How much are you wasting on duplicate records?

In recent years, as more companies have shifted how they promote their products and brand online; print catalogs seemed doomed to extinction. Why continue to design, print and ship a printed piece when it can easily be hosted online, with sophisticated tracking, and for a fraction of the cost?

As many retailers found, print catalogs aren’t dead, not by a long shot. Consumers want to connect with organizations across multiple channels, including social media, online, brick-and-mortar, and, yes, catalog. Retailers have adopted a cross-channel strategy of promoting their products to accommodate consumers. This allows them to connect with and offer products in a variety of channels to engage with prospects and customers in the way they most prefer.

However, there is still room for improvement. While many customers still enjoy thumbing through a print catalog and taking a break from the computer screen, what bothers them is coming home to find two, three, sometimes four copies of the same catalog stuffed into their mailbox.

The duplicate catalogs are partly a result of the new cross-channel strategy. Most companies are collecting information from a variety of channels, which gather data in a variety of different formats. In addition, as organizations look to better understand consumers, most are collecting as much information as possible with little regard for data accuracy. This results in a database with inaccurate and unstandardized data, and multiple records being continually created.

Having a database of duplicate records prevents your company from understanding who your customers are and hinders your ability to build a single customer view. This can lead to the same information being delivered to prospects more than once, resulting in wasted time, money and resources. Having a data quality strategy is a crucial step in building a single customer view and preventing your prospects from having a mailbox full of duplicate messages.

In order to prevent duplicate records, look at a data quality strategy that includes:

  • Real-time data verification: Ensure data is verified and standardized when it is first collected. This prevents inaccurate or incomplete information from making it into your database and helps match it to existing records already in your database.
  • Back-end data cleansing: Consistent and timely cleanses of your entire database will ensure that data coming in from a variety of sources is cleansed and duplicates are removed. Having a regular schedule, in addition to cleansing data before marketing campaigns, keeps your database up-to-date and accurate. 

Poor data quality can negatively effect on your internal processes, budget and brand perception. But, these errors can easily be prevented through a proper data quality strategy. Check out the essentials for building a data quality strategy by reading through our white paper entitled ‘Using contact data quality as a competitive advantage.’