impression_drop_detected = 0 => 0,          // No drop detected
   $acos_acceptable = 0 => 0,                   // Poor baseline performance
   $timing_ready = 0 => 0,                      // Cooldown active
   $target_bid <= bid => 0,                     // No increase calculated
   else 1
);

// === Diagnostic Properties ===
let $reason = case(
   target acos <= 0 => "No target ACOS set",
   orders(lifetime) < $orders_min_lifetime => "Insufficient lifetime orders",
   $baseline_daily_avg < $impressions_min_daily => "Low baseline impression volume",
   $impression_drop_detected = 0 => "No qualifying drop detected",
   $acos_acceptable = 0 => "ACOS too high for increase",
   $timing_ready = 0 => "Cooldown active",
   $target_bid <= bid => "No bid increase calculated",
   $action_needed = 1 => "Drop detected - increasing bid",
   else "Stable impression volume"
);

let $result = case(
   $action_needed = 1 => case(
       $impression_drop_ratio >= 0.75 => "Bid Increase: Major Drop (75%+)",
       $impression_drop_ratio >= 0.50 => "Bid Increase: Significant Drop (50-75%)",
       $impression_drop_ratio >= 0.25 => "Bid Increase: Moderate Drop (25-50%)",
       $calculated_target_bid > $dynamic_cap => "Bid Increase: CPC Limited",
       else "Bid Increase: Minor Drop (<25%)"
   ),
   $impression_drop_ratio >= 0.75 => "Major Drop (75%+) - No Action",
   $impression_drop_ratio >= 0.50 => "Significant Drop (50-75%) - No Action",
   $impression_drop_ratio >= 0.25 => "Moderate Drop (25-50%) - No Action",
   $impression_drop_ratio > 0 => "Minor Drop (<25%) - No Action",
   $impression_drop_ratio < 0 => "Impressions Increased",
   else "No Change Detected"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $action_needed = 1

/*
=== Utility: Target CPC Calculator ===
Purpose: Calculate target bids from performance efficiency metrics (ACOS, AOV, CVR) for manual bid optimization.
Dataset: Keywords & Targets
Recommended: Change Bid → Set ($) using $target_bid | Manual Execution
Note: Run on-demand after reviewing performance - not intended for automated daily execution
*/

// === Core Settings ===
let $orders_min = 2;                            // CORE: Minimum orders required for reliable calculation
let $clicks_min = 20;                           // CORE: Minimum clicks required for reliable calculation
let $period_eval = 30d;                         // CORE: Performance evaluation period [30 days including today]

// === Safeguards ===
let $bid_limit_cpc_multiplier = 2.0;            // SAFEGUARD: Max bid = Avg CPC × 2.0 [e.g., $0.50 CPC = $1.00 max]
let $bid_limit_cpc_period = 90d;                // SAFEGUARD: Period for calculating CPC-based limits

// === Segment Filters ===
let $include_campaigns = [""];                  // FILTER: Apply to all campaigns, or specify terms
let $exclude_campaigns = ["NEVER_MATCH"];       // FILTER: Exclude campaigns containing these terms

// ============================================================================
// === Segment Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// === Target CPC Calculation Method ===
// Formula: Target CPC = Target ACOS × Average Order Value × Conversion Rate
//
// Example: If targeting 30% ACOS with $50 AOV and 5% CVR:
// Target CPC = 0.30 × $50 × 0.05 = $0.75
//
// This ensures each click costs the right amount to hit your profit target
// given your actual conversion performance and order values.

// === Performance Metrics ===
let $recent_cpc = cpc($period_eval);
let $recent_acos = acos($period_eval);
let $recent_aov = aov($period_eval);
let $recent_orders = orders($period_eval);
let $recent_clicks = clicks($period_eval);

// Calculate conversion rate
let $recent_cvr = case(
   $recent_clicks > 0 => $recent_orders / $recent_clicks,
   else 0
);

// === Calculate Target CPC ===
let $calculated_target_cpc = case(
   target acos <= 0 => $recent_cpc,  // No target set - keep current bid
   $recent_cvr > 0 and $recent_aov > 0 => target acos * $recent_aov * $recent_cvr,
   else $recent_cpc  // Insufficient data - keep current bid
);

// === Apply Dynamic Bid Cap ===
let $avg_cpc_for_cap = cpc($bid_limit_cpc_period);
let $dynamic_max_bid = case(
   $avg_cpc_for_cap > 0 => $avg_cpc_for_cap * $bid_limit_cpc_multiplier,
   else 999  // No cap if no CPC data
);

let $target_bid = case(
   $calculated_target_cpc > $dynamic_max_bid => $dynamic_max_bid,
   else $calculated_target_cpc
);

// === Data Sufficiency Check ===
let $sufficient_data = case(
   $recent_orders >= $orders_min and $recent_clicks >= $clicks_min => 1,
   else 0
);

// === Diagnostic Properties ===
// Show calculation inputs for transparency
let $aov_used = $recent_aov;
let $cvr_used = $recent_cvr;
let $target_acos_used = target acos;
let $uncapped_target_cpc = $calculated_target_cpc;

let $reason = case(
   target acos <= 0 => "No target ACOS set - cannot calculate",
   $recent_orders < $orders_min => "Insufficient orders for reliable calculation",
   $recent_clicks < $clicks_min => "Insufficient clicks for reliable calculation",
   $calculated_target_cpc > $dynamic_max_bid => "Target CPC exceeds dynamic cap",
   $recent_cvr <= 0 or $recent_aov <= 0 => "Missing conversion or AOV data",
   else "Target CPC calculated from performance metrics"
);

let $result = case(
   target acos <= 0 => "No Target ACOS - Cannot Calculate",
   $sufficient_data = 0 => "Insufficient Data - Review Manually",
   $target_bid = bid => "No Change - Already at Target CPC",
   $calculated_target_cpc > $dynamic_max_bid => "Bid Set - Capped at Dynamic Maximum",
   $recent_cvr <= 0 or $recent_aov <= 0 => "Cannot Calculate - Missing Data",
   else "Target CPC Calculated Successfully"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and target acos > 0
and $target_bid != bid
and $sufficient_data = 1

/*
=== Core: Adaptive Budget Management ===
Purpose: Prevents budget waste while ensuring adequate spend for data collection and performance scaling.
Recommended: Change Daily Budget | Set ($) using $new_budget | Daily or Multiple Times Daily
*/

// === Core Settings ===
let $high_utilization = 90%;                    // CORE: Daily spend % that indicates budget constraint
let $low_utilization = 50%;                     // CORE: Daily budget utilization % that triggers rightsizing
let $enable_cpc_minimums = 1;                   // ADVANCED: Enable CPC-based budget minimums (1=yes, 0=no)

// === Budget Increases (High Utilization) ===
let $t_acos_threshold_increase = 130%;          // STRATEGY: Increase budget when ACOS ≤ (Target ACOS × 130%) [e.g., 30% target = 39% threshold]
let $budget_increase_pct = 20%;                 // STRATEGY: Percentage increase when scaling up
let $orders_min = 4;                            // STRATEGY: Minimum orders needed for reliable ACOS evaluation

let $acos_eval_short = 7d;                      // TIME: Recent performance period
let $acos_eval_medium = 14d;                    // TIME: Medium-term performance period
let $acos_eval_long = 30d;                      // TIME: Long-term performance period

// === Budget Rightsizing (Low Utilization) ===
let $spend_buffer = 130%;                       // STRATEGY: Buffer above avg daily spend when rightsizing (budget set to 130% avg daily spend)
let $budget_min = 5.00;                         // STRATEGY: Absolute minimum budget floor for rightsizing

let $cooldown_eval_period = 14d;                // TIME: Period for sustained utilization evaluation
let $cooldown_period = 14d;                     // TIME: Wait period between rightsizing actions

// === CPC-Based Budget Minimums ===
let $min_daily_clicks = 5;                      // ADVANCED: Minimum clicks per day budget should support
let $cpc_eval_period = 60d;                     // ADVANCED: Period for calculating average CPC for minimum budget

// === Segment Filters ===
let $include_campaigns = [""];                  // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto"]
let $exclude_campaigns = ["NEVER_MATCH"];       // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test", "Archive"]

// ============================================================================
// === Blueprint Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// Increase Path: Individual daily budget cap analysis
let $today_spend = spend(0d..0d);
let $yesterday_spend = spend(1d..1d);
let $day2_spend = spend(2d..2d);
let $day3_spend = spend(3d..3d);

let $today_capped = case($today_spend >= budget * $high_utilization => 1, else 0);
let $yesterday_capped = case($yesterday_spend >= budget * $high_utilization => 1, else 0);
let $day2_capped = case($day2_spend >= budget * $high_utilization => 1, else 0);
let $day3_capped = case($day3_spend >= budget * $high_utilization => 1, else 0);

let $any_day_budget_capped = case(
   $today_capped = 1 or $yesterday_capped = 1 or $day2_capped = 1 or $day3_capped = 1 => 1,
   else 0
);

// Increase Path: CPC-based data sufficiency check
let $avg_cpc = cpc($cpc_eval_period);
let $min_budget_for_data = case(
   $enable_cpc_minimums = 1 and $avg_cpc > 0 => $avg_cpc * $min_daily_clicks,
   else 0  // Data minimums disabled or no CPC data
);

let $budget_too_small = case(
   $enable_cpc_minimums = 1 and $avg_cpc > 0 and budget < $min_budget_for_data => 1,
   else 0
);

// Increase Path: Performance evaluation for increases (prioritize recent data)
let $orders_short = orders($acos_eval_short);
let $orders_medium = orders($acos_eval_medium);
let $orders_long = orders($acos_eval_long);

let $performance_acos = case(
   $orders_short >= $orders_min => acos($acos_eval_short),
   $orders_medium >= $orders_min => acos($acos_eval_medium),
   $orders_long >= $orders_min => acos($acos_eval_long),
   else 99999  // No reliable ACOS data
);

let $acos_good_for_increase = case(
   $performance_acos = 99999 => 1,  // No ACOS data = allow increase
   target acos <= 0 => 0,  // Invalid target
   $performance_acos <= (target acos * $t_acos_threshold_increase) => 1,
   else 0
);

// Rightsizing Path: Sustained utilization analysis
let $total_spend = spend($cooldown_eval_period);
let $days_in_eval = 14;  // Days in 14d period
let $avg_daily_spend = $total_spend / $days_in_eval;
let $avg_utilization_rate = case(
   budget > 0 => $avg_daily_spend / budget,
   else 0
);

// Calculate effective minimum for decreases early
let $effective_min_for_decreases = case(
   $min_budget_for_data > $budget_min => $min_budget_for_data,  // Use CPC minimum if higher
   else $budget_min  // Otherwise use absolute minimum
);

let $rightsizing_cooldown_passed = case(
   is_null(last budget change) => 1,
   last budget change < now() - interval($cooldown_period) => 1,
   else 0
);

// Decision logic by path
let $should_increase = case(
   $budget_too_small = 1 => 1,  // Data-starved campaign
   $any_day_budget_capped = 1 and $acos_good_for_increase = 1 => 1,  // Budget-capped + good performance
   else 0
);

let $should_rightsize = case(
   $rightsizing_cooldown_passed = 0 => 0,  // Cooldown period active
   budget <= $effective_min_for_decreases => 0,  // Already at or below minimum - don't rightsize
   $avg_utilization_rate < $low_utilization => 1,  // Sustained low utilization (including 0% from no spend)
   else 0
);

// Calculate new budget
let $increase_budget = budget * (1 + $budget_increase_pct);

// For rightsizing, calculate based on actual usage plus buffer
let $rightsized_budget = case(
   $avg_daily_spend > 0 => $avg_daily_spend * $spend_buffer,
   else $budget_min  // No spend = use minimum budget
);

let $calculated_budget = case(
   $should_increase = 1 => $increase_budget,
   $should_rightsize = 1 => $rightsized_budget,
   else budget
);

// Apply minimums - different rules for increases vs decreases
let $final_minimum = case(
   $should_rightsize = 1 => case(
       $effective_min_for_decreases > 1.00 => $effective_min_for_decreases,  // Use effective minimum if higher than platform
       else 1.00  // Otherwise platform minimum
   ),
   $should_increase = 1 and $budget_too_small = 1 => case(
       $min_budget_for_data > 1.00 => $min_budget_for_data,  // Use CPC minimum for data generation increases
       else 1.00  // Platform minimum
   ),
   else 1.00  // Platform minimum for budget-capping increases
);

let $new_budget = case(
   $calculated_budget < $final_minimum => $final_minimum,
   else $calculated_budget
);

// Diagnostic properties
let $reason = case(
   target acos <= 0 => "No target ACOS set",
   $should_increase = 1 and $budget_too_small = 1 => case(
       $avg_utilization_rate <= 0.10 => "[0-10%] Below CPC minimum threshold",
       $avg_utilization_rate <= 0.30 => "[10-30%] Below CPC minimum threshold",
       $avg_utilization_rate <= 0.50 => "[30-50%] Below CPC minimum threshold",
       $avg_utilization_rate <= 0.70 => "[50-70%] Below CPC minimum threshold",
       $avg_utilization_rate <= 0.90 => "[70-90%] Below CPC minimum threshold",
       else "[90%+] Below CPC minimum threshold"
   ),
   $should_increase = 1 => case(
       $avg_utilization_rate <= 0.70 => "[50-70%] Above high utilization threshold, ACOS acceptable",
       $avg_utilization_rate <= 0.90 => "[70-90%] Above high utilization threshold, ACOS acceptable",
       else "[90%+] Above high utilization threshold, ACOS acceptable"
   ),
   $rightsizing_cooldown_passed = 0 => case(
       $avg_utilization_rate = 0 => "[0%] Below low utilization threshold, cooldown active",
       $avg_utilization_rate <= 0.10 => "[0-10%] Below low utilization threshold, cooldown active",
       $avg_utilization_rate <= 0.30 => "[10-30%] Below low utilization threshold, cooldown active",
       $avg_utilization_rate <= 0.50 => "[30-50%] Below low utilization threshold, cooldown active",
       else "[50%+] Below low utilization threshold, cooldown active"
   ),
   $should_rightsize = 1 => case(
       $avg_utilization_rate = 0 => "[0%] Below low utilization threshold",
       $avg_utilization_rate <= 0.10 => "[0-10%] Below low utilization threshold",
       $avg_utilization_rate <= 0.30 => "[10-30%] Below low utilization threshold",
       $avg_utilization_rate <= 0.50 => "[30-50%] Below low utilization threshold",
       else "[50-70%] Below low utilization threshold"
   ),
   $any_day_budget_capped = 1 and $acos_good_for_increase = 0 => case(
       $avg_utilization_rate <= 0.70 => "[50-70%] Above high utilization threshold, ACOS too high",
       $avg_utilization_rate <= 0.90 => "[70-90%] Above high utilization threshold, ACOS too high",
       else "[90%+] Above high utilization threshold, ACOS too high"
   ),
   budget <= $effective_min_for_decreases => case(
       $avg_utilization_rate = 0 => "[0%] Budget below rightsizing minimum",
       $avg_utilization_rate <= 0.30 => "[0-30%] Budget below rightsizing minimum",
       else "[30-50%] Budget below rightsizing minimum"
   ),
   else case(
       $avg_utilization_rate = 0 => "[0%] Within acceptable utilization",
       $avg_utilization_rate <= 0.10 => "[0-10%] Within acceptable utilization",
       $avg_utilization_rate <= 0.30 => "[10-30%] Within acceptable utilization",
       $avg_utilization_rate <= 0.50 => "[30-50%] Within acceptable utilization",
       $avg_utilization_rate <= 0.70 => "[50-70%] Within acceptable utilization",
       $avg_utilization_rate <= 0.90 => "[70-90%] Within acceptable utilization",
       else "[90%+] Within acceptable utilization"
   )
);

let $result = case(
   $should_increase = 1 and $budget_too_small = 1 => "Budget Increase: CPC Minimum",
   $should_increase = 1 => "Budget Increase: High Utilization",
   $should_rightsize = 1 => "Budget Decrease: Rightsizing",
   else "No Action"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and ($should_increase = 1 or $should_rightsize = 1)
and $new_budget != budget

/*
=== Core: Dynamic Bid Management ===
Purpose: Intelligent bid optimization that adjusts more aggressively when further from target ACOS, with adaptive timing controls.
Recommended: Change Bid: Set ($) using $target_bid | Daily
*/

// === Core Settings ===
let $orders_min = 2;                                    // CORE: Minimum orders required for reliable ACOS evaluation
let $bid_min_change = 3%;                               // CORE: Minimum bid adjustment when change is warranted
let $bid_max_change = 10%;                              // CORE: Maximum bid adjustment when ACOS is at or beyond target ACOS thresholds

// === Target ACOS Thresholds ===
// Between buffer and thresholds: bid adjustments scale linearly from min to max change percent
let $t_acos_buffer_min_change = 10%;                    // STRATEGY: No-change buffer around target ACOS - min changes start outside this zone (Target ACOS ± 10%) [e.g., 30% target = 27-33% no-change zone]
let $t_acos_threshold_max_increase = 50%;               // STRATEGY: Max increase when ACOS ≤ (Target ACOS × 50%) [e.g., 30% target = 15% max increase threshold]
let $t_acos_threshold_max_decrease = 200%;              // STRATEGY: Max decrease when ACOS ≥ (Target ACOS × 200%) [e.g., 30% target = 60% max decrease threshold]

// === Time Periods ===
let $period_short = 0d..7d;                             // TIME: Primary evaluation period (7 days including today)
let $cooldown_short = 2d;                               // TIME: Wait period after bid change for short data periods

let $period_medium = 0d..14d;                           // TIME: Secondary evaluation period (14 days including today)
let $cooldown_medium = 3d;                              // TIME: Wait period after bid change for medium data periods

let $period_long = 0d..30d;                             // TIME: Tertiary evaluation period (30 days including today)
let $cooldown_long = 5d;                                // TIME: Wait period after bid change for long data periods

let $period_extended = 0d..60d;                         // TIME: Final fallback evaluation period (60 days including today)
let $cooldown_extended = 7d;                            // TIME: Wait period after bid change for extended data periods

// === Advanced Settings ===
let $bid_limit_cpc_multiplier = 2.0;                   // SAFEGUARD: Max bid = Avg CPC × 2.0 [e.g., $0.50 CPC = $1.00 max]
let $bid_limit_cpc_period = 90d;                       // SAFEGUARD: Period for calculating CPC-based bid limits

// === Segment Filters ===
let $include_campaigns = [""];                          // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto", "Research"]
let $exclude_campaigns = ["NEVER_MATCH"];               // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test", "Archive"]

// ============================================================================
// === Blueprint Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// Multi-period data selection with extended coverage
let $orders_short = orders($period_short);
let $orders_medium = orders($period_medium);  
let $orders_long = orders($period_long);
let $orders_extended = orders($period_extended);

let $evaluation_acos = case(
   $orders_short >= $orders_min => acos($period_short),
   $orders_medium >= $orders_min => acos($period_medium),
   $orders_long >= $orders_min => acos($period_long),
   $orders_extended >= $orders_min => acos($period_extended),
   else 99999  // No reliable data
);

// Track which period was used for diagnostics
let $data_quality = case(
   $orders_short >= $orders_min => "High Volume: Short Lookback",
   $orders_medium >= $orders_min => "Med Volume: Medium Lookback",
   $orders_long >= $orders_min => "Low Volume: Long Lookback",
   $orders_extended >= $orders_min => "Very Low Volume: Extended Lookback",
   else "insufficient"
);

// Adaptive cooldown periods based on data source
let $cooldown_cutoff = case(
   $orders_short >= $orders_min => now() - interval($cooldown_short),
   $orders_medium >= $orders_min => now() - interval($cooldown_medium),
   $orders_long >= $orders_min => now() - interval($cooldown_long),
   else now() - interval($cooldown_extended)
);

// Calculate performance ratio with Target ACOS validation
let $acos_ratio = case(
   $evaluation_acos = 99999 => -1,                     // No reliable data
   target acos <= 0 => -1,                             // Invalid target ACOS
   else $evaluation_acos / target acos                 // Performance ratio
);

// Check if within no-change buffer zone
let $within_buffer = case(
   $acos_ratio < 0 => 1,                               // No change if no data or invalid target
   $acos_ratio >= (1 - $t_acos_buffer_min_change) and $acos_ratio <= (1 + $t_acos_buffer_min_change) => 1,
   else 0
);

// Proportional scaling for bid adjustments
let $performance_gap = case(
   $acos_ratio < 0 => 0,                               // No gap if no data
   // Max increase region: ACOS at 50% of target or better
   $acos_ratio <= $t_acos_threshold_max_increase => 1,
   // Scaled increase region: ACOS between 50% and buffer zone (90% of target)
   $acos_ratio < (1 - $t_acos_buffer_min_change) =>
       ((1 - $t_acos_buffer_min_change) - $acos_ratio) /
       ((1 - $t_acos_buffer_min_change) - $t_acos_threshold_max_increase),
   // Max decrease region: ACOS at 200% of target or worse
   $acos_ratio >= $t_acos_threshold_max_decrease => 1,
   // Scaled decrease region: ACOS between buffer zone (110%) and 200% of target
   $acos_ratio > (1 + $t_acos_buffer_min_change) =>
       ($acos_ratio - (1 + $t_acos_buffer_min_change)) /
       ($t_acos_threshold_max_decrease - (1 + $t_acos_buffer_min_change)),
   else 0                                              // Within buffer zone - no adjustment
);

let $adjustment_percent = case(
   $within_buffer = 1 => 0%,                           // No change within buffer zone
   // Increase adjustments for ACOS below target
   $acos_ratio <= $t_acos_threshold_max_increase =>
       $bid_min_change + ($performance_gap * ($bid_max_change - $bid_min_change)),
   $acos_ratio < (1 - $t_acos_buffer_min_change) =>
       $bid_min_change + ($performance_gap * ($bid_max_change - $bid_min_change)),
   // Decrease adjustments for ACOS above target
   $acos_ratio > (1 + $t_acos_buffer_min_change) =>
       -1 * ($bid_min_change + ($performance_gap * ($bid_max_change - $bid_min_change))),
   else 0%
);

// Calculate target bid with CPC-based limits
let $initial_target_bid = bid * (1 + $adjustment_percent);

let $avg_cpc = cpc($bid_limit_cpc_period);
let $dynamic_max = case(
   $avg_cpc > 0 => $avg_cpc * $bid_limit_cpc_multiplier,
   else 999  // No CPC data = no dynamic limit
);

let $target_bid = case(
   $avg_cpc > 0 and $initial_target_bid > $dynamic_max => $dynamic_max,
   else $initial_target_bid
);

// Cooldown validation
let $cooldown_ready = case(
   is_null(last bid change) => 1,
   last bid change < $cooldown_cutoff => 1,
   else 0
);

// Diagnostic properties
let $reason = case(
   target acos <= 0 => "No target ACOS set",
   $evaluation_acos = 99999 => "Insufficient order data across all lookback periods",
   $within_buffer = 1 => case(
       $data_quality = "High Volume: Short Lookback" => "[High Volume: Short Lookback] Within target buffer zone",
       $data_quality = "Med Volume: Medium Lookback" => "[Med Volume: Medium Lookback] Within target buffer zone",
       $data_quality = "Low Volume: Long Lookback" => "[Low Volume: Long Lookback] Within target buffer zone",
       $data_quality = "Very Low Volume: Extended Lookback" => "[Very Low Volume: Extended Lookback] Within target buffer zone",
       else "Performance within target buffer zone"
   ),
   $cooldown_ready = 0 => case(
       $data_quality = "High Volume: Short Lookback" => "[High Volume: Short Lookback] Recently changed - cooldown active",
       $data_quality = "Med Volume: Medium Lookback" => "[Med Volume: Medium Lookback] Recently changed - cooldown active",
       $data_quality = "Low Volume: Long Lookback" => "[Low Volume: Long Lookback] Recently changed - cooldown active",
       $data_quality = "Very Low Volume: Extended Lookback" => "[Very Low Volume: Extended Lookback] Recently changed - cooldown active",
       else "Recently changed - cooldown active"
   ),
   $target_bid = bid => "No bid change calculated",
   $avg_cpc > 0 and $initial_target_bid > $dynamic_max => "Limited by CPC-based maximum",
   $adjustment_percent > 0 => case(
       $data_quality = "High Volume: Short Lookback" => "[High Volume: Short Lookback] ACOS below target threshold",
       $data_quality = "Med Volume: Medium Lookback" => "[Med Volume: Medium Lookback] ACOS below target threshold",
       $data_quality = "Low Volume: Long Lookback" => "[Low Volume: Long Lookback] ACOS below target threshold",
       $data_quality = "Very Low Volume: Extended Lookback" => "[Very Low Volume: Extended Lookback] ACOS below target threshold",
       else "ACOS below target threshold"
   ),
   $adjustment_percent < 0 => case(
       $data_quality = "High Volume: Short Lookback" => "[High Volume: Short Lookback] ACOS above target threshold",
       $data_quality = "Med Volume: Medium Lookback" => "[Med Volume: Medium Lookback] ACOS above target threshold",
       $data_quality = "Low Volume: Long Lookback" => "[Low Volume: Long Lookback] ACOS above target threshold",
       $data_quality = "Very Low Volume: Extended Lookback" => "[Very Low Volume: Extended Lookback] ACOS above target threshold",
       else "ACOS above target threshold"
   ),
   else "Performance at target"
);

let $result = case(
   $within_buffer = 0 and $cooldown_ready = 1 and $target_bid != bid => case(
       $adjustment_percent >= $bid_max_change => "Bid Increase: Max",
       $adjustment_percent >= $bid_max_change * 0.5 => "Bid Increase: Upper Range",
       $adjustment_percent > 0 => "Bid Increase: Lower Range",
       $adjustment_percent <= -1 * $bid_max_change => "Bid Decrease: Max",
       $adjustment_percent <= -1 * $bid_max_change * 0.5 => "Bid Decrease: Upper Range",
       $adjustment_percent < 0 => "Bid Decrease: Lower Range",
       else "No action needed"
   ),
   else "No action needed"
);

// === Final Filter ===
state = "effectively enabled"
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $within_buffer = 0
and $target_bid != bid
and $cooldown_ready = 1

/*
=== Basics: Search Term Waste Elimination ===
Purpose: Automatically negate zero-converting search terms to stop budget waste.
Recommended: Create Negative Exact Match | Daily
*/

// === Core Settings ===
let $base_clicks = 20;                       // CORE: Clicks required to negate zero-order terms (0 orders + 20 clicks = negated)

// === Campaign Filters ===
let $include_campaigns = [""];               // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto"]
let $exclude_campaigns = ["NEVER_MATCH"];    // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test"]

// ============================================================================
// === Blueprint Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// Pre-calculate performance metrics
let $lifetime_orders = orders(lifetime);
let $lifetime_clicks = clicks(lifetime);

// Simple waste removal: zero orders with sufficient clicks
let $waste_candidate = case(
   $lifetime_orders = 0 and $lifetime_clicks >= $base_clicks => 1,
   else 0
);

// Diagnostic properties
let $action = case(
   $waste_candidate = 1 => "Negate",
   else "Keep"
);

// === Final Filter ===
negated = false
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $waste_candidate = 1

/*
=== KDP Core: Search Term Waste Elimination ===
Purpose: Intelligently negate wasteful search terms using performance data and relevance analysis.
Recommended: Create Negative Exact Match | Daily
*/

// === Core Settings ===
let $clicks_threshold = 20;                  // CORE: Base click threshold for zero-profit terms
let $spend_threshold = 5.00;                 // CORE: Minimum lifetime spend required for evaluation

// === Strategy Settings ===
let $blend_profit_min_for_acos_eval = 20.00; // STRATEGY: Blended profit required for ACOS-based evaluation ($20.00 threshold)
let $clicks_min_for_acos_eval = 100;         // STRATEGY: Clicks required for ACOS-based evaluation
let $t_blend_acos_threshold_negate = 500%;   // STRATEGY: Negate if blended ACOS ≥ (Target Blended ACOS × 500%) when min clicks & profit are met [e.g., 100% target = 500% threshold]

// === Advanced Settings ===
let $clicks_scaling_per_dollar = 4.0;        // ADVANCED: Additional clicks allowed per $1.00 blended profit [e.g., $5 profit = 20 + (5 × 4) = 40 clicks]
let $threshold_multiplier = 1.0;             // ADVANCED: Scales testing thresholds for clicks and spend [e.g., 1.5 = 50% higher requirements]
let $spend_scaling_enabled = 0;              // ADVANCED: Scale spend requirement with profit using threshold multiplier (1=yes, 0=no) [e.g., 0 profit = $5, $5 profit = $10]
let $irrelevant_terms = ["NEVER_MATCH"];     // ADVANCED: Aggressively negate search terms containing these keywords (unrelated terms)
let $irrelevant_clicks_threshold = 10;       // ADVANCED: Clicks required to negate irrelevant terms (ignores all scaling and spend requirements)

// === Safeguards ===
let $safeguard_blend_profit = 50.00;         // SAFEGUARD: Never negate terms with this much blended profit or more
let $safeguard_min_blended_roas_ratio = 50%; // SAFEGUARD: Protect terms with blended ROAS ≥ (Target Blended ROAS × 50%) [e.g., 1.0 target ROAS = 0.5 protection]
let $protected_terms = ["NEVER_MATCH"];      // SAFEGUARD: Never negate search terms containing these keywords (your brand, product names, strategic terms)

// === Segment Filters ===
let $include_campaigns = [""];               // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto", "Research"]
let $exclude_campaigns = ["NEVER_MATCH"];    // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test", "Archive"]

// ============================================================================
// === Blueprint Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// Pre-calculate performance metrics
let $lifetime_blended_profit = blended profit(lifetime);
let $lifetime_clicks = clicks(lifetime);
let $lifetime_spend = spend(lifetime);
let $lifetime_blended_acos = blended acos(lifetime);
let $lifetime_blended_roas = blended roas(lifetime);

// Calculate scaled click threshold based on blended profit
let $base_clicks_threshold = $clicks_threshold * $threshold_multiplier;
let $allowed_clicks = $base_clicks_threshold + ($lifetime_blended_profit * $clicks_scaling_per_dollar * $threshold_multiplier);
let $spend_required = case(
   $spend_scaling_enabled = 1 => $spend_threshold + (($lifetime_blended_profit / 5.0) * $threshold_multiplier * $spend_threshold),
   else $spend_threshold
);

// Data sufficiency check (both clicks and spend)
let $sufficient_data = case(
   $lifetime_clicks >= $allowed_clicks and $lifetime_spend >= $spend_required => 1,
   else 0
);

// Blended ROAS-based protection calculation
let $target_blended_roas = case(
   target acos > 0 => 1 / target acos,
   else 0
);

let $blended_roas_protection_threshold = case(
   $target_blended_roas > 0 => $target_blended_roas * $safeguard_min_blended_roas_ratio,
   else 0
);

let $blended_roas_protected = case(
   $lifetime_blended_profit > 0 and $target_blended_roas > 0 and $lifetime_blended_roas >= $blended_roas_protection_threshold => 1,
   else 0
);

// Search term relevance analysis
let $protected_term = case(
   search term contains any $protected_terms => 1,
   else 0
);

let $irrelevant_term = case(
   search term contains any $irrelevant_terms => 1,
   else 0
);

// Protection safeguards
let $high_profit_protection = case(
   $lifetime_blended_profit >= $safeguard_blend_profit => 1,
   else 0
);

let $protected_overall = case(
   $high_profit_protection = 1 => 1,
   $protected_term = 1 => 1,
   $blended_roas_protected = 1 => 1,
   else 0
);

// Four negation paths: irrelevant, zero-profit waste, efficiency, and ACOS performance
let $irrelevant_candidate = case(
   $irrelevant_term = 1 and $lifetime_clicks >= $irrelevant_clicks_threshold => 1,
   else 0
);

let $zero_profit_waste_candidate = case(
   $lifetime_blended_profit = 0 and $sufficient_data = 1 => 1,
   else 0
);

let $efficiency_candidate = case(
   $lifetime_blended_profit > 0 and ($lifetime_blended_profit < $blend_profit_min_for_acos_eval or $lifetime_clicks < $clicks_min_for_acos_eval) => case(
       $sufficient_data = 1 => 1,
       else 0
   ),
   else 0
);

let $performance_candidate = case(
   $lifetime_blended_profit >= $blend_profit_min_for_acos_eval and $lifetime_clicks >= $clicks_min_for_acos_eval => case(
       target acos > 0 and $lifetime_blended_acos > target acos * $t_blend_acos_threshold_negate => 1,
       else 0
   ),
   else 0
);

let $negation_candidate = case(
   $irrelevant_candidate = 1 => 1,
   $zero_profit_waste_candidate = 1 => 1,
   $efficiency_candidate = 1 => 1,
   $performance_candidate = 1 => 1,
   else 0
);

// Diagnostic properties

let $reason = case(
   $high_profit_protection = 1 => "Protected - too much blended profit to negate",
   $protected_term = 1 => "Protected - contains protected keyword",
   $blended_roas_protected = 1 => "Protected - blended ROAS above safeguard threshold",
   $irrelevant_candidate = 1 => "Contains irrelevant terms, met click threshold",
   $irrelevant_term = 1 and $lifetime_clicks < $irrelevant_clicks_threshold => "Contains irrelevant terms, needs more clicks",
   $zero_profit_waste_candidate = 1 => "Zero blended profit, met click threshold",
   $efficiency_candidate = 1 and $lifetime_clicks >= $allowed_clicks * 1.5 => "Greatly exceeds profit-scaled click limit",
   $efficiency_candidate = 1 => "Exceeds profit-scaled click limit",
   $performance_candidate = 1 => "Blended ACOS far above target threshold",
   $sufficient_data = 0 and $lifetime_spend < $spend_required and $lifetime_clicks < $allowed_clicks => "Insufficient spend and clicks",
   $sufficient_data = 0 and $lifetime_spend < $spend_required => "Insufficient spend",
   $sufficient_data = 0 => "Insufficient clicks for profit level",
   $lifetime_blended_profit > 0 and ($lifetime_blended_profit < $blend_profit_min_for_acos_eval or $lifetime_clicks < $clicks_min_for_acos_eval) => "Converting within profit-scaled click limit",
   $lifetime_blended_profit >= $blend_profit_min_for_acos_eval and $lifetime_clicks >= $clicks_min_for_acos_eval => "Blended ACOS below negation threshold",
   else "Zero blended profit, needs more clicks"
);

let $result = case(
   $zero_profit_waste_candidate = 1 => "Negate - Zero Profit, High Clicks",
   $irrelevant_candidate = 1 => "Negate - Irrelevant Term",
   $efficiency_candidate = 1 => case(
       $lifetime_blended_profit <= 5.00 => "Negate - Low Profit, High Clicks",
       $lifetime_blended_profit >= 15.00 => "Negate - Converting but Inefficient",\
       else "Negate - Over Click Limit"
   ),
   $performance_candidate = 1 => "Negate - High Blended ACOS",
   $high_profit_protection = 1 or $protected_term = 1 or $blended_roas_protected = 1 => "Protected - No Action",
   else "No Action"
);

// === Final Filter ===
negated = false
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $negation_candidate = 1
and $protected_overall = 0

/*
=== Core: Search Term Waste Elimination ===
Purpose: Intelligently negate wasteful search terms using efficiency targets and performance analysis.
Recommended: Create Negative Exact Match | Daily
*/

// === Core Settings ===
let $clicks_threshold = 20;                  // CORE: Base click threshold for zero-order terms
let $spend_threshold = 5.00;                 // CORE: Base spend requirement for zero-order terms

// === Strategy Settings ===
let $orders_min_for_acos_eval = 5;           // STRATEGY: Orders required for ACOS-based evaluation
let $clicks_min_for_acos_eval = 100;         // STRATEGY: Clicks required for ACOS-based evaluation
let $t_acos_threshold_negate = 400%;         // STRATEGY: Negate if ACOS ≥ (Target ACOS × 400%) when min clicks & orders are met [e.g., 30% target = 120% threshold]

// === Advanced Settings ===
let $clicks_scaling_per_order = 20;          // ADVANCED: Additional clicks allowed per order [e.g., 2 orders = 20 + (2 × 20) = 60 clicks]
let $spend_scaling_per_order = 5.00;         // ADVANCED: Additional spend required per order [e.g., 2 orders = $5 + (2 × $5) = $15 spend]
let $irrelevant_terms = ["NEVER_MATCH"];     // ADVANCED: Aggressively negate search terms containing these keywords (unrelated terms)
let $irrelevant_clicks_threshold = 10;       // ADVANCED: Clicks required to negate irrelevant terms (ignores all scaling and spend requirements)

// === Safeguards ===
let $safeguard_orders = 10;                  // SAFEGUARD: Never negate terms with this many orders or more
let $safeguard_min_roas_ratio = 50%;         // SAFEGUARD: Protect terms with ROAS ≥ (Target ROAS × 50%) [e.g., 3.33 target ROAS = 1.67 protection]
let $protected_terms = ["NEVER_MATCH"];      // SAFEGUARD: Never negate search terms containing these keywords (your brand, product names, strategic terms)

// === Segment Filters ===
let $include_campaigns = [""];               // FILTER: Apply to all campaigns, or specify terms like ["SP-", "Auto", "Research"]
let $exclude_campaigns = ["NEVER_MATCH"];    // FILTER: Exclude campaigns containing these terms, e.g., ["Brand", "Test", "Archive"]

// ============================================================================
// === Blueprint Logic ===
// ============================================================================
// Advanced logic below - modify carefully

// Pre-calculate performance metrics
let $lifetime_orders = orders(lifetime);
let $lifetime_clicks = clicks(lifetime);
let $lifetime_spend = spend(lifetime);
let $lifetime_acos = acos(lifetime);
let $lifetime_roas = roas(lifetime);

// Calculate scaled thresholds based on order history
let $allowed_clicks = $clicks_threshold + ($lifetime_orders * $clicks_scaling_per_order);
let $spend_required = $spend_threshold + ($lifetime_orders * $spend_scaling_per_order);

// Data sufficiency check (both clicks and spend)
let $sufficient_data = case(
   $lifetime_clicks >= $allowed_clicks and $lifetime_spend >= $spend_required => 1,
   else 0
);

// Calculate efficiency for converting terms\
let $actual_clicks_per_order = case(
   $lifetime_orders > 0 => $lifetime_clicks / $lifetime_orders,
   else 999  // Treat zero-order terms as infinitely inefficient
);

// ROAS-based protection calculation
let $target_roas = case(
   target acos > 0 => 1 / target acos,
   else 0
);

let $roas_protection_threshold = case(
   $target_roas > 0 => $target_roas * $safeguard_min_roas_ratio,
   else 0
);

let $roas_protected = case(
   $lifetime_orders > 0 and $target_roas > 0 and $lifetime_roas >= $roas_protection_threshold => 1,
   else 0
);

// Search term relevance analysis
let $protected_term = case(
   search term contains any $protected_terms => 1,
   else 0
);

let $irrelevant_term = case(
   search term contains any $irrelevant_terms => 1,
   else 0
);

// Protection safeguards
let $high_order_protection = case(
   $lifetime_orders >= $safeguard_orders => 1,
   else 0
);

let $protected_overall = case(
   $high_order_protection = 1 => 1,
   $protected_term = 1 => 1,
   $roas_protected = 1 => 1,
   else 0
);

// Four negation paths: irrelevant, zero-order waste, efficiency, and ACOS performance
let $irrelevant_candidate = case(
   $irrelevant_term = 1 and $lifetime_clicks >= $irrelevant_clicks_threshold => 1,
   else 0
);

let $zero_order_waste_candidate = case(
   $lifetime_orders = 0 and $sufficient_data = 1 => 1,
   else 0
);

let $efficiency_candidate = case(
   $lifetime_orders > 0 and ($lifetime_orders < $orders_min_for_acos_eval or $lifetime_clicks < $clicks_min_for_acos_eval) => case(
       $actual_clicks_per_order > $clicks_scaling_per_order and $sufficient_data = 1 => 1,
       else 0
   ),
   else 0
);

let $performance_candidate = case(
   $lifetime_orders >= $orders_min_for_acos_eval and $lifetime_clicks >= $clicks_min_for_acos_eval => case(
       target acos > 0 and $lifetime_acos > target acos * $t_acos_threshold_negate => 1,
       else 0
   ),
   else 0
);

let $negation_candidate = case(
   $irrelevant_candidate = 1 => 1,
   $zero_order_waste_candidate = 1 => 1,
   $efficiency_candidate = 1 => 1,
   $performance_candidate = 1 => 1,
   else 0
);

// Diagnostic properties
let $reason = case(
   $high_order_protection = 1 => "Protected - too many orders to negate",
   $protected_term = 1 => "Protected - contains protected keyword",
   $roas_protected = 1 => "Protected - ROAS above safeguard threshold",
   $irrelevant_candidate = 1 => "Contains irrelevant terms, met click threshold",
   $irrelevant_term = 1 and $lifetime_clicks < $irrelevant_clicks_threshold => "Contains irrelevant terms, needs more clicks",
   $zero_order_waste_candidate = 1 => "Zero orders, met click threshold",
   $efficiency_candidate = 1 and $actual_clicks_per_order >= $clicks_scaling_per_order * 2 => "Greatly exceeds click-per-order limit",
   $efficiency_candidate = 1 => "Exceeds click-per-order limit",
   $performance_candidate = 1 => "ACOS far above target threshold",
   $sufficient_data = 0 and $lifetime_spend < $spend_required and $lifetime_clicks < $allowed_clicks => "Insufficient spend and clicks",
   $sufficient_data = 0 and $lifetime_spend < $spend_required => "Insufficient spend",
   $sufficient_data = 0 => "Insufficient clicks for order level",
   $lifetime_orders > 0 and ($lifetime_orders < $orders_min_for_acos_eval or $lifetime_clicks < $clicks_min_for_acos_eval) => "Converting within click-per-order limit",
   $lifetime_orders >= $orders_min_for_acos_eval and $lifetime_clicks >= $clicks_min_for_acos_eval => "ACOS below negation threshold",
   else "Zero orders, needs more clicks"
);

let $result = case(
   $zero_order_waste_candidate = 1 => "Negate - Zero Orders, High Clicks",
   $irrelevant_candidate = 1 => "Negate - Irrelevant Term",
   $efficiency_candidate = 1 => case(
       $lifetime_orders = 1 => "Negate - Single Order, High Clicks",
       $lifetime_orders >= 2 => "Negate - Converting but Inefficient",
       else "Negate - Over Click Limit"
   ),
   $performance_candidate = 1 => "Negate - High ACOS (Converting Well)",
   $high_order_protection = 1 or $protected_term = 1 or $roas_protected = 1 => "Protected - No Action",
   else "No Action"
);

// === Final Filter ===
negated = false
and (campaign name contains any $include_campaigns)
and (campaign name does not contain any $exclude_campaigns)
and $negation_candidate = 1
and $protected_overall = 0