Published: Jun 13, 2022

the future of in-store analytics and the values it unlocked

For years, there have been calls for the demise of brick and mortar shopping with e-commerce gaining popularity. The pandemic accelerated the trend and turned the retail industry inside-out. Overnight, brick and mortar retailers lost their avid fans to e-commerce outlets, and consumers had little choice other than online due to state-imposed lockdown and general unease of being in crowded places.

Two years have passed, many countries are starting to resume normal life. Consumers are slowly, albeit cautiously, re-engaging with everything they have missed in these last two years. The return to brick and mortar shopping tops their wish list.

However, the convenience and hyper-personalisation of online shopping have transformed consumers’ expectation of brick and mortar shopping. Demographic lines that separated online and brick and mortar consumers have also changed. For brick and mortar retailers, in-store analytics offers a way to provide a better customer experience and be relevant.

In-store analytics allows retail brands to dive into the motivations and trends that influence customers in-stores. The slices and dices of customer behaviours can include demographics (gender, age, etc.), dwell time, in-store navigation patterns, footfall patterns and much more.

Outlet and merchandising professionals will find these insights beneficial in making quick decisions. It also gives hard data for marketers and in-store owners to make business calls on campaigns and their business strategies. Key benefits include:

• Matching staff numbers with peak and non-peak periods. Frontline staffing is expensive, especially with the ongoing “Great Resignation” worldwide. In-store analytics helps retailers to finetune their staffing throughout the day. It also allows store managers to avoid understaffing during peak periods and keep a lid on their operational expenses.

• Optimising merchandising and layout to match customer wants. Hard data on customers navigating in-store will help retail brands to optimise their merchandising and design to maximise convenience — a key want for many consumers who’ve experienced online retail. Insights from in-store analytics can also help retail managers place products better and create better customer journeys within the physical environment.

• Measuring the effectiveness of marketing campaigns. In-store analytics can be helpful in marketing attribution for retail brands. Of course, they first need to establish the baseline for footfall patterns. Following this, in-store analytics can help retailers understand how marketing directly impacts the number of visits over time and the number of new visitors during every marketing campaign. Marketers can use these insights to finetune campaigns and determine which advertising channels are effective for in-store retail.

• Personalising the VIP treatment. With customer acquisition costs soaring, retailers' brand loyalty is now a primary focus. This saw many brands and outlets focus on VIP customers. But these customers have come to expect a certain level of service delivery from your brand after the pandemic measures. It is where in-store analytics can play a crucial role in ensuring high service levels by alerting your staff about the VIP arrivals. From meeting and greeting your VIP customer at the entrance and sending them personalised discount codes to enabling your team to deliver hyper-personalised promotions, in-store analytics can help retailers engage and strengthen relationships with your essential, influential customers.

• Measuring staff effectiveness on sales conversion. With in-store analytics, you have data on the sales conversion performance of your in-store staff. These insights can help retailers incentivise and reward their best-performing staff and train those who need it.

In-store analytics is not a new concept. But the challenge has been integrating legacy technologies that don’t allow retailers to realise the full potential of in-store analytics and insights. Some of these legacy solutions include:

• People Counter: Retailers worldwide widely use People Counter to count the number of customers who enter their stores. However, this number does not significantly impact or hold any critical insight into how the store can operate differently or sell better.

• Video Analytics on Surveillance Footage: Many retailers have explored video analytics technology to deliver behavioural insights like demographics and navigation patterns. Video analytics is based on the premise of applying an analytics layer to CCTV footage originally captured for surveillance. This is a cost-optimised solution as retailers don’t have to spend on new hardware. However, the accuracy of video analytics, in this case, depends entirely on factors like surveillance camera resolution, camera placement, and store size. COVID-19 has made video analytics even more complicated as many countries still require customers to wear masks in indoor spaces. There is also the privacy question that is being asked in some regions.

• AI-enabled Smart Cameras: Many OEMs have introduced smart cameras built specifically for in-store analytics. They look similar to conventional surveillance cameras, but have AI chip built into the system. Much of the analytics can be processed and generated within the camera, thus reducing the internet bandwidth required to transmit raw footage to the data centre. These smart cameras deliver higher accuracy in fundamental insights like people counting, demographics, and VIP customer identification. However, accuracy of advanced insights like dwell and engagement time still depend on factors like view occlusion. This challenge is especially common in Asian cities where retail stores are generally smaller in size.

Built by the manufacturers of people counter technology, 3D sensors are the latest frontier in in-store analytics. However, the difference between a people counter and a 3D sensor is significant in that the latter comes equipped with depth-sensing capability through infra-red or stereo lens technology.

This means that 3D sensors can map the multi-dimensional environment in their field of view, thus tracking individuals accurately and delivering advanced insights like dwell time and engagement time. 3D sensor technology also supports multiple units operating as one, allowing complete coverage of customers’ navigation patterns across the retail store.

This privacy-compliant technology can enhance in-store analytics and insights, allowing retail brands to get the maximum return on their investment.

Although 3D sensors can transform in-store analytics, they come with their limitations. For example, these sensors don’t deliver customer demographics like age and gender — fundamental insights that retailers expects.

We believe that combining the capabilities of smart camera and 3D sensors for in-store analytics can be a real gamechanger. Smart cameras can deliver insights like demographics and VIP customer identification, while 3D sensors can reveal dwell time, footfall and navigation patterns and engagement time.

Through analytics, retailers now can correlate these two separate data sets to get a digital unified picture of customer behavioural insights.

Gathering customer demographics and in-store behaviours is only the first step of retailers’ digital transformation journey. More critical for maximising ROI is correlating these insights with sales and marketing systems data to validate sales conversion ratio, marketing attribution, merchandising performance, and store staff’s sales effectiveness. This will help to create a positive feedback loop leading to increased sales and better customer experience.

As the largest Asian technology developer and system integrator, NCS has deep expertise and experience in helping our clients on their digital transformation journey. Our experts bring deep domain knowledge in customer experience journeys, IoT, video and advanced analytics. Reach out to us if you want to improve retail sales and enhance your customers’ in-store experience.