Putting your customers first and delivering valuable, personalized experiences gives your business a competitive advantage. In fact, 80% of companies report an uplift after implementing personalization.
But, in order to put the customer at the center of your strategy, you need to put customer data at the center of your organization. When customer data lives in multiple systems, owned by different departments, your customers will likely have a disconnected experience. This can slow their purchasing journey and become a major barrier to improving perceptions of your brand.
So, how can you use data and analytics to drive a better customer experience? And is automation the answer to maximizing the potential of the data you’re gathering?
Make use of useful data
Just capturing data about your customers’ preferences and interactions is not useful on its own. Instead, you need to find a way to analyze customer data to provide insights for personalization.
First, your data must be unified so that it’s accessible and usable by various teams across your organization. This will make things easier when it comes to analysis, as all the data you need to review is in one place.
However, as your data volume increases, it can be difficult to integrate and operationalize your customer data to ensure that it is usable.
The platform for success
This is where Customer Data Platforms (CDPs) come in. They can help you unify your customer data in a single repository, as well as supporting segmentation, decisioning and activation.
CDPs ingest customer data from many sources and combine it into a single view of the customer. You can then use contextual and behavioral datapoints to identify a customer’s next-best-action and show them relevant content or offers based on this information.
This insight enables you to act rapidly on key trends and create a personalized journey for your major user segments – giving you the power to delight customers and secure their business.
Machine learning is a critical component in scaling personalization. Integrating your organization’s customer data with AI and ML scoring models can enhance your personalization efforts and enable more efficient marketing campaigns. It can help you transform data into future insights, and reach more user segments.
Salesforce’s recent state of marketing survey captured a huge leap in the use of AI, with 84% of marketers in 2020 using artificial intelligence in their jobs (up from 29% in 2018). That’s a nearly three-fold increase in just three years. The same respondents said ‘personalizing experience in an individual channel’ was their number one reason for using AI.
Sophisticated marketing teams are starting to embrace more advanced AI use cases to optimize their campaigns and to syndicate content across multiple channels. AI scoring models can be used to identify an organization’s customers that are likely to convert and then improve the efficiency of campaigns by excluding customers that are least likely to convert.
AI algorithms can also help to uncover new opportunities by identifying segments that a human may never conceive – all while freeing you up to focus on overarching strategy and creative tasks.
The right content at the right time
Once your connected customer data is integrated with AI/ML, as part of your wider personalization strategy, you’ll be on your way to a dramatically improved customer experience. You'll be better prepared to deliver the right content to your users at the right time – creating experiences that keep them coming back for more. And when you exceed your customers’ expectations, you’ll start to exceed internal performance expectations too.
To find out how data, analytics and AI can help you go beyond what’s expected, get in touch with one of our experts today.
Jonathan Corley, Head of Sitecore’s Business Value & Strategy team for the Americas, leads an innovative team of value engineers and digital strategists. Find him on Linkedin here.