By Pradeep Nemadi, Microsoft Practice Head – Digital Business Services, Happiest Minds Technologies
Fueling retail customer experience is all about strategies and technologies that retailers use to improve the overall experience for their customers. Retailers can create engaging and enjoyable shopping experiences, which can lead to improve customer loyalty, increase sales and stand out with other brands.
Today we have lot of cloud technologies and services to improve the retail customer experience. There are many ways that retailers can significantly improve personalization and the overall instore experience, as post Covid in store experience is more challenging with customers wanting to spend less time in any store and complete their shopping list.
We recommend different approaches to improve the overall customer experience:
Personalization
Personalizing the retail customer experience involves tailoring interactions with customers to meet their individual needs and preferences. Here are some steps to follow to achieve this:
Collect customer data: Collect as much information as possible about your customers. This could include data from previous purchases, browsing history, social media activity, feedback, and surveys. Use this data to gain insights into customer behavior, preferences, and needs. The source for customer data collection includes websites, mobile apps, point of sales system, and ones can use any cloud provider to collect customer data.
Analyze customer data: Analyze the data you have collected to identify patterns, trends, and customer segments. This will help you create targeted marketing campaigns, design personalized product recommendations, and develop personalized shopping experiences.
Further, by using cloud tools, retail businesses can analyze customer data to gain insights into customer behavior, preferences, and needs. They can then use these insights to build personalized marketing campaigns, improve product recommendations, and provide a better customer experience.
Some of the recommended tools include:
Amazon Redshift: Amazon Redshift is a cloud-based data warehousing service that allows retailers to store and analyze large amounts of customer data. With Redshift, retailers can run complex queries on their customer data, perform data modeling and visualization, and build machine learning models to help personalize the customer experience.
Microsoft Azure Machine Learning: Microsoft Azure Machine Learning is a cloud-based service that provides retailers with tools for building and deploying machine learning models. Retailers can use Azure Machine Learning to analyze customer data, build personalized product recommendations, and optimize pricing and promotions.
Google BigQuery: Google BigQuery is a cloud-based data warehousing service that allows retailers to store and analyze large amounts of customer data. With BigQuery, retailers can run complex queries on their customer data, perform data modeling and visualization, and build machine learning models to help personalize the customer experience.
Provide personalized recommendations
Personalized recommendations and product suggestions provide better experiences to customer. For example, if a customer has purchased a specific product, you can recommend complementary products or accessories that they might be interested in. Utilize personalization technology such as AI, machine learning, and predictive analytics to improve the customer experience. There are several cloud tools available that can help retail businesses provide personalized recommendations to their customers. Here are a few examples:
Microsoft Azure Personalizer: Microsoft Azure Personalizer is a cloud-based service that provides retailers with tools for building personalized recommendation models. With Personalizer, retailers can analyze customer data and build machine learning models to provide personalized product recommendations, promotions, and search results.
Google Recommendations AI: Google Recommendations AI is a cloud-based machine learning service that allows retailers to build personalized recommendation models for their customers. With Recommendations AI, retailers can analyze customer data and build machine learning models to provide personalized product recommendations, promotions, and search results.
Amazon Personalize: Amazon Personalize is a cloud-based machine learning service that allows retailers to build personalized recommendation models for their customers. With Personalize, retailers can analyze customer data and build machine learning models to provide personalized product recommendations, promotions, and search results.
Salesforce Einstein Recommendations: Salesforce Einstein Recommendations is a cloud-based service that provides retailers with tools for building personalized recommendation models. With Einstein Recommendations, retailers can analyze customer data and build machine learning models to provide personalized product recommendations, promotions, and search results.
Offer personalized promotions and discounts: Use customer data to create personalized promotions and discounts for customers. For example, if a customer frequently purchases a particular product, you can offer them a discount on their next purchase of that product. Leveraging cloud services, retailers can create targeted marketing campaigns that offer personalized promotions and discounts to their customers. This can help increase customer engagement and loyalty, as well as drive sales and revenue.
Here are some examples of cloud services offered by Azure, AWS, and GCP that can be used to create and deliver personalized promotions and discounts to retail customers:
By leveraging these cloud services, retailers can create targeted marketing campaigns that offer personalized promotions and discounts to their customers. This can help increase customer engagement and loyalty, as well as drive sales and revenue. By using machine learning, automation, and event-driven workflows, retailers can create personalized experiences that meet the unique needs and preferences of their customers.
In-store experience
Retailers can create an engaging in-store experience by offering interactive displays, demonstrations, and events. This can help customers connect with the brand and its products in a more meaningful way.
• Real-time inventory management – Use IoT Hub to monitor inventory levels and trigger automatic reorders or alerts when stocks get low. Real-time inventory management system will ensure that products are always in stock and readily available for customers.
• In-store analytics – Collect data from in-store sensors, cameras, and other devices to gain insights into customer behavior, such as which products they are interested in, how long they stay in certain areas of the store, and which routes they take. Use this data to optimize store layout, product placement, and marketing campaigns.
• Mobile payments – Mobile payment system that allows customers to pay for their purchases using their smartphones. This can help reduce wait times at checkout, and create a more convenient and streamlined experience for customers.
• Virtual assistants – Virtual assistants can assist customers in-store with product information, directions, and other queries. This can help reduce the workload of in-store staff and improve the overall customer experience.
• Self-Checkout – Self-checkout systems can provide customers with a fast and convenient checkout experience, allowing them to pay for their purchases quickly and easily using their mobile devices.
In conclusion, fueling retail customer experience requires retailers to adopt strategies and technologies that enhance the overall shopping journey. By leveraging cloud technologies and services, retailers can personalize the customer experience, provide personalized recommendations, and create engaging in-store experiences.
By offering personalized promotions and discounts based on customer data, retailers can drive customer engagement, loyalty, and sales. Additionally, retailers can enhance the in-store experience by utilizing real-time inventory management, in-store analytics, mobile payments, virtual assistants, and self-checkout systems. Through these strategies and technologies, retailers can differentiate themselves, increase customer loyalty, and ultimately thrive in a competitive retail landscape.
