For marketers, there are countless benefits to gathering big data and using it regularly in business initiatives. Data collection can help with marketing products, gauging consumer interest and identifying important sales trends.
Data quality is an important driving force behind marketers' use of technology. If they aren't able to use address management solutions to ensure that consumers' mailing addresses, emails and phone numbers are recorded accurately, then they won't be able to effectively measure the efficacy of their promotional efforts.
They also won't be able to prevent fraud. According to Practical E-Commerce, one important use for big data in marketing is fraud prevention. The news source reports that fraud costs online retailers approximately $3.5 billion per year, which is 0.9 percent of total revenue. In an ideal world, this money would be part of the sector's profits instead of a cost of doing business.
Improving data quality can help the industry discover fraud cases. Stolen identities, stolen credit card information and fraudulent product returns can all be identified and prevented using big data initiatives. Here are a few ways that high-quality data can help.
Analyzing more data
In the past, marketers have attempted to use data for uncovering instances of fraud, but they've gone about it half-heartedly, using incomplete clusters of information. Their reasoning was that using entire data sets would be too expensive and too time-consuming to be worthwhile. Big data is becoming faster now, however, and data quality software makes it easier to ensure that information is accurate.
Using real-time detection
Because today's data analytics solutions work quickly, they should be able to analyze transactions immediately at the point of sale, detecting any suspicious financial activity right away. Nipping fraud in the bud now prevents a great deal of headaches later, both for consumers and merchants.
Simulating future scenarios
Insurance Tech points out that big data does much more than simply detecting individual cases of fraud - it enables marketers to repeat their fraud detection processes in the future to find possible trends. By simulating future financial activity and looking for potential irregularities that might arise, companies are able to predict future methods of fraud and enact mechanisms to prevent them.
Ideally, fraud wouldn't exist, and companies could allocate their funds toward profit and growth rather than fighting crime. Unfortunately, malicious agents are a fact of life in today's business world, and data quality is essential in the effort to combat them.