The way buyers shop and their expectations of services, personalization, and communication are ever-evolving, brands need to keep up with the trends. They need to stay at the forefront of ecommerce experiences if they want to succeed.
Aligning content with the customer’s journey is critical. As every person is unique and needs individual attention, they expect a focused, highly personalized approach rather than a generic “one-size-fits-all” approach. There are numerous personalization-at-scale examples that prove this idea. You will truly enhance your customer experience and optimize conversions by getting mass personalization right.
How Data can help in Personalization at Scale?
There are numerous factors to consider when creating excellent customer experiences— personalization, delivery, inventory, customer service, and more. All of which, of course, rely on data. Data is the most valuable asset for every business in the digital age. Companies can use analytic techniques to maximize customer lifetime value, protect existing revenue streams and create insights for the organization to take forward.
When brands can understand the critical drivers of customer (online) behaviour and pinpoint why some customers may be buying from competitor brands, they can find ways to compete effectively and accelerate innovation. Such insights can create new and improved business models, loyalty programs, or new incentives.
This is a virtuous circle. If customers have their expectations met, they will be more willing to share their data with companies to get even more personalized experiences in the future.
How to Personalization at Scale can Boost Conversions?
Brands can optimize growth and further elevate their ecommerce experiences with sophisticated personalization features. Data can be used to show the path a customer takes from search to purchase in real-time, with a number of suggestions being made to them throughout their journey.
Specific product types can be narrowed down and recommended in colours and styles that best-suits customer preferences. This hyper-personalization at scale can stay with them, even if they leave the site, to remind them to follow through with the purchase of products they’re interested in at a later time.
Personalized landing pages based on behaviour can target returning customers to show them products and services they might be interested in. Brands can choose to add specific customizations like pop-up campaigns, offering incentives in return for customer data.