Merchandising and Customer Service can set stores apart from online retail, helping to increase loyalty and sales. In-Store Analytics provides merchandising and operations teams with reliable customer traffic insights to improve operations, customer engagement and sales.
As part of the solution, Bosch IP panoramic cameras are installed to provide high visibility of the retail floor. The cameras use on-board Intelligent Video Analytics to create position data of shoppers’ movements. This data is then sent direct to the Cloud where it is further processed without video streams ever leaving the retailer’s premise, thus maintaining shopper’s privacy. Unlike many systems that need on-site PCs to pre-process the video streams, limiting their performance to a few cameras per site, Bosch’s solution easily scales to cover even the largest retail stores with a high camera count and large multi-store chains.
In the Cloud, position data is mined into performance results and visualizations that are shared with the retailer through customized and user-friendly web interfaces for merchandisers and operations managers.
Optimized merchandising decisions based on real-time customer behavior data
For merchandisers, In-Store Analytics delivers shopper behavior insights to enable more informed decisions. Sales of retail products often depend on their placement within the store and at what point shoppers see the items on their journey through the retail floor. In-Store Analytics provides merchandisers with store traffic visualization tools, such as a flow analysis, to determine if shoppers are moving through the store in the way that they intended. The solution shows where shoppers walk, stop and dwell, and provides performance metrics such as engagement times and rates, based on the actual number and behavior of shoppers at a display. This helps merchandisers evaluate the performance of each display in the store, providing them the information they need to increase customer engagement with products, which can lead to increased sales and revenue. The toolset for merchandisers includes:
Traffic Visualizations to increase placement profitability:
- Understanding which store layouts entice customer engagement in focus areas
- Identifying hot traffic zones to help guide product and promotion placement
- Uncovering cold traffic zones as reasons for low product sales
Engagement funnel to maximize display performance:
- Monitoring how product displays perform across all the stores
- Finding out which concepts most successfully engage passers-by
- Uncovering low-performers which need optimization
Flow Analysis to boost first impressions:
- Determining if shoppers navigate how the retailer intended and really see the most important displays first
- Understanding how different store layout types impact customer flows
- Uncovering flow-blocks as reasons for low product sales
Amplified customer service based on real-time customer traffic data
Limited staff can translate into long lines, abandoned shopping carts, and a lack of assistance on the floor for customer questions. Hence, planning the right level of staffing is essential to achieving service excellence – but this can be difficult without the proper tools and information. In-Store Analytics provides operations managers with insights into department and store level traffic. They understand how many shoppers are entering the store and at what days and times during the week. With these insights, they can ensure sufficient staff is onsite to serve shoppers during peak times. Traffic data also enables retailers to track customer service quality over time. The toolset for operations managers includes:
Store Traffic Meter to drive traffic into the stores and maximize service performance:
- Comparing traffic levels across stores and departments
- Spotting areas with declining traffic in need of service or marketing measures
- Measuring whether the taken actions have the impact needed to revert the trend
- Pulling traffic data into the resource management system to create precise staff schedules that keep customer service ratios on point, even at peak times
- Comparing traffic with sales transaction data to calculate conversion rates
- Identifying low conversion areas that need staff count adjustments or additional training
Queue Meter to reduce waiting times:
- Keeping checkout areas and service kiosks under control at all times
- Quickly identifying problem stores and diagnosing problem origins with detailed metrics
- Consulting store managers with actionable insights on how to improve the checkout experience
A scalable and reliable system setup
In-Store Analytics has been developed with three qualities in mind - privacy, data accuracy and scalability - to offer retailers a reliable solution on which they can trustfully base their business decisions.
Protecting shoppers’ privacy: The position data of In-Store Analytics is anonymous and sent to the cloud independent of the actual video streams, protecting the privacy of shoppers in the stores. The video streams are located locally where they can be used for loss prevention purposes. Recording solutions like Bosch Video Management system allow for smart forensic searches of the video recordings. The cameras can be painted over in the ceiling colour to seamlessly blend in.
Reliable data: Retailers will benefit from actionable insights from the solution, as the shopper data delivered by In-Store Analytics has a high accuracy rate. This is due to the superior reliability of the Intelligent Video Analytics that comes standard on Bosch FLEXIDOME IP panoramic 7000 MP cameras, as well as the advanced cloud-based processing algorithms that filter the shopper position data according to individual store environments. As a result, the solution achieves a minimum of 95% data accuracy.
Easily covering large store sizes: The position data generation on-board each camera allows distributed data processing, scaling across the largest store surfaces, so the retailers can analyse and optimize merchandising and service performance in any corner of their store.
Performance is not limited by the processing power of an onsite PC, a common hindrance to the success of other retail analytics solutions.
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