Real-time analytics in Retail: why it matters

Mar 27, 2020Solutions

Real-time analytics in Retail: why it matters

Mar 27, 2020Solutions

A new era of Customer Experience:
Real-time Personalization

 

In the era of the hyper-connected consumer, providing a personalized experience is the key to success: enterprises that fail to cater to specific customer needs lose out and clients soon switch loyalties to their competitors. That’s why companies need to leverage analytics at the most opportune time and place.

Increase sales and increase loyalty thanks to the personalization of the Customer Experience
Retail industry players can particularly benefit from analytics as it enables them to communicate more effectively with their customers in an era where clients are more informed and respond better to customized marketing efforts. Moreover, streaming analytics provides organizations with useful insights on customer behavior, which helps them to refine their marketing strategies. Here some data:

+ 20% Customers who received personalized suggestions within 1 hour of purchase spent an average of 20% more in the past 90 days

49% Nearly half of shoppers said they had purchased a product in the past three months that they initially did not intend to buy after a brand sent them a personalized recommendation

44% Three-quarters of consumers say they became regular buyers after receiving personalized advice from a brand

Building capacity for real-time data collection, integration & analysis
To achieve hyper-personalization, you need to have access to a large amount of data from different sources, be able to correlate these disparate data streams and make predictions to gain useful insights. But most of the enterprises are struggling to handle the enormity of data and the variety of data channels: actually, integration still remains the hardest challenge, besides the operationalization of machine learning models and the development of artificial intelligence algorithms, key points for immediate interaction with clients.

Use technology to understand your consumer. At the most granular level possible
Artificial Intelligence can serve as a boon for the retail industry that gathers and possesses customer data. AI can derive meaningful conclusions from a massive amount of data and help companies to give a personal touch to customers’ experiences, like providing error-free and personalized suggestions. 
This allows marketing experts to:

  • Use insights and recommendations on industry trends, consumer behavior and signs of intent
  • Experiment with new personalized experiences: test messages through the funnel
  • Ensure that content and messages reach the right customer at the right time in the right format and on the right channel

How retailers can improve their data management and analysis skills

  • Send personalized recommendations and offers at the most appropriate time
  • Use Artificial Intelligence to predict customer behavior
  • Segment customers with Artificial Intelligence algorithms
  • Identify customers to track their experiences through all touchpoints
  • Create a centralized data source for a complete customer view
  • Develop loyalty systems that recognize the individual customer

The Radicalbit RNA platform for DataOps
Radicalbit RNA Platform allows you to capture and manage the data belonging to the various company information systems to analyze them in an integrated way. Salesforce CRM, Warehouse Data, Google Analytics, Marketing, meteorological data … are just some examples of types of data that can be integrated, manipulated and analyzed by a single, scalable and flexible platform.

Send personalized automatic messages based on the context and customer behavior
Thanks to our RNA platform it’s possbile to develop a complete solution to send messages in real-time, suggest relevant products, based on customers’ tastes or offer personalized discounts when they are identified in the shop through the loyalty card.

How?

  • Artificial intelligence to achieve advanced segmentation based on behavior
  • Recommendation system to suggest products selected on the basis of interests and behaviors
  • Real-time data analysis to act at the exact moment the customer is identified

 

Improve Customer intelligence with real-time analytics

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