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Malaysia Airports develops data insights to optimize customer satisfaction

Airport operator company, Malaysia Airports, with interests in Turkey, India, and South Asia, is working with Fusionex on a proof-of-concept: to develop a Business Intelligence platform to further enhance Malaysia Airports’ retailer management system within KLIA and provide value-added services for travelers.


Malaysia Airports is an airport management company with a portfolio of almost 40 airports in and around South Asia and Turkey. Apart from the aeronautical business, the client also manages other portfolios including duty-free & retail operations, hotels, free commercial zones, commercial space leasing, and management of parking facilities. It also runs global training centers regarding airport management, airport fire & rescue services, and aviation security.

The Challenge

Malaysia Airports sought to enhance its customer data collection methods and determined to increase the accuracy of gathered information on the performance of its retail units within KLIA. This involves an approximately 400,000 square foot containing retail outlets at various locations including the arrival and departure halls as well as check-in counter areas. These outlets/locations see a fluctuating amount of shoppers at different times and days of the week.

Malaysia Airports aims to ramp up its data collection frequency near the shops area. A higher degree of prompt data collection would serve to accurately determine when promotional activities should be held, or if they were held – what their projected results would be. Accuracy of information garnered from this area is important to determine the customers’ hotspots and their spending trends.

A precise method to track spending trends at the terminal would allow Malaysia Airports to identify local shoppers and international travelers apart. This would also result in a more informed decision being made with regards to what the retail composition should be – whether the terminal should host more shops selling food, garments, souvenirs, or other goods base on the shoppers spending pattern and behaviour.

The Solution

A combination of the Fusionex Business Intelligence platform together with Internet of Things (IoT) devices was utilised to collect and manage the terminal’s retail data. Sensors were installed at the main terminal building’s arrival and departure halls and the contact piers for international and domestic flights.

Tracking the traveler jouney via the Fusionex BI Dashboard

Sensors are also placed in and around the airport’s retail sections to determine hotspots where the most retail activity occurred. The sensors are functioning independently without requiring wiring or lengthy installation methods. Among the sensors used were those with Bluetooth capabilities and Wi-Fi detection capabilities installed in collaboration with solution provider Tapway.

A mobile application was developed to track the basic demographic background of customers including details such as gender and nationality. A campaign was conducted to encourage travelers to sign up for the mobile app. The app could then use the demographic information to craft personalized marketing messages and promotions for the customers.

Using a wide set of connectors, various type of data set and system can be integrated into single platform with speed and ease. The dashboard reporting is then rendered automatic as well, giving the client the ability to view revenues in near real time. These endeavors were supported and co-funded by the Malaysia Digital Economy Corporation (MDEC).

The Benefits

The ability to receive performance data from their existing tenants quickly, together with traveler information from installed sensors, allowed Malaysia Airports to make more accurate decisions:

Understand traveler habits and shopper behavior, preferences. Malaysia Airports will be able to determine travelers’ flow and identify trends of unique shoppers via the installed sensors. Other than that, demographic data such as gender, date of birth and nationality will also be gathered to help Malaysia Airports understands which retail outlets appeal the most to which groups of people. This provides insights into what composition of retail outlets would be optimum in the airport – whether or not certain shops fit, and whether they fit better in domestic or international halls.

Ability to perform more accurate marketing efforts. Passengers’ traffic data gathered, which could be drilled down to daily and even hourly, could inform Malaysia Airports when would be the right time to hold promotional and marketing events within the terminal. Connectivity via travelers’ mobile devices provides a possibility for future marketing undertakings such as customer-specific push notifications. When walking near a particular shop which the traveler might be interested in, the platform pushes a notification to their phones for a promotion on items or services available.


By utilizing IoT devices and gathering useful data on a centralized system, Malaysia Airports is able to get a good overall view of its airport’s retail sector. Being provided with user-friendly BI dashboards also enable management-level personnel to get quick looks at the information to make timely and accurate data-driven decisions.

Industry: Aviation / Retail

Big Data Solutions Provider: Fusionex is an established multi-award winning IT software group that specializes in Analytics and Big Data. Their business is to help clients manage, make sense of and derive useful insights and information from the vast amounts of structured and unstructured data at their disposal. Fusionex is focused on bridging the gap between business and technology, and in doing so, providing an exceptional and positive experience to customers of various markets.

Big Data Use Cases in Retail

Dynamic pricing across multiple channels is not new, but big data allows for a much more refined set of indicators for price elasticity in comparison with traditional influencers such as time and availability. Other indicators include the weather, the location, the complete buying profile of a customer, and the social media presence of a customer (prescriptive analytics).

Fuzzy matching helps when people search for jobs, hotels, secondhand cars, houses and other goods with many characteristics. Fuzzy matching pairs results that are almost fitting, like a dark blue car instead of a black one, or a hotel on a different Greek island from the one requested (prescriptive analytics).

Counter-dynamic pricing is the opposite of dynamic pricing. If big data analytics can refine price-elasticity models, the optimization algorithms can also be reversed and put to use for consumers. Personal analytics help determine the best moment to buy goods or services for the lowest price, and carry out the order immediately (prescriptive analytics).

Fraud detection is important in most industries. Specifically for the retail sector, one can think of tracking fraud in returns and abuse of customer service, or credit risk for larger purchases, based on, for example, uncovering fraud rings, the social media activity of customers and detecting patterns (descriptive analytics).

Dynamic forecasting complements traditional demand and supply chain forecasting, taking more external factors into account, such as traffic conditions, weather forecasts, shop video feeds suggesting demand, and sensors (moving from sensors attached to checkpoints and monitoring objects [products, materials, parts] to sensors attached to every single object to be monitored) (predictive analytics).

Recommendations are the mostly widely adopted big data use in the retail sector. Based on what other customers have bought, a customer could also be interested in another product. This is also called “best next offer” recommendation. Recommendations can benefit from a much broader context, not only checking which combinations are most likely, but also, based on a very fine-grained “graph analysis,” identifying a closely related peer consumer group. It can also work with people, such as when LinkedIn recommends other people to connect to. It can additionally be used with locations, based on common or complementary characteristics (descriptive analytics, prescriptive analytics).

Retail data can be monetized by selling it upstream to partners and suppliers, to give them more insight into how their products are selling and in which circumstances. Information on, for instance, buying patterns throughout the day, in relation to the weather and how busy stores are, helps suppliers optimize their marketing (general management).

Market basket analysis traditionally matches products that are purchased together. Big data adds more context, including time of day, music played in a store, store visit duration, weather, length of queue and so forth (descriptive analytics).

Mall experience gamification is a new concept, based on smartphone location data (or data from any other location-aware device). Visitors to a mall can be tempted to buy more and stay longer by tracking their movements through a mall and sending them special offers — for instance after checking in at more than 10 stores (descriptive, predictive analytics, prescriptive analytics).

Real-time offers respond in real-time to changing patterns in visitor numbers. Not only online, where dynamic promotions were pioneered, but also in the “real world.” For instance, in airports, shops can put different items on sale based on flights to or from specific locations. Shops can change their promotions not only based on the weather forecasts or commuter streams, but also based on more fine-grained algorithms, including social media analytics (what are people talking about in the neighborhood) (predictive analytics, prescriptive analytics).

Shopping cart defection is not a new form of analysis in the online retail sector. But big data enables consideration of many more factors, next to clickstream analysis (diagnostic analytics).

Loyalty management benefits from big data by extending channel reach from point of sale, Web and call center to include mobile and social capabilities. Rewards may be accrued by more than purchases; people may also earn them for being good product or brand ambassadors. Rewards may also come from more than personal contributions — social relationships may be included (descriptive analytics).

Multichannel location analysis involves researching and evaluating optimal locations in which to develop profitable retail stores in conjunction with e-commerce and mobile commerce market analyses. It includes the use of store location analysis techniques, including the analog method, gravity-modeling multiple regression analyses, and the use of geographical information systems and e-commerce and mobile commerce trade market analysis tools to analyze multichannel trading in geographic areas (descriptive analytics).

Real-time store task management helps with the allocation of staff to, for instance, shelf restocking, customer service, checkout support and order picking, based on actual customer traffic, as determined by, for example, video analytics (prescriptive analytics).

Customer-centric merchandising helps retailers improve their product- and supply chain-centricity. Instead of selecting products based on the offerings of their suppliers and pushing them to customers, big data analytics help identify customer needs and aid the selection of new products that could increase a provider’s “wallet share” on the basis of demand (descriptive analytics).

(Courtesy of Gartner Leader’s Toolkit: Big Data Business Opportunities From Over 100 Use Cases)

Visitor Traffic Analyzer Boosts Revenue of Global Sporting Goods Retailer

This solution helps businesses such as a popular sporting goods retailer in Malaysia find out the number of people walking into their stores, who among them are buying, and how to allocate budgets for improved profits. Known as the Visitor Traffic Analyser or VTA, it helps the retailer improve its sales conversion ratio (from walk-ins into customers), increase store traffic and improve advertising for the company. By electronically counting traffic at each entrance, solid information can be obtained to manage all its stores more efficiently. VTA will be useful for improved staff management, promotional impact assessment, and high and low traffic period identification. All this can bring about more cost-effective budget allocations which will have a direct bearing on the bottom-line of the business.


In the current business climate, retailers face a multitude of challenges that severely threaten their ability to operate profitably, such as market over-saturation, and ever-rising operating costs. These challenges magnify the importance of every business decision and budget allocation. Before, sales results was the only KPI to determine if a business was healthy or not; but sales figures alone cannot identify problem areas that needed addressing. It is more important than ever for retailers to accurately monitor the industry’s two most vital sales performance metric: shopper traffic and conversion rate.  Therefore, it is necessary to identify which segments of the retailer’s organisation is performing its function optimally, from Marketing to Operations or Merchandising. Visitor traffic intelligence can help pinpoint which particular department needs improvements in order to boost sales and profits.

Big Data & Analytics Solution

The Visitor Traffic Analyzer (VTA) is an electronic device with sensors that are mounted near entrances and connects to any PC to capture visitor traffic data. Once captured, hourly analysis of data will be available, enabling easy and accurate visitor count monitoring. This data can be used to generate reports and display statistical information on a computer for analysis.  Retail experts agree that accurately counting customer or visitor traffic with automatic electronic visitor counting is the only way retailers can make sound strategic decisions.


The Visitor Traffic Analyzer (VTA) technology

VTA can help companies of any size position themselves well in today’s highly competitive market; such a solution helps the sporting goods retailer to easily evaluate staffing needs, staff performance, conversion ratios, marketing campaigns, floor plans, product displays and more. With hard visitor counting data, decisions are based on facts, not guesswork. Additionally, the impact of the company’s marketing activities can also be monitored and analysed with VTA by comparing people traffic during different days of the week.

Benefits Obtained

People counting provides a range of useful statistical indicators, giving management a clear and detailed picture of visitors’ and customers’ behaviour. There has been an uplift in sales after using VTA’s people counting solution.  Customer service in its outlets has also improved. Stores with low traffic can now have access to customised marketing activities to increase their traffic.  This means a more efficient allocation in budgets as there is no need to have across-the-board marketing activities.

Management can make their business decisions with real-time, accurate, and relevant information. Knowing its traffic patterns gives insights on seasonal fluctuation and other buying behaviours, much of which managers have only been guessing until now.  By understanding traffic patterns and available information, marketing efforts can be optimised and customised to each relevant outlet.

Moving Forward

People traffic from real-time data provides information to aid in the understanding of visitor trend and the factors that affect visitors in various industries and sectors. This solution can enable more and more data collection for the client to analyse; information can be captured at Points of Sale (POS), for instance, identifying which products or colors or sizes are more sellable.  All information are captured on-premise or sent to the cloud depending on what the Client requires.

Industry: Sports
Client: A global leaders in the sporting goods market
Big Data Solutions Provider Profile: VTA Corporation Sdn Bhd deals in the manufacturing and delivery of Intelligent People Counting Products that provide a complete range of solutions from the electronics and packaging to the analytical reporting software. The company uses its long-time research expertise in order to develop products that set the benchmarks in the field of people counting.  With this accurate and meaningful traffic data, maximization of efficiency and effectiveness of employees, floor area, advertising budgets, and sales potential of the business can be done. Operators of shopping centers, airports, museums, art galleries, libraries, government agencies, and retailers can monitor and quantify people traffic with VTA which provides important information needed to make critical business or management decisions that will distinguish VTA users from the competition.

Boosting customer relationship and store revenue via retail analytics

A Malaysian Café chain was able to boost its business by adopting a WiFi-based Customer Relationship Management (CRM) solution from Tapway, which helped to collect valuable customer behavior data and to monetize by targeted advertising and promotions via email and SMS. WiFi-enabled smartphones are constantly broadcasting a unique device ID and the solution’s hardware detects and anonymizes these IDs, adds time and location data and stores them in the database. Tapway’s analytics engine crunches the data to provide the Café owner with customer analytics and Tapway’s Hub centralizes all the data and turns them into charts and visualization which the Café owner can access anywhere, anytime. With this retail analytics solution, highly targeted campaigns can be designed in order to attract new customers and retain loyal ones.

The Client was having difficulties obtaining sign ups and creating a customer database for their loyalty program, and they did not know their customers’ engagement patterns in the outlets, such as the time and amount spent there, how often they returned, as well as their demographics.


A Tapway retail analytics solution in all their outlets provided the Client with a Guest WiFi captive portal solution, which helps to collect customer data and provide advertising space for the Client. The WiFi sensor also collects mobile device data, which is then processed through Tapway’s algorithms to derive customer shopping behaviour data, such as the number of walk-bys, visitors, new versus repeat visitors as well as a calculation on retention rate, visit frequency and recency, average dwell time of each customer, and dwell time distribution.

Based on the customer data collected and the derived shopping behaviour information, Tapway then crafted highly targeted campaigns such as first time WiFi sign up campaign to attract new customers by giving a 15 percent discount on cake products, loyal customer campaign which was used to attract existing customers to return by giving a special 20 percent discount on coffee on certain days and time.  There was also a new products campaign aimed at keeping existing customers interested in the Client’s new product launches.


In-store Analytics: A 360-degree understanding of the Client’s store performance through insights like walk-by traffic, visitor traffic, capture rate, average visit duration and customer retention

Business Benefits:
The Tapway solution generated more than 3,000 names for the database in three months. And the Client was able to obtain detailed visitor trends in all their outlets such as visitor demographics, number of visits, average dwell time and visit frequency. This information then helped the Client to craft targeted campaigns to boost their sales. The company then launched these campaigns and was able to measure the ROI for each campaign in detail, such as the percentage of emails viewed and the percentage of coupons claimed.  Overall, the Client generated around RM1,800 per campaign, which is a 3% revenue increase.

The Future:
The Client has chosen to introduce more targeted campaigns based on their customers’ visiting behaviour, such as rewarding customers  entering for the fifth time in the past 30 days, or sending a message to those exiting the café for the second time in one week. There was also a decision to integrate the retail analytics solution with their Point of Sale (POS) system to enable seamless coupon claiming as well as incorporating sales data to the CRM platform.