Brand loyalty can be elusive in today’s consumer-driven mass market where savvy shoppers surf and tweet to find the best deals. Discover how Big Data 2.0 helps you drive profit by delivering the right products to the right customers at the right time.
- Customer Experience Management
- Omni Channel Campaign Management
- Budgeting Planning Forecasting
- Business Intelligence
- Big Data & Analytics
- Talent Management & Learning Management Solutions
EXAMPLES OF USE CASES
Retail is highly volatile business, particularly during economic recessions. This makes tracking industry trends all the more important to both large and small retailers.
What do customers at Store #283 really want? It’s likely to be at least slightly different than those heading to Store #59.
Inventory is often the retail KPI that determines success. Getting the balance just right – not too much, not too little – is retail nirvana. How do you create this crystal ball? It relies on aggregating the right data and then visualizing it in a way that lets you make informed decisions.
Back of the store – or the front? A store’s layout drives competitive differentiation and sales. So how can you determine the best approach? Use data to turn layout decisions from art to science.
See how fast and easy it is to gain product placement insight
Retail leaders understand that product placement is key. Maximizing selling potential for every square inch of aisle and shelf space is an absolute necessity. Tracking the effectiveness of these placements as products change and demographic tastes shift is equally important in order to retain customer interest.
Market Basket Analysis and Pricing Optimization
Historical, inventory, pricing, and transaction data
1M+ rows of additional pricing data added daily
Retailers and e-tailers have more data available to them than ever before. From historical transactions, to current inventory, pricing, and more, the value in these datasets increase exponentially when combined. Find out how this leading retailer used Datameer to combine datasets to come up with competitive pricing, determine where to target ads, and more.
In retail, historical inventory, pricing and transaction data are spread across multiple devices and sources. Business users need to pull together this information to understand seasonality of products, come up with competitive pricing, determine which platforms to support so that their online users would have optimal performance, and where to target ads. With Datameer, these business users could do their analysis in 3 days instead of 12 weeks with their traditional tools and heavy IT involvement.
Know the customer, know the products, conquer the marketplace
Predict consumer shopping patterns with increasing precision
Personalize products and offers for micro to nano-segments
Rapidly create and test micro-campaigns to increase response
Make tradeoffs to optimize assortment, price, promotion, and inventory
Dynamically set pricing to increase profits
Expand demand signaling to include market and other outside influences
Optimize multi-channel transactions and communications
Take market basket analysis to the store level
Combine merchandising optimization with deep customer analytics
Operationalize loyalty analysis to inform channel and customer preference
Turn digital interactions into in-store insight
Optimize store operations and product placements