Analytics is the enabler for value-oriented efficiency
The global rise of online sales has long turned from a prediction into an unavoidable reality. Forrester Research estimates that, by 2023, e-commerce will drive two-thirds of retail growth, up from 50% nowadays. Consequently, the online channel is no longer the place for effortless differentiation, but a challenging arena where retailers are hard-pressed to strive for excellence.
Within this competitive context, let’s recall five reasons why analytics is the key for retailers to reap the benefits from the e-commerce explosion:
1. Retailers need analytics to truly get to know their online clients
The million-dollar question in retail has always been: what makes the client return to buy again? In other words, what are the key drivers of client experience? In the past, the answer relied mostly on clerk-based gut feeling and, at best, small-scale surveys. As customer interactions move from the physical to the digital world, new ways have emerged to grasp client behavior.
Analytical techniques such as machine learning, when applied upon historical data that frequently encompasses millions of distinct purchases, make it possible to find and measure the drivers of client retention. Is the speed of delivery the main trigger of repeated purchases? Is it shipping cost? Or is it the quality of packaging? In-depth understanding of client preferences is vital for retailers to refine their value propositions and gain a competitive edge.
2. Analytics enlightens the design of an e-commerce operation
Provided that the retailer knows what its clients really want, another question arises: how to shape the ecommerce operation in order to strike the perfect balance between value proposition and efficiency? For instance, faster deliveries are bolstered by placing inventory closer to the final client. Still, this enhanced service certainly comes at a cost. Using simulation, retailers can test and assess different scenarios in a risk-free environment, finding the optimal shape for their operation.
3. Analytics brings intelligence to tactical planning
Besides strategic operation design, tactical planning is another decision level in which e-commerce players can drive value from analytics. For instance, by tackling key decisions such as capacity planning and pricing in an integrated fashion.
Let’s use “attended home delivery”, very typical in grocery retail, as an example. In that case, the client must be available to receive the goods. Therefore, delivery slots outside working hours are clearly favored. It is obviously impracticable to size the operation to cater for such demand peaks, since idle capacity during working hours would compromise overall efficiency. An obvious remedy is to allow for a limited number of deliveries in each slot.
While availability caps can work, dynamic pricing is a smarter way to balance capacity. Predictive analytical modelling leverages transactional data to grasp the relative willingness of customers to pay for each delivery slot. Therefore, retailers can differentiate prices, making slots equally appealing and thus preventing them from becoming unavailable too far in advance, a typical customer pain point.
4. Optimized operational management requires analytical tools
For planning decisions that take place at a more operational level, such as delivery routing (for retailers that don’t outsource transportation), off-the-shelf analytical tools are typically favored, since differentiation is not as relevant. Still, companies should devote particular attention to provider selection, putting an emphasis on both flexibility and price, rather than only the latter. Today’s ever-changing competitive environment requires a continuous customization process that monolithic tools or rigid providers cannot cope with.
5. Abundant data is available for retailers to grab and take advantage of
From strategic design to operational planning, sound analytics can improve decision-making across the board. But the potential impact of data goes way beyond planning processes. Take as an example website morphing, that uses massive amounts of click-stream data to adapt the “look and feel” of a retailer’s website to the cognitive style of each individual visitor, boosting both sales conversion rates and customer experience. An almost endless range of opportunities is available for e-commerce players that embed analytics in their culture.
In these new times, analytics is the enabler for value-oriented efficiency, the key ingredient that makes online retailers more likely to succeed in the challenging e-commerce arena.