The Omnichannel Environment Presents New Data Challenges for Retailers

As retailers continue to work on creating an organization revolved around the consumer and the omnichannel environment, there are new challenges to consider. These are especially true around consumer intelligence and accurate data.

According to a recent Experian QAS study, retailers interact with consumers across an average of 3.6 channels. The most popular channel for interaction is the organization's website, followed by the point of sale (POS) and face-to-face interaction with a sales representative. In addition, social media and mobile are growing points of consumer interaction.

To appeal to consumers in this competitive environment, retailers are working to provide a personalized customer experience to entice them to buy now and remain loyal to the brand. To achieve this goal across channels, retailers need data that can be used to better understand the customer.

However, gathering meaningful customer intelligence is no easy task. The biggest challenges cited by retailers when engaging in cross-channel marketing are having enough information on the consumer and having accurate consumer data.

Retailers struggle to collect accurate data, not to mention consolidating it across departments and channels. There are several key factors affecting data quality in the omnichannel environment.

First, it's easy for individuals to incorrectly enter information. Manual data entry can be fraught with errors, especially when information is entered by consumers online. There are many distractions to consider, including a variety of formats and abbreviations in entries as well as basic typing errors.

Second, different data elements are collected through different channels. What's collected from consumers online is often different from what's collected at POS. In addition, consumers expect transactions to be completed as quickly as possible, limiting the retailer's ability to collect a significant amount of information.

Finally, call-center representatives may add information to the wrong account or accidentally create duplicate records. Most systems have poor search functionality when it comes to finding existing records. When data entry errors occur, it can be almost impossible to pull an existing account, resulting in duplicate entries that spread customer history across multiple records.