Businesses either need to learn to leverage customer insights and quantify the business influence of customer experience (CX) initiatives or discover themselves in a vulnerable position. A report from Adobe revealed that companies considered “CX leaders” were three times as likely to have exceeded their business goals. Customer experience is competitive in every industry, from finance and insurance to healthcare, logistics, and education.
Customers expect seamless, frictionless, and personalised experiences but with the human element intact, powered by Big Data. As innovative technologies emerge, many enterprises incorporate them to enhance customer experiences.
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The following sections explain how customer-centric data analytics techniques are the latest competitive benefit.
Growing Datasets Promotes Better Customer-Centric Data Analytics
According to Salesforce, 80% of consumers say that a company’s experience is as vital to them as a brand’s products or services. But grasping, analysing, and working on customer understanding has long been a challenge for institutions. While “small data” has been available through sales reports, web analytics, and social media reporting dashboards, multiple organisations stumble in securing transactional insights with emotions.
And as communities have become more digitised, the story of customer data available has grown exponentially in just a fleeting time. You can also collect meaningful data about your customers by integrating mobile app usage, location data, and chatbot interactions.
These tracks connect to seize tons of raw data retaining beneficial insights into where and how customers like to engage with labels. Here are some instances of how brands use Big Data analytics to enhance customer experience:
- Understand Evolving Consumer Expectations: Customer behaviour and expectations have varied dramatically over the past few years. Amid the COVID-19 pandemic, consumers developed in response to the rocky, unprecedented time.
- Break Customer Experience Silos: Today’s marketers, sellers, and customer service experts encounter enormous pressure to reimagine traditional roles, break down silos, and apply recent technologies to provide differentiated, digital-first customer engagement.
- Traditional organisational standards: Marketers concentrate on one stage in the sales funnel or one area, such as email marketing or lead generation. In contrast, sales and service teams each did their own thing. Now more than ever, it’s crucial for all customer-facing groups to have a cohesive knowledge of a customer’s journey to provide a consistent end-to-end experience.
- Utilising Big Data Analytics to Improve Service: Customer feedback can inform processes for handling issues moving forward or improving products and services.
- Personalisation: McKinsey reports that personalised marketing increases revenue by at least 5% and increases marketing efficiency by at least 10%.
Understanding customer needs throughout complex journeys requires data analytics
Big Data analytics extracts the guesswork for comprehending customer requirements, pain points, goals, and interests and forms total visibility into the buying cycle.
Companies can now examine thousands of real-time data points, allowing them to understand their consumers in context. For instance, by leveraging AI-enabled analytics tools, marketers can study insights to understand their performance, such as
- What makes some products more popular among a particular age group or demographic
- What can they do to increase the number of leads generated by their marketing campaigns?
Institutions can also gain complete visibility into the customer journey by examining transaction data, purchase histories, social media insights, market trends, and environmental conditions. This lends sense to which factors triggered certain events. Companies now create super-specific customer segments and precisely target each group, optimising customer interactions by serving personalised content and communications at every touchpoint.
How can AI (Artificial Intelligence) & ML Improve Customer Experience and Data Analytics?
Artificial intelligence has transformed how brands connect with customers, making creating personalised experiences and nurturing long-term relationships easier. AI and ML are being embraced increasingly by businesses to bridge the gap between high-volume, high-speed data and the capability to use that data to entertain customers in real-time.
For marketers, obtaining more automation into the mix is huge. Over the past several years, marketers have collected more customer data and a growing list of duties. The advent of AI-enabled platforms allows marketers to recover some of their time by eliminating ad hoc manual efforts.
What Are Different Industries Doing with Data Analytics?
AI tools allow institutions to leverage real-time insights to entertain customers browsing a brand’s website. Brands might provide content that speaks to particular pain points.
- As a result, AI is increasingly used in sales to score leads and analyse which tactics have historically performed well at various sales process stages.
- Banks use Big Data analytics in the financial services industry to provide relevant offers to customers by examining milestones like weddings, births, college, home purchases, and retirement.
- Big data analytics in healthcare provides personalised patient journeys and enhances health results. As customer expectations continue to achieve new heights, a data-driven customer experience is no longer the exclusive domain of tech giants and well-funded businesses.
- Banking, retail, insurance, healthcare organisations, and numerous other sectors compete on experience. Without Big Data analytics, rising CX challenges won’t get any easier.
In a Nutshell
Data analytics is the most effective technique to stay abreast of today’s customers’ rapidly evolving needs. You can keep your business afloat by analysing commercial and consumer data, including trends and feedback, coupled with your company’s operations. To cater to your customer’s needs at all stages of their journey, you must have the right insights and interpret them correctly.
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