According to respected sources in the arena of commerce, the translation of data into actionable insights is both a crucial benefit and a current challenge for retailers operating brick-and-mortar outlets.
A number of reports into the state of the retail industry, including those published in 2017 by Deloitte and PwC, highlight the importance of business intelligence (BI) and analytics technology for store operators, along with the difficulties many experience in turning it to their competitive advantage.
Some traditional retailers are successfully harnessing big data, using the insights gained from analytics to increase sales and profitability, but just how do they do that and perhaps more to the point, how can your company use retail business intelligence to increase revenue in its shops or stores?
Of course, it’s not the data, the software, or even the two combined that drive sales, but the way your business makes use of these primary business-intelligence components.
BI helps you reveal insights into customers, sales, and inventory. To boost sales, your organization must use these insights as a basis to improve specific operational aspects like customer-personalization, marketing activities, and inventory management. These improvements, in turn, create conditions that encourage customer loyalty and stimulate purchasing activity.
As brick-and-mortar retailers ride the big-data maturity curve from descriptive reports and dashboards toward the use of predictive and prescriptive analytics platforms; customer-experience, inventory management, and marketing strategy receive the lion’s share of attention. These areas are typically rich in opportunities (some of which are outlined in the bullets above) to benefit from the application of retail business intelligence.
The ability to aggregate structured and unstructured data is invaluable for learning about your customers. With access to details of their preferences and purchase histories, you can create the kind of personalized customer experience that today’s shoppers have come to expect.
Indeed, when it comes to the overall shopper-experience, in-store retail still resonates more with consumers than its online counterpart. For example, shoppers value the face-to-face assistance and advice they receive from in-store sales staff. They also appreciate being able to receive their purchases on the spot, rather than waiting for delivery.
Business intelligence applications can help you capitalize on these strengths (and others inherent in brick-and-mortar retail channels). Immediacy, for instance, is a quality that can be strengthened by using BI to analyze historical stock-availability trends. The results of such analyses can then be used to identify and rectify inventory-management weaknesses.
Similarly, interrogation of customer histories captured through point-of sale (PoS) and customer relationship management (CRM) applications, aggregated within a BI database, can highlight shoppers’ behavioral patterns and preferences. This intelligence can assist sales associates to provide greater personalization when helping shoppers in-store.
In addition to improving your understanding of customers, retail business intelligence enables you to perform detailed analyses of sales data, helping you answer questions about retail performance, such as:
Nevertheless, the real value offered by intelligence software is the ability to aggregate answers to questions like these, delivering insights to support strategic and tactical decisions related to merchandising, marketing campaigns, and promotions.
Let’s assume for instance, that your analysis shows that stores in one particular region are experiencing high sales-volumes of a certain item, and that those stores display the item differently to outlets elsewhere. The revelation might drive a decision to standardize the item’s placement across all your company’s stores.
There is even evidence to suggest that without such abilities, your retail business will at some point, suffer a critical disadvantage. If recent study-results reported by Forbes are to be believed, 75% of retailers in the United States expect to have big data analytics capabilities in place by 2025.
Should that forecast become a reality, an absence of retail BI capability will soon become a major competitive handicap, especially since the volume and variety of data generated by your business and customers is only likely to increase over time.
While it’s all very well to improve the targeting of retail promotions through business intelligence, marketing activities are only as effective as the inventory planning that supports them. Fortunately, though, this is another retail area to benefit from BI platforms and applications.
Improving inventory availability is a sure way to increase sales in your retail stores, and by pooling data from multiple systems (POS, warehouse management systems, and ERP for example), interrogating it, and visualizing the results, a business intelligence solution can help you make smarter inventory decisions.
BI reports can assist you in determining, for example:
When your inventory decisions become better informed fewer sales will be lost, because the products your customers want are more likely to be available—where and when they want them.
Although the sections above describe briefly how BI can help your retail company improve sales performance, it should be noted that results are not automatically guaranteed. It’s not uncommon for retailers to be disappointed (at least initially) with the outcomes of BI deployment.
These disappointments however, typically result from mistakes made during planning, selection, and implementation of a retail BI platform.
Happily, many early adopters of retail BI have discovered over time (by trial and error) how to stay on track, sharing best practices to help latecomers prevent and avoid these mistakes. Though there’s not sufficient space to cover them all here, many are encapsulated within the following broad guidelines.
The last point on the list above is particularly important, as data redundancy (arising from the use of multiple business information systems) and data errors (incorrect data entries, duplication, and corruption) can seriously degrade the value of business intelligence output.
In fact, poor-quality data can cost your company dearly. Gartner reports that on average, organizations are impacted financially by data-quality issues to the tune of $9.7 million per year.
When you begin to look at the options available to your business, you’ll find there’s no shortage of BI vendors and platforms to choose from. In order to find the solution that best fits your business therefore, it will pay to conduct an in-depth assessment of requirements before commencing the selection process.
Just about every pre-built solution will be packed with attractive-sounding features, but these should not be allowed to distract your selection team’s attention from the critical considerations, which should include the following:
If you want to improve your company’s sales by tapping into the masses of data generated by retail activities, it's time to retire your static spreadsheets and reports.
The latest business intelligence solutions, when chosen carefully and implemented properly, can provide real-time insights into your operation, supporting decisions that promote customer loyalty and business profitability.
The best news of all is that cloud technology has reduced the implementation costs of business intelligence considerably, making it possible for SMEs and larger corporations alike to boost sales with the help of big-data analytics. With that in mind, there’s little reason for your business to be left behind in the intelligence race—or to wait and see what the retail BI landscape will look like in 2025.