Retailers today must deal with the growing need for customer expectations, including more choices, more customizations, and a seamless shopping experience, both offline & online. A major part of the festivities for the consumers involves purchases and this pattern repeats year after year. Yet, we observe that retailers have a lot of untapped potential to understand and deliver personalized consumer shopping experiences.
Data doesn’t drive the retail industry, it’s analytics that does.
According to a Salesforce report, only 32% of retail executives say they possess the ability to convert data into real-time insights and informed decisions on personalized prices, products, and offers for shoppers.
When B2B sectors are heavily reliant on data-driven decision-making, the retail segment is still falling behind. So, what causes this challenge of tapping into data in the retailing community?
With the presence of various digital channels and technologies, retailers are armed with a huge arsenal of customer data. However, a lot of effort goes into working on the sales channel, without consolidating the data across various streams. This results in a lack of unified data experience leading to data mismanagement. This not only holds back the potential market revenue but also creates roadblocks for just-in-time decision-making.
Decision makers have to deal with market, logistics, and operational data. When the data streams are compartmentalized, how can one break the shackles of unifying them to make informed decisions?
Data analytics investments in the retail market are estimated at USD 4.18 billion, so clearly retailers are trying to harness the power of data. But with fragmented data stored in dashboards that don’t contextualize, creating customer-friendly experiences is an uphill task.
To help with these issues, Al and ML are often deployed to automate decision-making, but rather than create new chances; they run on established patterns. This prevents retailers from gaining a holistic view of hidden opportunities and threats within data streams.
Unifying the data beyond the dashboard
The solution however lies in unifying the data to maintain accurate information across the channels.
Unifying data is essential to the retail sector to tap into the available market potential and to make just-in-time decisions. An average retailer deals with a number of products, customers, purchase history, warehouses, and information systems. This drives the need for a freer-flowing data stream that integrates and enhances the system.
Breaking down the silos and looking at data as one unified stream allows in-time and intelligent decision-making, not just running diagnostic, pre-emptive, or predictive analytics – the trump cards flaunted by every data analytics platform or service.
The myth of truly unified data needs to be busted.
So, what does truly unified data look like?
Cross-checking or juxtaposing one stream of data with another is not unifying data. You are still trying to connect the dots between two silos. For instance, if a marketer can see campaign performance data for the month and the over-store sales projections on two different windows simultaneously; and then open another excel to infer insights and plan actions – it is still siloed data.
A unified view is where every possible data across functions, regions, categories, and more is accessible as one stream for anyone and everyone at any point in time. This flow of different streams of data allows different functions in the retail business to infer scenarios, understand trends, and take just-in-time decisions, breaking free of department-wise data. For instance, the supply chain team can look at sales data in different stores in conjunction with running offers, planned campaigns, and available stock to keep their vendors alerted to the requirements. Retailers can easily extract valuable insights and plan actions from this 360-degree picture of the organization's data.
The business has the ease of data management while the algorithm at the backend streamlines data and enhances processes. The actual innovation in the effective usage of data lies in its productization of it. Retail owners need to look beyond the data professionals, the strategy, and the tools. To enable just-in-time decision making data demands to be viewed through a product development lens.
Winning customer delight is always a work in progress, winning over data challenges need not be. Breaking free of data silos is liberating, and retailers are in the best place to gain from it. End of the day, it’s your data, go play with it.