As consumers become the centre of every business product and service, just providing an interface is not enough. Today, it should also add value and build long-lasting relationships with them. In my opinion, the consumer-facing internet would not have been possible without big data and analytics. Big data is enabling businesses to better interact with consumers, improve satisfaction and retention, and bring in more revenue. Here’s how big data and analytics plays a major role in meeting the high expectations of today’s digital customer – both in terms of usability and seamless, multi-channel access.
One of the biggest mistakes many businesses make is to assume that customers would take out time to sift through large amounts of content to get what they’re looking for. However, as customers get more and more tech-savvy, they expect interfaces to be as intuitive as possible – delivering the right content at the right time.
Big data and analytics help build context-sensitive user interfaces that automatically detect a user’s intent, deliver the right number of options needed on the screen at any given point and reduce the number of clicks or swipes required to carry out any given operation. With context-sensitive user interfaces using big data and analytics, businesses can provide their users with UIs that can adapt as much as possible to customer needs and helps in guiding them through the right pieces of content.
Zomato uses big data and analytics for a variety of tasks: from homepage customization to user personalization, intuitive search, among others. Since most customers have a tough time deciding what to order and from where, Zomato showcases context-sensitive options based on the user’s preference for specific cuisines, establishment types, locations, and price bands or what is most popular or new or exclusive at a given location and time. Such suggestions eliminate user effort, simplify the decision-making process while simultaneously reducing anxiety and shaping intent. By applying analytics to every interaction, Zomato is making the most of the countless opportunities to connect with customers, earn trust, and build value.
Customer experience is all about offering relevant data in the quickest way possible. If you get the data right, you can apply big data and analytics and shape the overall customer experience. Personalisation tools are great for showing people items they will like, but are unlikely to discover by themselves. They improve the overall experience by offering relevant items at the right time and on the right page. As Steve Jobs once said, “a lot of times, people don’t know what they want until you show it to them.” By analysing massive amounts of data, big data enables companies to learn about user preferences and offer personalised suggestions.
With a market value of $151 billion as of May 2018, Netflix leverages big data and analytics to a large extent for the purpose of content discovery; by highlighting as much of its content library as possible, Netflix has been able to increase viewership and lower churn. Tuned for extreme categorisation, Netflix can offer content to the exact people who would be interested in them. With global expansion, Netflix has now done away with the region as well as language-based preferences. As the user base increases, more data gets generated that strengthens the algorithm and results in more insights into user behaviour. The end result? Efficient content discovery and extreme personalisation that is enabling it to achieve its global ambitions.
With the growing amount of information on the Internet and with a substantial rise in the number of users, it is becoming really challenging for consumers to get to information that interests them and increasingly important for companies to offer information according to their tastes and preferences. Big data and analytics power modern recommendation engines that make use of algorithms and data to recommend the most relevant content to a particular user. By 2020, 51% of consumers will expect companies to anticipate their needs and make relevant suggestions before they make contact.
Amazon Prime’s recommendation engine is a major driver for Amazon’s stunning revenue growth and successfully integrates recommendations across the buying experience – from product discovery to checkout. The retail giant’s big data and analytics algorithms take cues from just a few elements, namely users’ purchase history, items in their shopping cart and items they’ve viewed, rated and liked. Amazon displays the most relevant products in real-time and delivers a personalized shopping experience.
Recommendations are especially important in e-commerce, as rare, obscure items that are not very popular and don’t drive a lot of revenue end up being overlooked. Using big data and analysis, Amazon is able to recommend these items to shoppers and enhance the potential of ROI on slow-moving inventory. By enhancing their online store’s user experience with personalissed recommendations, Amazon is able to drive better product discovery and improve sales.
Gain Customer Loyalty
As companies struggle to improve their time-to-market deliveries, they end up delivering products and services in haste. However, such products don’t generally scale and deliver the performance users expect. Since today’s modern applications are inherently used by many people, offering personalized user experiences is more than essential. 72% of consumers expect companies to understand their needs and expectations.
Customer success today goes beyond offering solutions in unique moments of need. Despite the millions of dollars which businesses spend on improving customer experience, there is a huge gap that puts a strain on customer service channels as well as on customer relationships. To deepen customer engagement and stay ahead in this constantly evolving business environment, businesses need to dig deeper and serve customers in each individual moment. Consumer-facing internet is quickly becoming a great way for businesses to connect and communicate with customers. By creating an experience that will help increase engagement and satisfaction, businesses can gain customer loyalty and achieve more sales and revenue.