How Data Analytics Can Help Improve Customer Experience


Steve Cannon, former CEO of Mercedes-Benz USA once said, “Customer experience better be at the top of your list when it comes to priorities in your organisation. Customer experience (CX) is the new marketing” and it still holds true.

CX is quintessential to retaining customers and businesses of various industries are placing more importance on data analytics to better understand customer behaviour, preferences, and needs as this information can be leveraged to create better products and services. In this article, we'll explore how data analytics can help improve customer experience.

Customisation or Personalisation

Data analytics enable you to segment your customers based on their behaviour and preferences. By analysing customer data such as income level, purchase history, and values and segmenting them based on those characteristics, you can customise your products, services and communication to each segment, which translates into a great brand experience for them. To simply put, you know what makes customers happy and what ticks them off. As an illustration, a fashion retailer could leverage data analytics to recommend products based on a customer's browsing and purchasing history, eliminating the need for customers to search through a potentially time-consuming product catalogue.

The word “personalisation” is often and strongly associated with brands like Amazon and Netflix. Netflix has revolutionised the way we consume content. It uses a recommendation system that analyses customer data like viewing history and ratings, to curate content for its customers. It claimed that 75% of viewer activity is powered by recommendations. This content personalisation strategy has generated over USD 1 billion for Netflix. Furthermore, it utilises time-based KPIs such as viewing time and overall satisfaction to gauge its engagement and churn rate.

Aside from Netflix, a Fortune-500-ranked Malaysian oil and gas brand experienced success in customer acquisition through the use of data analytics. Its petrol stations and convenience stores suffered poor footfall traffic during the onset of the COVID-19 pandemic. During the recovery period, by using ADA’s Consumer Profiler, customer footfall trends were better understood, and different buyer personas were created, allowing hyper-personalised creatives and messages to be served to them. The campaign has led to high engagement and motivated consumers to patronise their stores.

Customer demand prediction

Predictive analytics can facilitate the ability to anticipate customer demands by detecting recurring patterns and trends that indicate what customers are likely to require or desire in the future. An example would be a financial services company using predictive analytics to anticipate a customer's financial needs at different lifecycle stages, offer personalised financial advice, and promote products or services based on his or her needs and financial state.  

It is imperative for luxury retailers to strike a balance between brand experience and elegance. To build and foster brand loyalty, a French skin-care brand, L’Occitane combines machine learning and predictive analytics to antedate what their customers might buy in their next purchase. Referring to their previous purchase history, returning customers might see a restocking suggestion based on the stock turn of the products they previously purchased. L’Occitane also created a sense of urgency to incentivise their customers to purchase sooner by showing them the fast-selling products on their website.

A large Vietnamese fashion retailer wanted to maximise reach to highly affluent women, explore consumer engagement opportunities, and identify potential store locations. With ADA’s Location Planner, we helped our client to identify potential store locations with a high concentration of target audience based on their age, gender, and affluence.

Besides that, this tool also helped an Indonesian commercial bank to assess the distribution of the Syariah segment as their target audience and map out the ideal locations to address their Syariah banking needs. The said bank has since integrated ADA’s Location Planner into their 5-year branch transformation blueprint.

Customer Service and Process Improvement

Data analytics facilitates the acquisition and analysis of customer feedback, providing valuable insights into areas that necessitate improvement. Customer feedback, obtained from sources such as surveys, social media platforms, and websites, serves as a first-party data source that allows for the identification of pain points and satisfaction factors.

During the early phases of COVID-19, the number of passenger count taking rail transit dropped. Even in the new norm, the passenger count was still approximately half of what it was before the pandemic. With ADA’s IFA-Targeted Survey, our client, a Filipino rail transit provider was able to identify the pain points of current commuters and reasons non-commuters taking alternative transportation options – to save time. With this insight, our client can focus on improving their service and win back the passengers who stopped using its commuters since the pandemic started.

It is a known fact that a customer’s complaint can be deemed as a gift in the service industry. How so? With customer service data, you can identify and proactively tackle the problems before they exacerbate. Additionally, you will be able to pinpoint the performing and non-performing customer service representatives who warrant more training or are probably caused by other factors such as time-consuming, manual processes that hinder their performance. For example, simple requests like account details updates and balance-checking can be done by customers themselves via online and mobile banking applications instead of customer service officers of a bank. This not only reduces the call waiting time for customers but also allows customer service officers to attend to other more complicated issues.

Ever wonder why Amazon consistently receives recognition for their customer service? The answer is big data and data analytics. Simply look at how they optimise their supply chain management. Their shipping optimisation allows their customers to select their preferred carrier and know the expected delivery time. Amazon heavily invested in its distribution infrastructure that allows them to offer same-day delivery and one-to-two-day ground delivery in the USA.

Delivering next-level CX with data analytics

Data analytics is transforming the way companies operate, attract, and retain customers. With an improvedunderstanding of customer behaviour and preferences via data analytics, you can customise your interactions and offerings to meet or exceed your customers’ expectations. Equip your business with the right data analytics tools and techniques with ADA’s data solutions today and you can take customer experience to another level while staying competitive.

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