One of the advantages that online retailers hold is access to a huge amount of customer data, helping them provide personalised and better product results. Aaryahaan International offers solution to help offline retailers with the same benefits, providing them the data and the tools to understand their consumer behaviour and guide them with offline search for the product.
‘Data is the new oil’ as it has become a mantra for the fashion retailers. We are well aware of the storm created by the e-commerce players in the market, posing huge competition for offline retailers. One of the advantages that online retailers hold is access to a huge amount of customer data, helping them provide personalised and better product results. They know exactly what the customer is looking at, through the products listed in their wishlist and cart. “The biggest threat for the offline retailer is the e-commerce industry, and the advantage that e-commerce has is too much information about their customer’s search. Our solution helps offline retailers with the same benefits, providing them the data and the tools to understand their consumer behaviour and guides them with offline search for the product,” says Jagmohan Batra, Founder, Aaryahaan International Pvt. Ltd.
Aaryahaan International, based in Delhi (India), is a retail technology supplier which provides business analyst solutions for offline retail. The technology helps analysing customer’s journey and behaviour in a physical store or a mall. Aaryahaan is the refinery for this new oil (data).
Built on technologies like Wi-Fi sensors, Beacon and Data Analytics, the solution helps the retailer get a detailed insight into the consumers’ shopping journeys. The solution is not only limited to mapping the physical journeys at one’s bricks-and-mortar locations, but also understands when the physical shoppers revisit; what is the frequency; how much time they spend in cross-store or cross-section activities; conversions, passer-byes and many more. In a nutshell, the technology can capture and analyse the consumers’ entire shopping behaviour from their searches to their path-to-purchase. The tracking of the consumer’s journey further assists in providing a more personalised experience to the consumers which leads to brand loyalty. “We not only act as Google Analytics for bricks-and-mortar retail stores and malls, but we are also the biggest loyalty programme by default, which does not require any enrolment or personal information. We are able to identify the consumers uniquely by their shopping behaviour and not by their demographics. We deliver transparency about consumer behaviour in offline locations; we then use this data to identify ways to measure the change in consumer behaviour and advise retailers and mall operators with actionable decisions they can take accordingly,” explains Jagmohan.
The company offers two solutions: Analytics and Target-Ad. Analytics enables retailers to manage, benchmark and continuously optimise their stores and marketing campaigns based on actionable consumer behaviour insights. Shopping malls, for example, often lack the transparency of how consumers move between stores. A key challenge is understanding how the arrangement of retail tenants influences the consumer journey. Aaryahaan solves this problem by tracking how visitors move through the mall, from entry to exit. The in-store sensors capture the dwell-time per store and per floor, and the heat map tool reveals which stores are usually visited together within a single shopping trip. The mall operator is thus able to better plan the tenant mix, to adjust the rent pricing, and to incentivise visits to less-frequented mall sections.
Analytics works to offer a consumer-oriented shopping experience and develop a highly targeted marketing campaign. It works in an aggregated manner and does not work on identifying any personal consumer data/information. For example, if a retail store/mall has a total footfall count of 8,000 people on a single day, it will analyse the percentage of store/mall visitors that are visiting each section/store of the store/mall. This will assist in defining which of the section was most visited and which one was the least visited. The data obtained here is used to improve marketing efficiency and drive people into the store. The Beacon technology further analyses how many customers entered the store and how many passed by. It can then pass advertisements to the customers to motivate them to visit the store.
The second solution is ‘Target-Ad’, which uses aggregated and anonymised information of shoppers’ offline journeys and shopping behaviour to precisely target them using various online platforms. This solution not only provides the right and most relevant target group for one’s marketers, but also equips them with the capability to define target on the basis of consumer choices and searches in offline space. This also helps retailers to realise their most important task of using consumer behaviour in Offline to Online (O2O) targeting.
Aaryahaan records local shop visitors via in-store sensors and engages them through tailored online and mobile ad campaigns. The ads incentivise browsers to return to the local store, to visit the online store, or to download and engage with the retailer’s app. Aaryahaan is also able to attribute individual walk-ins to specific advertising campaigns that consumers were exposed to before the store visit. The outcome? Advertisers are able to optimise their online and mobile marketing campaigns based on actual in-store conversions. A premium fashion retailer, for example, used Aaryahaan retargeting to increase repeat visits to its flagship store. The retailer faced the challenge of only 11 per cent of consumers revisiting the flagship outlet within the same month, which significantly diminished the overall sales potential. Aaryahaan was able to retarget 25 per cent of all store visitors via online and mobile ads with the help of its in-store sensors. As a result, the retailer saw a 23 per cent increase in visits by loyal consumers within a campaign period of only 4 weeks.
How does the technology work…
Aaryahaan’s sensor solution brings transparency around each store/mall’s performance on the basis of new consumer engagement KPIs. The parameters quantify visitor traffic and enable the retailer to improve marketing campaigns as well as operational efficiency, to drive more consumers into the store and make them dwell longer. Traffic mapping is built on in-store Wi-Fi technology. Aaryahaan’s sensors record the Wi-Fi signals of consumers’ smartphones once the sensors are connected to power. The anonymised data streams are sent to Aaryahaan’s in-house data centre and they are analysed according to proprietary algorithms. Aggregated information on consumer footfall is then extracted and intuitively visualised in charts, diagrams and heat maps, which are powered by the industry-leading data visualisation tools. All insights can be accessed through Aaryahaan’s dashboard by C-level decision-makers and by store or mall management.
However, for the technology to work, the only requirement is that the consumer should carry a mobile phone with activated bluetooth or Wi-Fi. For the consumer passing by the store, the technology needs a few seconds to capture the probe request.
Based on the data collected, the algorithm-based software does a complete analysis of the consumer behaviour, mapping it with the store map. The results can be viewed simply on the dashboard, describing which area of the store is performing well and which area is not doing well. The dashboard is customised as per the needs of the retailers and according to their understanding. The company offers a bouquet of KPIs which the consumers can choose from.
The KPIs reflected in the analytics dashboard provide shopping mall operators with a detailed understanding of visitors’ cross-store visit behaviour and their overall engagement with the mall facilities. Retailers, as well as shopping mall managers, need this transparency to take the right measures that enhance the in-store shopping experience. Such measures entail among others the optimisation of marketing activities, store design, tenant mix as well as staffing.
Keeping the security of consumers as priority, the only data that is collected is the MAC-ID of the mobile handset of the consumer and no other personal information of the consumer is recorded. These MAC-IDs are anonymised or hashed so that they cannot be identified by the consumer or misused. Once hashed/anonymised, nobody can identify the name, gender and other such information of the consumer.
This is how technology helps apparel retailers…
Understanding the consumer is the key. The technology is not only capable of capturing the shoppers’ entire journey at retail location, but also has the highest capture rate in offline retail space. For a retail store, the technology can help identify which section of the store the consumers are visiting more – perfumes or shoes or garments or accessories. This understanding can then be used to promote the less popular sections of the stores by giving deals and offers. Also, this will help identify how well their advertisement worked for them.
For multi-brand outlets like Shoppers Stop and Pantaloons, Aaryahaan’s technology can help identify what percentage of people are going to which brand. “In fashion, we believe that trends are to be understood in an aggregated manner, so out of 50,000 people who come to a mall or a multi-brand outlet, we can understand their preferences brand-wise, category-wise, frequency-wise and on the basis of the amount of time spent,” explains Jagmohan.
To achieve a 360-degree view of the consumer journey, Aaryahaan offers to supplement the sensor data with insights from related data sources. The data pool can be enhanced by integrating additional analytics technologies, such as camera, cashier or CRM data, as well as weather report data, depending on the retailer’s or mall manager’s needs and requirements.
Consumer behaviour and trends change every few months, so brands need to evolve with the changing demand. A good example of the implementation of the technology that Jagmohan states is, “The data of a company where the technology was implemented when integrated with the sales data depicted that there was a particular section in the store that was being visited a lot by many customers but the product was not being sold. The finding was that the people were reaching there, which means the product was appreciated but there was some reason that it was not being sold. This was shared with the retailer, which then worked on the issue by conducting a survey and other methods to identify what was the reason for the product not being sold. Upon research, it was found that sales was not happening because the product was too expensive, based on which they later started giving discounts and other offers which resulted in making the product the hottest selling item.”
So, the solution helped in giving an important insight into the company’s product, leading to obtaining better strategies and decisions. This created a significant difference in overall sales of the company.
Commenting on the relevance of technology for the retailers of India, Jagmohan explains, “Indian market is very tough; every geography has different complexities, trends, styles, cultural differences, etc. Not just different states, but the cities within them have different consumer demands which makes it important for brands and retailers to understand their customer segment.”
“Sooner or later, all traditional retailers will need to adopt new technologies to survive. Darwin’s theory of evolution ‘Survival of the Fittest’ holds true even in retail. If traditional retailers want to survive the onslaught of e-commerce, then they need to be fit, to be fit they need to change, adapt and evolve and thus survive. The change can either be arbitrary (hit and trial) or focused based on real consumer behavioural data. When the shopper’s data combines with the existing traditional retailer’s inputs and experiences over the years, it becomes a formidable inspiration and ingredient for developing the right and accurate new technologies. Those who change based on real and accurate data have better chances of survival and success,” concludes Jagmohan.