duDi - driving under Data influence

The B2C businesses continue to evolve at a fast pace – whether it is to fight recessions or to maximize gains from a thriving economy. Technology further pushes innovations and keeps reducing the time to market and hence shortening the lifecycles.

Handheld device driven e-commerce and social media is fast over-taking desktop computing. Phone apps seem to be becoming ever creative and powerful (with Geo tagging and linking back to your preferences while shopping or sightseeing etc). Under threat desktop web sites are making it easier-faster for customers to surf by evolving to a Google kind of search and sort interface. E-commerce aggregators allow customers to run searches across sites to pick out deals. Malls and shops are fast turning into product display and advertising channels with ultimate conversions pushed through on-line deals. Virtual reality threatens to replace the physical shopping experience (still some time before it can be commercialized for distribution). 3-D printing could be the next mass manufacturing technology.

However (without wanting to sound clichéd) all roads lead to one destination – “more customers and more sales per customer”.

The pace of discovery of roads sometimes hinders the ROI from each of the roads. Which makes it paramount for companies to keep learning about the different routes customers could take. Such learnings are typically carried out in 2 ways – running your own internal customer analytics and learning from the industry.

The first is a “tracking” mechanism which can be seen as a parallel to someone following you from your home to all the stops you make at malls/ shops and then looking over your shoulder when you make your purchase and running back and storing all this data and bombarding you in the future with pamphlets, billboards and customized mailers. The modern world does not make it easy to first track a smart on-line shopper and then close onto a strategy that would make sense. It involves analyzing through multiple customer transactions and segmentation – proudly bill-boarded by many as “big data” analysis.

Trade data is usually available in various forms and prices based on your appetite. Extend this to conferences and exclusive invitation only small group events – the data sharing can be as revealing as you would want.

Both the above do not give any relevant messages unless tailored. For me it is always about creating a relevance framework before committing to a strategy. Such frameworks usually evolve around the direct influence of the trend/ innovation to my product, lifecycle stage, risk appetite, budgets, ROI etc.

Data is usually intoxicating. Please remember to dilute it and spike it enough with your due diligence and sanity to make it a drink worth enjoying. At times don’t be afraid of over-drinking if you know how to be on your feet always. The doctors too advise a drink or 2 to remove the clogs – let data unclog your analysis arteries than drown you in un-connected detail.