This content was previously published on Fortune.com.
Today’s savvy customers have little tolerance for generic offers or “clueless” phone reps. At a minimum, they expect relevant, real-time answers to their immediate needs. And why shouldn’t they?
Yet many companies are challenged by putting this thoughtful immediacy into practice. For as much data as we have on our customers, it’s still daunting to develop new culture, processes, and systems that are centered on customer insight and understanding.
But it’s possible.
If you know the steps a customer has taken in a transaction or series of transactions as well as the context, you’ll be more likely to know their next move. And more prepared to accommodate them.
Applying predictive analytics to big and small data establishes a connecting thread that can be used to fine-tune customer interactions and experiences. It’s now possible to use real-time data to calculate and anticipate customer needs, delivering the best action to take with a customer based on their relationship, their personal history with the company, and their transactional behavior.
In The Power of Customer Context, Forrester’s Carl Doty states that “personalized interaction data creates context,” and that proprietary algorithms “enable the application of machine learning to customer interactions, using the context of the moment to proactively guide the customer to the next best interaction.”
Four points to consider when leveraging relevant context.
Leading global brands can enhance customer experience with four components critical to the effective utilization of context in predictive analytics:
Understand your customer
Predictive analytics is driven by the constant refinement of data. You need to understand what your customers want or need, their value and potential future value, and the benefits and risks of fulfilling a customer request in a certain way.
Personalize every customer experience as much as you can. Be relevant and contextual. Knowing your customers allows you to tailor the budget for retention and to invest in the relationship in a way that’s commensurate with the customer’s value.
Track and keep up with customer needs
Real-time data means immediate data, not the day-old variety. People talk to each other in real time. They expect the same from enterprises. Customer data should be current, and data captured on service calls, chats and emails should be promptly added to the customer’s file. This action increases the relevancy of the interaction, shedding light on the meaning behind it.
Pay attention to how customers feel
Emotional cues can be found in cold data. Identify customer moments of truth and capitalize on them to create more value. Multiple calls to fix an unresolved issue are clear signs of frustration. Bypassing IVR prompts in order to reach a “representative” or asking immediately for a manager are additional cues that provide insight, as are customer comments on social media.
These approaches help guide customers to the next best action in real time, so you can provide the most relevant offer or content at the right moment. This attention to detail creates stronger relationships and more valuable customers—customers that are happy to continue their business relationship with you for years to come.