Retailers

Realizing the Value of Granular Transaction Data
is More Important for Retailers than Ever Before

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The Amazon Effect and the Survival of the Fittest

The retail landscape is undergoing a dramatic transformation, signaling the start of the analytics arms race. The conventional weapons of the past (i.e., syndicated data, targeted loyalty mailings, etc.) are simply not going to be as effective in this new battle against Amazon and new, non-conventional brick-and-mortar formats.  For convenience, grocery, and discount, fresh food offerings and in-store experiences are becoming a core differentiator as the center store moves online.

On one side of the spectrum is Amazon, who is everywhere now with a combination of online and physical stores. They have led the rise of e-commerce, creating a disruptive and highly convenient shopping empire by engaging shoppers with personalized experiences like no other retailer can. AmazonFresh was launched to reshape the $800 billion food industry, and was designed to compete with grocers and mass merchants such as Walmart and Target.  With their massive loyal Prime customer base, Alexa, drones, Echo and now an employee-free concept store called AmazonGo, it’s nearly impossible to tell where they will move next? With the purchase of Whole Foods, Amazon’s largest acquisition ever, they delivered their most significant threat to the food industry. Amazon will deliver marketing relevancy and personalization integrated with sophisticated pricing and personalization algorithms.

On the other front, the emergence of dollar stores and hard discounters which rely on aggressive pricing strategies has created loyalty through value. These retailers are asking brands to deliver absolute net lowest cost, which is passed to consumers alongside a no-frills retail experiences.

To compete in this new world, it’s more important than ever that retailers adopt a data-first, analytics-centric approach across the board, from supply chain, to store, to online. Until retailers offer a seamless, convenient, and compelling shopping experiences, they will be behind.

SwiftIQ brings this new foundation to help retailers, brands and suppliers transform their retail execution through software that powers decision automation, retail localization and vendor collaboration to create efficiencies and great customer experiences in-store and online. Our Platform empowers retailers to maximize the value of their data through its Retail Execution Cloud and artificial intelligence applications, which process hundreds of billions of records of granular transaction, customer, and shipment data to drive revenue profitably.

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Become Data Driven!

Regain Control
Analytics are challenging and have a steep learning curve. SwiftIQ empowers all retail users (category managers, analysts, consumer insights, executives) to make smarter decisions using fact-based insights, not pure intuition
Store Optimization / Localization
Implement changes that are relevant and unique to the behaviors occurring at each store. With a few clicks, insights help you manage tactical decisions for assortment, food and promotion bundling, and other incremental revenue generating opportunities
Monetize Data
Seamlessly turn data into immediate insights, from supply chain to store to customer experiences, to realize the value of your most granular receipt-level transaction data. Build better automated, data-driven processes alongside your vendor and distributor partners by allowing them to upload their product, location and shipment data to enrich yours and discover new behavioral patterns
Drive Fresh Food
Capitalize on strong demand for fresh food by store, and with optimal promotional bundles. Unlike syndicated data, SwiftIQ provides insights from every receipt - not just UPC data
Enrich Data
SwiftIQ’s proactive data health monitoring bots track data duplicates, missing data, and anomalies to ensure high quality data is stored and analyzed. Bad data equals poor decisions

Translate Insights into Tactical Strategic Actions

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Category Management
  • Measurement: Measure the revenue lift, full store impact, and return on investment for displays, coupons, media and other initiatives
  • Merchandising: Optimize product distribution and assortment by evaluating revenue and basket size for any item, brand or attribute
  • Promotion Recommendations: Identify the strongest affinities between products by month, time of day and day of week to create most effective bundles.
  • Pricing Effectiveness: Measure price elasticity to implement the most effective pricing strategy
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Data Management
  • Data Unification: Capture, collect, and unify data from multiple sources, including in-store, shipment, space, ecommerce, and more
  • Improve Data Quality: Proactively identify and correct corrupt, irrelevant, and inaccurate data
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Best-In-Class Vendor Collaboration
  • Vendor Collaboration: improve business planning and decision-making with vendors by accessing the same data resources and analysis as they do, so you can limit bias and verify their findings in real-time.  Allow vendors to invest resources to help your buyers analyze complex patterns to optimize sales and profitability
  • Enrich Your Data: Share data repositories with suppliers, enabling them to enhance your product, location, and shipment data with their proprietary metadata
  • Hands Off Integration: SwiftIQ automates data sharing, vendor platforms, and training allowing you to focus on your day-to-day business needs.
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Shopper Behavior
  • Identify full chain basket behaviors, whether or not you have loyalty data
  • Identify the behaviors of your most valuable customers, including how much they spend, what and when they buy, and how frequently they visit your store
  • Benefit from the deepest customer insights to identify key shopper missions, to deliver more localized, personalized customer experiences
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New Item Launch
  • Easily manage new item launches by tracking distribution, basket, and daypart performance
  • Understand how new items affect the category and create substitution away from other items
  • Understand shopper behavior to optimize digital experiences
  • Set thresholds for removing poorly performing new items
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Labor Management
  • Identify how shoppers behave by hour of the day and day of the week to identify on-shelf availability risks when key items need to be restocked (like beer at 4pm on Fridays)
  • Manage staffing levels through advanced dayparts
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Lost Sales
  • Quantify lost revenue by zero exceptions and underperformance by store, category, item, and brand
  • Identify growth opportunities by location, time, category, or item
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Out-of-Stock Reduction
  • Diagnose key problem areas faster with real-time data
  • Improve direct-store-delivery (DSD) operations via seamless data sharing and alerts
  • Anticipate out of stocks by accessing sell-in/sell-out data and forecasts analytics

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