A data scientist is working with a feature set that includes the following schema: customer_id STRING, spend DOUBLE, units INTEGER, happiness_tier STRING. The customer_id column serves as the primary key. Each column in the feature set contains some missing values. The scientist plans to replace these missing values by imputing a common value for each feature. Which columns from the feature set are best suited for imputation using the most common value (mode) of the column?