B2B marketers invest in marketing technology to gain customer insights and drive personalization to better engage their customers. While technologies like artificial intelligence and self-learning are the martech foundation of personalization strategies, marketers must also be aware of each customer’s evolving needs as they arise in context. Savvy B2B marketers don’t just collect personal data, but also understand how and when to use this personal data to engage customers in the right context.
Contextual personalization, defined
Personalization means different things to different people at different times. Ultimately, personalization must be evaluated from the customer’s perspective. At its core, personalization means relevancy, shown by offering the right (useful) messages to the right customer at the right time (i.e., when they have the actual need your message addresses). When your marketing is relevant, a customer will answer “yes” to this all-important question: “Are you helping me resolve the need I have right now?”
B2B marketers may know all a customer’s demographic information and be aware of her complete buying history, but still fail to either piece it together into a complete picture of the customer and/or use that complete picture with any contextual awareness. If a sales person reaches out to me as if it’s the first time I’ve interacted with their company when I’ve actually filled out a demo form on their website and stopped by their trade show booth two months before, then I’m going to be turned off from interacting with not only that salesperson but with the company overall. Context is a necessary component of effective personalization. Few marketing tactics frustrate and alienate customers more than “failed” personalization attempts that are blind to customer contexts.
Does this “contextual” personalization place more demands on how B2B marketers manage their customer data? Does this level of personalization also drive more customer lifetime value for businesses? Yes and yes. As a Salesfoce.com post on contextual personalization explains, “it’s more about delivering an empathetic experience that helps people live better lives.” That’s a big ask, but is exactly what customers want from companies they choose to interact with.
Climbing the data ladder to contextual personalization
It’s easy to use a customer’s first name in a marketing email and call it personalization. But reaching contextual personalization requires maturity in how your B2B organization manages its data. Here’s what you’ll need to gain that data management maturity:
- Unified view of customers. All B2B marketers must have a unified view of their customer data to even begin the process of achieving contextual personalization. A customer data platform enables exactly that unified view by integrating all your data in one place. But assembling customer data, gaining a “single source of truth,” is just the beginning: your integrated customer data must also be analyzed and then acted upon.
- Customer analytics. Because B2B marketing teams aren’t made up of data scientists, analytics has historically been a bottleneck. With today’s CDPs, much of this analytics “heavy lifting” gets done through easy-to-use self-service tools and self-learning methods like AutoML. This CDP-enabled process of making sense of your customer data allows you to cross the bridge of “data-to-insight-to-action” and achieve contextual personalization, driving more lifetime customer value.
- Insights into actions. The top rung of the “data ladder” involves leveraging your customer analytics to take actions that address the contextual needs of your customers, such as:
- Next best action for each of your customers at any time. Driven by AutoML models capturing life cycle event patterns, buying behavior, social media interactions, and other aspects, you can learn when (and how) to approach each customer, enabling you to create the right experiences at the right time via the right channel.
- Advanced lead scoring analyzes thousands of buying signals to identify the leads that are most likely to purchase at each and every point in the sales funnel.
- Propensity prediction enables you to use a customer's historical data to identify common behavioral patterns before a certain event, like making a purchase, upgrading a service, or leaving your company for a competitor. You can then reach out to customers at those crucial moments with appropriate offers.
Conclusion: Data maturity enables contextual understanding
B2B businesses may have different levels of data maturity, which will directly impact their ability to deliver contextual personalization. Having a single, unified view of your customer data is a great start, but achieving contextual understanding requires deeper capabilities in customer analytics, self-learning, and transforming insights into action.
It comes down to effectively knowing your customers through all of the data you have on them. Customers value personalized experiences and reward companies that provide them. But “shallow” personalization won’t cut it anymore. It’s essential that B2B marketers go deeper with their personalization efforts, which means understanding customer contexts. It takes effective data management tools, such as a CDP, to do this.
Chuck Leddy is a Zylotech contributing writer.
If you liked this post, check out our recent blog post: How an automated CDP is the foundation for better marketing.