The retail industry is a thriving marketplace, especially on the internet. As the world has transformed to make the “shopping experience” much easier for the consumer, a person can easily compare prices and other features in a range of products and directly purchase what they believe is their money’s worth. A retailer starting out will soon learn the difficulty of determining what a consumer wants. Every month, consumer and market trends fluctuate. Retailers must be up-to-date on the latest trend and versions to ensure sales occur. This is where predictive analytics can help retailers in the industry. By integrating this technology into retail operations, accurate predictions can be made to assess the demand for a specific product. This allows retailers the flexibility to purchase products in bulk only where necessary. In other words, retailers can prevent losses from occurring if they invest in a predictive analytical tool. The benefits retailers can gain from predictive analytics is not new. Predictive analytics is also associated with big data analytics. According to a research report published by Allied Market Research, in 2020, global big data analytics in retail markets was valued at USD 4,854 million. This is projected to reach USD 25,560 by the end of 2028. All this leads to the conclusion that analytics is a digital tool that should not be missed out on. This article will explore predictive analytics use cases in the retail industry in detail.
Five Ways Retailers Can Employ Predictive Analytics to Succeed
Predictive Analytics works together with Artificial Intelligence (AI) and Machine Learning (ML) capabilities to ensure futuristic insights are provided. When a retailer incorporates such a system into its operations, it is the data collected through the consumers in the loyalty program, the retailer’s websites, point-of-sale systems, CCTV camera’s in their physical store, mobile apps, in-store sensors, supply chain system and others that play a vital role in providing accurate analytical data. Here are ten use cases where predictive analytics is used in the retail industry.
Help You To Think Like A Consumer
Predictive analytics help retailers get into the mind of their consumers. This is sometimes referred to as behaviour analytics. As people often browse through social media, go to their online stores, and use specific apps, enormous amounts of data on specific consumers can be found. Retailers can use this data to assess each consumer, the brands it commonly associates with and the products they generally buy and use that information to understand how consumers behave. Not only will retailers be able to use such predictive data to increase sales, but they can also categorise each consumer demand according to the items in store, identify what kind of consumers would purchase them and carry out campaigns successfully. By understanding the consumer, the retailer can also make the consumer’s experience much more customised and relevant by featuring products the analytical tool predicted they would most likely buy. As these insights are based on analysing the buying pattern of a person, decision-makers can rely on this data-driven information to strategise future plans.
Find Out How Positive Their Interaction Was At Your Retail Store
Sometimes, you may find insights highlighting that a certain percentage of consumers visited the online store on the website or social media. However, the number of transactions carried out in that month may be lower. Predictive analytics allows retailers to see whether consumers had a good or bad experience to determine why those who visit their online store did not carry through with their purchase. Was it the layout of the website? Does it take too much time to load? Find out whether it was a problem with the platform or was it due to the unfriendly customer service provided or anything else. Essentially, knowing how each consumer experiences helps retailers improve their operations. This makes predictive analytics one of the most interactive tools a retailer can have, as it monitors consumers’ experiences in real-time.
Find Out How Successful A Marketing Campaign Is
Success in marketing campaigns can be a subjective concept for each retailer. Some would purely measure it from the number of sales received. Others would consider it a success based on how many new consumers it attracted. A predictive analytical tool distinguishes its results when generating detailed reports. Retails will be aware of how their marketing campaign did or did not succeed by considering the entire picture instead of focusing only on one aspect. The number of clicks to the website since the market campaign was released, the transactions carried out and finding the most famous products in a store that had the highest demand all helped the retail to plan out how to retain the new consumers to keep purchasing from them after the campaign is over. The end goal of any retailer should be consistency. Hence, with every new customer that successfully makes their order, retailers can innovatively use the analytics given to keep them coming.
Find Your Strongest Platform
Not everyone will have sales on all platforms consistently. More often than not, there is one main channel which a retailer gets more transactions from than from any other. Identifying this is vital so retailers can focus on maximising sales through that platform. While it is good to take action to ensure consumers engage with all mediums equally, a retailer should note that this is not necessary. The prices retailer may have to pay for being on a platform may be similar. Hence, identifying one or two platforms that have worked wonders for a retailer may also help them to invest smartly. For instance, removing themselves from a platform that does not generate much engagement is a good choice if enough profit is provided from one. This metric, moreover, gives data analytics the possibility of differentiating each consumer based on age. For instance, younger people today tend to purchase through social media marketplaces or directly from the website. Middle-aged or older consumers may look at the online retail store but visit it physically before making a transaction.
Know What To Store and When to Store
Predictive analytics is a critical tool that helps in inventory management. If a retailer’s most popular products are running out faster or their less popular items are in the store for much longer, these are both concerning for a retailer. There should be a balance between purchasing enough stock for their best sellers and not oversupplying themselves with less popular items. In other words, a retailer should never buy all items for its store in bulk. Making informed decisions on what to purchase more helps them invest in certain brands or items smartly and ensures no losses. Predictive analytics assesses the changing markets in the industry and considers how consumer behaviour change. Based on these indicators, the system will predict how much inventory is needed each season.
Unlock A Rage of Benefits in the Retail Sector With One Solution
You can enjoy various benefits by incorporating predictive analytics into your retail operations. In addition to shifting the focus to consumers to strategise ways to gain more sales, it also helps you reduce and eliminate unnecessary costs when it comes to inventory management or investing on numerous platforms with no revenue potential. It moreover allows you to streamline in-house operations in each of your departments, helping your retail business become efficient and grow in every way possible. Are you a futuristic retail business that wants to have more control? Either invest in a predictive analytics solution or a suite with predictive analytics as a tool to achieve your maximum potential.
