A Strategy for Acquiring Accurate Internal Data
Retailers have always relied on business intelligence to strengthen marketing efforts. This intelligence can be anything from age and gender to geographical location and income level. All of this data helps retailers identify their target audience and produce marketing materials that are relevant to prospects and customers.
While external data plays a significant role in customer intelligence, internal data is equally important, especially when looking at customer contact data. This data often informs decisions around external data purchases and is also used to make important business decisions.
Customer contact information can supply a great deal of intelligence to retailers by providing geographical information and household details. Additionally, with information collected through so many different channels, contact data plays a critical role in identifying unique accounts to prevent duplicate records.
Unfortunately customer contact information is often riddled with errors. A recent Experian QAS study showed that 91 percent of retail respondents don't completely trust their contact data in terms of it being completely clean, accurate and current. To improve contact data quality for business intelligence, retailers should review the current state of their data to more clearly understand how better information quality can be achieved.
Current State of Retail Contact Data
Contact data touches every business process and department. Therefore, bad data can lead to poor brand perception, wasted budget and diminished potential revenue. It's important to review your current data quality to see how much inaccurate data exists and which business processes it's affecting.
While every organization is different, there are some similarities across businesses. Experian QAS just conducted a global research study to gain insight into how retailers feel about their current contact data quality. The study revealed that 84 percent of retailers believe at least one negative consequence has occurred during the last two years as a result of data accuracy issues. Common consequences included lost customers and negative brand perception.
Ninety percent of retailers think at least some of their departmental budget was wasted during the last 12 months as a result of inaccurate contact data. On average, 15 percent of the budget was believed to be wasted.
When retailers were asked why they lacked trust in their contact data, 50 percent said it's because of human error. Retailers have data management strategies in place across the board, but most rely on manual processes to clean data. This isn't only time consuming, but also ineffective because it doesn't prevent human error, the main cause of data inaccuracies.
Assessing Your Need
Each retailer has different data quality problems and needs, so it's important to tailor strategies to fit each organization. Retailers should make sure to review the following areas before shopping for a solution:
1. Data usage: Certain data sets are far more valuable to a business than others. Retailers need to understand their own unique needs before choosing tools to clean data that might not be crucial to business processes. See if marketing relies more heavily on email or direct mail to communicate with consumers. Determine what external list vendors need when providing demographic information for individuals. Answering these types of questions will help to prioritize data sets.
2. Entry points: Understanding the flow of data allows businesses to select tools for given points of entry. Websites, call centers and point-of-sale channels should all be reviewed. Look at which types of data are taken at each location.
3. Data errors: Business analysts should figure out what type of data seems to be the most error prone. Running data through a batch-type engine will help flag errors and allow trends to be identified.
Without some of this basic information, it's difficult to find the right solution. This information will allow you to select tools based on actual need rather than assumptions.
Benefits of Improved Data
Almost half of the retailers surveyed in the most recent Experian QAS study stated that they maintain contact data to capitalize on marketing opportunities through customer profiling and to enable more informed decisions.
It's important to create sophisticated, customized data strategies that diminish the possibility for human error. Ultimately, improving contact data will permit retailers to improve business intelligence, allowing them to market to customers and prospects more effectively and make more informed business decisions.