MAKE SMART DECISIONS
CASE STUDY: IoT for Retail
Within retail we are seeing IoT become common place and help drive operational costs, improve prediction of operational issues and direct resources to address immediate problems.
“Increase Same Store YoY Revenue”
A Clear Intelligence Case Study
A retailer wants to maximize revenue at each store by better positioning inventory and store personnel to reduce out-of-stocks.
The Problem: Retail stores are continually battling against online commerce, but continue to play a role in local economies for convenience items tha,t when optimized, are extremely profitable. How does a store maximize local sales based on date beyond its 4 walls?
The Solution: Leverage localized data that includes weather, major local events, social media trends and people foot traffic predictions to optimize the existing portfolio of products to meet the demands created by the combination of these factors. Outdoor events inked to hotter weather create demand for inventory items such as drinks, hats, and sun cream. Same outdoor event with rain predictions would suggest increase in stock for umbrellas and rain macs for example. Local foot traffic analysis would allow the store to better plan customer to associate ratios to increase customer conversion.
Implementation of the solution is just the beginning. We remain engaged with your team in a collaborative effort to drive adoption and scale to extract the full value of the solution. With continuous improvement frameworks in place, we will ensure the solution continually evolves and drives increased value as the business changes. This is where the full ROI and competitive disruption is realized and, more importantly, maintained.