Transactions are at the crux of marketing analytics. A customer making the commitment and buying a product sends the strongest possible signals to a company about what is working and what is not with regards to sales pitches and investment. According to Clickz, however, companies limiting themselves to online purchase statistics may be missing a key part of the picture. The source noted that companies with the proper analytics tools can apply business intelligence (BI) to both internet and in-person purchases, vastly increasing the depth of analysis.
Two sides of marketing
Retailers these days often exist in both the physical and online arenas. Considering the rise of the internet as a shopping venue, any other approach would be near-suicide for brick and mortar operators. Media firm CTO Joseph Benjamin told the news provider that the proportion of time spent in a venue to make purchases made is wildly uneven between physical and online stores. While shoppers spend long hours inspecting products online, he estimated that 90 percent of purchases are made in person, making it vital to capture information about those transactions and subject it to analysis.
The rise of big data as a tool has enabled companies to make the shift toward new information sources. Clickz reported that marketers working with online campaigns no longer have to limit themselves to "click-through" counts to see how effective a sales mailing was. Not every customer that clicks a link in a marketing email is going to make the purchase. However, some that seem to have backed off could make that same transaction later in a store, influenced by the message. A way to measure that response could be important for companies.
There is more than one variable available to marketing experts once they add big data to their BI toolkits. According to CIO, users can take information from everything from direct online contact with customers to the general sentiment of the populace. Firms can launch specific programs to cater to supposed shopper interest and then, taking in new response data, measure those efforts' effectiveness.
Analytics has also given companies the ability to make accurate guesses about the future of the market. CIO noted that predictive analytics can tell firms when inventory is correct relative to expected sales and demand. Merchants can avoid running out of products at key moments of market excitement and prevent obverstock when ordering in lean times.