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Find out how retail analytics can guide the customer journey.

Retail Omnichannel Analytics - Make decisions to satisfy customers who can shop anywhere, anytime. Apply analytics to every step of the customer journey to improve operations – and customer experiences.

Mobile devices, social networking sites and other technologies have prompted major shifts in customer behaviour – so you need to be equally empowered. Just as customers can quickly research products and compare prices through multiple channels, you can respond with relevant offers, competitive prices and the right merchandise.

  • Turn big data into insight, across all channels. By managing and analyzing data from a wide range of sources, you'll gain a more complete understanding of who your customers are, and what they're looking for

  • Tailor retail efforts to accommodate specific areas. Omnichannel trade area analytics helps you understand customers in defined communities and across multiple channels. As a result, your pricing, sales and marketing are always on target down to the store level

  • Optimize merchandising and store operations. The more you know what customers are looking for, the better you can adjust inventory and make precise decisions about what to stock and when. As operations become more efficient, your sales margins increase

Right merchandise, right stores. Right when the customer is ready to buy.

As customer preferences evolve and options for where – and how – they shop expand, you need a better understanding of who your customers are in order to stay competitive.

  • Merchandise assortment optimization. Efficiently rationalize assortments by becoming more customer-centric and less product-centric, using analytics and advanced clustering to understand a customer's path to purchase – and identify missed opportunities

  • Merchandise financial planning. Predict customer demand by channel, and strategically plan key initiatives. Identify opportunities to improve performance, boost customer satisfaction and increase profitability

  • Merchandise location planning. Understand the true omni-channel demand and use automated processes to predict sales by location, optimize inventory and support e-commerce full-fillment initiatives

  • Size/pack optimization. Increase margin potential by understanding historical sales as well as the true size demand by forecasting quantities down to the store/size level. Recommend pack configurations to meet supply chain constraints and distribution costs

  • Revenue optimization. Gain incremental margin by optimizing profitable price strategies over product life cycle. Use analytics to understand competitor pricing, shape demand and meet financial goals

Know exactly what customers want. And make sure they get it.

The new reality of retail is that customers are mobile and have more control over the purchasing process – which means retailers must rethink how to use customer data and insights from analytics to improve customer engagement.

  • Connect with customers in real time. Engage and respond to customer needs instantly with contextual listening and advanced data integration, enhancing the in-store and online shopping experience

  • Sell more. Understand what actions drive transactions and customer value. Know which message or offer is most relevant to your customer – as well as the best way to deliver the message. Personalize interactions to drive the best performance, and integrate the experience across all customer touch-points

  • Spend less. With an omni-channel approach, you can spend less than your competitors on customer acquisition. Improve the outcome of your marketing interactions by using predictive modelling as the basis for comprehensive integrated marketing

#Analytics #ArtificialIntelligence