• Address standardization and correction; parsing and matching technologies; and programming logic must be carefully integrated to match ("group") accounts, leveraging a combination of factors such as name, address, company name, "hard links" such as phone number, and sold-to/bill-to/ship-to relationships.

• For B-to-C account records, matches must be determined at the individual and household levels. Also, the matches must be unified into a non-circular cross-reference that assigns each account to a single individual, and each individual to a single household. Likewise for B-to-B account records, the same must be done at the individual, site and super-site ("company") levels.

• Incremental periodic matches of new accounts to the existing base must be executed, to add activity to existing individuals, households, sites and super-sites, and create new ones.

• The entire database must be periodically re-matched whenever the number of address changes reaches critical mass, or key USPS^® tables have been updated.

• All programming logic must be maintained such that it can be easily adjusted and enhanced, and data re-consolidated, based on the results of ongoing quality assurance of the matches.

• Logic must be dynamically imposed to make the historical data consistent and usable, and correspond with "real world" behavior. For example, "split-shipment" order records must be aggregated into "true" orders.

• Rapid classification of customers as of any point-in-time must be done, at the individual, household, site and super-site levels, employing atomic-level histories up to that point-in-time only. This multiple-level aggregation of data, performed dynamically and at-will, is essential for:

1) accurate response attribution, analysis, scoring, and selection for promotions, and

2) the appropriate allocation of marketing-spend to each customer.