Beehive for retail

Maximize workforce utilization. Meet customer service levels.
Stem fraud and loss

A picture of a monitor

Do it all with one solution

Retail margins are typically very tight, making opportunities to lift staff productivity, increase customer service levels and cut losses through theft or fraud extremely valuable.

Beehive gathers rich data at the register and across the retail space, combining video and Point of Sale (PoS) data to identify multiple opportunities to raise profitability. From self checkout loss and internal fraud at the register to schedule rebalancing that meets customer service levels while reducing register idle time and increasing staff productivity, Beehive can transform operations across your network.

Beehive applies machine learning and advanced analytics to physical world activity data

Our highly secure edge deployment platform allows remote management across hundreds of sites - solving multiple issues with no additional hardware installs.

Workforce & customer service optimization

Finding opportunities to increase staff productivity and keep customer service levels on target can make a huge difference to profitability.

Beehive gathers and analyzes rich data at the register area, providing clear insights to  confidently enable evidence-based schedule and roster changes.

  • Benchmark and manage customer service level targets 
  • Highlight inadequate register staffing or register idle time and improve lane / register management & scheduling
  • Arrest customer service level falls (and associated falling conversion-rates and basket-sizes)
  • Reduce register idle time and improve staff productivity

Loss prevention at the register

Even though CCTV is collecting hours of footage every day, how can your loss prevention teams review it all to identify fraud incidents?

Beehive combines automated video analysis with Point of Sale (PoS) data and AI smarts to surface high risk transactions, such as refunds and discounts, for review. This unique capability allows the system to isolate:

  • Refunds or discounts with no customer
  • Missing supervisors for large refunds and discounts
  • Sweethearting (i.e. actions that look like a product being scanned, but which do not result in a PoS entry)

During review, the full transaction details are presented with video of the register at the time of the transaction, greatly simplifying identification of fraud and theft. Once theft is identified, other transactions by the staff member can be checked to gather evidence and establish longer term behavior patterns.

Loss prevention at self checkout

Customer theft is a big contributor to shrinkage, making effective action on self-checkout discrepancies a key focus for many retailers.

Beehive compares a feed from your Point of Sale (PoS) system with vision from an overhead camera above the scanner to identify issues at the checkout, such as:

  • Scanning a product that doesn’t result in a corresponding PoS record
  • Swapping barcodes to scan a cheaper product

Discrepancies are prioritized by differences in price and forwarded immediately as mobile app alerts to the supervisor, who can confirm the product was correctly identified and intervene with full knowledge of the substituted or entirely un-scanned item.

Beehive automatically learns to detect your products including new products and changes to packaging. 

Covert scheduling for loss prevention

Maximize your loss prevention efforts with intelligent covert scheduling based on expected high risk or repeat offender visit times and locations.

Deciding which retail stores loss prevention coverts should visit each day is often left to chance or based on recent thefts. Until recently, deciding how to position your coverts to be in stores where repeat offenders visit has been near-impossible without massive investment in covert teams and, typically, staff without loss prevention training can’t approach these customers. 

Beehive is changing this paradigm, providing scheduling of covert teams based on intelligent review of patterns and behavior - approximately tripling the times coverts are in store when a high risk or repeat offender arrives.

Sales & marketing optimization

Go beyond standard customer arrival and conversion rate analytics and get a deeper understanding of sales and marketing effects, customer retention and loyalty. 

Retailers typically assess strengths and weaknesses in their sales and marketing mix using customer arrival and conversion rate analytics. But with attacks on physical retailer revenue from online alternatives, it’s becoming ever more vital to focus on customer retention and loyalty in addition to growth.

Beehive benchmarks sales and marketing performance such as customer arrivals, conversion rates and yield. But it also adds insight from rich data gathering at the register to help understand the impacts of customer service issues or sub-optimal staff scheduling.

  • Gain a clear view of network, regional and store key sales performance
  • Identify and resolve issues with stores that are underperforming
  • Quantify the performance of all sales and marketing efforts

Cleaning & public liability risk optimization

Public liability insurance claims and cleaning are the two largest shopping center operating expenses.

To mitigate the risk of slip and fall and to meet legislation, cleaning is typically undertaken on time based rotations. It’s not time, however, that increases the likelihood of spillage and resulting slips or falls - it’s space usage.

Beehive monitors shopping center usage patterns to create cleaning schedules that reflect the reality of space usage, redistributing cleaning efforts to when and where they’re needed and significantly reducing injuries and the resulting claims.

Customer theft and staff fraud at the register are the biggest contributors to shrinkage, making a considerable dent in retailer margins. In 2019, shrink was estimated to have cost retailers an eye watering 1.62% of revenue. In Australia the cost was $2.5B and, in the USA, $61B.
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