diff --git a/src/main/scala/com/amazon/deequ/suggestions/rules/RetainCompletenessRule.scala b/src/main/scala/com/amazon/deequ/suggestions/rules/RetainCompletenessRule.scala
index df2f4930..9f995a11 100644
--- a/src/main/scala/com/amazon/deequ/suggestions/rules/RetainCompletenessRule.scala
+++ b/src/main/scala/com/amazon/deequ/suggestions/rules/RetainCompletenessRule.scala
@@ -20,6 +20,7 @@ import com.amazon.deequ.constraints.Constraint.completenessConstraint
 import com.amazon.deequ.profiles.ColumnProfile
 import com.amazon.deequ.suggestions.CommonConstraintSuggestion
 import com.amazon.deequ.suggestions.ConstraintSuggestion
+import com.amazon.deequ.suggestions.rules.RetainCompletenessRule._
 
 import scala.math.BigDecimal.RoundingMode
 
@@ -30,7 +31,10 @@ import scala.math.BigDecimal.RoundingMode
   * @param minCompleteness : minimum completeness threshold to determine if rule should be applied
   * @param maxCompleteness : maximum completeness threshold to determine if rule should be applied
   */
-case class RetainCompletenessRule(minCompleteness: Double = 0.2, maxCompleteness: Double = 1.0) extends ConstraintRule[ColumnProfile] {
+case class RetainCompletenessRule(
+  minCompleteness: Double = defaultMinCompleteness,
+  maxCompleteness: Double = defaultMaxCompleteness
+) extends ConstraintRule[ColumnProfile] {
   override def shouldBeApplied(profile: ColumnProfile, numRecords: Long): Boolean = {
     profile.completeness > minCompleteness && profile.completeness < maxCompleteness
   }
@@ -67,3 +71,8 @@ case class RetainCompletenessRule(minCompleteness: Double = 0.2, maxCompleteness
     "we model its completeness as a binomial variable, estimate a confidence interval " +
     "and use this to define a lower bound for the completeness"
 }
+
+object RetainCompletenessRule {
+  private val defaultMinCompleteness: Double = 0.2
+  private val defaultMaxCompleteness: Double = 1.0
+}