Competitive companies know that it’s all about the customer these days. At Symphony Retail Ai, we’ve been focused on the customer for years. We take customer-centricity to a new level to help retailers and CPG manufacturers gain a holistic real-time view of their customers — cross-retailer, cross-channel — to fuel an AI-enabled application of deep, relevant customer insights.

A first-of-its-kind interactive customer data intelligence system that uses hundreds of shopper attributes for insights beyond just purchasing behavior.

Some have breadth, some of have depth. We have both.

We’ve been working with point-of-sale (PoS) data for years. And while other firms may have a few hundred thousand households of data to analyze, we analyze over 70 million US households across 43 states weekly. This alone is a very deep and rich resource, but we take it a step further. We add 360-degree enrichment to this data — what we call Customer 360 AI. We combine it with federated panel data to get a full view of the customer, not simply PoS insights. Now, we have a massive data pool which our AI-enabled solutions with machine learning can access to uncover customer trends and anomalies. Our customers can search for hundreds of customer attributes in their data and, in doing this, better serve their customers. We make work easier for retailers and CPGs by:

  • Ingesting a comprehensive set of data elements collected across multiple sources
  • Powering Symphony Retail Ai applications and providing analytical and trending capabilities
  • Providing an interactive visual interface for retailers and CPG manufacturers to quickly respond to changing market conditions

You choose the view for what you want to do

Like everything we do at Symphony Retail Ai, we make things work for the way you work. And we make things easy to use. With access to our extensive data, you can choose what you want to see. A single view of the customer? A single view of a product, or pricing or promotions? No problem. We use intelligence to bring the data to life, to apply it to the customer, to ultimately help you make the shopping experience more personal, more differentiated.

  • What makes Symphony Retail Ai unique when it comes to FMCG data?
    There are several reasons that Symphony Retail Ai stands out in the FMCG industry:
    • We have deep industry knowledge. We currently serve over 300 retailers globally, 70 wholesalers, and more than 550 international manufacturers
    • We have a longitudinal data collection from years of work with retailers and CPG manufacturers. We analyze over 70 million US households of data each month (other companies may have data on a few hundred thousand households).
    • We build on this rich information by adding in federated data that give richer insights into customers, so it’s not just simply about analyzing purchase behavior but understanding as much as possible about the customer to create promotions and products that resonate with their lifestyle.
    • We can analyze information in real time, having moved away from just batch processing (where data is sent to be analyzed and may take several hours to be processed) to real-time processing, given users deep insights when they need it, so they can act on it and make a difference for the business.
    • Everything we build is made to help our customers do their work better, faster, and grow through extensive insights never before made available to them.
  • How does CINDE fit into the Customer 360 AI picture?
    CINDE, short for Conversational Insights and Decision Engine, is our digital analytic assistant. Think of her as the Alexa of FMCG retail for merchandising, marketing and supply chain. Using pervasive insights based on AI and machine learning, she understands retail business trends specific to grocery and hard goods. She continually learns, and proactively alerts users to critical issues that need attention. CINDE is our visualization of Customer 360 AI.

    CINDE provides answers to highly detailed questions through use of deep analytics, data mining and immersive visualization into stores at department, planogram, and product level. Because of her contextual intelligence, CINDE serves that information using the most appropriate visualizations to give holistic insights for actions that can or should be taken. She provides alerts and notifications of trends and events, using predictive intelligence to suggest the next best actions, enabling retailers to seize opportunities. Users can speak to CINDE in conversational English, just as they would a human analyst.

  • What is the difference between reactive analytics and prescriptive/predictive analytics?
    Most analytical firms work with reactive analytics. That is, a user wants to know what happened around a specific event in business, for example, a seasonal promotion. To gain insight into this promotion, the user asks a team of analysts to process a variety of data elements to gain insight into trends and anomalies from the promotion. The process of analyzing this data can often takes weeks, is highly worker intensive (often involving large team of analysts), is highly manual (wasting time across personnel who could be focused on higher value activities) and is often error prone.

    Prescriptive analytics is different. Using artificial intelligence and machine learning, it analyzes deeply within the data to find trends and anomalies, but it doesn’t stop there. Based on what it finds, it can suggest what a user might find if he were to take a different approach to a business problem. This type of analytics can suggest best next actions for a user, not simply produce a report that must be analyzed and sorted yet again by the user. In addition, AI-enabled data analytics can learn and improve in what it produces over time, just like a human.
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