Finding Duplicate Customer Records in Your Database

Problem: Identifying and Removing Customer Records Duplicates 

Your company has a robust database that has taken years to cultivate. The problem is there might actually be thousands of duplicate records hiding in plain sight. 

Databases that contain duplicate customer records is a common problem. Marketers that have trouble achieving a single customer view see effective linkage as the main barrier to creating a truly customized, personalized, cross-channel marketing strategy. According to a 2021 State of Personalization Report, 60% of shoppers say they are “likely” to become a repeat buyer after a personalized shopping experience, up from 44% in 2017. Without achieving a single customer view, your marketing and sales team will face barriers in creating and developing personalization strategies. 

As IMPACT reports, there are many ways that duplicate data can negatively affect your sales and marketing returns. For example, you could be spending double the money to reach the same customers twice, thus negatively impacting your outreach and appearing as spam. Other issues include a decrease in email marketing deliverability, customer confusion and frustration, and a lack of personalization. 

The best practice marketing techniques require a single customer view, but duplicates can be difficult and time-consuming to find and correct. 

Solution: Duplicate Detection Using Machine Learning

Duplicate detection machine learning makes it easy to identify when multiple records are likely to be for the same customer, making sure your database is in prime operating condition. 

Eliminating duplicate customer records will allow your marketing and sales teams to deliver a clearer, more accurate, and customized message; saving your company time, effort and money. 

Why DataRobot: Eliminate Database Duplicate Data with Ease

Considering doing a database cleanup without AI? Database queries for duplicates will not find spelling mistakes, typos, missing values, changes of address, or people who left out their middle name. The solution to these duplication problems is to use fuzzy matching instead of looking for exact matches. Fuzzy matching is a computer-assisted technique to score the similarity of data. 

Before you get frustrated, consider that DataRobot pioneered automated machine learning, and offers the most comprehensive, easy-to-use solution for optimizing and accelerating the development and deployment of AI applications. Our automated text mining and state-of-the-art algorithms are perfect for analyzing customer records, helping you turn an overwhelming administrative project into a focused task that adds immediate value. 

Let’s get your database cleaned up and move ahead with confidence.

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