Traditionally, the apparel retail industry has consisted of customers going into stores, trying on clothing, and then deciding whether or not to buy. However, now that people frequently buy apparel online, businesses are leveraging the power of predictive analytics (PA) to improve their customer conversion rates and reduce returns. Machine learning, predictive modeling and data analysis are the backbone of PA technology, which uses historical shopping data to help businesses make well-informed decisions.

Apparel companies are finding innovative uses for predictive analytics.

Image Source: Unsplash user rawpixel.

PA allows companies to better anticipate fashion trends, predict items that will appeal to specific customers and determine which marketing campaigns will be the most effective. Here are five of the most important ways in which PA is transforming the retail industry.

Improved Product Recommendations

Customers need to feel valued in today’s retail environment, increasing the need for personalized recommendations. Fortunately, predictive analytics creates highly focused customer segments that allow businesses to develop unique offers to customers based on their browsing and shopping patterns. So, based on a customer’s online shopping habits, you may suggest apparel items that will likely appeal to that customer’s clothing preferences. By offering personalized recommendations, retailers can increase sales and boost customer loyalty. Many companies are finding success with this technique, including retail heavyweights Amazon and Etsy.

The technology can also tell whether or not a consumer has the potential to be a recurring customer by monitoring how frequently they visit your site, how much time they spend on each item and their shopping history. Predictive models can identify if a customer hasn’t shopped at the store for a while, which means the company could be losing them. With predictive analytics, you can then work to bring them back. After all, the right product recommendations can be all it takes to transform an occasional customer into a frequent buyer.

Better Merchandising and Marketing Campaigns

How a business markets its products can be just as important as the products themselves. Predictive analytics provides some powerful capabilities, as the technology can compare your prices and inventory with those of your competitors in order to improve your merchandising campaigns. The technology offers a way to forecast the demand for certain items based on seasonal factors, popular fashion styles, geographical area and the age range of your customers.

Predictive analytics also uses natural language processing to understand the lingo of a certain audience and create marketing campaigns and ads geared towards that demographic. You can even use PA to make strategic decisions about the location of your new store based on where your target audience spends time, their purchasing power and market conditions. Essentially, the technology helps you determine the right price points, marketing avenues and customer conversion rates by analyzing large swathes of data from various sources.

Accurately Predicting Stock Requirements

Many retailers are still plagued with inventory uncertainties such as whether or not they are overstocking or understocking an item. Fortunately, PA can help you garner a better understanding of how well a product will sell and how quickly you need to restock. Predictive analytics identifies high-demand areas and determes emerging sales trends in real-time, helping you reduce the time and money spent optimizing your inventory.

The technology can also optimize supply chain planning, ensuring that your inventory is always sent to the correct store on time. By automating the process of determining how your store should be stocked based on market conditions and emerging shopping trends, PA can save you money and improve your bottom line.

Helping Customers Find the Right Fit

It can be difficult for many of us to find clothing that fits well, especially when shopping online. Predictive analytics is changing the game in this regard, though. The technology can be combined with augmented reality (AR) and image processing technology to help customers quickly find apparel that fits them using virtual fitting rooms. PA analyzes a person’s body measurements, then predicts which items of clothing will fit them best. Customers get to see how the item will actually look on them without ever having to step foot in a store.

For example, the Fit Freedom mobile app is designed to measure a person’s body in minutes. The app uses a mobile device’s camera to create accurate measurements to half an inch. Based on these measurements, Rebel Athletic can create customized athletic wear.

PA can save customers a lot of time spent trying out different clothes and help them find a better fit. This leads to happier customers who are more likely to buy more items in the future and a reduced amount of returns and exchanges.

The Future of Predictive Analytics in the Apparel Retail Industry

Predictive analytics is still evolving and advancing, but it has already shown plenty of promise in the apparel world. The technology is changing the way we buy and sell items by offering more data about customers and allowing companies to provide personalized suggestions. The end result is improved marketing campaigns, better product recommendations, inventory optimization and lower return rates.

If you’re hoping to leverage predictive analytics to improve your apparel retail business, you will need to work with a skilled developer. At SevenTablets, we specialize in custom mobile app development and predictive analytics. In addition, we have extensive experience with a host of cutting-edge technologies, such as augmented reality, virtual reality, artificial intelligence, blockchain and natural language processing.

SevenTablets has headquarters in Dallas, but we also serve clients in Austin, Houston, and across the United States. If you would like to discuss your project, we invite you to contact us today.


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Shane Long

Shane Long

President at SevenTablets
As President of SevenTablets, Shane Long brings experience in mobility that pre-dates the term “smartphone” and the release of the first iPhone. His work has helped revolutionize the growth of mobility by bringing to market one of the first graphics processors used in mobile phones, technology that after being acquired by Qualcomm lived well into the 4th generation of smartphones, as well as helped pioneer the first GPS implementations in the segment. With a strong engineering and business background, Shane understands how the rise of mobility and Predictive Analytics is crucial to greater business strategies geared toward attaining competitive advantage, accelerating revenue, and realizing new efficiencies. As the leader of a B2B mobility solutions provider, he partners with business leaders including marketers and product developers to leverage enterprise mobile applications, big data and analytics, and mobile strategy.

Shane earned a B.S. at Texas A&M (whoop!) and studied mathematics as a graduate student at Southern Methodist University.
Shane Long