As consumers become more and more reliant on online shopping, both on their desktop computers and via their mobile devices, the e-commerce industry has become increasingly more competitive. People looking to spend their money have a wide variety of options at their fingertips, and for the merchants themselves, it difficult to win the battle for more customers. There are a lot of rivals for each individual vendor to fend off.
Big data analytics can play a large role in helping merchants complete sales more successfully. By helping companies optimize their pricing and marketing strategies, successful data use can giving sellers a leg up on their rivals. If executives are willing to devote significant resources to collecting information, maintaining data quality and analyzing trends to find successful courses of action, the effects can be very significant.
Practical E-Commerce recently expounded upon the benefits of big data analytics in online commerce. The news source cited an example offered by the e-commerce consulting firm McKinsey and Company, which talked about a major retail company that received a series of unfavorable sales reports and discovered the decline was largely due to the gains that a rival company had made with big data.
"The competitor had made massive investments in its ability to collect, integrate and analyze data from each store and every sales unit and had used this ability to run myriad real-world experiments," McKinsey and Company's report said. "By constantly testing, bundling, synthesizing, and making information instantly available across the organization…the rival company had become a different, far nimbler type of business."
Examples like this are commonplace in today's business world. If companies aren't able to make good use of big data, they're inevitably going to fall behind in their competitions with their rivals.
Here are a few ways that optimal data use can help companies improve their operations.
Improved pricing strategies
When competing with other e-commerce sites, it's good for merchants to have dynamic pricing strategies that adjust quickly to sales activity around them. Real-time tracking of sales trends can help companies find the perfect price points. If a certain item begins selling quickly, companies can recognize that immediately and adjust the price accordingly. Merchants want to keep their prices high enough that they can ensure future profits, but they also need to stay competitive in rapidly evolving markets. Data collection can help them stay on top of their game.
Better targeting in marketing
The best way to market products is to be specific, finding particular items that can be sold and targeting particular consumers that might be interested. By keeping an eye on customers' past purchases and their spending habits, companies can draw conclusions about what items people are interested in buying, when they're willing to buy and how much they have to spend. Analyzing individuals' habits will undoubtedly lead to a spike in sales.
Personalized customer service
If anything goes wrong, merchants must also have dedicated customer service staffs on hand to help customers with their problems. Collecting big data can help in this pursuit, too. By monitoring customer service complaints over time, companies can make themselves aware of what problems are cropping up repeatedly with their products and what strategies work well for solving them.
Predicting future sales trends
If vendors want to ensure successful sales initiatives in the future, it's always good to look ahead. By using data on past sales to develop models and predict future trends, companies can offer the right goods at the perfect prices down the road.
Information mining and data quality can have major effects on e-commerce. Those who climb aboard the bandwagon will help their bottom lines for years to come.
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