One of the biggest differences between small and large businesses is their ability to take risks. Small businesses, new or old, are often one bad decision away from failing while large businesses have the resources to recover.

Therefore, it is paramount that small businesses make profit consistently. AI based video analytics can help small business make those crucial decisions.

But first, what is video analytics? Well, video analytics gathers data by attaching a small hardware to existing CCTV systems. The software recognises shoppers as objects and tracks their journey throughout the store. The video footage is then gathered and processed using artificial intelligence and machine learning, before being presenting as aggregated data, providing deep insights into consumer behaviour and help make strategic decisions.

Here are some solutions video analytics can provide:

Customer Insights:

Small retailers don’t have the resources to perform much market research before creating products, branding, and marketing. This can often leave them guessing customer demand and trends in the market.

AI Video analytics can solve this problem by tracking consumers behaviour in-store. Modern video analytics tools can provide important insights such as footfall, dwell and path analysis, flow and heat maps etc, identifying behaviours, patterns, and trends overtime. The retailer can also narrow the data down to specific date, time, and zones, giving a very in-depth analysis on how consumers use the store and which products they like and dislike.

Let’s consider a new product. A retailers can use data from research and development, to marketing, to merchandising, and finally selling the product. Having an understanding of what consumers like means they can create better products that are in demand, staying ahead of competition. Moreover, knowing what makes consumers tick means retailers can target shoppers who are more likely to move to the purchasing stage with precise marketing. Such personalisation is the key to improved conversion while cutting costs at the same time.

Strategic Decisions:

A new store, or a small store, looking to improve sales doesn’t have a lot of time to make important business decisions. So, using real time data is the only way to make informed strategic decisions quickly and reduce waste.

For example, customers often leave stores without purchasing anything when the queues are too long or they are not receiving the right sales attention. This can be rectified with data which can predict footfall and therefore the number of staff required. With this simple solution, conversion rate is improved through customer satisfaction and staff morale is also high when operations run smoothly.

Furthermore, with many retail stores turning into mini fulfilment centres, maybe a small business needs to consider omnichannel sales. In this case, it is imperative that you know what your customers are using the online and offline stores for: are they using the brick-and-mortar store for product discovery, to interact with products, or to engaging with the brand? The most important data to measure is engagement, which many retailers currently don’t do in brick-and-mortar stores, slowing their growth in comparison to online stores.

Furthermore, once you’ve established the role of a store in the customers’ journey, you can decide how to market and merchandise on each sales channel. Data provides insights into what the demographics of that channel demands from your brand. Small retailers can even use data to test out new locations for expansions.


Video analytics, unlike other technology, is not limited to marketing. It is an all-in-one solution used to optimise sales, marketing, merchandising, and strategic decisions.

Data backed decisions have proven to yield higher results in the most cost-effective way. Firstly, it is highly accurate; in fact, the industry average being above 85%. It can provide in depth analysis which human eyes can miss or struggle to keep up with, eliminating any human errors. Unlike humans and manual recording, video analytics is fully automated and can gather large amounts of data while maintain high accuracy, zero lag, and minimum errors, saving resources in the long run.

Moreover, since the data is available in real time, quick decisions can be made to reduce costs and increase sales. For example, if it’s clear through data that shoppers are not engaging with a new product, the retailer can make it more visible in the store, promote it differently, or reduce the price.

Video analytics also helps accurately predict things like footfall and engagement with new products, helping management teams create staffing schedules and R&D teams create products in demand.

The most important thing for small retailers is that it isn’t costly to implement. The hardware is a one-off investment and the cameras do not necessarily have to be expensive, making video analytics accessible to businesses of small sized.

Ultimately, smaller retailers have no room for mistakes. The ROI for video analytics comes from optimising all areas of the business by making informed data backed decisions and improving operations. This will improve profits and minimise loss quicker than any other technology.

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