Retail

Identify potential churn risk and target at-risk customers

Analyze customer data from different systems and identify patterns that may indicate a higher risk of churn. This could include factors such as decreased frequency of purchases, negative feedback or reviews, or a lack of engagement with loyalty programs. With this information, we automatically target at-risk customers with personalized offers or incentives to try and […]

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Identify opportunities for upselling and cross-selling

Use RPA and AI to analyze customer data and purchase history which includes data on the products and services purchased in the past, their demographics and behavioral characteristics. Using this data, intelligent automation can identify trends and patterns that can be used to predict which products or services customers are most likely to be interested

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Targeted promotions based on feedback and reviews

Use intelligent automation to process customer feedback and reviews, and then use this information to create targeted promotions for those customers. This can be done using RPA to extract data from customer review platforms, and using AI to analyze this data and identify trends and areas for improvement. This helps retail businesses quickly and accurately

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Evaluate competitive costs when a product is available from multiple suppliers

Use automated screen capture and record to track and scrape pricing and other relevant information from supplier websites for products available from multiple suppliers. This data can then be fed to advanced analytic tools that use AI to analyze the data and determine the best supplier for a given product based on cost and other

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