In 2020, e-commerce sales accounted over 15.5% of retail sales worldwide. In terms of purchases 1 in 4 occurred online, in 2021 is estimated the year-over-year increase at 4,4% (source: Statista).
A growing number of commentators and studies agree on the downsizing of the “Retail Apocalypse” scenario in favor of a radical paradigm change, already underway, which redefines some basic concepts, as Luca Innocenzi effectively analyzed in the article “Retail e COVID – speranze e strategie“.
The reality is that, in any case, even in the worst and least probable scenario, Retail will still represent the most important slice of turnover for most brands. It will remain at the center of business strategies and if anything trying to “unite per osmosis ”online, through cultural reconversion projects within the company and sensible investments in the context of omnichannel-oriented integration.
Retail is not over, it just needs to be rethought.
Starting from this assumption, the most shrewd Retailer can only choose to start a path of knowledge and awareness, first of all wondering what are the practices and tools that can be “borrowed” from online and specific benefits that can derive from them.
Now let’s try to ask ourselves this question: is it permissible in 2021 that any ecommerce site can do without an Analytics Data Driven system? (for example Google Analytics just to name one of the most popular).
Clearly not, not even the most irrelevant ecommerce site would consider it an option.
An analytics system provides increasingly in-depth and articulated metrics: number of accesses to the site, content seen, days, hours, locations, devices, gender, age group and other relevant characteristics of the audience. These tools became part of our daily life, explaining to us in detail who our customers are, what they expect and if they appreciate our initiatives and our products.
Why do we consider them fundamental to develop 15.5% (on average) of turnover and for the remaining 84.5% we perhaps just aggregate statistics on sales or use trivial instruments?
Logically (and depending on a budget), we should first of all worry about overseeing that 84.5%, studying it, protecting it, understanding it if possible and developing it in a “customer oriented” perspective, as we normally do on the e-commerce site.
So why does it still happen so timidly among large retailers? Leaving aside all the secondary reasons, it happens for two kinds of reasons.
1 – implementing an analytics system on an ecommerce site is relatively cheap
It is a simple calculation: if to implement an online data driven strategy it is necessary to spend a lot, hire specialists, consultants, invest in platforms etc, the cost is unique, its impact on ROI compares entirely with that 15.5% in revenues, presumably growing.
On the other side, the monitoring of each individual physical store cannot be centralized, has internal costs and the overall investment is, at least, the sum of those of each individual store. For this reason, it is essential that the cost of adoption and possession for a single store is sufficiently low to be comparable. Once aggregated, with the online one, on the basis of a proportion that compares the levels of overall turnover and does not neglect to consider the additional advantages deriving from the union of the two datasets within a single omnichannel Business Intelligence ecosystem.
Let’s take an example:
If total turnover is 100, and Google Analytics contributes in a decisive way to produce an average increase of 4.4% per year on the online, the utility threshold of the investment will have to remain as widely as possible below 2-3%. of that 15.5% of online turnover, to ensure a positive ROI.
The rational retailer will be willing to invest a maximum amount between 0.31 and 0.465.
2 – the data production tools have not proven themselves
Once the relevance and value perimeter of this instruments has been clarified, the topic shifts to availability: Are there any instruments that can guarantee data consistency, total costs of ownership below the ROI threshold levels, low impact on processes and infrastructure costs while ensuring data readability, protection of customer privacy, opening up to different technological ecosystems, extending the scope of intervention to contexts such as Smart Digital Signage and user experience, all integrated into a single platform?