Big Data zeroes on Apparel

Akanksha Chaudhary1, Ankit Sinha2, Arpan Chandra3, Akshay Maheshwari4, Savidh Soni5

Keywords: Big data, business Intelligence, Hadoop, Analytics Abstract: The aim of this report is to provide insights on how big data can be used to analyze the smallest consumer behavior as well as the largest global trends in retail apparel. Big data is identified as one of the major technology trends of 2014. It encompasses huge volumes of unstructured, structured and semi-structured data running into exa-bytes that cannot be analyzed using traditional or conventional data analytics systems or platforms. The advent of new systems such as Hadoop and SQL has now made it possible to interpret the enormous amount of data. Big data analytics would help retail businesses to predict shopper behavior and personalize consumer experiences by gathering as much information about the behavior, shopping history, and interests of consumers, thus enabling retailers to implement a dynamic pricing, personalized recommendations, shopper-specific discounts, and more.

Introduction The retail apparel industry comprises of clothing, accessories and footwear. It is currently a multibillion-dollar industry. The retail apparel portion of the overall market is expected to generate $3180 billion in 2015 with a yearly growth rate in excess of 4%. China, UAE and Chile are the top three top three developing countries in terms of market attractiveness, retail development and country risk for their clothing retail industries, according to the AT Kearney 2013 Retail Apparel Index. Dubai's economy has been progressing very rapidly and this has made difficult for the retailers to adapt to the changing needs and preferences of the consumers. Retail map in UAE has grown from the traditional culture of local markets to that of more organized and sophisticated modern culture of malls with international retail chains and brands trying to establish themselves. The retail industry makes up a third of Dubai's economy according to the Oxford Business Group and it has identified Dubai for major expansion.

Fig.1: Predicted Global Apparel Sales till 2018 Interestingly, the global apparel industry has experienced dramatic changes in demand over the last few years due to the economic downturn post 2009. Even though it was not

impacted as adversely as compared to other sectors of the economy, it wasn’t spared either. As the economy recovery is continuing to gain strength, apparel industry is gradually feeling the effects of improving business. Retailers and brand owners have passed the turbulent times with resilience but not without taking some stringent measures and in the same process some firms have significantly fallen out of the business. The industry is still facing some challenges. Over the years price reductions to increase demand, boost the buying behavior of the consumers and lure them has affected the industry in the form of lower prices and less profit margins. Apparel retail out of stock rates average 10-12% as retailers try to ensure adequate shelf availability while at the same time limit the amount of inventory they carry to avoid costly markdowns on unsold merchandise. To overcome these challenges apparel industry is planning to find ways to stretch the boundaries of its creativity and imagination to find new ways to increase selling opportunities, reduce operating costs, achieve competitive advantage and improve the bottom line. Apparel retailers and brand-owners are stepping up their efforts to marry improvements in business processes with innovative technology that touches every step in their workflows, often collaborating to create synergistic, holistic solutions from the manufacturing source through distribution and all the way to the retail store’s back room, sales floor and point-of-sale. Industry is exploring technology-based solutions to spot the global trends, changing consumer behavior and growing awareness of industry practices to provide invaluable shopping experience to the customers. Many companies have started outlining the Key performing indicators, a.k.a. KPI(s) to translate strategy execution into quantifiable terms. It allows an organization to see where it's doing well and where it requires improvements and/or course adjustments.

Basically KPIs are metrics that are: Outcome-oriented, Target-based and can be Rated or graded. Based on this, some of the significant performance measures are: Customer Analytics, which understands customer requirements and deals with ever-changing market conditions The pointers to look out for are- Average number of items per transaction, Average shopping time and Visit to buy ratio.

Fig.2: Top three Best-in-class retailer BI strategies The Financial Analytics deals with tracking trends in product demand and opportunities in sales. Marketing analytics can help us track effect of campaigns in sales and help us target customers and plan for promotions. The pointers to look out for are- Total Sales, Gross Profit Margin, Price premium and Actual expenses. The Store Analytics monitors store operations vital to measure management efficiency and how campaigns are working regionally. The pointers here to look out for are- Sales per hour, Number of transactions per hour, Percent (%) of returning customers and Inventory Turnover. Apart from these, there are many other behavioral aspects, which this industry is targeting on. Some of them are: Cross-Selling Techniques Cross selling means that a company has the access to customer data that deals with demographics, preferences, past purchases, locations etc. This helps the retailer to analyze the market trends and try and sell a different type of a product to an existing customer. A basic example of cross selling would be in the case of a retailer who tries to sell a new design of apparel to an existing customer. This is possible only if the retailer has adequate information about the customer. Amazon.com deploys collaborative filtering to produce “you might also want” prompts for all product bought or visited. At one point, Amazon stated that 30 percent of sales were through its recommendation engine.

Emergence of Omni Channel Retailing Retailers need to be creative enough to be able to connect with the consumers using various means of communication. This has compelled retailers to approach the consumers and enhance their shopping experience through various channels such as TV, internet, radio, brick & mortar, emails, etc. It also enables the retailers to promote their products through various channels in order to boost their sales. UK fashion retailer Oasis is doing a very good job in Omni channel retailing. The merchant gives customers the flexibility to browse inside the store, then purchase online and vice versa. Shoppers can have their products shipped, or they can choose to pick it up. Location-based Marketing Location based marketing has emerged in the recent past, all credit to the availability of modern technology such as cell phones and GPS systems. The retailers are now able to connect with the target customer base with the help of mobile technology. Retailers are able to target the customer base based on the area of operations. Brick and Mortar Stores With the advent and popularity of online shopping portals it has become very crucial for the retailers following the brick and mortar model to be innovative in order o cope up with the growing competition. One way of overcoming such a stiff competition is by way of analyzing the available data related to the customer history. Big data may be useful and may come handy. For example Burberry once invited customers to its store to live-stream the London Fashion week. Behavior analysis Customer preferences and attitudes towards the designs play an important role in the growth of a retailer in the apparel sector. It is vital for the retailer to observe the behavior of the customer who has walked into the store in order to constantly update the stock as per the changing preferences. Even though retailers are now able to capture the behavior of customers who enter into the store, it is very important to be able to interpret it correctly. Tools such as big data can assist in analyzing the behavior of the customers. Loyalty Programs Retailers can come up with creative loyalty programs if they are able to analyze the buying trends of the customer. This would enable them to target the growing spending power of the customer by retaining the existing customers by way of loyalty programs. But this is possible only if the retailers are able to analyze the available data, which would then help them to come up with the most optimum plan. For example office depot started implementing a program that gives customers rewards based on their frequently bought items, shopping behavior and the amount information that they shared with the brand.

Figure 3: Design to reduce marketing cost Customer Segmentation Retailers need to segment the customers based on various factors such as location, age, incomes, preferences, etc. This is possible only by way of using sophisticated tools such as big data which is able to analyze large amounts of data and provide a recommendation. This would then enable the retailers to price and position their products accordingly Assortment optimization It is important for any retailer to position one’s product in such a way that it is able to attract the interest of the consumer. The decision about the same depends on factors such as preferences, age, incomes, etc. This would enable the retailer to place the products on the basis of local demographics and buyer perception. Price optimization Retailers can benefit from the availability of data and its use by way of analysis which would help them to optimize their price. Analysis of data collected from various sources and locations would provide the company access to the data dealing with different tastes and preferences of consumers across a large geographical area. This could help the company to price its products in a more optimal manner depending on such factors. This process of price optimization would ultimately lead to profit maximization. Space optimization Brick-and-mortar retailers can benefit by way of utilizing their space in the most optimum way and also ensuring that they do not compromise with regards to the display of the store which would attract the customers. Data analysis can help to understand customer behavior which can then be analyzed to place a product accordingly in a store and optimize the space available.   For example, eBay has conducted manifold experiments on different aspects of its Web site to find optimal layout.

The global apparel retail industry generated revenues totaling to $1,323.6bn in 2013, with a compound annual growth rate (CAGR) of 4.1% between 2009 and 2013.The womenswear segment was the best performing segment in 2013, with total revenues of $660.4bn, equivalent to 49.9% of the industry's overall value. The industry is expected to grow at a CAGR of 5.1% from 2013-2018 and the market is expected to touch revenues totaling to $1,695.6bn by the end of 2018. Source: MarketLine – Research Store It is quite evident from the above that the global retail sector is a very promising one considering the fact that it is expected to grow at a stable pace over the years. Although this indicates plenty of opportunities in the coming years across the globe, almost all the retail companies globally are also facing certain challenges that need to be addressed in order to ensure that the dream run to 2018 is not hindered due to bottlenecks of inefficiencies or lack of resources. Some of the key challenges faced by retailers around the globe are: Competitive pricing: The global market has become very competitive with the advent of multiple brands catering to a particular segment of people. Consumers now have a large variety of products to select from and are spoilt for choices. Also the emerging markets are extremely price sensitive and the demand from such regions is expected to grow rapidly in the coming years. This forces the retailers to remain competitive as compared to their peers in order to survive in the market

1. Procurement and logistics: At the international level it is essential to be able to provide the right product at the right time to the right consumer. In order to be able to do so, retailers need to have a fool proof procurement and logistics process in place that ensures that the products reach the consumers when demanded.

2. Quality and reliability: Quality has now gained global importance and consumers place quality as one of the prerequisites of buying a product. Retailers need to ensure that the quality is maintained and improvised with time

3. Consumer preferences: Consumer preferences are dynamic and are continuously evolving. Hence it is equally important for retailers to be innovative so that they can provide better products to the consumers. Products also need to evolve with time in order to cater to the changing preferences of the consumers

4. E-commerce: The brick-and-mortar retailers are facing stiff competition from the e-commerce vendors. Apparel retailers now need to come up with innovative ideas to promote their products in order to keep up with the stiff competition of the e-commerce industry

5. Large Data: Retailers collect and storage large amounts of data on a daily basis but are unaware about the usefulness and the interpretation of such data. Techniques that help in analyzing such data can help in serving consumer preferences better in the coming years.

Adapt to Change…Now!! Here is what some of the industry leaders feel about the need of greater customer intimacy by overcoming the above challenges and tapping new opportunities. “The idea of customer-centric marketing cuts across the major technology trends for 2014. It’s really about using technology to return to the early days of retail — when every shopkeeper knew each and every one of his or her customers as individuals — but at scale." Daniel Druker - Chief Marketing Officer - MyBuys @DDruker “The retailers that are able to tap into integrated customer data repositories, mine it for consumer insights and then execute promotional campaigns that are truly relevant to the consumer will be the big winners in 2014." Lori Mitchell-Keller - Head of Global Retail Industry - SAP @LORIMITCHELLKEL Retailers need an innovative process/tool that can help them to turnaround their current business processes and help them become more efficient and customer focused. Lot of data is collected by companies on a daily basis which is not used effectively. Companies need to analyze trends using the data collected and develop strategies to perform better. Retailers rely on the data and strategies implemented in the past with little changes assuming that the strategy will remain foolproof even in the next year. But it is important to understand that the world is dynamic and is changing rapidly. The retail sector also undergoes changes on a continuous basis with regards to preferences, prices, designs, etc. Advertisements and promotions of a retailer are linked to the strategy adopted. However, if the strategy is not modified as per the changing environment, there is not much chance that the company would be able to perform better. Hence in order to ensure that the market share is maintained at current levels or increased, development of innovative strategies that are in line with the changing preferences of the consumer is the need of the hour. Customer is the king and with the changing dynamics between the consumer and the retailer, the retailer hardly has any influence over the consumer’s preferences. Hence the retailer has to ensure that innovation takes place on a regular basis in order to keep up with the changing consumer preferences. Implementation of an innovative technology that can assist retailers to analyze the trends in the changing consumer preferences has done wonders for an organization in the retail sector. It has enabled them to exploit the current markets in which they are operating and also open doors to venture into new markets. It will also ensure that retailers streamline their operations with regards to accurate pricing, optimizing costs, removing obstacles in operations, most

optimum stocking (including the most preferred products depending on factors such as price, design, location and time of the year). It has become even more important for the brick-and-mortar retailers to keep innovating and streamlining operations considering the stiff competition from the e-commerce companies. Such retailers are now looking at using modern techniques/tools to analyze the stored information and analyze trends that would attract consumers. Better data analysis can contribute in a positive way in terms of higher sales, better KPIs, reduced costs, optimized store spaces, streamlined processes and logistics, best promotion strategies and of course higher foot falls i.e. customers. Companies like Marks and Spencer’s was established in 1884, and it aims to be the market leader in retail apparel. M&S launched one of the best innovations in technology, the virtual rail. The virtual rail gives the opportunity to the customers to browse and view their dresses on a 3 X 46” touch screen, which is an imitation of the real clothing. This is a 9 panel video wall, which uses digital signage and displays a full catalogue. The company emphasizes that the technology is a great success it is has been launched in the Internet savvy countries. Puma is one of the first companies to incorporate tablets inside their stores. They provide their customers Personalized shoe designing experience. This technology emerged in 2010. Puma gave their customer an option to create their own sneakers and give an order online or in the store. They were given the option for fabrics, materials and design on the I-Pad. The customers can design sneakers , the way they want it to be. This concept was named as ‘Creative factory’. This concept is a great success and Puma still uses it as it is very popular. Competitors like Nike and Adidas have also imitated the concept. Also, pushy sales are no more a trend in the Retail industry. The Retail apparel industry has realized that pushing customers for selling their products is the wrong strategy. The companies have changed the trend and have started investing in the relationship marketing. Relationship marketing is to change the role of the store associates from selling products to advising, building relationships and solving problems. The associates will provide tailored advices according to the taste and choice of the customers. Retailers have started investing heavily in training their employees so that they build relationships and long lasting customers. Hackett is luxury apparel retail chain from United Kingdom that now has stores almost all over the world, which has invested in relationship marketing. They have trained their store associates to build relations with customers and advise them which helps Hackett build a better customer base. Hackett has achieved a huge increase in the number of repeated and loyal customers.

Although companies have started to contemplate on the fact that better innovative techniques can help them to perform better in business, it is still in the initial phases. Very few sectors (including retail) have started to use such techniques in their day to day operations. The use of such techniques/tools can span across sectors enabling businesses to benefit from its advantages. The issue faced by organizations today is not the quantity of data but its interpretation. At times it becomes extremely difficult for the management to use and analyze the data due to its complexity as they are unable to relate to the data available. The issue faced in most cases is not due to the size of the data but its complexity to be understood. This raises doubts over the long term sustainability of big data. However, it must be noted that in the years to come data analytics would be more complex and it is important that analysis techniques are able to assist companies to analyze these large chunks of data in a more meaningful manner with the help of better techniques of analyzing and interpreting data. Big Data to the Rescue

The model above emphasizes on the fact that with the advent of modern technology and growing competition amongst retailers for maximizing their share in the market, it is important to maximize the use of various channels of communication with the consumers (also known as Omni channel retailing) and also optimize the various resources available. Big data is an analytical tool that can analyze the dynamic data available and provide required solutions for implementation. Optimization of resources along with ensuring to connect with the consumer through various means in order to cater to their growing needs and preferences would ultimately lead to success. Data Driven analysis are needed because businesses have realized that in order to predict shopper behavior and provide truly personalized experiences, they would need to gather as

much information about the behavior, history, and whereabouts of consumers. It helps to collect and analyze vast trenches of data relating to personal lives to highly sensitive information at work and is able to capture and provide the output with regards to the trends of the consumer. This analysis enables retailers to implement dynamic pricing, personalized recommendations, shopper-specific discounts, and more. Data management has now evolved to be a very crucial consideration for many organizations across the globe since the size of data that companies generate or/and source has increased by leaps and bounds over the years. It is very crucial to analyze such data and evaluate the relevance of such data to an organization. Many companies have realized the same and have started using data driven analysis to understand how they can transform their businesses and grow. It might help in - improving effectiveness of existing applications, build new applications if required, develop customer database to serve the customer better and increased loyalty, sales and growth. All these factors would help to retain existing customers and target new segments and markets thereby leading to a boost in the revenues of a company. Data analysis would in this way help an organization to grow in terms of increased revenues and customer base and will assist an employee to achieve his/her targets in the organization thereby paving a road for growth. Big data is changing the way companies are doing business. This is because it has enabled the businesses to analyze the data collected and develop strategies relating to day to day operations of the company. Big data has assisted companies not only with regards to their operations but it also extends to activities such as mergers, consolidation, acquisitions, etc. which requires companies to analyze large amount of data before they come to a final conclusion. Big data provides companies the added competitive advantage which is not accessible to companies that are not using big data. With the complex nature of business and considering the fact that our environment is a dynamic one, data driven decision making plays a very vital role in assisting managers to make sound decisions as they are able to rely on the data that can be supported by analysis and logical reasoning. To take any decision whether related to office or personal life, one needs data. This high volume and high-variety of data, when processed, allow us to take decisions better by getting a clearer picture and sometimes getting a different picture of problem. “Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.” [www.Gartner.com]. Today, the data is generated from every sphere of world.

“Big data is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it. Big data is arriving from multiple sources at an alarming velocity, volume and variety. To extract meaningful value from big data, you need optimal processing power, analytics capabilities and skills.” [www.ibm.com]. This large chunk of data when transformed into information will serve for the betterment of society and mankind. “The ability of society to harness information in novel ways to produce useful insights or goods and services of significant value” and “…things one can do at a large scale that cannot be done at a smaller one, to extract new insights or create new forms of value.” [Book: Big Data: A Revolution that Will Transform How We Live, Work, and Think]. In short, “Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. And big data may be as important to business – and society – as the Internet has become. Why? More data may lead to more accurate analyses.”[www.SAS.com]

The five V’s that define Big Data are – Volume- Tremendous amount of data is generated everyday whether it’s the internal data such as customer’s transactions or inventories data or external data such as whether data or traffic data. Velocity –The speed at which the data is gathering is tremendous. The sole reason of high-speed data generation is the digitalization of society. Variety- The complexity between the data, which is raw, unordered and can’t be processed without analysis adds a new dimension to define big data. The variety attribute is contributed with of large and diverge source of data generation. Veracity - Big Data is messy but trustworthy. The accuracy and quality of data pose a big challenge as the amount of data is very large. Value – The last but not the least V is Value. If the large amount of data available or stored is not able to provide any meaningful information then it is useless. So the Value is the most important V of all the five V’s of big data.

To tame the mishmash of Big data, various tools in the industry have been developed such as: Talend – It is a global Big Data integration platform. The latest version of Talend 5.6 promises of creating new benchmarks of big data profiling and productivity and will broaden the spectrum of Internet of Things (IoT) devices connectivity. The software uses Hadoop to boost productivity and connectivity across the board. Another is Splice Machine – Its a real time SQL-on-Hadoop database. It is one of the powerful software that offers ability to process real-time-updates. Another offering is Google Charts- it is the free tool that offers a wide variety for visualizing data, which is received from the website. The advantage of Google charts is the customization of page to provide a website look. The charts can be implemented by simply embedding a JavaScript in website. The ever increasing river of data needs to be stored so that data can be reused for a greater amount of time. The latest big data storage technologies are: Optical Storage: The latest optical storage that is used by enterprise widely is M-disc technology aka Millennial Disc. The Hitachi Digital Preservation Platform (HDPP) currently uses this technology. GridBank: Gridbank won the Big data storage product of the year for two years consecutively (2014 and 2013). The product provide highly scalable and data management solutions. TCS Active Archive™: It combines the strong capabilities of product development and process expertise of TCS in big data. The EMC analytics platform and infrastructure of EMC is use in building the software. Every coin has two sides. The bright side of having too much data is to extract information, which is more relevant in making decision making while the negative side of too much data results in stolen information or compromised networks. As it seems that Big Data has created many security issues, it also seems as Big Data analytics has provided the solution. The big data security analytic tools can be used to accelerate the detection of incident and reduce the number of false positives. Big data Model consists of five pillars and works on principle of management controls and business values. The first and basic pillar of model is Data Visualization and Analysis. The large quantity of data is processed and turned into information using analysis and visualization. The next pillar of model is storage optimization and security. The large data is optimized for storage using classification to save costs associated with storage. The security of large data can be beefed up using real time analysis of data. The third pillar of model is Reduce Cost and Complexity of E-Discovery. E-discovery is a way of reducing the cost of action. In an effort to reduce the gap of ever increasing data and cost, software models are relying heavily on Electronic Discovery Reference Model.

The fourth pillar of model is Policy based Information Governance. Gartner defines information governance as “the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archival, and deletion of information. The last pillar of model is Intelligent data-driven Decision. The data driven intelligent decisions help managers to make timely and effective decisions. Challenges Of Big Data For Retail Apparel In UAE Local Retail Apparel companies are having difficulty in identifying the right data and determining how to best use it. Building data-related business cases often means innovative thinking and looking for revenue models that are very different from the traditional business. These companies are also struggling to find the right talent capable of working both with new technologies and interpreting the data to find meaningful business insights. Data access and connectivity is also an obstacle. A majority of data points are not yet connected today, and companies often do not have the right platforms to aggregate and manage the data across the enterprise. The technology landscape in the data world is evolving extremely fast. Leveraging data means working with a strong and innovative technology partner that can help create the right IT architecture that can adapt to changes in the landscape in an efficient manner. Leveraging big data often means working across functions like IT, engineering, finance and procurement, and the ownership of data is fragmented across the organization. To address these organizational challenges means finding new ways of collaborating across functions and businesses. Finally, security concerns about data protection are a major obstacle preventing companies from taking full advantage of their data. Apart from all the above factors, 80% of Dubai’s population consists of Foreigners: • 42.3% -Indians • 17% -Emirati • 13.3% -Pakistani • 7.5% -Bangladeshi

• 9.1% -Arab • 10.8% -Others Hence, it becomes extremely difficult to cater to the taste of such a diverse population. Although Dubai has been called the "shopping capital of the Middle East” the trend actually started in early 2013 and since then has started picking up slowly. Although capturing the cosmopolitan market later than the west, it still does not have enough competent data to predict and gain advantage with big data sophisticated tools. Methodology Adopted To study the big data usage a survey conducted within 52 big data users in various industries across the globe. Respondents ranged from high level management to various task oriented people. The trend thus obtained when studied to understand conclusions for big data’s usage. The challenges and opportunities with identifying gaps. It is observed that Middle East has some gaps that can be covered by reading the trends and opportunities in various regions. Two types of users were identified who use big-data to leverage on the basis of the way they collect data. A majority of users that have been using data analysis for much more than 3 years now use old documents etc. as their source of data. Due to lack of knowledge and security concerns regarding data they have not been leveraging on it as it was expected. Other users who have recently been using data for analysis, use unconventional sources such as social media and online data to collect information. These users are aware of the opportunities and capabilities of big data and are using it intensively. Also, these users are outsourcing data for processing and are leveraging on it with useful information collected. From the data collected, it was inferred that the high-level management are aware of the opportunities and possibilities of big data. But it was observed that the mid and low level users are still unsure of the same. Approximately 30% of the users have been using big-data for more than 3 years. It is felt amongst users from around the globe that major challenges in usage of big data are lack of knowledge and awareness of its capabilities followed by poor quality of data present. More than 62% of the users feel that security is also one of the issues in sharing data with third party vendors for processing. High management users feels that cost is a huge constraint due to which they support data analytics in house rather than outsourcing. The lower management users feel that security and company policies prevent outsourcing and processing of data using third parties. In retail only 50% agree that data analysis create importance for the retail industry and provides several opportunities. Compared to other industries the share is very low. Data used in retail is collected from enterprise applications only.

The major challenge in usage of big data in retail is lack of knowledge. In Dubai only 80.4% users are aware of the opportunities of data analytics in various fields, this percentage is 98% in the northern region including the USA. Middle-east has been leveraged from data analytic in the last 1-2 years whereas others regions have been using it for past many years now. Most businesses including retail are in favor of outsourcing data analytics part which is similar in Middle East with some, others still feel that there are security concerns in outsourcing data processing Challenges related to Data Analytics

Challenges faced by organizations in using Big Data

Obstacles to outsourcing for Data processing

Organizations interested in data Outsourcing to third party

Outsourcing related to specific sectors

Conclusion: The above survey reflects that big data is slowly becoming as the next big trend in retail apparel and retailers are also realizing its importance to tap the opportunities. Also, as the experts in Retails industry say, Customer is the pivot for the retail apparel industry. All the activities that take place in the industry are performed keeping the customer in the mind. Data is not for the customer, the customer is the data in the case of this industry. Middle east is an emerging and immature market. The growth rate of the retail apparel industry is very high. The CAGR of this industry is 22% to 25% in the previous years. The barriers of entry in this region are low which encourages apparel brands to enter this region. Challenges faced by the retail apparel Industry in the Middle East show that there is no sharing on the market research information in this region and is done individually by companies. We cannot find the down trending and up trending fashion as there are no agreements for sharing unlike US which forms a barrier to explore the untapped market.

Big Data does not exist holistically in this region as it is still a immature market. Only a few companies are there which are researching and collecting data. It will take some time for the companies in this region to attain that mindset and maturity so as to adopt this technology. According to Andrew Rippon, Big data Expert, "The big data has been potentially exploited by the Online Retail Apparel Stores in Middle East such as Amazon and Souq to analyze the consumer preferences and purchasing pattern. The major problem the outlet retail stores in this region is facing is the adoption of correct tools to analyze the huge volume of data. The other reasons for region being reluctant on readily adoption of Big Data are the closed governance structure and strict privacy issues." The Landmark group has utilized big data by introducing Loyalty program called “Shukran”. This has helped them to analyze sales and trends. It has also increased their customer base and loyalty. Great opportunities exist for big data in Dubai especially due to expo 2020 and the large chunk of data the country currently has. Due to collaboration between different fields like open source, big data, machine intelligence has led to the expansion of the industry. Enlisted below are the strategies that companies can adopt to shrink the gaps that exist in Middle East and transform using big data to big business. First, Companies should identify the data sources that currently exist, and how are they utilizing it. Second, Which is the type of data source and analytics model that will help them to find a solution to their existing business issues and concerns. For e.g. if I want to understand my loyal customers I need to find out which is the big data type that will match my business problem and Lastly formulate strategies, which helps to minimize the regret of loosing new customers. References: MarketLine – Research Store

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