The Art of Selling Video Analytics for Perimeter Protection

Selling Video Analytics

When selling video analytics, what type of product should you promote? Are there any hidden sales costs and are you leaving any value on the table?

Video Analytics has been around for a while.  Over the years the algorithms have continued to evolve, from simple pixel motion detection to today’s much more advanced deep learning algorithms.  With the advent of lower cost hardware and advanced learning neural networks, video analytics is poised to make some great strides in the coming years in many different markets, including perimeter security.

The sale and install of video analytics can be challenging, as it’s sometimes unclear if it’s a product, a feature, or even a service.   So, what does that mean for the security dealer and integrator when you are building your sales model around video analytics?   How do you engage with your customer correctly when looking to provide them this capability?  How do you ensure there is enough revenue to warrant the sale, and more importantly, how do you avoid unforeseen costs?

Let’s take a look at some items to consider when developing your plan to market and sell video analytics to your customers, including what type to choose, potential hidden costs, as well as, and some scenarios where you may be leaving value on the table.

What type of Video Analytics to sell?

Video analytics come in many shapes and sizes, but for now let’s look at three differentiating factors to consider when choosing a type to promote:

Embedded versus Stand Alone

Embedded video analytics are those that reside on the camera itself, or possibly on another hardware device, versus stand-alone, which are essentially software programs that can be deployed on commercial off-the-shelf servers or mini computers.

Embedded video analytics are very convenient, as they are already included in the camera.  No extra wires or power source required, and they may be tightly integrated with the camera or video management system (VMS).  However, they can reduce your sensor choices, and may increase the cost of upgrading existing systems, if it requires all new hardware to gain functionality.   Additionally, the algorithms embedded in the camera are limited due to processor and storage constraints.

Stand Alone video analytics can be more expensive than embedded versions, involving dedicated hardware, wiring and the cost of the software itself.  However, they tend to result in higher performing algorithms, additional software features and flexibility integrating with other sensors and/or existing security systems.

Rule-Based versus AI

Whether to choose rules based versus deep learning video analytics comes down to the complexity of the scene and when you want to devote your man power to the installation.

Rules-based video analytics requires you to program the system for exactly what and where you want to detect.  The more detailed you can be, the better.  On the positive, these algorithms work the minute they are turned on.  The downside is they detect as the rule is written, so if they are creating false alarms due to a difficult scenario (severe lighting, shadows, etc.), they will continue to do so until the rule is modified, or the scenario is changed.

Selling video Analytics - Deep Learning

Deep Learning video analytics, also referred to as A.I or artificial intelligence, uses neural networks that must be “trained” to understand what does and does not constitute an alarm condition.

On the other side of the fence, pun intended, is deep learning video analytics. This type of algorithm may also be referred to as A.I or artificial intelligence and consists of a neural network that is “trained” to understand what you are and are not interested in.  The software will come with a training set of data, but there will be a break-in period where a human in the loop must let the software know when it has done well, and when it is alarming on something that is not of interest.  Out of the box, deep learning will not likely pass a stringent acceptance test, however, given the time and proper feedback, the system will learn to be more accurate and become adept at avoiding false alarms related to difficult scenarios.

So, the choice really comes down to whether you want to support the customer early in the process, stay engaged while you teach a system, or leave it to the customer to actually train the deep learning algorithms.  Other factors that may drive your decision might include your customer’s patience in allowing the system time to learn and the number of difficult scenarios or problem camera views at the site location.

Cloud versus On Site Server

Selling cloud-based versus on-site video analytics can be a difficult choice for the integrator / dealer. On-site video analytics is the traditional sale of hardware, software and installation directly at the customer location.  Although there is opportunity for future hardware and software upgrades, this is likely a one and done opportunity.  It is, however, the bread and butter of the security market and the sales model with which most integrators are most comfortable.

Cloud-based analytics involve little to no hardware at the customer’s site beyond the cameras themselves, with most of the heavy lifting hardware and software being located remotely “in the cloud.”  That means there is not a significant amount of installation labor or product to sell at a mark-up.  Most hardware or software upgrades happen in the cloud, unbeknownst to the end user.  As such, the initial business case of these installs may not look very attractive from a resale aspect.   However, often times, you as the integrator / dealer can receive a small commission from the monthly cloud-based service charged for this service.  This can add an interesting facet to your revenue model helping to smooth out seasonal dips.  Even small commission amounts can really add up over time, and in most cases, this is a purely passive income stream, requiring no additional work on your part.

Considering the Cost versus Performance Curve

Once you’ve selected the type of video analytics you’d like to sell, you must remember that all video analytics are not created equal.  They come in a range of cost and performance levels to suit the variety of security needs in the market place.  It is important to understand the type of video analytics you are selling and the customer to which you are selling them.  If you provide a low cost, low performance algorithm to customer with critical perimeter needs, you will likely have a costly disconnect.  The same goes for a customer that needs very basic detection, but is sold an advanced learning algorithm that requires a lengthy training cycle.  If you don’t select the correct performance / cost point, you will end up with an unhappy customer and a long list of warranty actions to try and align their expectations with the product they purchased.

The Cost of Selling “Free” Video Analytics

Today, there are many camera providers that embed the video analytics algorithm within the camera and include them for “free” with the cost of the camera.  The idea is of course, to sell more cameras.  On the surface, this seems like a great deal.  If the customer needs a new camera anyway, video analytics can be included at no additional charge, providing them more value for the same cost.

Selling FREE video analytics

Providing the customer with added value is always a good thing, however, there are a couple things to consider before committing to the free video analytics model.

Providing the customer with added value is always a good thing, however, there are a couple things to consider before committing to the free model.  A top consideration is the difference between roadmaps of cameras and video analytics.  One of the top roadmap features for cameras is decreased size and decreased cost.  This is great for the consumer, but leaves little margin for dealers and integrators.  Similarly, as the camera drops in price, the perceived value of the video analytics also drops in price.  By setting a perceived value of $0, it may then prove difficult to upsell advanced or improved intelligent video features in the future.

The video analytics roadmap is a slightly different trajectory.   Cheaper hardware and faster CPUs are enabling a wide range of capabilities which can be applied to real time and recorded video.  The consideration that must be made is whether to sell more cameras with “free” video analytics at a lower margin or sell video analytics as a product with its own margin.

Don’t Forget Your Current Install Base

An often-overlooked segment for video analytics is the retrofit market.  Today’s video analytics come with SDKs and APIs that allow them to easily integrate with existing NVRs and both analog and IP cameras.  As such, the ability to add increased automation and detection may be as simple as adding an edge device or video analytics server.  That means that every customer in your database is now potentially a new lead to update their system with video analytics.

In addition to the sale itself, regaining the business of an existing customer is much less expensive than capturing the attention of a new customer.  You already have the customer contact, they have already done business with you and you may already be communicating of a regular basis for on-going support items.  Approaching them with the value of adding video analytics to their system is a low-cost sales action.

Another significant cost saving for retrofitting video analytics over a new install is that it does not require huge capital expenditures such as trenching, running wires and installing networks.   Adding video analytics to an entire site may only require the addition of a single server in the equipment room.

Despite the higher return on investment associated with retrofit opportunities, upselling video analytics to an existing install base is often an overlooked opportunity.

Planning for Camera Placement, Views and Lighting

The sales and installation of video analytics always includes assessment of camera placement, camera views, camera mission and lighting.  Let me repeat that.  The sales and installation of video analytics always includes assessment of camera placement, camera views, camera mission and lighting.  A key item to your business case is whether you accounted for this cost.  You can choose to absorb the cost or include it as part of the installation charge to the customer.  Another option is to engage the video analytics supplier to help.  The developers of these analytics can quickly identify problem cameras or difficult scenes and propose workarounds.  In most cases, there is no charge for this guidance, as they understand that great video analytics can’t always correct poor camera placement.  Either way, not accounting for this action can quickly cut into your margins.

Video Analytics at Night with Thermal

When selling video analytics, not including assessment of camera placement, camera views, camera mission and lighting may cost you.

Missing Out on Software Maintenance

Software maintenance is a business model used in many markets, whereby a recurring fee is charged for ongoing support and often access to new features.  Everyday examples include Adobe Creative Suite, Windows 365, among others.  Software maintenance has been part of the security market for many years, with a vast list of software companies, including video management providers and video analytic developers, providing such programs.   Software maintenance is also a major source of overlooked income for the security integrator.

When it comes to video analytics, software maintenance is actually a nice benefit, in that it is basically a continuous software upgrade program.  These days, video analytics systems don’t require ongoing “service,” so what does a developer of intelligent video algorithms do if they aren’t providing “service?”  They create new and better algorithms for detecting and deterring bad guys.  In most cases, many of these new features are included as part of the software maintenance program.  Getting these new features is typically as easy as updating the system with the latest software.  Most times this is done via a remote connection, with no need to even set foot on the property.  As such, it’s a very affordable way the end user to have the latest and greatest video technology available.

However, this isn’t even the best part of the software maintenance fee.  The best part, and most overlooked aspect from a business model perspective, is that this software maintenance is encouraged to be resold through the integrator.  So, as an integrator you have the right to apply your standard mark up to the service …. every year.   You should now be asking yourself, what is your role in the transaction besides discussing the value of the cost to your end user?  Exactly!  In most cases, this is just a paper and scheduling transaction for the integrator or dealer.  Unfortunately, many integrators forgo the reselling of software maintenance as it falls out of their traditional definition of an installation or product upgrade.

Leveraging the Marketing Buzz

People like new and interesting things, this is true of your Facebook friends and directors of security.  Having video analytics in your quiver of products provides you a wealth of interesting features to talk about with your client.  This includes retina scans, face searches, scenario replays, automatic drone dispatch, risk scenarios from social media images and various other video detection and analysis features. Cameras, VMS systems, beam breaks are all valuable products, but they do lack the excitement of the current roadmaps for video analytics and AI-Based security.

Even if your customer may not have the money to purchase this type of capability, and perhaps many of the technology is yet to be fully vetted, the end user still wants to know what’s out there and how it might be beneficial to them, now or in the future.  Even if it isn’t the highest performer in your line sheet, actively promoting video analytics is a nice sales tool to although you to be in front of your customer with new capabilities and continue the conversation about their needs.

Ignoring the Trend

Search the internet for “artificial intelligence,” “deep learning” or “intelligent video” and look at the number of results.  These technologies are improving by leaps and bounds and they are here to stay.   Those without this insight may try to ignore video analytics completely, claiming it is too complicated or perhaps not robust enough.

If we can trust a computer to control a driverless car, how long until a computer independently monitors and automates your security system?  Video Analytics are providing the security market with accurate detection, event insight,affordability and response automation.  All indications are that this trend will continue well into the future.   Not taking the time to understand how to add these capabilities to your offerings today, will likely result in the need to play catch up in the near future.

Video Analytics Driverless Car

If driverless cars can become a reality through the use of intelligent video and A.I., how long until security systems are completely automated using this same technology?

Conclusion

Video Analytics is an exciting technology that is going to continue to grow, not only in the security market, but in transportation, entertainment, home automation and many others.  The key for integrators and dealers is understanding where to gain value, where to plan for costs and to know how selling this capability aligns with long-term goals.

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