Retail Data Analytics: How Data Analytics Will Transform the US Retail Industry
Players in the US retail industry are forced to cut costs to stay afloat during the recession period. Though a pain point, cost-cutting offers a good head start towards achieving the desired sales and profit margins. The recent advances in data analytics and technology have made data analysis much simpler, helping retailers to identify and [...]READ MORE >>
Players in the US retail industry are forced to cut costs to stay afloat during the recession period. Though a pain point, cost-cutting offers a good head start towards achieving the desired sales and profit margins. The recent advances in data analytics and technology have made data analysis much simpler, helping retailers to identify and capitalize on new opportunities in the US retail industry. With retailers across geographies offering a diverse range of offerings use similar promotional campaigns, retail data analytics has turned out to be a key differentiator in the US retail industry, helping players make important business decisions with ease. This has made it crucial for retailers to not only integrate and analyze data obtained from different sources but to also leverage retail data analytics to improve their overall decision-making ability.
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Top Data Analytics Applications That Can Help Players in the US Retail Industry
The use of data analytics has evolved significantly over the past few years from generating simple reports to helping retailers devise robust data analytics models to improve business processes. The following are a few applications of retail analytics that can benefit retailers:
Identify profitable customer segments
To succeed in today’s hyper-competitive retail industry, businesses must ensure they adopt suitable retail analytics solutions to maximize MROI by targeting the right customers. Once the profitable customer groups are identified it’s essential to analyze their needs and align offerings to meet customers’ demands. Also, by ensuring the availability of the right items at the right locations and in the right quantities businesses can improve their margins significantly.
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Analyze customer behavior
Though no two customers would have the same requirement, businesses can still group customers into homogenous groups based on their behavior. This not only helps them analyze customer’s needs but also empowers businesses to use data analytics to target the most profitable customers with customized offerings. Apart from offering new cross-selling and up-selling opportunities, retail data analytics empowers businesses to leverage hierarchical clustering techniques and decision trees to make crucial pricing decisions.
Improve assortment planning and optimization
Data analytics can help businesses discover associations in purchase behavior and assortment plans. Based on these insights, retailers can devise suitable strategies to achieve their capacity requirements. The use of data analytics models to classify customers based on their purchase behavior and needs can help businesses to optimize their assortments based on the market demand.
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Leverage operational analytics
Data analytics can help retailers automate decisions based on certain criteria, thereby playing a major role in improving the efficiency of business operations. The use of operational analytics not only offers real-time visibility into shopping cart information but also helps in the rapid scoring of purchase behavior, making it easier to develop targeted promotions and maintain real-time customer information.
While these retail data analytics applications are moving into the mainstream, leading retailers in the US with multiple business units are now leveraging advanced data analytics solutions to support a wide range of initiatives. Collating and analyzing all necessary data elements from disparate sources, however, can be a challenge without expert assistance. Working with a trusted third-party retail data analytics solution provider can bring sanity to an otherwise chaotic process plagued by resource constraints.
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