FAQ Index:
- What does Artificial Intelligence (AI) add to the platform?
- How much data is needed to use the AI features?
- Can 12CU also support our customers internationally?
- Can we also offer the 12CU platform white-labeled?
- What insights do you provide as standard, and is there an additional cost for extra insights?
- What does a typical implementation of the 12CU occupancy intelligence platform include?
- How are the 12CU services priced?
- What is the main difference between occupancy measurement using WiFi and sensors?
- How accurate are WiFi solutions compared to sensors?
- What about the installation and operational costs of WiFi versus sensors?
- How scalable are WiFi and sensor solutions?
- What are the privacy and GDPR implications of using WiFi versus sensors?
- What data can be obtained from WiFi-based solutions compared to sensors?
- How do WiFi and sensor solutions respond to changes in space layout?
- How quickly can WiFi and sensor solutions be implemented?
- How do WiFi and sensor solutions affect network performance?
- What are the potential drawbacks of WiFi versus sensor solutions?
- How does combining WiFi and sensor data deepen the breadth and depth of data collection?
- How does combining WiFi and sensors improve data accuracy and reliability?
- Can WiFi be combined with sensors on some strategic locations on all floors of buildings?
- Why is scalability improved by adding WiFi to sensors?
- How does WiFi enrich sensor data?
What does Artificial Intelligence (AI) add to the platform?
AI enhances the platform by analyzing data to identify trends, such as significant increases or decreases, that might not be immediately obvious. The AI processes large amounts of information quickly, spotting patterns and changes that could be important. Once these trends are identified, AI generates a detailed report that includes visual charts to help you easily understand the data. Alongside the charts, the report provides a clear, written explanation of the trends, helping users grasp what is happening and why it might be important. This makes it easier for users to make informed decisions based on the insights provided by the AI.
How much data is needed to use the AI features?
You only need one month of data to start using the AI trend analysis report. After just a few weeks, the AI will begin to show trends in building usage and group behavior. This means that you don’t have to wait years to see valuable insights. The AI quickly identifies patterns and changes, helping you make better decisions based on real-time data. Whether it’s optimizing space, improving efficiency, or understanding how groups interact within the building, the AI provides clear and actionable insights soon after data collection begins. This early access to trends allows you to respond faster and adjust strategies as needed, making your building management more effective and responsive from the start.
Can 12CU also support our customers internationally?
Yes, we offer comprehensive international support for our platform. The dashboard menus are fully available in English, making it accessible and easy to navigate for users worldwide. Our dedicated support team is not only fluent in English but also trained to provide exceptional assistance across different time zones, ensuring that help is always available when needed. We are committed to delivering a seamless experience for all our international customers, with prompt responses and solutions tailored to meet the specific needs of businesses operating globally.
Can we also offer the 12CU platform white-labeled?
Yes, we can provide both the dashboard and AI trend reports as fully customizable white-label solutions. This means that you can rebrand the platform with your own logo, colors, and other brand elements to seamlessly integrate with your existing services. Our white-label offering allows you to present a unified experience to your clients, enhancing your brand presence while leveraging the powerful features of the 12CU platform. Whether you need customizations in the user interface or specific adjustments in the reports, we are flexible in meeting your needs to ensure it aligns perfectly with your business objectives.
What insights do you provide as standard, and is there an additional cost for extra insights?
The AI trend analysis report provides standard occupancy rate comparisons between different months or years, with the ability to drill down into specific buildings, floors, or zones, which are customizable sections of floors. In the dashboard, you can choose from various occupancy rate views, including Compare Graph, Daily Group History, Campus Headcount, Floor Heatmap, Retention, and Density and Spread. The dashboard also allows you to submit feature requests. If these feature requests are useful for multiple users, they will be added to the roadmap. We do not create custom reports.
What does a typical implementation of the 12CU occupancy intelligence platform include?
A 12CU occupancy intelligence platform can be implemented in just one week. The implementation involves setting up a VPN connection between the API of the location engine in the Wi-Fi network and the 12CU cloud platform. Additional information, such as building capacity or zone layout, can be added afterward if needed.
How are the 12CU services priced?
The 12CU services are primarily priced as an annual fee for a core module, which is essential for every implementation. Additionally, there is an annual fee per building, regardless of its size, whether large or small. If customers wish to divide a floor into zones, we charge a one-time fee per building for this setup. Understanding that our partners may want to maintain uniform pricing for their customers, we are flexible and can adapt to the partner’s pricing model.
What is the main difference between occupancy measurement using WiFi and sensors?
WiFi-based solutions utilize the existing WiFi network to detect the presence of devices like smartphones and laptops, providing an overview of space utilization over larger areas. Sensor-based solutions, such as optical sensors, offer highly detailed data at a micro level, for example, regarding the occupancy of specific desks or rooms. Sensors detect physical presence regardless of whether someone is connected to the network.
How accurate are WiFi solutions compared to sensors?
WiFi solutions can offer high accuracy, with location determination within 1 meter. By deduplicating multiple devices from the same user, double counting is avoided. However, sensors, such as optical sensors, provide a more precise measurement on an individual level.
What about the installation and operational costs of WiFi versus sensors?
WiFi-based solutions are generally more cost-effective because they use the existing WiFi infrastructure of a building without the need for additional hardware. In contrast, sensors often require new installations, structural adjustments, maintenance, and sometimes battery replacement, which significantly increases initial and operational costs.
How scalable are WiFi and sensor solutions?
WiFi solutions are highly scalable as they can be easily expanded using existing networks, regardless of the size of the building or campus. Sensor solutions often require the installation of additional sensors as coverage needs to be expanded, which can complicate scalability.
What are the privacy and GDPR implications of using WiFi versus sensors?
Both technologies can be GDPR-compliant, but WiFi solutions have an advantage by allowing data anonymization and encryption directly at the point of collection. Sensors, such as optical sensors, can also be configured to collect only anonymous data, such as using low-resolution images that are immediately destroyed after analysis.
What data can be obtained from WiFi-based solutions compared to sensors?
WiFi-based systems can provide insights into movement patterns, such as which spaces are used by which groups, how often, and for how long. On the other hand, sensors can provide detailed insights into the occupancy of specific workspaces and the nature of the occupancy (active vs. passive). This makes sensors useful for detailed analyses of specific spaces.
How do WiFi and sensor solutions respond to changes in space layout?
WiFi solutions are more flexible because they do not require physical repositioning of equipment when spaces are reconfigured; a software update is sufficient. Sensors often need to be relocated and recalibrated to remain effective after a change in the space layout.
How quickly can these systems be implemented?
WiFi solutions can be implemented quickly, often within a week, because they utilize existing infrastructure. Sensor solutions can take more time due to the need for hardware installation and testing.
How do WiFi and sensor solutions affect network performance?
WiFi-based solutions have minimal impact on network performance because they use a very small portion of the available bandwidth. Sensor solutions operate independently of the network and do not affect network performance, but they do require regular maintenance and monitoring.
What are the potential drawbacks of WiFi versus sensor solutions?
A potential drawback of WiFi-based solutions is their reliance on the presence and connection of devices, which can lead to missing data if a device is not connected. Sensors offer higher accuracy in smaller spaces, but the total cost of ownership (TCO) is much higher, and sensors are less flexible in terms of installation and scalability.
How does combining WiFi and sensor data deepen the breadth and depth of data collection?
By combining WiFi and sensors, a platform can provide both broad (macro level) and deep (micro level) insights into space utilization. WiFi provides an overarching view of movement and occupancy patterns in large areas, while sensors deliver detailed data on specific spaces and individual workstations. This combination enables organizations to make both strategic and operational decisions based on a full spectrum of data.
How does combining WiFi and sensors improve data accuracy and reliability?
Combining WiFi and sensor solutions enhances the accuracy of the collected data. WiFi can detect large-scale trends and patterns, while sensors ensure that individual details, such as the exact occupancy of a workstation, are accurately recorded. This reduces the chance of errors like double counting users and ensures more reliable analyses.
Can WiFi be combined with sensors on some strategic locations on all floors of buildings?
A combined platform can optimally use existing infrastructures. WiFi coverage is often already present on every floor of the buildings, and by combining this with strategically placed sensors, an organization can gain in-depth insights without requiring large-scale installations. This makes the system cost-effective and flexibly adaptable to future needs.
Why is scalability improved by adding WiFi to sensors?
The combination of WiFi and sensors offers flexibility in both scale and detail. WiFi can be used for large-scale monitoring across entire buildings or campuses, while sensors accurately monitor specific spaces or even individual workstations. This allows an organization to decide where detailed data collection is necessary and where a broader overview suffices.
How does WiFi enrich sensor data?
When WiFi and sensor data are combined, a more complete picture of space usage emerges, leading to richer analyses and more actionable insights. For example, by using WiFi data to determine which spaces are most used and sensor data to understand how these spaces are specifically utilized, organizations can optimize their space layout, reduce energy consumption, and improve the work environment.