Electricity accounts for a significant part of a retail store's cost-to-serve. For a retail business spread across several stores, it is important to identify the correlations between cost, energy, operations, and location. To this end, we present a measurement-based analysis of energy and operations data gathered from 201 stores of a leading retail chain over a two year period. We employ statistical techniques and unsupervised learning to understand the inter-relationships across the various dimensions. Specifically, we find that: (i) The well-known Pareto cost-benefit principle (or the eighty-twenty effect) does not hold when considering the energy consumption as cost with customers served and store area covered as the benefits; (ii) After accounting for the time-of-day effects, sales counts do not affect energy consumption statistically, while ambient temperatures do so; (iii) Stores that exhibit a greater degree of energy proportionality have larger areas; and (iv) Opportunities for improvements exist in reducing the energy cost of operations. Many stores switch their operations on well ahead of their opening times. The average annual energy savings that could potentially be achieved across 201 stores if their operations are in tune with their opening time is roughly 8.2 GWh (2.5%). These savings can be achieved with just changes in operational procedures with zero capital investment.