Retail Intelligence- How data is disrupting retail

Retail Intelligence is all set to drive the next wave of disruption in the retail industry by enabling retailers with capabilities to deeply analyze their data, create predictive models and extract incisive insights.

The biggest disruptor in retail is the availability of data. As retail went digital courtesy eCommerce, m-commerce, social commerce, and now connected retail, each customer touchpoint is producing huge amounts of data. The data, if harnessed well, can deliver deep insights into your customer’s mind, his motivations, influencers in his purchasing decision, his path to purchase, and more. It can also help retailers in building products, processes and providing experiences that delight customers. This provides an exciting opportunity as we look ahead.

The other factor at play now is the mainstreaming of data science technologies like AI, Machine Learning and Computer Vision, etc. Today we see wider adoption of these technologies in business.  And some fast strides in its innovative applications.


Retail data intelligence

Retail Analytics To Retail Intelligence

Data Science technologies can now help retailers to think beyond retail analytics to retail intelligence. These technologies can help retailers take a big leap by not only collecting and measuring data but also creating models that can learn on its own. AI and Machine learning can help retailers infer from unstructured data, images, and videos to provide crucial insights and intelligence. It can help them not only understand trends but also predict it with higher accuracy.

Read How We Analyzed Customer Sentiments From Amazon’s Product Reviews Click here

Let’s look at how Retail Intelligence is disrupting retail and creating new opportunities-

Micro Customer Segmentation

In traditional retail, customer segmentation is done by macro-segmentation. A retailer segments its customers based on age, gender, demography, etc. Retail data intelligence will empower retailers to adopt micro-segmentation by uncovering many layers of customer data to build a 360-degree buyer persona.

Smart Product Recommendation

Product recommendations will move beyond suggesting items based on purchase history and browsing behavior to context-aware recommendations. Machine Learning driven recommendation engines will self-learn from the data to extract deeper insights into what, why and how of a buyer’s needs.

Real-Time Pricing

Retail intelligence will enable retailers to adopt Predictive pricing wherein pricing will be set at store levels based on the prevailing market conditions. Various internal and external sales drivers like weather, time, demand fluctuations and inventory, etc., can be factored to adjust product prices in real-time.

Predictive Inventory Management

Data Intelligence will help retailers monitor the stock situation in real-time and predict inventory requirements by analyzing customer behavior, market trends, weather patterns, etc.

 AI and ML-driven Retail Intelligence offer enormous potential for retailers to build smart, context-aware processes, deliver compelling experiences, drive cost advantages, and empower the workforce.  

Data has already disrupted the way retailers do business. Data Intelligence will further drive it. Retailers who can optimally leverage their data will get a competitive edge.

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