Advances in AI-based personalization technology allow retailers to tap into vast amounts of customer data. Analyzing customer data allows you to create personalized experiences that help secure customer loyalty.
The ability to not only capture customer data but use it to increase revenue, through upselling and increased retention, has changed the way retailers interact with customers and prospects. Leveraging personal data based on user experiences and interests can deliver five to eight times the ROI of its marketing spend and lift sales by 10% or more, according to research firm McKinsey & Company. However, this requires a clear strategy that should be based on a robust technology platform.
Ensuring Data Quality is Critical
Every time a customer interacts with your company, important data is obtained that helps retailers create targeted personalized experiences. However, in order to use the data properly, the technology being used to improve customer engagement must be processed and scrubbed very carefully. If the data isn’t leveraged properly, the next engagement with the customer could be the last one.
The problems that we see for retailers who gather and use customer data generally occur because it comes from disparate sources which can taint it. For example, you might have valuable customer data that has been accumulated over many years based on dozens of marketing campaigns. But without knowing its source or how it was collected, the information could be inaccurate or outdated. Problems with data typically fall into these four categories:
- Too much data
- Missing or incomplete data
- Bad data
- Disparate data sources
Too much data
Can you have too much data? It’s a fair question to ask. Regan Yan, CEO of Digital Alchemy, put it best with the following comment:
“Imagine having 700,000 customers, 878 products on offer, 130 promotions running, and 50 different content communications. You would already be looking at 35 billion+ unique possible conversations you could have with your customers.”
What’s important about the data you have is making it actionable in order to drive engagement and increase revenue. The goal for retailers is to tap into large amounts of data, find the kernels of information that resonate with each customer and deliver hyper-personalized experiences that leads customers to take action.
Missing or incomplete data
Leveraging data to engage customers requires high-quality data. If you don’t know the source of the data or how it was collected, you might do more harm than good. For retailers, the best way to use customer data to your advantage is to micro-segment your audience since, as the saying goes, if you personalize for everyone, you personalize for no one.
One way to gather the best data is to use progressive web apps (PWA) and break down the silos of information within your company. According to Mobify, “PWAs combine the high-converting features of an app with the wide reach of the web.”
Another strategy to improve your data quality is to break down silos of existing information. This is done by researching additional data sources within and outside your organization to fill in gaps, or by using a personalization tool that unifies data sources to give you a holistic view of the customer.
According to Harvard Business Review, the yearly cost of poor quality data in the U.S. is $3.1 trillion, based on a 2016 study conducted by IBM. It’s clear that poor quality data can have a dramatically negative impact on retailers. Imagine the repercussions of targeting a specific customer based on inaccurate information. Odds are you’ll lose that customer.
Having access to high-quality data means you can properly segment and personalize customer engagements and turn them into lifelong fans. Retailers that want to secure long-term customer satisfaction should look for technology solutions that have a history of producing highly accurate customer data.
Disparate data sources
Data on customers exists in a variety of locations within most organizations: Web forms, emails, marketing automation, mobile apps, IoT and CRM systems, just to name a few. As the number of customer touchpoints grows, so too will the volume of customer data. Since 73% of consumers shop on more than one channel, retailers need to take advantage of technology platforms that access highly accurate customer data.
Delivering targeted and personalized data that engages customers and leads them to take action is one of the key benefits of a hybrid content management system (CMS) which includes AI-driven personalization capabilities. In its recent report, Hybrid Headless Content as a Service Is the Future of Digital Experiences, Gartner stated, “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 provide more flexibility and versatility to digital workplace application leaders responsible for customer experience.”
Having a hybrid CMS, coupled with a core data management strategy that taps into the power of a customer data platform allows you to deliver hyper-personalized content to the right customer at the right channel, anytime and anywhere. This in turn helps drive customers to take action and convert.
Superior Personalization Leads to Increased Revenue
Building a customer engagement strategy requires deploying technology that provides a holistic view of the customer. This is key to delivering personalized experiences that help secure customer satisfaction and long-term loyalty.
Michael Gerard is the Chief Marketing Officer of e-Spirit