Automated Reporting

WithImage Recognition enabled “Click and Go” store audits, the tedious task of analyzing an ocean of data and insight generation is reduced to a mere click of the camera. Traditionally, CPG companies have relied on manual store audits to collect data on product placement, pricing, and promotions. This process is timeconsuming, expensive, and prone to errors. However, with image recognition powered by AI, companies can automate this process by analyzing images captured by in-store cameras or mobile devices.

AI-powered image recognition can quickly identify and extract data from images, such as product placement, shelf space, and pricing information. This data can then be analyzed and integrated into the company’s reporting systems, providing realtime insights into store performance, sales trends, and inventory levels.

By automating the reporting process, CPG companies can achieve significant cost savings, reduce errors, and improve data accuracy. The use of AI-powered image recognition can also help companies identify new market opportunities, optimize supply chain operations, and improve customer engagement.

For example, with image recognition powered by AI, companies can quickly identify outof-stock products and adjust their inventory levels to meet demand. They can also identify shelf placement and promotional display opportunities, which can increase product visibility and sales.

Trivia:

According to a study by HFS Research, companies that adopt RPA for reporting can achieve a 3050% reduction in manual effort and a 40-60% reduction in processing time. The same study also found that companies can achieve a 2-5 times ROI within the first year of implementing RPA.

Another study by PwC found that companies that use RPA for reporting can achieve a 25-50% reduction in labor costs, a 35-65% reduction in cycle time, and a 70-90% reduction in errors. The study also found that RPA can improve data accuracy and enable faster decision-making, leading to better business outcomes.

Better product placement:

Real-time retail execution insights can help CPG companies to understand how their products are being placed in stores and whether they are being positioned in high-traffic areas. This can help companies to optimize their product placement strategies to maximize visibility and drive sales.

Real-Time Execution Insights

Improvedcompliance:

Real-time retail execution insights can enable CPG companies to monitor compliance with planograms and promotional displays, ensuring that their products are being displayed in accordance with their brand standards. This can help to prevent out-ofstock situations and ensure that promotional displays are executed as planned.

Enhanced promotional effectiveness:

By monitoring the execution of promotional activities in real time, CPG companies can gain valuable insights into the effectiveness of their promotional campaigns. This can help companies to identify which promotions are driving the most sales and adjust their strategies accordingly.

Real-time retail execution insights can help CPG companies increase their revenue significantly. CPG companies can gain a better understanding of their retail execution performance, identify areas for improvement, and take proactive steps to optimize their sales strategies by leveraging real-time data and insights. Here are a few examples of how real-time retail execution insights can help CPG companies:

Increased product availability:

Real-time retail execution insights can help CPG companies to identify out-ofstock situations and take proactive steps to address them. This can help to ensure that their products are always available to customers, which can drive sales and increase revenue.

More effective sales strategies:

By leveraging realtime retail execution insights, CPG companies can gain a deeper understanding of their sales performance and identify areas for improvement. This can help companies to adjust their sales strategies and focus on the most effective activities to increase revenue.

Store audits can be automated and streamlined with the help of image recognition and AI, which quickly and efficiently collects data on in-store execution. This is made feasible by giving merchandisers the option to use mobile cameras on their devices to take a few images of the retail shelves. The recorded images are subsequently processed by the image recognition AI to produce crucial business and retail execution insights. With the aid of image recognition technology, audits may be digitized and standardized to obtain correct data more regularly, allowing the sales and marketing teams to act quickly.

Additionally, the data analyzed by the image recognition software can be used to monitor sales patterns. Retailers may increase the sales of priority SKUs by positioning them closer to the buyer’s eye level by drawing on the data on how well different brands and SKUs are selling.

Trivia:

A study by McKinsey & Company, companies that adopt AI for store audits can achieve a 20-30% reduction in manual effort and a 10-20% increase in productivity. The same study also found that companies can achieve a 2-3% increase in revenue growth through better data quality and analysis.