Online is an amazingly profitable channel for retailers. Its convenience, no need for spacing, enlarged customer pool and supply on demand boosts retailers profitability by huge amounts. Yet it comes with some issues  that decrease the profitability like “showrooming” and affects brick-and-mortar store efficiency negatively. To deal with this, brick-and-mortar businesses can employ visitor analytics technology and boost performance by analyzing in-store customer experience.

In the most basic sense, the increase in efficiency for the store can be linked with increase in sales. However, the increase in sales alone cannot be considered as an increase in productivity. There are other factors to be considered like optimal store layout with minimum cost, and staff effectiveness.

How to use visitor analytics to increase the store efficiency?

In order to increase store productivity, brands benefit from the opportunities offered by technology. This is where image processing systems and software come into play. The operating principle of these systems offered in the context of business intelligence is actually quite simple. In many cases it is possible to integrate the technology with the existing store surveillance cameras without additional hardware costs. Visitor analytics system consists of two basic stages.

1)Data collection

Cameras track customers throughout the store and collect various data on their store journey like most visited categories, time spent in each and customer’s route for exit.

2)Dashboard Presenting

Collected data are visualized on store dashboards with graphs, charts and heat maps to help managers understand their store performance in the most suitable way.

3)Udentify – AI Analysis

In addition to mainstream visitor analytic technologies, Udentify also offers an AI-based recommendations system which analyzes store and category performance and offers insights on optimization.

The data help managers in the retail sector make concrete and observable results. With the systems used, increasing the productivity by visitor analytics in the store actually offers many solutions. These solutions that increase productivity can be listed as follows.

Store Layout Optimization

System finds inefficient categories with low visitor attraction and sales numbers. Then informs managers to help them optimize categorical squaremeter efficiency.

Udentify AI-based recommendation system compares store and categorical squaremeter performances with other stores and gives acctionable recommendations.

CASE STUDY: A multinational retail firm adapted Udentify to its stores and worked specifically on a category, aiming an increase in visitor attraction. By acting according to Udentify’s recommendations, firm increased category’s visitor attraction by 52%.

Pricing and campaign efficiency

Looking for anomalies and outliers in the store, system figures out how campaigns affected categorical performance.

Udentify AI-based recommendation system analyzes these anomalies and gives insights on most suitable pricing for the category.

CASE STUDY: Udentify investigated the campaign performance of one of its clients and found out that a secondary campaign would be unnecessary. Firm increased its conversion rate by 11% and average sales volume by 28%.

HR Improvement

System tracks in-store staff movement, and finds out about how staff interacted with customer and how they affected turnover

Thanks to Udentify’s notification system, store managers are infomed instantly about crowd intensites so they can prevent any loss caused by inefficient staff allocation.

CASE STUDY: Lack of data caused a global retail firm to adapt static working hour plan for its employees. Collaborating with Udentify, firm got real-time notification system and employee number estimation service, and reduced its in-store employee costs per store up to 22%.

Inventory and Product Range Optimization

Visitor attraction, sales number and staff performance are analyzed to find product performances which are used to achieve effetive SKU tracking.

Udentify AI-based recommendation digs deeper by analyzing productivty of all stores and A/B testing outputs to reach best product range and SKU tracking.

CASE STUDY: One of Udentify’s clients wanted to evaluate categorical conversion throughout stores. With using Udentify, firm cut 29 SKU’s and got rid of unnecessary costs and eventually increased categorical conversion rate up to 12% and sales up to 18%.

When all these solutions are sought together, a significant increase in efficiency can be achieved in physical stores. The most important factor for the increase in efficiency is the consumption behavior of customers in stores. Accurate analysis of these behaviors will help retail stores increase their productivity in the above-mentioned areas.

If you seek any further information about computer vision-based visitor analytics and how Udentify may help you, see Udentify website.

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