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Revolutionising retail: the power of CCTV and video analytics

Retailers continue to use video surveillance for more than just security - according to key trends that have emerged from the NRF 2023 Retail Show. 

Yes, the shift towards AI-based solutions is driven by significant challenges - the National Retail Federation’s 2022 Retail Security Survey highlighted that inventory loss is a nearly $100 billion problem annually. But “Retaillance” (Retail surveillance) is a technique growing in potential and popularity that uses CCTV surveillance for retail analytics, as a way to find out more about customers and their shopping behaviours. 

Recent studies emphasise personalisation marketing significantly benefits companies, which boosts revenues by up to 15% and increases marketing return on investment by up to 30%. It also enhances performance and customer outcomes, with faster-growing companies earning 40% more revenue from personalisation compared to slower-growing ones. 

Through artificial intelligence, retailers can perform video analytics to save time, cut costs and build a better shopper experience - whilst simultaneously monitoring for theft. They can: 

  • focus on shopper insights and demographics

  • measure foot traffic of daily entries and exits, occupancy levels and queue times

  • object detection, head-counting, anomaly detection

  • analyse performance indicators (e.g. sales volume, average transaction sizes, and rate of return), and more

Retailers can use this information to make decisions on staffing numbers, priority areas, and how to adapt the store layout. They can even analyse the weather and events in surrounding areas that may affect footfall. For example, the expansion of Amazon Go's "Just Walk Out" reflects a broader trend towards frictionless shopping experiences. 


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Internal sharing challenges around CCTV video

Retail video analytics faces significant data access and integration challenges. 

The Global AI Video Analytics Market predicts a growth in AI in retail from $18.11 billion in 2023 to $75.35 billion by 2028. 

This growth reflects not just a technological advancement but a paradigm shift in how retail businesses view and use customer data. Retailers are keen to integrate AI-based video analytics at points of sale and self-checkouts to streamline operations and reduce wait times - improving service efficiency. 

However, marketing teams often struggle to use or even view security footage for customer insights due to privacy concerns.


Privacy still matters

While shoppers are keen for more personalised experiences, privacy rights are also a growing awareness. This is especially the case when it comes to more intrusive forms of video surveillance like biometric identification. 

Retailers have to comply with GDPR and data protection laws - that's a given. But it is also in their best interests to go above and beyond when it comes to privacy, data collection and usage, to maintain a transparent, ethical and supportive brand reputation. For example, a 2022 survey found that 74% of US consumers would abandon their favourite retailers if they did not secure personal data properly.

Shoppers are willing to give up their personal data, but only if their data is handled ethically and transparently. 

This is where advanced solutions like video redaction play a crucial role. By anonymising individuals in footage, retailers can leverage visual data whilst adhering to privacy regulations and ethical standards. This approach respects customer privacy and opens new avenues for customer behaviour and store layout analysis, without infringement on individual rights.


Video analytics seems to be a win-win for both customers and retailers but the data needs to be handled responsibly. There is a pressing need to address significant inventory losses, and the adoption of these technologies is not just an upgrade but a strategic necessity. Retailers who embrace this data-driven future are set to innovate and excel in the competitive marketplace.


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References:

  1. https://www.g2.com/categories/retail-analytics 

  2. https://techcrunch.com/2020/03/12/deep-north-raises-25-7m-for-ai-that-uses-cctv-to-build-retail-analytics/?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAADu3VsXnoSorYQxYNl06sneB5WrL9fdHCXskzOCv3ItXkYlAJ_txj-_K5tJf_2an2xP0qoXRJp3aLYBj-m4pEDCmbeJXreEUAIAuTP42uUI6shbXEwzwQWdEYNVaf1KxnLFGlpwv9VV8eHF9PcKUIkWDeW_eacl__QkKzopDoJ7d 

  3. https://www.thegrocer.co.uk/stores/sainsburys-reports-success-of-ai-concealment-detector-to-spot-thieves/647294.article 

  4. https://www.mckinsey.com/industries/retail/our-insights/personalizing-the-customer-experience-driving-differentiation-in-retail 

  5. https://www.researchgate.net/publication/348941548_Retaillance_a_conceptual_framework_and_review_of_surveillance_in_retail/link/60afb1cf458515bfb0aaf2fd/download 

  6. https://advisory.kpmg.us/articles/2021/bridging-the-trust-chasm.html?utm_source=vanity&utm_medium=referral&mid=m-00005652&utm_campaign=c-00107353&cid=c-00107353  

  7. https://www.cisco.com/c/dam/en_us/about/doing_business/trust-center/docs/cisco-cybersecurity-series-2021-cps.pdf?CCID=cc000742&DTID=esootr000875&OID=rptsc027438  

  8. https://www.bbc.co.uk/news/technology-54418936