All Chief Marketing Officers know that collecting data isn’t enough. The real value of data is in leveraging it to develop behavioral insights about your customers and using those data-driven insights to inform better decision-making in real time, driving marketing relevance. To perform this essential work of deeply understanding your customers you need a customer analytics platform that accesses, analyzes and renders your customer data fully actionable.
As the amount of data accelerates, poor data quality will make it harder to implement a successful data-driven culture. Your marketing stack and marketing team exist for just one reason: to drive an understanding of (and engagement with) your customers that supports more relevant customer experiences. What are the capabilities that CMOs need to execute on a strategy that improves marketing’s efficiency, agility and customer engagement?
1. Integrate your “data house.” The challenge that many CMOs confront in leveraging their customer data is that it’s often trapped in various silos. In pursuing the latest “shiny object” or hot trend, companies proliferate tools and platforms that end up becoming “data spaghetti.” Another problem is data becoming outdated if it’s not continuously updated in real time. So the starting point is to get a platform that brings you agility and decentralization with governance and centralization of your customer data.
You should look to standardize your customer data, remove duplicates, and enhance it further with missing information towards getting a single source of truth about your customers across their entire organization. By doing so, you also open up the opportunity to connect specific marketing activities to ROI, enabling the type of marketing attribution that enhances your credibility in the C-suite (where “prove it” is the mantra).
2. Self-learning benefits: drive memorable customer experiences with deep, actionable customer insights. A self-learning customer analytics platform analyzes customer data in near real time to give marketers deep, actionable insights that support strengthened customer engagement, the type that fosters cross-selling, upselling, and higher lifetime value. By uncovering valuable behavioral trends and patterns in your customer data, a self-learning customer analytics platform enables you to map the customer’s journey and reach out to your customers with relevant, personalized messaging across the web, email, and any other marketing channel. The beauty of self-learning is that the platform learns as it goes, unlocking and offering deeper insights about customers as it collects more data. A self-learning customer analytics platform can thus be seen as a 24/7, “always-on” customer engagement/nurturing engine.
3. Automate key drivers of your CX with AI. Autonomous, data-driven decision-making at scale is fast becoming a reality, especially as artificial intelligence continues to emerge. Let’s explore one simple example to understand the enormous possibilities.
The global B2B telecommunications industry, which generates over $30 billion annually, is renowned for promotions, as firms like Verizon, Vodafone, and AT&T battle for B2B customers. A B2B customer might call their existing telecom provider and say, “I have a better offer for my business from a competitor/other provider. What can you do for me?” A telecom company can now create an end-to-end automated process where those business customers are asked to take a photograph of the offer or send a text message. The AI-enabled system would then read the offer and, since the system maintains an ongoing database of B2B telecom offers, confirm that it’s real.
Then it looks at the customer’s lifetime value and history and, based on that, computes a response: “Here is the updated deal we can offer your business today. We want to keep you.” All this takes place in real time, with no humans involved, except in setting up the data/AI system.
4. Democratize your customer data. Key customer insights gleaned from data were once accessible only to the few: the leadership team and data scientists. In today’s marketing landscape, everyone in your organization impacts the customer experience and therefore must have access and use of relevant customer data. It takes a clear, cross-departmental approach to sharing and leveraging your customer data across the organization, something a customer analytics platform enables.
The culture, mindsets, and capacities of your people are as important as, and sometimes more important than, any technology. Today, human and technological capacities are increasingly blended into hybrid solutions. In fact, technology won’t be of much use unless you mobilize your organization around creating a data-centric and customer-centric culture. Meeting and improving the customer experience is a key priority for CMOs, requiring that your people have the tools and capabilities needed to succeed.