Rewiring the Customer Journey: Using Analytics to Create Lasting Brand Experiences
By Arijit Banerjee
Today’s customers expect high quality customer experience to be delivered consistently - across multiple channels. According to a Capgemini study, eight out of 10 customers in several countries across the world, including India, are willing to pay more for better customer experience. So, how can companies better engage with their customers and offer an exceptional experience at every step of their journey?
Enter customer journey analytics. Leveraging big data across customers, channels and touch points, journey analytics zeroes in on areas of improvement. Using customer behaviour analyses and channel opportunity scans, organisations can redesign customer journey for enhanced end-to-end customer experience.
Here are three ways customer journey analytics can help companies create delightful customer experiences every time.
1. Understand customer emotions and identify gaps in the customer journey: As customers move from one touch point to another, it is critical to understand how they feel at each point. Journey analytics includes sentiment analysis at every touch point. For example, it can help identify if the customer was able to switch seamlessly from a social media channel to a voice channel or vice-versa. These moments of truth can help brands address specific issues with accurate information and optimise customer journey practices.
In addition, through journey analytics, companies are better equipped to understand the gaps in customer communication. This helps pin point specific interactions and link it back to customers, eliminating bottlenecks in their journey. Bloomberg, for instance, sifts through interactions between employees and customers using emotion analytics to better understand customer sentiment and prevent market abuse.
2. Enable personalisation: Leading Indian companies such as FlipKart, ShopClues and Paytm are leveraging machine learning (ML) for deciphering customer purchase cycle and predicting their next purchase. This has helped them craft promotions for serious buyers, refine customer queries, and ensure a rapid and seamless check out process. Lesson to learn: combing journey mapping with customer behaviour analyses and machine learning algorithms help improve the bottom line by enhancing customer experience, increasing sales, and generating customer retention. Providing personalised product offers based on the past customer interaction with the brand is yet another way to inspire customers to take desired actions.
3. Reduce customer churn and capture new customers: Identifying customers at risk and reducing churn are critical to organisational success. Data-driven understanding of customer preferences allows companies to identify opportunities for improvement and reduce customer churn. Companies such as Zivame and Arvind Limited are using analytics to better understand customer preferences and target customers. The result: enhanced market traction, customer loyalty and reduced cost of customer acquisition. Journey analytics also provides an opportunity for businesses to translate product preferences, customer lifestyles and behaviour, into focused campaigns that increase new customer acquisition.
Developing expertise in customer analytics through training can help employees identify and activate the best path to maximise customer lifetime value. Identifying high value customers, in turn, enables companies to not only create a unique engagement strategy but also identify points where customers abandon their journey. The outcome: sustainable and targeted customer engagement programs for a robust bottom line.