Direct customer relationships are a privilege, but they also generate massive amounts of data. This wealth of information holds the potential to drive real frontline differentiation, if retailers have the right tools and approaches to make the most of this unique asset ‘Big Data’. In our experience of working with retailers across the globe, we have found Big Data to be getting a lot of interest, but most retailers struggle with some common challenges such as how to align big data with business decisions, how to identify new types of data and how to gather big data for improved decision making.
So, What should one do to leverage this so called Big Data?
- Get your house in order: With retailers it is possible that customer data and transaction databases are disparate first order of business would be to harmonize these. Invest in a good big data system. Azure or HP Vertica are all viable options.
- Know your customers: Do you have all the information about your consumers in your own database? Is there value in evaluating 3rd party data sources to enrich what resides inhouse?
- Invest in a good social listening tool: The adage ‘action speaks louder than words’ no longer rings true for most part in this age of social media. Can go from a 140-character rant to a rambling tirade. Pick your Poison. It is important to be aware of where one stands in social media. Can have long standing impact on your brand and consequently on the topline and the bottom-line.
- Use data and decision engineers: All this big data will necessitate folks that can enable you to use the data efficiently. Data engineers are essential to maintain your big data ecosystem and decision engineers will be able to derive maximum information from the data. Be it basic EDA or complicated machine learning algorithms. The larger question is whether to nurture this talent in house or partner with a analytics service provider. The size of your operation will answer this question best. No matter what the right answer is, it is best to get started with an experienced analytics service provider.
- Optimize your supply chain, distribution and campaign: Having all of the above in place will enable one to derive most from big data. For retailers with conventional storefronts, machine-learning algorithms can
Identify your most popular product based on legacy data, integrating POS data will help inform your supply chain – identify SKUs that are likely to be most on demand and adjust/plan production accordingly and also adjust distribution. Being able to aggregate data as close to real time as possible will also enable smarter campaign planning and management. All of which will ensure that your feet are firmly planted in black.
To compete in a consumer-empowered economy, it is increasingly clear that retailers must leverage their information assets to gain a comprehensive understanding of markets, customers, products, distribution locations, competitors, employees and more.