Not only do R-Com offer the technology to make Smart Cities and Buildings a reality, but we offer the analytics service to make sense of all the data too. We help you to understand and manage the data collected from our IoT devices to be able to make smarter, data-driven decisions within your business.
Big Data Analytics
What can be done to increase the business potential of each person entering a store?
How to make efficient use of the huge amount of data available and vast know-how, achieving a 30% rise in sales in just a few months.
Optimising for just three parameters can dramatically increase sales:
- Raise conversion ratio
- Raise the average transaction value
- Raise the average number of items per transaction
Continue the improvement over time
How to Achieve these?
Retail Excellence Aims Combine technology and expertise in retail management with the five stages model.
The 5 stages to achieve retail excellence
Data Collection, Analysis, Planning, retail adjustments – adjusting a customised tool boxActBack to Data, Collection to monitor, measure and make more improvements to the key performance indicators.
The Retail Toolbox
There are various retail analytics tools which can be used to increase sales and optimise the retail process.
These include the following:
Average shopping or dwell time – The average shopping time reflects the overall level of service in the store. The better the service, the longer people stay and the more likely they are to make a purchase.
Measuring and improving average shopping time results in an increase in the number of people buying something. The number of items they by the amount of money that they spend
Queue Monitoring Nobody likes queuing. Too long a queue annoys customers, drives them away and makes it less likely that they will return another day.
Measuring queues – knowing exactly how many people are in the queue at the moment, the average queuing time, how many people leave the queue before reaching the front and so on – allows retailers take steps to remedy any problems found. The tool can also predict when queues are likely to form and enable retailers to take pre-emptive action.
Tool: Conversion Rate – Integrating people counts with the point-of-sale system allows staff to see the current conversion rate of the store – down to 5-minute intervals. They can immediately take action to improve performance.
Big Data – The footfall counts and other information can be integrated into big data sets, sending real-time data to “brokers”. The brokers process the data and make it available to authorised end-users via cloud reporting.