Navigating the complexities of crowd analytics technology can be a daunting task and aligning the granularity of the tool required to key ROI metrics to your business's goals can be a murky task. Sometimes, the answer requires a mutual development roadmap and multiple solutions. We've outlined some key questions to help brainstorm where to start...
Ask your team these questions...
1) What key problems are we trying to solve?
Going into your meeting with the tech team with specific KPI's and problems that you are trying to solve can help make sure the product is the right tool to help you address your specific needs. Need to know granular number of people within a building to better map guest experience journeys and allocate staffing? Or is a less accurate but more personal count via wifi device connections sufficient?
2) What assumptions do we currently have that might be adding risk to our operations?
Take a close look at what current operations standards might be based on "muddy" assumptions.
Let's consider a generic real life retail use case: from a general data source, a retail venue decides to use a general factor of 2.5 people per vehicle are visiting their site. They are able to accurately track how many cars are in a parking lot, but unable to determine which level or entrance they come in. After more granular analysis, we are able to determine that on Tuesdays the factor is 1.8 and on Saturdays the factor is 3.5. This in turn helps the retail venue build more informed staffing schedules as well as be proactive with tenant based leasing agreements.
Let's consider a real life sports use case: cash drops and staff breaks are scheduled to be at 10 minutes past the end of half time with the assumption that all crowds have cleared. However, following an installation of WaitTime's crowd analytics platform, we find that there are two types of crowd queueing profiles- standard fare queues (hot dogs, french fries) and specialty experience concessions (local food, craft beer and cocktails). At standard fare, the guests are very likely to drop out of line at the restart of the game. At specialty experience concessions, the queue remains and is active throughout the event. Here, we can adjust staffing schedules based on queueing styles to prevent disruption of operations and better inform future builds.
3) What are the physical parameters you are measuring?
Are you looking to measure a queue of 40 people all at once in a large space? Or are you measuring a occupancy of a small threshold? What ceiling heights do you have available? Some technologies are limited in accuracy to certain ceiling heights and angles.
4) What granularity of information are you looking for? And why?
If you are looking to determine the queue times and guest experience journey between transactional actions, generic information might not be enough. You need to know what level of precision is required to answer your questions- do you need an "exacto blade" or a "sledge hammer"? Are you looking for granular information because you need to know how many people are onsite and what they are doing or is it sufficient to know who is onsite but have there be false positives for multiple devices? If the answer is both, you might be looking at multiple solutions that need to work together.
5) Who needs access to the platform and how will it be actionable?
Determine the departments who need access to the data. Some departments may be using existing platforms that need to integrate. Info might need to be quickly available in real time as well as robustly available historically.
Questions to ask the technology solution team...
1) What existing platforms do you integrate with?
Typically crowd management technologies rely on infrastructure- whether that be a CCTV platform or a WiFi network. Understanding the nuances of how the crowd management platform integrates into your existing infrastructure can be critical to ensuring scalability. Here are a few to ask about:
Security Management Systems
Building Management Systems
2) How do you calculate accuracy?
Accuracy is based on the level of precision you need to solve the task. Determining how that accuracy is calculated is critical to understanding whether or not your tool performs well. We often find that accuracy is not comparable from technology to technology- for example a device based technology might read 100% of the devices within a network but each person may be carrying multiple devices. Another consideration is what the technology is comparing accuracy against. With camera based technology, being able to go back to crowd images is critical to setting a performance standard, but if there is no reference image than what is the measurement of success?
Want to learn more about how WaitTime calculates accuracy? Stay tuned for our accuracy blog.
3) Do you work well in an ecosystem of solutions?
As your team answered your internal questions, you may determine that your crowd solution requires a multi-faceted approach. Determining if technologies work well with others and have experience navigating within an ecosystem can help illuminate what products you should pair together. Ask for specific examples and use cases.
4) How do you strategize your Proof of Concepts?
Crowd analytics are often the result of measuring what was previously hidden, so a well scoped proof of concept tied to clear success criteria from all parties is critical. Ensuring you get a taste of all available products so you are well informed is also key to best plan post PoC scale.
5) How do you align with technology infrastructure plans?
Crowd management tools can be a significant investment and should be tied to ROI. Whether the system relies on onsite compute, digital displays, and/or cameras, aligning crowd management tools to upcoming technical refreshes can help optimize onsite technology. Due for an upcoming compute upgrade? Ask if the technology can run on a VM.