Customer Lifetime Value (CLV) is an important metric that e-commerce companies use to measure the value that they can generate from each customer. As the world has turned towards online shopping due to the ongoing pandemic, it has become important for e-tailers to monitor and grow their CLV.
What is Customer Lifetime Value?
It is the total amount of money spent by a user with a brand during his/her customer lifetime. This is from the user’s very first purchase from the brand to the last before he/she drops out and doesn’t buy from the brand again. For e-commerce, the CLV is the total revenue generated by a single customer.
An e-consultancy survey done in 2019 stated that various tactics were employed by companies to boost their CLVs. These tactics mainly involved the usage of new and innovative marketing technologies, machine learning, and Artificial Intelligence (AI).
CDP: A Data-Driven Approach to Boost Customer Lifetime Value
In this COVIDian era, Customer Data Platform or CDP has grown in prominence in assisting e-commerce marketers to radically boost their customer lifetime values.
A CDP is an innovative martech tool that uses a data-driven approach. Its primary feature is to aggregate and stitch together first, second, and third-party customer data in one location. The data is unified to present a single view for each individual customer. This means that e-commerce marketers can unify first-party customer data, second-party data generated from their partners, and third-party data from other third-party websites in a central data hub.
The single unified view helps marketers in deriving valuable customer insights that can help them in designing personalized campaigns for each customer. There are 3 ways that e-commerce marketers can employ to grow their customer lifetime value using a CDP:
1. Customer Segmentation
As a CDP brings together customer data in one place, it gives a holistic view of the customer which includes all kinds of details such as their buying propensity, purchase history, etc. Based on these parameters, e-commerce marketers can categorize or segment customers into various buckets. These buckets can be termed as first-time visitors, returning customers, cart abandoners, high-value customers, big spenders, frequent shoppers, discount shoppers, festival shoppers, shoppers who purchase only during a major sale, etc.
Based on these buckets, marketers can devise customized campaigns that will appeal to each customer segment. This will help in attracting more customers to the e-tailer’s website as well as increasing their respective CLVs.
2. 1:1 Personalization at Every Step of the Customer Journey
A CDP can be coupled with AI to tailor 1:1 personalization for each and every customer. If an e-tailer has 1 million customers, each of these customers can be given their own unique personalized journeys. This is mainly possible due to the unified view generated by the CDP for every user. Using machine learning algorithms, marketers can craft highly personalized campaigns and deliver them individually to each customer.
Whether it is cross-sells/up-sells or back in stock alerts or cart abandonment reminders or collecting feedback, 1:1 personalization can be delivered at every step of the user journey for both anonymous and existing customers using a CDP. Therefore, whenever a customer receives a 1:1 highly personalized offer from her brand, the chances of her making a purchase are more, which, in turn, boosts her CLV.
3. Customer Channel Behavior Tracking
Tracking a customer’s online-offline channel behavior informs the marketer about his/her brand interaction preferences. There will be customers who prefer interacting with e-tailers on certain online channels such as email or Facebook. Some of them might prefer to restrict their brand interactions via the brand’s mobile app. There are others who rarely use an online channel but frequently visit the company’s physical stores. Lastly, there will be customers who use a mix of both online and offline channels to interact with an e-commerce brand.
A CDP can help marketers in tracking these channel behaviors on an individual customer level. So if a customer named Andrew prefers using the mobile app and email, his single unified view in the CDP will show these channels as his preferences. Using AI, he can be targeted by his e-tailer only on these 2 channels. This feature is called AI-driven Channel Orchestration. In this way, Andrew gets a positive impression about his relationship with the brand. Hence, his customer lifetime value is bound to increase here.
The competition has been extremely fierce in the online e-commerce space in the past 1 year. As e-tailers grapple with the intricacies of doing business completely online, the customer has become all the more picky when it comes to their experience and satisfaction. This has resulted in an increase in the overall customer acquisition cost and a decrease in the customer lifetime value.
Therefore, it makes perfect sense to invest in a tool like a CDP to understand what the customer exactly wants and deliver it at the right time and on the right channels. The 3 measures mentioned above explain how e-commerce marketers can efficiently utilize a CDP to boost their CLVs and focus on considerably improving the financial health and growth of their organization.
By Bijoy K.B | Marketing Manager at Lemnisk