In "Understanding Big Data For Ecommerce," I provided a general overview of how online merchants can use Big Data. In this article I will describe in more detail how Big Data — i.e., large amounts of seemingly random data from many sources — can be used to create competitive advantages.
Necessity of Analytical Tools
Collecting Big Data is the easy part. Storing, organizing, and analyzing it is much more complex. Sources can be as diverse as Facebook, Twitter, CRM software, AdWords, and your own website. Making sense of it can be overwhelming without analytical tools.
These tools facilitate the examination of large amounts of different types of data to reveal hidden patterns and correlations that are not otherwise easily discernible.
For example, a merchant could analyze data on visitor browsing patterns, login counts, past purchase behavior, and responses to promotions — to eliminate what isn't working and focus on what does. Some of the off-the-shelf analytic solutions are so finely tuned, they can tell a vendor whether it needs to offer a 25 percent discount or if a 15 percent discount will suffice for a particular customer.
Association rule learning is another analytics method that is a good fit with Big Data. This could be, for example, a shopping cart analysis, in which a merchant can determine which products are frequently bought together and use this information for marketing purposes.
4 Uses of Big Data Analytics
Big Data can be most useful in analyzing a customer's shopping and purchasing experience, which can help a merchant in the following four ways.
Become more efficient by alerting you to merchandising efforts that are ineffective, and products that are not selling, such as an apparel product may be selling well only in two colors while your offer five.
Increase conversion rates by better identification of successful sales transactions.
Encourage more purchases by presenting existing customers with complementary items to what they've purchased previously.
Enhance inventory management by eliminating slow-moving items and increasing the supply of fast-moving merchandise.
McKinsey & Company, the consulting firm, provides this example. "The top marketing executive at a sizable U.S. retailer recently found herself perplexed by the sales reports she was getting. A major competitor was steadily gaining market share across a range of profitable segments. Despite a counterpunch that combined online promotions with merchandising improvements, her company kept losing ground….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. At the same time, it had linked this information to suppliers’ databases, making it possible to adjust prices in real time, to reorder hot-selling items automatically, and to shift items from store to store easily. 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."
Is Big Data Analysis Affordable?
Is launching a Big Data initiative expensive? It doesn't have to be. A single disk drive that could hold all the recorded music in the world costs $200, according to McKinsey. Cloud data storage is also a good alternative for small ecommerce merchants because it is relatively inexpensive and is scalable — it can expand as data requirements grow. A variety of cloud analytics software programs are now on the market. While big players like IBM focus on enterprise companies, there are providers that cater to smaller ones — examples are Custora, SumAll, InsightSquared, and Metamarkets.
Relying on data-driven decision-making is crucial in industries in which profit margins are slim. Amazon, which earns increasingly thin profit margins, is one of the most effective users of data analytics. As more Big Data solutions for small online businesses come to market and more online merchants incorporate Big Data into their business tool set, employing Big Data will become a necessity for all ecommerce merchants.