It is hidden in plain sight – the advances in video analytics have crept up and are now poised to make a huge impact on the world we live in. The technology has so much power and can do so much, it’s almost as if the biggest obstacle is knowing where to start.
Like many tech advances, the budget holders are the key-holders to making the first critical steps and so, this blog has the aim of helping the process of use case identification as well as prioritization of the elements needed to create a compelling business case.
The good news about investing in video analytics, is that it’s perfectly feasible that existing hardware is ‘good enough’ for immediate wins that will provide more than enough CFO satisfaction to make further investment requests fall on ears that remember the wins and not the failures.

The stakeholders who need to be part of any conversation involving video analytics tend to include: ‘Business Process Owners’ as well as Analytics for the use cases in question, the people who own the existing camera infrastructure, Enterprise Architects and Loss Prevention.

Ok, so what use cases are ‘hot’ in 2022?

If you are in retail, chances are that the topic of ‘self-checkout’ is near top of mind. Some of the more successful implementations of self-checkout leverage Video analytics as a critical element of the deployment ‘playbook’. The two most important factors in successfully rolling out self-checkout technology on a large scale include utilization rate and customer satisfaction. When things go wrong and one (or both) of these elements are lacking, how do we learn and improve? This topic is worthy of a blog on its own, but simply put, video analytics allows stakeholders to collect and evaluate crucial behavioral insights enabling root cause analysis and iterative A/B testing. You have at your fingertips the information to understand how physical positioning, impact of store layout, and customer/associate interaction impact the utilization rates and user satisfaction. Having these key insights in the early days of a self-checkout roll-out allows for lessons to be learned and applied before we scale, making each deployment more successful than the last!

Video Analytics is a new and extremely powerful tool for evaluating and improving ‘customer experience’. Understanding when customers are abandoning queues or counters / service points out of frustration and not engaging specific in-store elements in a meaningful manner is extremely powerful information. It is now possible to measure and benchmark strategies for queue management, first associate/customer contact, and product interaction on a country / global scale. Like the self-checkout use case, building a ‘playbook’ with empirical data and A/B testing is key. All the metrics that companies normally use for evaluating the performance of their e-commerce platforms can now be applied to physical retail on a global scale. For businesses that operate thousands of locations across several states, countries or continents, video analytics is a ‘must-have’ for consistent quality of service and successful implementation of continuous improvement initiatives.

According to Ricardo Badalone, CEO at C2RO; “We have seen that many retail customers are gaining confidence in video analytics, AI and are now realizing that they have a treasure trove of incredibly valuable in-store analytics readily accessible through their existing infrastructure. It is fascinating to see the universal transition from skepticism to enthusiasm, as they realize the power of this new technology and the impact it can have on helping them solve daily operational problems on a global scale.”

The elephant in the room

We do need to call out the elephant in the room – you won’t maximize your camera tech investment by needing to have a human watch over and make the learning or action assessment – it’s just not going to happen. The key point is that the ‘value adds’ that are made available from the tech requires a degree of commitment, trust and belief and most crucially, the commitment to learn, evolve and change how we do business today based on the output from video analytics. Without this, there is a high degree of risk that the budget investment was wasted and should have been spent elsewhere. And why I have your attention, there is a second elephant sitting in the same room – video analytics makes people uncomfortable – the trust aspect as well as the ‘what could it mean for my job’ need clear recognition before you spend the money.

According to Mike Jude, Ph.D., research director for IDC's Video Surveillance and Vision Applications research practice, the video surveillance analytics market is an exciting one that is rapidly adopting new technologies. Jude notes: "Video surveillance analytics is an early adopter of AI capabilities and is demonstrating that AI and other cutting-edge technologies can be applied to deliver better security and valuable business intelligence. Yet the market to deliver these capabilities is still evolving, and there are many players with excellent solutions. It is up to the business technology decision maker to determine what the intended uses of such technology will be and select vendors that can help address those use cases."

Further reading
Justifying Video Surveillance Technology through ROI | IDC Blog
So, what is the compelling reason to act now?
The need to ‘steal a march’ on your competitors has arguably never been more front of mind for retail executives. And whilst that feels like a blindingly obvious statement, the tech industry provides opportunities that are compelling. Video analytics doesn’t require physical disruption to operations in the most part, and so ‘getting started’ is more straightforward than many business and technical initiatives.
Forrester wrote about the topic of the importance of integrating data and analytics recently and it’s worth pointing out that the incorporation of video analytics into your landscape is essential if you are to get the value from your investment.
If you are looking for some further reading on data integration basics, I recommend this paper from a series on fundamentals on integration and this paper on predictive analytics.

Call to action

The getting started aspects of incorporating video analytics into your business begins with getting your core stakeholders aligned on the core aims I have identified in this blog.
The next step conversations that typically fall from the themes highlighted in this blog often include; how to show the value of investment / how to manage risk / what is it in for me etc – bottom line is that being prepared for the journey is critical and your leadership team showing a transformation vision is a critical element.