Overview
Businesses often organise various marketing events over time to boost sales. However, marketing managers face challenges in assessing the effectiveness of individual campaigns and identifying those that resonate with their target customers. Typically, they must gather data from multiple sources and rely on guesswork to estimate campaign effectiveness. FootfallCam's Marketing ROI Tracker app simplifies this process by providing marketing managers with a streamlined and scientific way to quantify the ROI of each campaign, requiring minimal effort.
FootfallCam AI
Typically, marketing managers would have visibility into the spendings, footfall, and sales data of each event from multiple sources.
Leveraging Big Data and market intelligence from AI models, FootfallCam AI intelligently learn from historical campaigns to provide data prediction and helps you to quantify the lift rate.
Continuously learning from the AI model, intelligently assess and recommend the effectiveness of an event and predict likely outcomes for upcoming events.
Features
Compare the return on investment (ROI) of various events, identify patterns, and quantify the relationships between demographic groups, dwell time, and spending in relation to event investments.
By analysing footfall, sales, and other metrics across stores, the app provides insights into marketing effectiveness for different store types, enabling targeted campaigns for each.
By targeting the right audience with relevant marketing messages, Marketing Director can increase their return on investment (ROI) and reduce marketing costs by avoiding wasted efforts on audiences that are unlikely to convert.
How Does the App Work?
Configure a list of marketing events with their respective parameters such as event dates, evaluation periods, campaign types, metrics to be measured and other relevant attributes for evaluation purpose.
Marketing managers can determine the effectiveness of their events by comparing pre- and post-event traffic and sales data patterns obtained by measuring shopper traffic patterns and combining them with sales data.
Analysing the measured responses of ongoing and past marketing events enables marketing managers to identify common response patterns and correlations between different attributes.
With built-in predictive analytics and machine learning algorithms, a marketing manager can simulate the effectiveness of previous campaigns to upcoming events by forecasting potential outcomes based on historical data.
Case Studies
See all Case StudiesA Fashion Apparel Store in United Kingdom
