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7 ways in which e-Retailers can leverage Data to increase ROI

Big Data helps in analyzing the market from consumer’s perspective and thus is necessary to customize products and services

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PCQ Bureau
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ways etailers can leverage data

Big Data helps in analyzing the market from consumer’s perspective and thus is necessary to customize products and services to bring better returns from the business. Here we discuss the 7 key ways it can be leveraged

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-SumitGupta,Founder,Dealsnprice.com

ECommerce is a competitive market with numerous  players and more emerging on day-to-day basis. An easy set up to start with the venture and innovative utilization of resources has helped entrepreneurs to stride into this market. Moreover, rapid penetration of internet across the globe and an exponentially increasing usage of mobile devices fostered the most amicable environment for the industry. As the market is quite competitive, ventures and business houses are seeking opportunities to standout ahead of their competitors through innovative approaches. Marketing have become research oriented, Products and services are becoming more customized and customer services are becoming outright. In this scenario, customer information and data have become imperative to device more effective marketing strategy and hence incur better ROI.

When it comes to information and data, lately, Big Data have become the most pertinent concept. Enterprises and corporations around the globe are at haste to utilize this in their own ways. For E-retailers, on the other hand, customer data is of much value that shapes marketing strategy and business decisions. For these companies, comprehensive consumer information helps to understand the market, its demand and its orientation. Analyzing the market from consumer’s prospective is necessary to customize products and services to bring better returns from the business. Leveraging Big Data helps to increase ROI in following ways.

1.    Understanding geographical distribution of customers

E commerce businesses have the potential to encompass the whole world. As a web domain is not localized, such businesses reach out to billions of potential customers across the globe. However, e commerce businesses have to be locale specific for better profit. Being locality specific, helps segmentation of customer bases and promote specific services and products. Companies can locate potential customers based on their location and direct modified marketing campaigns to specific locations. This helps enterprises to direct resources to more meaningful investment and to utilize them more intuitively. Therefore, wastage of extra resources in advertisement or marketing in places with less potential customers could be prevented.

2.    Optimization of price

Consumer data about their purchasing power is of much importance to e commerce companies. This helps to optimize price according to buying power of consumers. For instance, a product can be sold to different customers at different prices if information on how much a can the customer pay for the product is in hand. Using such information, products can be tagged with a price, which is oriented by buying power of customers. Such changes in product prices help the business to gain more profit. Such strategies leverage companies to get away with bulk of stocks rolling them in lesser costs and additionally, help the enterprise to sell products at higher prices than their margin value.

3.    Better inventory management

Managing inventory is one of the major operations of any e commerce business. Delivery time of products or services to customers is central to the company’s popularity. In times of greater demands, a strain on the supply chain management of e commerce companies is common. Big data helps these companies to tackle such situations and maintain a standard product delivery time. Inventories can be shipped and stocked at locations from where the orders are most likely to arrive. Determining such locations is possible through analysis of past data and purchase trends of customers. By implementing such procedures, it is possible to provided fast and agile delivery through well-maintained logistics systems.

4.    Prediction of demand

Demand prediction is one of the most effective usages of consumer data. With precise prediction of demand, e commerce companies can device effective marketing strategies. Demand of particular product can be estimated beforehand by observing specific trends such as festivals and special occasions. Customer information helps to offer specific products that match to consumer demands. This helps companies to focus on marketing customized products for specific seasons and occasions.

5.    Expansion in multiple business verticals

E commerce is expanded throughout various industry verticals such as Banking, Logistics, Social Media, marketing and others. Big data helps to gather customer information related to diverse industries. This offers e commerce companies to provide clustered or la carte services combined with familiar services the customer uses. Many E commerce companies collaborate with banks and finance companies to provide special offers.

6. Understanding traffic sources

Big Data helps in better analytics and analysis of traffic. Since, e commerce is web based, it is easy to identify traffic sources. This data helps to modify business plan to bring out the best possible Return on Investment. This helps in directing advertisement and digital marketing campaigns towards specific regions. Better understanding of traffic sources enables effective social media marketing.

7.    Micro segmentation of consumers

Micro Segmentation of customers is the most effective usage of consumer information. Big data helps to segment customers based on their age, locality, sex, choices and income. Hence, companies can direct customized range of products depending on the group of consumers. Micro-segmentation assist companies to roll out products targeted to specific consumer groups. Utilizing Big Data, e retailers can also predict about specific time slots when the site encounters high traffic. This helps in managing risks arising from probable server crush or technical glitches.

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