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Big data: the key to building a customer ‘footprint’

Leveraging consumer data is critical to maintaining and building a customer base as outdated methods of customer profiling quickly become obsolete.

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Data says a lot about a customer’s purchasing behaviour, but brands need to also recognise the power of what is being unsaid by existing data. Focusing on filling these gaps is the real secret to creating authentic relationships with customers, because this positions the brand powerfully in knowing and meeting needs and wants without customer’s necessarily expecting it.

As the Australian retail industry becomes increasingly competitive, the ability of an organisation to engage with customers by delivering seamless experiences will be the key to giving retailer’s a competitive upper hand. More and more multi-nationals are setting up shop on Australian shores, and are bringing with them highly sophisticated technologies and techniques to delight customers.

A recent survey found only five per cent of Australian businesses have ‘Customer-360’ initiatives as their data-focused priority for the near future. This is a figure that requires significant improvement in the changing context of the Australian retail landscape. In order to keep up with the pace of change, local businesses need to invest in leveraging data to gain a deep understanding of their customers. This understanding will arise from multidimensional customer profiles, which are essential to deliver the experiences customers now demand.

Amazon is a key example of an organisation that is pioneering customer profiles for business growth. It’s been estimated that as much as 35 per cent of its bottom line is due to its recommendation engine, a portal which generates purchase ideas for customers based on buying behaviour, preferences, and anticipating wants and needs.

Using data to build customer profiles will converge the numerous channels by which a customer interacts with brands — social media, online, entertainment and leisure preferences, as well as physical movements — and integrate them to illustrate the full customer journey and profile, personalised to each individual.

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Out with the old, in with the new

A traditional approach to customer profiles that neglects to focus on recommendations, or that doesn’t adjust its journey based on the preferences of individual customers through leveraging data, is incomplete and quickly becoming obsolete. This is not an abstract business concept, but a problem that has real-world implications. For example, retailers such as Blockbuster and Borders incorrectly conceptualised their customers, and through not taking on the appropriate form for market context, ultimately didn’t survive the high-stakes game of customer engagement. A data-based technology such as predictive analytics can aid in examining and anticipating future customer behaviours, wants and needs.

Working in tandem with predicting future behaviours, businesses must also focus on creating customer profiles using different types of data holistically. Organisations should be tracking aspects of their customers’ digital footprint such as social media activity, browsing habits, mobile application downloads, past purchases, entertainment preferences, and so on. Understanding customers’ digital footprints is vital as businesses will have the opportunity to build individualised strategies around these unique insights. Doing so will enable businesses to form a true view of the customer.

The role of big data for customer profiles

In addition to relying on outdated data, companies too often only use a fraction of the data in their possession. The ability to condense and intelligently leverage this data to personalise outreach to customers should be a top priority, as global incumbents enter the Australian market.

Data typically exists across siloes, which involves both online and offline aspects of the customer journey. Location intelligence is one example of how data can improve customer profiling. Retailers can now geo-target customers with automated offers based on location and previous purchasing behaviours, demonstrating the correlation between online buying patterns with an increase in foot traffic.

Leveraging such real-time, multidimensional profiles that capture all footprints customers leave will ensure retailers will be able to make clear sense of their customers’ data, derive meaning from it, and act upon it.

Balancing privacy concerns with business objectives

There are challenges that businesses have to be aware of after implementing a data strategy to create customer profiles. Specifically, these challenges lie in customer privacy and regulatory issues. Customers are aware of what their personal data can be used for and oftentimes issues become apparent when large companies use and have access to supposedly private data with little perceived reward to the customer.

However, studies have shown that customers’ resistance to data collection becomes negligible once they receive clear benefit from the interaction, or when they are interacting with brands they trust. A recent study of millennials by Columbia Business School found 75 per cent of respondents were willing to share data such as mobile phone number and date of birth with companies in exchange for a product or service they value, or with a brand they trust.

Customers are eager for increasingly authentic relationships with their favourite brands, including greater convenience and better targeted offerings. Data analytics allows businesses to give these sought-after experiences to customers, promoting loyalty and establishing a competitive advantage in the tight race for shoppers’ dollars. It is up to companies to leverage the data systems available, developing strategies to engage with and understand their consumers, and build multidimensional customer profiles which improve the relationship between company and consumer. The natural exchange of data will then continue to be of mutual benefit.

By Gaurav Sharma, Head of Products and Resources, ANZ, Cognizant

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