Data Analytics: Four Steps to Help Retailers Gain Competitive Advantage
Jan. 16, 2014 – The proliferation of information from non-human sensors, devices and machine-generated data is a treasure trove on everything from consumer engagement on social media and click through rates to mobile device usage and location-based purchasing habits. While data analytics remains a priority for retailers, the ability to harness that data into true insight remains a challenge.
Today’s powerful analytics call for a new mindset around the value that’s possible to uncover within the data collected. While the “What?” – e.g. How many American Girl dolls did we sell in December vs. July of 2013, and what will happen in 2014? – is still important, the “Why?” is even more critical.
With an “investigative analytics” approach, you can ask a series of quickly changing, iterative questions to figure out why something did or did not happen and how to optimize a particular outcome in the future. Instead of a traditional analytics approach defined by rigid KPIs and reports, investigative analytics can help you identify patterns of consumer behavior to capitalize on: Are certain regions’ in-store sales spiking after a mobile advertising campaign? Why was there a rise in leads from social media – is there an increase in Pinterest engagement that’s leading to rising sales of specific dolls?
As retailers rethink how to capture and exploit data to drive improved business results, they can consider the below factors for implementing an effective analytics strategy.
Identify project goals. Big data analysis can be an overwhelming task, but it doesn’t have to be. Start small and allow your analytics strategy to grow organically based on business goals. For example, since repeat shoppers spend up to seven times more than first-time site visitors (Adobe, “The ROI from Marketing to Existing Online Customers”), maybe your first priority is to increase engagement with existing customers? Or, are you trying to acquire customers in a new retail location? By focusing your project goals, you’ll ensure the questions you’re asking of your data, as well as the resources you’re devoting to the project will map back to positive impact on business goals.
Set budget. Specifying analytics requirements in line with project goals will help pinpoint the right solution. Determine the budget range, but don’t assume you need to invest in an army of DBAs. Data analysis can be surprisingly affordable, easy to use and easy to implement, so look for low-touch solutions optimized to deliver fast analysis of large volumes of data, with minimal hardware, administrative effort or customization needed to set-up or change query and reporting parameters.
Determine departmental and data access requirements. Data analysis must not be siloed as a function of only the CIO and IT. Instead, conduct a review to determine which departments will need to be involved. Today, data-driven decision making can and should be the realm of anyone who has a stake in the organization’s and customers’ success – marketing, sales, customer service, supply chain, etc. As a result, analytics solutions should offer cross-functional support that puts actionable data in the hands of the right people.
Assess technology platform pros and cons. The one-size-fits-all approach no longer works; big data has created pockets of specialization, where some databases are great for warehousing, while others excel at analytics. In order to glean dynamic insight into investigative questions you haven’t even contemplated yet, look for a flexible technology foundation that delivers real-time analytic performance, cost effective scale and ad-hoc querying. Analytics solutions that allow for open-ended data interrogation hold the key to getting deeper, richer insight from social, mobile and machine-generated data sources.
There’s no doubt that data-driven decision making and effective big data analytics can make or break a company’s ability to quickly respond to shifting market dynamics and consumer behavior, and will serve as a true competitive differentiator in 2014 and beyond. The question is: are you ready to be on the winning side?
Don DeLoach is CEO of Infobright, a high-performance investigative-analytic database provider.