Business & Strategy

Knowing the new-age customer

By mining customer data and generating actionable insights, companies can craft marketing strategies relevant to the digital age

Updated: Aug 17, 2016 02:42:27 PM UTC

Concentrix, a wholly-owned subsidiary of SYNNEX Corporation (NYSE: SNX), is a leading business services company. We focus on customer engagement and improving business outcomes for over 450 global clients across 5 continents. Our 100,000+ staff deliver technology-infused, omni-channel customer experience management, marketing optimization, digital, consulting, analytics and back office solutions in 40+ languages from 125+ delivery centers. We serve automotive; banking and financial services; insurance; healthcare; technology; consumer electronics; media and communications; retail and e-commerce; travel and transportation; and energy and public sector clients. Visit www.concentrix.com to learn more.

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Safaricom, the cell phone company behind M-PESA, has extended the same platform to offer its customers M-SHWARI, a cell phone-based savings account (Photo: Adwo / Shutterstock.com)

Today’s marketplace is rapidly going digital, thanks to a tech-savvy and very mobile customer base. The profile of the traditional customer has been changing; in less than a decade, customer expectations have transformed quite radically. No longer are customers willing to tolerate long waits, slow response times or poor service. They are well aware that the market place is extremely competitive, and with the click of a button they can find someone else willing to do business with them on their terms.

Even well-established companies are waking up to the fact that they cannot rest on past laurels. A few decades ago, they might have been assured of customer loyalty based on their reputation or because they were one of the few providers of a particular product or service. But economic liberalisation helped open up the market and competition flourished. In the decade thereafter, technology changed the market landscape yet again.

In the last decade, many established players have often been caught unaware by young startups that launched their business on a digital model. These upstart companies have the advantage of having been born into a digital world; they understood the habits and preferences of the digital generation, which make up a large part of today’s customer base. The new age customer is more extravagant in her spending habits; a large part of these young customers’ disposable incomes go into the market unlike the older, traditional customer who tends to be thrifty. This goes to show that identifying and knowing customer demographics is paramount today, if companies are to retain and expand their market share.

As companies realise the importance of knowing their customers, they are re-examining their marketing techniques and turning to technology to help them in intelligence gathering. There is plenty of information available about customers (actual and potential) in the form of unstructured data coming from non-typical sources—social media, for example, can be a source of huge amounts of data in the form of tweets, posts, reviews, etc. The challenge for companies is to mine this data and generate actionable insights.

Big data in the digital world can be likened to water; essential to survival (in the marketplace) but if not managed and harvested appropriately, the deluge goes down the drain, or even worse, can cause damage and destruction. Analytics is the set of processes and tools to help make sense of the data deluge.

CXOs looking to consolidate or expand their market share are turning to customer analytics to help them build a detailed and intimate profile of their customers. Big data analytics helps companies in their effort to understand consumer wants, needs and motivations in a granular fashion, so that they can craft a marketing strategy that is specific to their product and market segment. Using analytics, companies can slice and dice their customer data in a variety of ways, enabling them to gain valuable insights that might have otherwise remained buried in vast data stores.

For example, an e-commerce apparel retailer analysing customer demographic by age may find that 70 percent of revenues come from customers under the age of 35. This data point can allow them to manage their inventory more efficiently by stocking more items in the fashion category and reducing stocks in other categories that have low volume of sales. Furthermore, they may also find that most of this under-35 demographic shops on mobile devices, rather than computers. This insight might motivate the company to invest in IT to improve the mobile experience (quicker loading of pictures, not too much cramped text, etc.).

The use of analytics does not end at the point of sale. It continues, so companies can create a superlative customer experience, thereby retaining customers and also adding many more, through word-of-mouth, positive reviews, and so on. For example, they may note a particular style of clothing has a high rate of return. If they dig in and analyse the root cause, they may identify the reason as poor fit or poor quality. This allows them to take corrective action quickly before they lose more sales. They may alert the designer/supplier so alterations can be made, or they can add more product detail (like a size chart) that allows customers to better gauge the appropriate fit. In other words, they are looking to make the customer experience as smooth and hassle-free as possible.

Another benefit of big data analytics is improved campaign management. Companies can use data insights to reach the customer in the most effective manner. For example, rather than sending repetitive weekly emails that tend to get routed to the spam folder, marketing teams may come to the conclusion that rather than email, alerts about deals or discounts on shopping or restaurant apps or sites will get more eyeballs by reaching customers who are actually looking for their products or services. Analysing search histories of customers allows companies to dynamically target their ads to customers who are searching for similar items. For example, a customer who has searched for a dining table is a good prospect for other furniture and home/kitchen items that are relevant to setting up a new home.

Online retailers are using customer insights to provide customers the tools that they need to make their shopping decisions easier. If they are shopping for a large appliance, the decision to spend a large amount of money is made easier if they have access to unbiased reviews from other shoppers. Tools that help them compare different brands and features (e.g. size, capacity, energy efficiency of a refrigerator) gives customers a sense of confidence and comfort, and a high likelihood of a successful sale.

With a thorough understanding of the benefits that Big Data can bring, companies can put together a strategy to procure and manage customer data that helps them provide their customers a better experience that starts pre-sale and continues on well after the sale. And that process starts with having the right data analytic tools and expertise to manage and channel mountains of big data to give them the advantage in a hyper-competitive and globalised market.

-By Rick Rosso,  Senior Vice President, Global Sales & Account Management

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