Today’s retailers are using Big Data analytics to reach for topline growth and increase their market share. The latest challenge is collecting, assessing, prioritizing, and executing this data to master Dynamic Pricing in real time. “28% of retailers feel pressure to evolve from current, historical datareporting tools to those that are capable of multivariant modeling and testing of whatif scenarios.” RIS March 2014 Report, “Supercharging Predictive Analytics with Big Data.
Tips for working with Predictive Analytics:
● Create a clearly defined strategy.
● Define shortterm goals that can produce quick wins.
● Define longterm goals that will transform the enterprise.
● Identify tools, skill sets, and resources that can build a fully functioning analytics team.
Tools needed for successful analytics:
● Highspeed, advanced analytic tools to leverage performance.
● Ability to convert large volumes of data into actionable insight.
● Ability to monitor progress.
● Ability to predict/recalibrate outcomes or “what if” scenarios.
● Ability to act and react quickly.
● Ability to create marketaware rules, such as changing product price in realtime, to respond to a combination of competitor actions.
What retailers want in their ideal platform/tool:
● Easy to use interface. 95% of retailers say that this is the most important feature of their analytics tool (EKN Benchmark Study, The future of retail analytics SAS).
● Streamlined operational effectiveness and efficiency (access to data).
● Fast, scalable, and intuitive predictive insights.
● Userfriendly and graphically effective.
Secret: The “2% Solution” Only about 2% of all big data streams is actually relevant to solving a particular business problem. That means that 98% of data is just noise. To rid yourself of this noise, you need the right tools to quickly identify the 2% of data that is relevant. Being able to get to this data quickly allows you to solve one problem and move onto the next, keeping you ahead of the competition.
Bottom Line For Your Bottom Line
To thrive in today’s market, retailers must use analytics wisely and in a timely manner to optimize functions, drive sales, and increase profit. Utilization of these tools is necessary to survive and thrive. The competition is growing, developing, and becoming even smarter. You must keep up if you want to compete