3. How to avoid some of the most common pitfalls around implementing and using data analytics?
More and more companies are recognizing that they’re accumulating ever increasing amounts of data but not necessarily gaining business insights from it. The missing link is the transformation of data into information that is comprehensive, consistent, correct and current. Some of the most common mistakes around implementation and using data analytics are:
– Ignoring data shadow systems
-Not building sustainable and on-going processes
-Not dealing with change management
-Focusing on technology instead of the business need
– Not executing a cost-benefit analysis
-Running environments in business-as-usual model
What gets organizations in trouble is how they actually go about implementing data analytics programs. A combination of factors usually derails data analytics implementations. Problems and failures occur due to factors including strategy, people, culture, capacities, inattention to analytics details or the nuances of implemented tools, all exacerbated by the rapid advancement of the digital economy.
4. How data analytics can make a concrete impact on the bottom line?
The analytics and information provided by a coalition loyalty program such as PAYBACK, helps in forecasting customer behavior which is helpful. Data analytics is slowly changing the dynamics of the retail industry. It is leading to more targeted and sharper segmentation basis consumer behavior and usage. Big Data reveals the trend, opportunities, and challenge areas, and importantly, customer focus and segmentation through passing in the loyalty program filters. At PAYBACK, we identify the customers and lapsers based on the analytics gathered and we customize programs according to their needs.
5. Do you think it is proving difficult for some organizations to implement data analytics? If yes then why?
Data analytics is not easy. We all know how much experience, expertise, and industry knowledge it requires to derive value adding insight from a data set. But implementing a platform so that data quality is constantly re-evaluated and defined is an intimidating task for many.
In November 2011, PAYBACK and Future group came together to manage the latter’s loyalty segment. The partnership proved to be a winning one drawing on PAYBACK’s strength in data analytics and Future Group’s large format retailing outlets. Future Group been able to understand trends, and customize offers to suit customer needs and aspirations with the help of PAYBACKS Data Analytics.
Big Data has helped in studying the traits of Indian consumers relevant to FG, that PAYBACK identified and customized the program/offers/campaigns for. PAYBACK also helped FG formats like Big Bazaar & Central with customer insights to segment their transacting customer base on the basis of their Regency, Frequency & Value (RFV model). This has helped FG formats in segmented targeting which has resulted in increasing the overall response rates to the campaigns. Big Bazaar Diwali gifting program in 2012 was exclusively launched for PAYBACK members, which helped in increasing the value penetration from 35-40% range to 50% during the festive period.