diff --git a/integrationExamples/gpt/id_lift_measurement.html b/integrationExamples/gpt/id_lift_measurement.html
index ac1aeaac112..220fbf47f8c 100644
--- a/integrationExamples/gpt/id_lift_measurement.html
+++ b/integrationExamples/gpt/id_lift_measurement.html
@@ -5,7 +5,20 @@
     <title>Measure Lift of Multiple ID Modules</title>
     <script>
         const FAILSAFE_TIMEOUT = 2000;
-        const ID_MODULES = ["id1", "id2", "id3"];
+        const ID_MODULES = [
+            {
+                name: "id1",
+                params: { key1: "value1", key2: "value2" }
+            },
+            {
+                name: "id2",
+                params: { key3: "value3", key4: "value4" }
+            },
+            {
+                name: "id3",
+                params: { key5: "value5", key6: "value6" }
+            }
+        ];
         const TREATMENT_RATE = 0.95; // 95% chance to include an ID module
         const targetingArray = [];
 
@@ -37,9 +50,9 @@
         googletag.cmd = googletag.cmd || [];
 
         // Randomly enable each ID module based on dice rolls
-        ID_MODULES.forEach(id => {
+        ID_MODULES.forEach(module => {
             const isEnabled = Math.random() < TREATMENT_RATE;
-            targetingArray.push(`${id}:${isEnabled ? 't1' : 't0'}`);
+            targetingArray.push(`${module.name}:${isEnabled ? 't1' : 't0'}`);
 
             if (isEnabled) {
                 pbjs.que.push(function () {
@@ -47,7 +60,8 @@
                         userSync: {
                             userIds: [
                                 {
-                                    name: id,
+                                    name: module.name,
+                                    params: module.params
                                 }
                             ],
                             syncDelay: 5000,
@@ -117,21 +131,36 @@
 
     <h2>Measure Lift of Multiple ID Modules</h2>
 
+    <h4>Generated IDs:</h4>
+    <pre id="ids-div" style="border:1px solid #333; padding:5px; overflow: auto"></pre>
+
+    <h4>Generated EIDs:</h4>
+    <pre id="eids-div" style="border:1px solid #333; padding:5px; overflow: auto"></pre>
+
     <!-- Instructions Section -->
     <h3>Instructions</h3>
     <ol>
-        <li>Ensure that the `abg` key is set in GAM targeting. Each value will be a combination of `id1:t0 or t1`, `id2:t0 or t1`, and `id3:t0 or t1`.</li>
+        <li>Ensure that the `abg` key is definied in GAM targeting with all possible keys. Each value will be a combination of the following six possible key-value pairs:
+            <ul>
+                <li><code>id1:t0</code></li>
+                <li><code>id1:t1</code></li>
+                <li><code>id2:t0</code></li>
+                <li><code>id2:t1</code></li>
+                <li><code>id3:t0</code></li>
+                <li><code>id3:t1</code></li>
+            </ul>
+        </li>
         <li>In Google Ad Manager (GAM), create a report with the following setup:
             <ul>
                 <li><strong>Dimensions</strong>: Ad Unit, Key-Value Targeting (`abg`).</li>
-                <li><strong>Metrics</strong>: Impressions, Clicks, Revenue.</li>
+                <li><strong>Metrics</strong>: Impressions, Revenue.</li>
                 <li><strong>Filters</strong>: Include the `abg` key in the report.</li>
             </ul>
         </li>
         <li>Analyze the report for each ID module:
             <ul>
                 <li>Filter by combinations of `t1` (treatment) and `t0` (control) for each ID module (e.g., `id1:t1`, `id1:t0`).</li>
-                <li>Compare performance metrics (Impressions, Clicks, Revenue) for the `t1` vs. `t0` values.</li>
+                <li>Compare performance metrics (eg Impressions, Revenue) for the `t1` vs. `t0` values.</li>
                 <li>Calculate lift for each module using the formula:
                     <pre>Lift (%) = ((Treatment Metric - Control Metric) / Control Metric) * 100</pre>
                     Replace "Metric" with the relevant performance metric.