Today we live in a digital economy with diverse consumer expectations, preferences, and buying patterns. As a result, retailers are discovering that they need to adapt and engage with their customers in a more personalized and targeted manner. Research reveals that personalized engagement with customers results in a significantly higher shopping basket with a nearly 40% chance of customers spending more than originally planned. More shockingly, Gartner reports that brands can lose 38% of customers due to poor marketing personalization.
While a few brick and mortar retailers have taken the leap towards personalization, many are still in the early stages of reorienting their business models towards offering personalized experiences. Most studies indicate retailers are nowhere close and lack a robust personalization strategy. According to BCG’s Personalization Maturity Index, even the best-in-class retailers rank in tier two, and no retailer has so far excelled to rank in tier one to deliver hyper-personalized or highly connected experiences.
Given the current maturity levels, retail enterprises have little choice but to utilize every tool in their digital technology arsenal to deliver to the promise of their customer’s personalized experience.
The 4 Steps to Personalize Retail Experience
The consumers in this digital technology age respond well to two key features – engagement experience and rapid fulfilment of products & services, delivered at a price which is perceived to provide best value for money. In this context, retailers today find themselves in a complex environment which requires them to operate across digital channels, with an unrelenting focus on personalization, seamless experience, operational efficiency, and superior customer service. In this quest, retailers have realized that next-gen digital technologies and data analytics need to be complemented with a flexible supply chain and streamlined processes, to achieve omni-channel success in a digital economy.
Organizations that wish to develop mass-personalization capabilities need to consider four key components – data capture, analytics for insights, supply chain aligned with insights-driven strategy, and data security and customer privacy of the vast personal data gathered in this endeavor.
- Capturing Context-Rich Customer Data
For a long time, achieving enhanced personalization has been a slow and uncertain process, since the quality of data is rarely as good as the analytical capabilities. Capturing the right data at the right time is crucial to unearthing meaningful customer insights. With the right data, organizations can convert prospects by offering them personalized offers and engage the customers at the right time. These offers are most effective when they are based on demographics, geospatial analytics, customer preferences, and buying needs, all of which can be acquired through a robust data capturing approach.
Costco is a good example of data capturing done right. The company maintains a very successful membership program for its customers. The deep-rooted loyalty program has enabled Costco to capture reams of customer data even before big data became the marketing buzzword. Though Costco has never been on the leading edge of digital retail, it has built a strong foundation of customer data. The company uses it effectively for communication; for example, food contamination alerts only to customers who purchased specific items.
This data capturing process can be further enhanced with digital channels, customer profiling, and tools like in-store sensors, that allow an even more granular data gathering capability and enable far more effective personalization. This results in greater sales conversion through cross-selling, up-selling, and bundling of products and services.
Retailers are exploring novel ways of data capture to understand and capitalize on customer intent. For instance, Lowe’s has been using Pinterest over the last five years to help potential customers visualize home improvement products, and gauge customers’ future intent based on their position in the buying journey. It serves curated pins based on the user profile, as well as past purchase transactional data. This has helped Lowe’s uncover insights on the customer journey, interests, buying triggers, relationship between Pinterest interactions, and traffic to the physical stores.
- Deep Analytics for Actionable Insights
If relevant data is the fuel, right analytics solutions are the vehicle to unlock actionable insights for personalization at scale. Retailers can strategize their personalization journey by deploying solutions that derive insights from multiple touch points, for instance websites, POS systems, mobile applications, in-store interactive systems, and other sources along every customer’s retail journey. Combining specific customer data with cognitive technologies based on machine learning, retailers can define predictive retail strategies that delight customers and maximize their customer experience. Offers that target the right part of the sales cycle are able to generate greater personalization and higher sales conversion ratios.
"Becoming more personal will al start with the power of our data" says Kevin Hofmann, President of Online and CMO at Home Depot. As part of its ‘One Home Depot’ omni-channel strategy, it uses 1.7 trillion data points generated per week from 50 million active households. It uses mobile location technology to understand traffic patterns, and over-penetrated and under-penetrated neighborhoods. It also leverages data to create a single view of customer through its ‘My View tool’ at is Pro sales desk, that gives store associates a view of the customer’s spending pattern, and offers product recommendations.
With access to customer buying history and buying behaviors, retailers can refine their omni-channel customer experiences. The integration of the entire gamut of information from different digital channels creates a unified view of the customer that allows retailers to achieve higher customer engagement and greater revenue. A case in point is Best Buy which has reinvented itself by focusing on the buying history and lifecycle of its customers.
- Creating a Flexible Supply Chain
Combining relevant data with cognitive tools yields actionable customer insights and provides a tremendous opportunity to create hyper-personalized experiences. However, delivering ‘personalization at scale’ calls for reinventing the supply chain to make it more predictive and responsive to consumer needs. Retailers seeking mass customization are now leveraging technologies like augmented reality and artificial intelligence to make their supply chain more flexible and agile.
The impact of customers entering the purchase funnel at multiple touchpoints is most profound on the apparel sector. Faster apparel launches are now becoming the norm. Smaller niche online-only players are bringing manufacturing closer to their distribution outlets, reducing lead times, and increasing stock churn rates.
Stich Fix is an excellent example of a born-digital company bringing a personalized experience closer to the customer. It has re-invented the paradigm of clothing with an integral personal styling delivered at a cost and time that customers value, and has led to the company making profits as early as 2014 after it was launched in 2011.
Traditional retailers are rediscovering themselves as well like Nordstrom Local, as virtual stores with zero inventory and a logical extension to BOPIS (Buy Online, Pickup in Store). Zara is another example of a nimble supply chain, churning out new stocks bi-weekly to its global store network. The company uses the data from its online search box as a powerful tool to understand customer intent and new trends. It uses these insights to launch new products aided by aligned technologies, to reshape the supply chain. It is investing in digital technology solutions for predicting consumer behavior, robotics for stock handling, computer vision to optimize inventory management, and much more. The need for reinventing and creating an agile supply chain is equally important in all retail sectors, in this age of digital economy.
- Data Security and Customer Privacy
And while the three steps of capturing data, deep analytics, and aligning supply chains remain critical to the growing digital retail sector, customers are wary of sharing and the misuse of their personal data. Hence there is a fourth step: the ethical and responsible use of customer data. Please join me in Part 2 of this blog post, to learn about how retailers can achieve personalization at scale, while ensuring data and privacy protections.