LOOK-UP, real-time duplicate check
Avoid duplicates in your database by performing a real-time pre-existence check at the point of data entry.
Obtain a high-quality single
customer view (SCV) for all your touchpoints
The LOOK-UP module is a solution enabling you to perform a preexistence search from your front-end applications to avoid entering duplicates in your database. The look-up function incorporates advanced matching algorithms that make relevant suggestions without considering typing, abbreviations, or spelling errors.
In this way, you can immediately see whether a customer or prospect record is already in the appropriate database. Integrated in your front-end applications, LOOK-UP enables you to communicate with your single-customer view.
This feature is populated with customer information from all systems (e-commerce, ERP, SCV, etc.) and avoids reentry of existing customers’ information.
Features
Preexistence search in real time
Find a customer or prospective customer contact in real time despite typos.
Personalization of deduplication rules
established beforehand by relevant users.
Why choose the LOOK-UP module?
Above all, to avoid creating duplicates in your B2B or B2C databases.
The LOOK-UP module gives you recognition and unique identification of your customers and contacts (customers and prospective customers). The single view of the contact available in your database enables you to develop a quality customer relationship. It’s now possible for your organizations to identify your customers at every stage of their journey and offer them a seamless experience across all channels. With LOOK-UP, you support your company’s SCV strategy and avoid the challenges of your contacts’ data being siloed.
The benefits of the LOOK-UP module
Real time
Identify a contact or customer in real time when they are input in your systems.
360° single view
The contact record is unique, centralized, and enhanced by multiple data sources.
Buying journey
Optimize the buying journey by identifying the golden record with unique, reliable and exhaustive data.
Customer knowledge
Improve the quality of all the data on a contact record thanks to autocomplete for postal addresses.
Effective communication
Communication campaigns are consistent and targeted with verified and relevant contact data.
Single Customer View (SCV)
The single customer view (SCV) lists and centralizes all customer data (online, offline, CRM, customer service, etc.) a company has in one information system to have a single, 360° view in an omnichannel environment. An SCV enables you to optimize data usage by relying on its high-quality consolidation.
FAQ
What is real-time deduplication and when is it needed?
Real-time deduplication is the process of checking, at the moment a new record is created, whether a matching record already exists in the database. It is used in CRM systems, e-commerce platforms, and customer service tools to prevent the creation of duplicate contacts, leads, or accounts. Unlike batch deduplication — which finds and merges duplicates after they’ve accumulated — real-time deduplication stops them from being created in the first place. DQE’s Look-Up module performs this check instantly at every data entry point.
How do duplicate customer records form in a CRM?
Duplicates typically arise from multiple entry points feeding the same database without coordination: a customer registers online, then calls a support line and a new record is created, then visits a store and is registered again. Acquisitions, CRM migrations, and manual data imports are also major sources of duplication. Even within a single entry point, variations in how a name or address is spelled can cause the same person to appear as multiple distinct records.
What is fuzzy matching and how does it help find duplicates?
Fuzzy matching is a technique that identifies records as potential duplicates even when they are not exactly identical — accounting for typos, different abbreviations, name inversions, or address formatting variations. For example, “Jon Smith, 12 Oak St” and “John Smyth, 12 Oak Street” would be flagged as likely duplicates by a fuzzy matching algorithm, whereas an exact-match system would treat them as two separate people. The quality of a deduplication solution depends heavily on the sophistication of its fuzzy matching engine.
What is a "Golden Record" in customer data management?
A Golden Record (also called a Single Customer View or master record) is the authoritative, consolidated representation of a customer built by merging data from multiple sources and resolving conflicts between them. It contains the most accurate and up-to-date version of each attribute — the best-known address, the verified email, the correct name spelling. Creating and maintaining a Golden Record is the goal of deduplication and data unification efforts, and is foundational to reliable CRM analytics, personalization, and regulatory compliance.
How does preventing duplicates at the point of entry differ from merging existing duplicates?
Prevention (real-time deduplication) intercepts the creation of a new duplicate by alerting the user or system that a matching record already exists — before the new record is saved. Merging (batch deduplication) finds and consolidates duplicates that have already accumulated. Prevention is lower-cost and avoids data fragmentation entirely, while merging is necessary to clean up historical data. The most robust data quality strategies combine both: real-time Look-Up to block new duplicates, and periodic Duplicate processing to resolve existing ones.