MatchView is an innovative platform designed to revolutionize retail experimentation. It allows retailers to easily conduct and track experiments related to product placements, in-store space planning, marketing campaigns, and new product launches. The platform provides real-time results tracking and insights into the effectiveness of interventions and tests.

Key Features

Test Drivers and Drainers Identify factors that positively or negatively impact retail performance

• Analyze various elements affecting store performance
• Pinpoint key drivers of success and areas for improvement

ROI Calculator Evaluate the financial impact of retail experiments

• Calculate return on investment for different interventions
• Make data-driven decisions based on projected outcomes

Optimal Store Selection Choose the most suitable stores for conducting experiments

• Utilize sophisticated algorithms to identify ideal test locations
• Ensure representative sample selection for accurate results

Market Basket Analyzer Gain insights into customer purchasing patterns

• Examine product associations and cross-selling opportunities
• Optimize product placement and promotional strategies

Pre- and Post-What-If Simulator Predict and analyze experiment outcomes

• Simulate various scenarios before implementation
• Compare actual results with predictions for improved decision-making

Benefits

Improved Accuracy Enhance the precision of marketing campaign assessments

• Select appropriate control stores for experiments
• Obtain more reliable results for informed decision-making

Time Efficiency Significantly reduce campaign turnaround time

• Streamline the experimentation process
• Implement and analyze tests more quickly

Data-Driven Decision Making Base strategies on concrete evidence and insights

• Allocate marketing budget to demonstrably successful campaigns
• Optimize resource allocation based on experimental results

Enhanced Customer Experience Deliver more impactful customer interactions

• Test and refine various strategies to identify the most effective approaches
• Continuously improve in-store experiences based on experimental data