5 Keys to Better Customer Experiences and Revenue

real-time customer data

The key: Fresh, timely data that drives insight and action. Here’s how to create a steady stream.

Regardless of the business you’re in, delivering a superior customer experience (CX) is the key to increasing retention, satisfaction and ultimately revenue. While growth is the top priority of CEOs, customer-centricity has become so important to revenue growth that Gartner research found that four out of five companies believe they’ll be competing mostly on customer experience.

Why is customer experience so critical to growth? Maybe it’s because investing in CX initiatives has the potential to double your revenue within 36 months, according to data from the Temkin Group. In fact, 86% of buyers are willing to pay more for a great customer experience and 73% say it is an important factor in purchasing decisions.

Fresh Data Key to Real-Time

While the ideal customer-centric state is a lofty goal, it’s one worth seeking. In this ideal model, organizations are able to gain customer insights and act at the exact right moment. The core requirement is access to more, disparate, fresh(er) data that is used to drive key decisions across all interactions – and continuously improving those decisions with new insights.

See also: How AI Transforms the Real-Time Customer Experience

However, there are often roadblocks that prevent organizations from reaching this state of customer-centricity. Siloed technology and business units that hinder collaboration, applications that aren’t designed for customer decisioning, and dispersed and unstructured data sources are common challenges. Additionally, organizations can rely on IT-dependent, time-intensive processes to develop and deploy solutions, or lack the “glue” to holistically manage customer actions.

The Five Fundamentals

To address these challenges, there are five fundamentals for driving a customer-centric digital transformation. These will enable the organization to connect all business-critical decisions across the customer lifecycle.

  1. Adopt a unified, scalable decision platform across the enterprise that optimizes and monetizes the use of people, data and analytics.
  2. Create personalized customer treatments while addressing economic, business and regulatory challenges.
  3. Empower business users to create and manage the strategies, rules and analytics that drive decisions and actions – without IT intervention.
  4. Re-use connected decision assets across the customer lifecycle to improve decision, while making them transparent and explainable.
  5. Validate decisions before they are put into production, with dashboards displaying predicted and compared-to results.

By applying these principles to customer engagement, organizations can move toward real-time customer understanding. There is exponential value derived from centralizing decisions. First, don’t discount the power of moving decisioning to the cloud. The cloud provides the scale to gain more efficiency. By utilizing compute on a demand basis, a cloud-based solution reduces time-to-value and doesn’t require a huge investment upfront. Organizations can quickly begin to gain better customer understanding and begin innovating.

Platforms Beat Point Solutions

Enterprises everywhere are investing in machine learning and AI solutions to gain a competitive edge. While machine learning can uncover insights from various kinds of data, it can’t convert them into actions that create business value. That requires a decision management platform. A decision management platform is the connective tissue for enterprises to transform data into insightful decisions while automating value-creating actions.

Rather than invest in disparate point products, companies moving to a platform approach are improving efficiencies by creating connected asset repository usable across the business. Two key benefits arise from creating sharable assets.

First, connected assets enable better collaboration. This is an important advantage as the majority of analytic insights fail to add business value use – frequently due to lack of collaboration across stakeholders.

See also: Early Wins for IoT: Customer Experience and Supply Chains

With a decision management platform, IT, data scientists, data analysts and business users can organize around effective analytic usage. This approach creates version-controlled assets business users can search for, access if their privileges allow and string together in novel ways. As such, enterprises can easily consume, operationalize and measure the performance of analytics regardless of how they were sourced or built. This enables a collaborative environment where everyone has visibility into where decision assets are being used, how they impact decisions and how they’re being improved. It ensures that everyone is aligned on the best use of the data to get the most important insights on the customer, and the right action.

The Importance of Re-Use

Second, and perhaps most importantly, a platform approach also enables organizations to re-use decision and analytic assets.

With the platform providing a common repository for decision assets as well as the connective tissue between authoring tools for decision logic and analytics, organizations can translate customer characteristics and rules into business terms everyone understands and uses. Once an organization has determined which extracted attributes to target and how to action that customer in an intelligent way, that information can be repurposed. It creates a core set of customer understandings and analytics that can used for many different decision areas. If you are successful automating one decision, you can apply that model and automate many decisions, faster than before.

See also: Case Study: Employing AI to Personalize Customer Experiences

Further, as more initiatives are launched, each one costs less – which means more initiatives get launched and you are able to drive more growth from a smaller incremental expense. This translates into an accelerated time-to-value and a dramatically improved revenue-to-expense ratio. Let’s not discount the ability to increase consistency in decisions and interactions with customers, because multiple lines of business and customer lifecycle functions use the same decision assets wherever appropriate. That means an organization can demonstrate a single coherent “voice” across all touchpoints.

Future Belongs to Insight-Driven Business

Being customer-centric is no longer a nice-to-have, and meeting customer demands for personalized, engaging experiences is not optional. By moving to centralized decisioning, it’s possible to unleash your organization’s potential for customer-centric innovation and boost returns on past, present and future analytic investments.

I’ll leave you with this. Forrester anticipates that insights-driven businesses will “grow at least seven times faster than global GDP,” “drive customer insights into every part of their business” and “create and sustain barriers to entry through insight.” In the not-so-distant future, these companies will become so smart, they’ll be uncanny in their ability to anticipate and align with customer needs. Will you be one of them?

Bill Waid

About Bill Waid

Bill Waid is vice president and general manager of FICO Decision Management, which builds and delivers predictive analytics, decisioning and optimization solutions. Prior to joining FICO in 2002, Bill held various leadership roles at HNC Software, Brokat Solutions, Blaze Software, Neuron Data, and Stone & Webster.

Leave a Reply

Your email address will not be published. Required fields are marked *