How Artificial Intelligence and Big Data Analytics is Helping Brands Understand their Consumers Better Through their Online and In-store Behavior?

Let's look at how AI (Artificial Intelligence) and data analytics have been helping the retailers to eliminate manual activities that are time taking and exhaustive.
How Artificial Intelligence and Big Data Analytics is Helping Brands Understand their Consumers Better Through their Online and In-store Behavior?

The advancement of technology in the retail industry has been bringing a huge surge of innovation over the last few years contributing to a new phase in the e-commerce revolution. We see that many retailers now adopting innovative technologies like IoT, AI, and Machine Learning which is transforming their retail operation, bridging the gap between digital and in-store experience and creating a new enhanced and seamless customer experience.

On the other hand, the retailers are also understanding the need for data analytics in retail as they are always on the lookout on the measures that can help them understand their customers, evaluate their customers’ purchase journey, to have an overall view of how well their campaigns are working, seasons where their target audience are the most active and the most important of all how much engaged their customers are.

Let’s look at how AI (Artificial Intelligence) and data analytics have been helping the retailers to eliminate manual activities that are time taking and exhaustive. Here are a few areas where retailers have adopted Ai to anticipate customer orders, make smarter decisions with better accuracy and real-time forecasting which in turn has contributed to optimizing their supply chain, create impactful promotion strategies and improve their customer experience.

  1.  Self-checkout counters: Many retailers are now offering self-checkout counters option to their customers where they can just scan and pay for their items to let their customers exit the store without any need to queue or wait at the checkout thus improving their buying experience.
  2. Personalized recommendation engines: Using AI and Machine Learning for personalized recommendations helps retailers to understand the customers taste and preferences across all touchpoints via their browser history, page clicks, social interactions, location, etc.
  3. Optimized price and loyalty programs: Retailers are now introducing AI in price, promotion, and markdown optimization involves tailoring prices to customers in a way that they view them as attractive, and fair for the products they want to purchase the most and also giving them the ease to join their loyalty programs removing the tradition store-branded credit cards.
  4. Automated Inventory Management: Automating inventory management lets the companies keep a track of total purchase orders, order status, shipment updates making it easier for the customers to buy, receive and return their orders thus, reducing  the manual interference
  5. Smart AI Chatbots: The retail bots can handle the most complex of questions, analyze consumer behavioral patterns and enhance the shopping experience by providing personalized alerts and offers.

Let’s now understand the need for data analytics so that how businesses can stay informed better, gain meaningful insights and overcome challenges by making data-driven decisions.

  1. Knowing your customers’ touchpoints: Consumer data holds major importance for retailers reason being they want to be aware of what their consumers are looking out for which means understanding consumer-related to most searched items, items added to the cart, abandoned cart items, etc.
  2. Effective marketing campaigns: The retailers have to understand their consumer behavior patterns so that they can run profitable marketing campaigns. This gives them data on open rate, click-through rates and times when the consumers will engage with brands and more.
  3. Personalized Offers: Offering personalized deals to the right customer at the right time. Analytics helps businesses track down transaction histories and consumer preferences. It indicates what the customer wants, and allows retailers to offer similar choices at affordable rates, closing sales most effectively.
  4. Store Optimization: Retailers want to understand how a  customer visits the stores and how long he stays in which section and making further sales easier. With the help of analytics, it is also possible to stock up sufficient inventories based on consumer demands and market trends.Customer Satisfaction: By using analytics, retailers are able to offer the customer exactly what he wants and engage him most effectively. This, in turn, helps in building a positive brand image, gaining trust and developing long-lasting retail relationships.
  5. Customer Satisfaction: By using analytics, retailers are able to offer the customer exactly what he wants and engage him most effectively. This, in turn, helps in building a positive brand image, gaining trust and developing long-lasting retail relationships.

Consumers of today have access to a wider breadth of information based on which they make an informed decision. The need for adopting towards automated retail helps e-commerce powerhouses want to generate revenue and ROI such that it can bridge the gap between in-store and online shopping in order to provide the consumers with the seamless and frictionless customer experience and meet their demands.

The article has been penned down by Shalaka Tayade, Business Success Manager, Retail Insights

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