Want to Be a Data-Driven Company? You Better Think About Data Quality

Retailers struggle to provide a meaningful, consistent customer experience as the number of channels continues to grow. The increase in infrastructure and interaction points has led to separation in management, for example, for in-store and online programs. This results in various messaging distributed to customers at ill-coordinated times. Unfortunately, that's not how customers wish to interact in today's environment.

Many retailers are working to realign teams to improve the cross-channel experience. This effort is strongly rooted in data and analytics, as marketers need to better understand the consumer to improve the dialogue across channels. With greater understanding, marketers can tailor not just the message, but also the distribution channel and the timing. Cross-channel marketing is now used by 87 percent of companies, according to a recent Experian Data Quality study.

It's clear that retailers are making an increased investment to understand their customers and use data to make better business decisions. However, this new coordination isn't without its challenges. Eighty-three percent of companies stated that they face challenges related to this area of marketing. The main challenges are having accurate and enough information on customers.

While an accurate customer database seems simple, the average U.S. company believes 25 percent of its data is inaccurate. This not only impedes marketing efforts, but also basic operations. In addition, this division between departments has segmented valuable customer information across various databases. The average business maintains eight different databases, making it difficult to gain a complete view of the customer.

Poor data management practices directly relates to the main challenges retailers are facing in this cross-channel environment. The list below explains three key data quality components that produce challenges for marketers:

1. Incomplete or missing data: Contact information on consumers is often incomplete. Different channels require different pieces of contact data to complete a transaction, leading only to the collection of details required for that transaction. In addition, some consumers don't wish to provide contact details. That makes it impossible for retailers to communicate with consumers across all desired channels.

2. Outdated information: Even if accurate information is collected for a given consumer, data expires over time. For example, once-engaged consumers become inactive as they move or change email addresses. It's estimated that 2 percent of contact data goes bad each month, which is 24 percent of a database over the course of a year.

3. Duplicate data: The cross-channel environment creates a data disconnect. Different departments or channels may have different databases or different data standardization requirements. Variances in formatting and quality can make it difficult to consolidate information to gain a complete customer view for analysis.

When investing in new tools for cross-channel marketing, retailers need to incorporate data management initiatives. It's important to consider the total information required, the rate of data expiration, and the ability to access quality information when implementing analytics solutions.

Without accurate and complete information, retailers will make decisions based on poorly generated analytics that could harm brand image and campaign success. Marketers need to work closely with IT and other departments across the organization to implement a data-quality strategy and ensure the infrastructure and data requirements exist internally for reliable analytics and intelligence.

By incorporating data quality into a new analytical investment, retailers are better positioned to ensure a return on investment and a better cross-channel marketing strategy.

Courtney Cunnane is the director of marketing for Experian Data Quality, a provider of address verification software.