Retailers can now use AI-based personalization to access vast amounts of customer data. You can create personalized customer experiences using customer data.
Data capture through upselling and retention has changed how retailers interact with customers and prospects. According to McKinsey & Company, personal data based on user experiences and interests can deliver five to eight times the ROI of marketing spend and increase sales by 10% or more. But this requires a clear strategy built on a solid technology platform.
Ensure Data Quality
In every customer interaction, valuable data is gathered to help retailers create targeted personalized experiences. However, to properly use data, the technology used to improve customer engagement must be carefully processed and scrubbed. If data isn’t properly leveraged, the next customer interaction may be the last.
We see issues for retailers who collect and use customer data because it comes from multiple sources and can be tainted. For example, you may have gathered valuable customer data from dozens of marketing campaigns over the years. But without knowing where it came from, it may be inaccurate or out of date.
Too much data
Is there such a thing like too much data? Regan Yan, CEO of Digital Alchemy, said:
“Consider 700,000 customers, 878 products, 130 promotions, and 50 content communications. You could have 35 billion+ unique conversations with your customers.”
Making data actionable is critical to increasing engagement and revenue. For retailers, the goal is to mine massive amounts of data, find relevant information for each customer, and deliver hyper-personalized experiences that inspire action.
Data gaps or omissions
There is need for quality data is to engage customers. You may cause more harm than good if you don’t know where the data came from. The best way for retailers to use customer data is to micro-segment their audience because personalizing for everyone is personalizing for no one.
Using progressive web apps (PWA) can help you collect better data and break down information silos. “PWAs combine the high-converting features of an app with the web’s wide reach,” says Mobify.
Breaking down information silos is another way to improve data quality. A personalization tool that unifies data sources gives you a holistic view of the customer.
According to a 2016 IBM study, the annual cost of poor data quality in the US is $3.1 trillion. Poor data clearly has a negative impact on retailers. Visualize the consequences of targeting a specific customer with incorrect data. You may lose that customer.
Quality data allows you to segment and personalize customer engagements, turning them into lifelong fans. Want to keep customers happy? Look for technology solutions that produce highly accurate customer data.
Diverse data sets
Most companies have customer data in web forms, emails, marketing automation, mobile apps, IoT, and CRM systems. Customers’ data volume grows with the number of customer touchpoints. Because 73% of consumers shop across multiple channels, retailers must use technology platforms that provide highly accurate customer data.
One of the key benefits of a hybrid content management system (CMS) with AI-driven personalization is delivering targeted and personalized data that engages customers and drives action. Gartner recently stated that “modern businesses must provide optimal digital experiences across a growing variety of channels.” This multi-experience strategy requires hybrid headless ‘content as a service’ to give digital workplace application leaders more flexibility and versatility.
With a hybrid CMS and a core data management strategy that leverages a customer data platform, you can deliver hyper-personalized content to the right customer at the right time. This encourages customers to act and convert.