Online shopping has become so popular that traditional retailers are looking to modern analytics tools in order to help them remain competitive. Robert Hetu, a research director at Gartner, noted that consumers have taken control of the shopping process and that the way we shop is changing.
The Internet of Things has expanded and will continue to grow over the next several years, and this is going to be more disruptive to the way that we shop than any other recent trend change. Retailers will need to use advanced analytics systems to guide them through this disruption.
The model of using large items as loss-leaders, then making money back on consumables - for example, selling a cheap water filter and then making a profit on the replacement filters - is something that has worked well until now, but the era of connected devices means that stores can no longer rely on a consumer coming back to their premises to make a purchase. What if the water filter jug is Wi-Fi-connected and shops for the best deal on replacement filters automatically?
That’s where tools such as business intelligence come in. Retailers who are able to keep track of revenue-generation opportunities will be better off when it comes to deciding whether certain opportunities to secure a purchase are worthwhile, or whether they should let that opportunity pass and focus on something else.
Real-time analytics and decision-making will benefit consumers because it will make the marketplace more competitive. However, it will take some time for retailers to acquire the big data analysis capabilities that they need to compete. Rather than doing their data analysis in-house, many may opt to outsource big data and decision-making by using data feeds generated, and distilled, by third parties.
The tools are already out there for big data discovery, but the skillset required to understand them is complex. Most retailers don’t have a background in BI, so it makes sense for them to focus on the simplest problems - the low hanging fruit that will allow them to make better-informed decisions and get access to the information that will yield the fastest results. Generic data generated by third parties, and targeted at a broad base of users (including other retailers), will most likely be enough to support retailers in the near term as they get comfortable with analytics.