Until recently, the only way for customers to achieve instant shopping gratification was to enter a brick-and-mortar store. The Internet has changed all of that. It has allowed online retailers such as Amazon to successfully engage with customers and create a shopping experience that has driven foot traffic away from stores and on to computers, tablets and phones. These online retailers have a leg up because they often offer a wider product selection, lower prices and customer interactions that promote product reviews and ratings.

Sales from traditional retailers have gone down drastically, leading to the demise of a significant number of brick and mortar stores. By August 2017, approximately 6,300 stores announced that they were shutting shop. However, some retailers have their own set of characteristics and specialties that are still alluring to today’s customers. As shown in Exhibit A, there are off-price and extreme value retailers who have remained stable given their business models that cater specifically to certain tranches of the population.

However, a large part of the growth of mega online retailers has come at the cost of traditional retailers, especially those in the department and discount stores segments.

For traditional retailers, there is a lack of coherence in customer engagement across online and offline platforms, which makes it difficult to strive for a meaningful experience across all channels of engagement. The major pain points faced by the traditional retailers in adapting to the digital ecosystem are:

1. Integration of legacy systems with the digital ecosystem

2. Addressing the proliferation of customer channels and touch points

3. Consistent and unified channel focus strategy

4. Leveraging customer moments and journeys

To successfully win over a customer’s heart and wallet, it is important to provide a seamless customer experience. However, this can only be done by understanding customers well, playing to one’s core strengths, and developing a game plan attuned to the customer lifecycle. Successful retailers will tailor their strategies around their main stakeholders—their customers—and the most important asset—data. Only by developing a data-driven, customer-centric approach can traditional retailers achieve success in the present day marketplace.

Creating an effective and consistent customer experience is both a challenge and an opportunity because the rapidly evolving customers are more demanding and tech savvy than ever before. With today’s customers always on the move, technology holds the key for the brick and mortar retailers to adapt their customer experience according the needs of the new breed of empowered consumers. Technologies like augmented reality, virtual reality and A-GPS bring the retail experience closer to the customer while enabling higher engagement levels and customer satisfaction. To be competitive, retailers must embrace the technology to enable comprehensive integration of front-end and back-end channels that create the omni-channel focus to not only meet, but also beat competition.

To build a successful retail strategy, players can follow these guidelines:

1. Incorporate a customer centric view and derive insights that add value to a customer’s journey

2. Build upon their core business strengths

3. Leverage cutting-edge analytics across the board

4. Use cross channel integration for a seamless customer experience

A Customer Centric View

The first step in understanding a customer’s buying behavior and preferences entails building a 360-degree customer-centric view. This includes:

  • Identification and collection of customer information from a variety of sources like online interactions, in-store experiences and customer flow captured using beacons or Wi-Fi pings. This has been made possible because of the developments in many areas of technology. In just the past few years alone, there has been a massive development in the customer database collection technologies, which allow for better and more valuable insights. Additionally, the developments in big data technologies have enabled combined processing of structured and unstructured data from disparate data sources for data enrichment operations which are a precursor to efficient data analysis. These rapidly developing tools and technologies are a natural progression of data collection for retailers who have been relying for a long time on just transaction data for trends and insights.
  • Building a master 360-degree view of a customer that integrates all data across all channels, including product, order, inventory, purchasing, and vendors to ensure that everyone in a retail organization, from in-store associates to warehouse pickers, has access to the same real-time data needed to deliver total customer satisfaction. Integrating the interaction and transaction data from the POS, web, contact centre, mobile apps, and social channels create a seamless experience the customers expect.
  • Leveraging the master view of the customer to derive insights such as uncovering the drivers of loyalty using customer response and behavior. This includes tracking response to loyalty offers delivered online and offline in both same channel and cross-channel purchases and segmenting multi-channel behavior of customers to identify differentiated patterns of purchase and customer journeys. A 360-degree view of the customers helps in the channel selection for targeting customers and helps retailers to optimize their marketing mix to get the highest conversion rate and sales performance.
  • Measuring the constant feedback loop in terms of customer response and loyalty to ensure the efficacy of the data-driven strategies implemented as a result of the insights derived from this 360-degree view of customers.

Creating Customer Context

The purpose of creating a customer-centric view is to establish a relevant customer context. This context is further enhanced by information on customer’s buying behavior and preferences providing inputs for improvising the individual customer experience. This requires collation, management, and analysis of customer data from different sources to arrive at an analytical model aimed at enhancing the numerous journeys customers undertake to complete their respective purchase cycles. It also involves predictive modeling based on the collated data to design and market offers based on shopping behavior thus achieving better ROI. Advanced analytical approaches such as machine learning, deep learning, natural language processing and network analytics are the enablers to these analytical models which are complex to implement manually.

Building upon core business strengths

Once the customer context is clear, the business strategy of any retailer should focus on leveraging their core business strengths. These strengths are identified in several ways, but most certainly take into account the retailer’s industry expertise, competitor research, as well as knowledge of the latest trends in their category.

Some retailers build on their strength of providing exclusive offerings or service delivery. For example, the core strength of Best Buy is its highly trained sales associates, who are available to educate customers, assist them in making an informed decision, and provide technical support. In order to keep up with the growing digital consumers, Best Buy launched a new service called the Geek Squad. The service augments Best Buy’s core competency by combining online and offline customer touch points in sync with the digitally savvy consumer’s journey.

Geek Squad’s core strengths and its multiple touch points

Consumers can reach Best Buy for repairs through a variety of touch points which includes web, mobile app, and in-store. This helps Best Buy to extend their services in the form of in-home repairs/assistance, in-store repairs/ assistance and remote assistance.

Likewise, Walmart uses analytics from in-store and online sources to not only provide customers a seamless experience, but also to make better decisions for managing large volumes of inventory. WalmartLabs, the retailer’s digital innovation constituent, utilizes visualization techniques to study social activity to capture insights that may indicate variations in product demand. Walmart uses these insights to stock the extra inventory at locations where higher demand is expected and to reduce the surplus inventory at locations where lower demand is expected.

Because customers still shop at physical locations, it becomes important to have an integrated multi-channel strategy.

Additionally, the retail giant has also introduced technologies like RFID in its supply chain process. This has enabled Walmart to predict the demand patterns for uncommon products such as cake-pop makers and electric juicers by understanding their correlations with other products which have an impact on their demand. As per a research estimate from Capgemini, Walmart has been able to reduce its out-of-stock inventory by 16 percent through the application of such digital innovations.

Because customers still shop at physical locations, it becomes important to have an integrated multi-channel strategy. Local retailers seeking to increase sales activity can make use of geo-targeting by using location based apps send out promotional messages to customers within the vicinity or even to people in a competitor’s store. Retailer can also leverage the presence of customers searching through price scan apps in the store by devising and offering more focused promotions. Another approach common in use is to make the best use of store location by using the store as a show room and offering alternative methods for buying and offering same day pick-up.

The customer’s shopping journey, which once followed a simple sales pattern, has now been replaced by a complex relationship that stretches across several touch-points.

To take this further, consider Amazon, a pure-play online retailer in the home improvement category, and Lowe’s, a traditional home improvement retailer. Lowe’s, unlike Amazon, provides solutions to help customers along their home improvement journey. The customer journey in this case includes online, point of sale, phone calls to customer service, and professional services in a customer’s home. To accomplish this, Lowe involves mixing of digital and physical worlds. If a customer is shopping for a single item, the Lowe’s experience might be comparable to one at Amazon. However, when that item is part of a project, then Lowe’s differentiated service experience comes into play. This project-centric, omnichannel strategy is central to Lowe’s competitive positioning against Amazon and other retailers outside the home improvement segment of the market. The secret of Lowe’s success lies in its ability to guide customers and quality of sales services.

Omnichannel retailing should aim at providing a uniform brand experience like Lowe, but at the same time be cognizant of differing service level expectations across channels – as the same individuals won’t shop in the same manner across different channels.

Leverage cutting edge analytics across the board

The customer’s shopping journey, which once followed a simple sales pattern, has now been replaced by a complex relationship that stretches across several touch-points. This has resulted in large volumes of data and has made understanding customers and reaching out to them more complicated. There is a need to employ analytics in all domains and make data-driven decisions. A few dimensions are discussed below.

Understanding customers

As retailers compete to drive traffic to their stores and website what varies is how well each retailer understands its customers’ buying preferences, likes and dislikes, and how each retailer uses this knowledge to influence shopping behavior. Customer segmentation helps omnichannel retailers gather insights to pinpoint effective marketing strategies and deepen customer loyalty. With the number of marketing channels available to retailers today, careful segmentation has become a mandate for those who want to remain relevant, and has been shown to grow sales, reduce attrition and increase profitability.

A customer segmentation plan can help leverage the customer segment data to implement the following activities: creative messaging, revamping experiential benefits or reward structures, differentiation of offers, proactive retention, and deciding the frequency and cadence of customer contacts, customer service, and channel strategy.

Reaching customers effectively

To be dominant in the marketplace, data-driven analytics techniques help omnichannel retailers boost sales, develop a competitive advantage, cut costs, and most importantly, create a comprehensive view of the ideal customer. It can help accomplish otherwise tedious tasks like managing marketing campaigns where key performance indicators are specific to channels and visualizing profitability/ROI metrics that are segmented by channels, customer segments, content type, and other factors to ensure efficient use of marketing dollars.

Omnichannel retailers typically use both online and offline channels in tandem. Data analytics forms the backbone of list selection in all marketing campaigns run by the retailers. Multiple channels such as text, email, direct mail can then be used to create coherent messaging and matching offers across campaigns. The end result is a focused customer experience that avoids over-contacting premium customers while ensuring customized content and timing.

Data analytics also plays a role after the campaign rollout. It supports the evolution of campaign strategy through performance measurement, defining of KPIs specific to channel and campaign objectives, such as influencer reach for general social media campaigns, or repeat purchase behavior for discount campaigns. In addition, it aids in the development of clear profitability/ROI metrics across various dimensions, including overall, by channel, by customer segment, or by content type to ensure efficient use of marketing dollars.

Maximizing revenue

Another aspect where analytics can help omnichannel retailers is pricing. To keep customers coming back, many of the big retailers offer a price match guarantee. Walmart, eBay, Best Buy and others all offer a minimum price match guarantee. This is where most retailers struggle most because retention across the lifecycle is made more difficult by the lack of even knowing what is going on with competitors. An omnichannel strategy includes having access to product price and availability information, so the best price is the one customers see. Earlier retailers used to rely on barriers such as geography and customer ignorance to markup their prices and advance their positions in traditional markets. However, technology has removed these barriers. To embrace the competitive pricing model, retailers should consider implementing a dynamic price optimization of different customer segments based on real-time analytics of competitor prices and demand-altering macro factors such as holidays, seasonal events or trending fads.

Cross-channel integration for a seamless experience

Although traditional retailers have moved online, they haven’t integrated their online and offline channels, keeping each channel in isolation. This has resulted in the failure of online initiatives of many brick-and-mortar businesses. Take, for example, a retailer like Target. Almost 98 percent2 of their customers shop online, with 75 percent3 of the sales starting on a smart phone or tablet. In terms of omnichannel performance, almost 25 percent4 of all Target.com orders are either picked up in store or shipped from a store, which doubles to 50 percent5 during the year-end peak season. So, what does this mean when you look at how the shopper behaves when they enter the store for a pickup? Because each channel as a separate category, traditional retailers are limited to using the insights they can derive from one channel towards providing better experiences for others and don’t leverage the best of the possibilities.

Multichannel integration in practice—a scenario

An omnichannel setup can help customers by providing information about stock levels, delivery times and shipping options regardless of where within the retailer’s network they are situated. Whether the customers are in a physical store, on a computer or on a mobile device, the service levels offered are similar. For instance, the high street fashion store Oasis enables the customer to browse online, pay online and place orders through iPads online while in the store. Customers can choose to try an item on in store, and then order it online and have it delivered. The in-store staff can order out of stock items online for customers and help secure a potentially missed sale on the part of the retailer. Through iPads, shoppers can also search different stores for the out of stock item and get it delivered to their homes from the stores where it is available.

Oasis demonstrates a good example of how to integrate processes related to both customer-facing functions and back office functions such as supply chain management. However, to truly become integrated, logistics, supply chain, marketing, branding, payment options and the overall customer journey needs to be synced. The steps in offering a seamless personalized experience in the purchase process starts right from the stage of order processing. The key to enduring engagement here is to deliver a great user experience and give the customer reasons to move online. Once the customer is online, the ability to control access, manage an order, track order status and make changes on the fly eliminates phone calls and provides sales staff time for more productive purposes.

Back-end supply chain integration is equally important to increase business efficiency and provide a seamless experience. It starts with optimizing network design which includes connecting the locations and integration of various facilities used to meet different channels’ demands. This entails operational challenges such as the integration of inventory and transport, assortment management, the balance of the capacity of operations, the interconnection of picking operations and sales returns processing. A unified view of the supply chain from end-to-end, as well as inventory sharing across channels, is bound to improve efficiencies by optimizing fulfillment based on business rules such as inventory, service, markdowns, and revenue.

Segmentation and predictive modeling can help to minimize the cost, improve user experience, and reduce return policy misuse. Such an approach will help the retailer in their inventory optimization journey, as well as in anticipating inventory needs. Retailers will also be able to avoid ordering too large a quantity of certain inventory items, ensuring that their cash flow is preserved and that they aren’t weighed down by excess inventory.


While the hyper growth of online commerce has created many challenges for traditional offline retailers, emerging technologies and evolving customer preferences have also opened up new areas of opportunity. Thus, by leveraging their core strengths, becoming laser focused on the customer and mastering the full value chain of data analytics, traditional retailers have the potential to establish themselves as leaders in the omnichannel environment that will characterize commerce of the future.

The way forward is to match the experience of the local stores, where the storekeepers used to have a detailed understanding of their every customer’s proclivities and preferences, allowing them to provide a very personalized service, and make it available across the breadth of interactions spread geographically and across channels becoming a “local global store”.


Exhibit A: Characteristics of general merchandise retailers


1. https://etaileast.wbresearch.com/blog/customer-centricity-model-best-buy

2. https://www.smartinsights.com/online-brand-strategy/multichannel-strategies/omni-channel-reshaping-commerce/

3. https://www.businessinsider.in/More-than-6300-stores-are-shutting-down-heres-the-full-list/articleshow/59867729.cms

4. http://ebooks.capgemini-consulting.com/dm/Walmart.pdf


1. Quoted from “Business Insider” article published on August 1, 2017

2. Exhibit A: Characteristics of General Merchandise retailers

2-5. All these figures are based on an article published in MultichannelMerchant (Paul Mandeville, 2015)

Written by

Ankor Rai
Senior Vice President, EXL

Namit Sureka
Vice President & Analytics Practice Leader, EXL


Gaurav Lal
Senior Assistant Vice President, EXL Analytics


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