The first industrial revolution began just over 250 years ago. Another followed just under 150 years ago, and now we are in the midst of a new revolution – rather than using steam power or electricity, this revolution is now being driven by big data and data analytics.
Data analytics is essentially defined by its use, so, what is retail analytics? The answer is refreshingly simple: employing data analytics in a retail context.
Black Friday is approaching. Traditionally this is a time when retailers offer their best deals on products, and is significantly the most important date in the retail calendar.
>See also: Black Friday? Something is very wrong
With technology changing, retailers need to adapt the equally changing needs of their customers.
They can use newer technology to enhance the customer experience, deliver a more personalised experience and in doing so increase customer loyalty, and ultimately customer retention.
By creating a more loyal customer base a retail organisation can then develop a unified view of the customer activity and in turn begin to anticipate changing customer needs, therefore increasing subsequent sales.
This is not the only way retail analytics brings benefits to organisations; stock control and availability is another key ingredient to a successful customer engagement.
Too much stock is inefficient use of display or warehouse space, too little stock means customers go elsewhere, and once gone can be lost forever.
Therefore, the streamlining of all operations from customer presentation through the sales cycle, stock control and even delivery becomes a key component of business today, especially during period of high traffic such as Black Friday, which the intelligent use of data enables to happen efficiently.
This is where big data solutions come in. It lets companies take advantage of several data sources, potentially in-store, online or external to the business.
To benefit from its potential, companies must ingest data from multiple sources, the create a suitable data platform (commonly known as a data lake) and the transform the raw data into business information and, ultimately, to usable knowledge.
>See also: How retailers can prepare for a Black Friday
These processes allow retailers to gain new insights into customer behaviour, develop an understanding of their activity through loyalty cards or online activity, and ultimately allows targeted marketing to individuals based on previous behaviour.
Of course, some time immediate decisions need to be made.
For example, one of the most critical decisions an online retailer can make is when to put up a holding or busy page on their website to protect it from being overwhelmed by sheer load from visitor traffic, or when to deploy additional capacity to cope with traffic created by Black Friday trading, for example.
This decision has profound implications for key success factors such as customer experience, ability to trade, and brand credibility.
Using data analytics for real time insight enables retailers to see immediately, and predict in the future, these trends and make well-informed decisions ahead of time, often saving the business from potential trading disasters.
Real-time insight into data is enabled through the deployment of the correct technology solutions, these solutions allow crucial retail decisions to be made to maximise business opportunities.
The quicker you can put enlightening information at the fingertips of decision makers, the more effective the decisions they make can be.
>See also: How to prevent Black Friday being a blackout
However, it’s not just in predicting trading patterns where retail analytics can add value.
There are several emerging trends that can be identified in every day retail scenarios.
Computacenter has worked with many retail organisations to provide solutions creating targeted offers that can be received at a kiosk or on a receipt as a result of the day’s shopping.
Video analytics are also becoming commonplace to gather information on the flow of shoppers in-store, measuring how shoppers observe product placement and to gain insight on how best how to lay out displays.
Finally, sentiment analysis solutions are becoming an important business tool, examining the language and extracting that data from blogs, social networks, reviews etc. to gauge customer feeling towards a product or service.
It may take a little longer for retailers to transform themselves into precision analytical machines and whilst the initial investment may delay some retailers from exploring their analytic capabilities, these investments in analytics can generate income quickly, improve productivity and lower costs.
Not only that, the ability to predict buying trends, customer preferences and trading patterns helps to safeguard business against future disruption.
The overall trends are clear: retail is a data-intensive industry, and taking advantage of all that data to operate and manage the business better requires the combination of technology solutions and retail analytics.
Most retailers have only scratched the surface of what is possible, and now it’s up to decision makers and business owners alike to fully realise and embrace the potential of this new digital revolution, enabling both their users and their business, and ultimately enabling their customers.
Companies need to embrace the digital revolution during this seasonal rush – the future of retail depends on the intelligent use of data.
Sourced by Bill McGloin, chief technologist – information, at Computacenter