Increasingly businesses today are being forced to implement a more customer centric approach to their business strategy. This is in response to rapidly changing consumer behavior and the compelling move to digital platforms. To be able to respond and make better, faster decisions, business need a clear view of their decision-making strategies and the ability to apply risk analytics, strategy improvements, automation and advanced analytics. Often, organizations mistakenly believe that issues with data are holding them back from embracing a customer-centric approach. Yet myriad examples prove that businesses can reap the benefits through centralized decisioning and demonstrate real business impact without “fixing” the data.
The driving force behind change is that consumer expectations have risen, with a strong preference for working with trusted and transparent brands. A study from Label Insight found that when a brand offers complete transparency, 94% of shoppers are likely to be loyal to that brand. Consumers also expect more personalized experiences, so no longer will one-size-fits-all marketing campaigns work to drive sales. A staggering 86% of customers say that personalization affects their purchasing decisions. We want companies we do business with to know what we need when it’s important to us -- perhaps even before we realize it.
But before a company can personalize experiences for customers, it must first have a holistic view of the customer, which can often be a challenge. Across industries, companies are breaking away from siloed divisions that each have insight into one slice of the customer. No longer can businesses rely on account-based strategies to grow their businesses. Instead, companies must focus on delighting customers so that they become loyal, long-term advocates who increase their spend because they are highly engaged with your brand. Yet legacy technology systems have often been perceived as an obstacle to fully delivering on the promise.
It is not unusual to hear IT departments struggling to link different technologies or complaints about poor data quality. In fact, research from Monetate found that the top barriers to personalization include data quality (23%), building sustainable data architecture (17%), integrating third-party data (10%) and organizational constraints/silos (3%).
It’s understandable that businesses believe they need better data to drive better actions, but it’s not true. What is needed is the addition of intelligence to the volumes of data that already exist across the organization. With centralized decision strategies, businesses can leverage data lakes and streaming data sources from anywhere in (and outside) the organization and operationalize data-driven actions to support real-time outcomes. By moving the analytics closer to the data, value is extracted and contextual customer responses are made faster.
For example, at FICO we recently worked with a large global retail bank to help it better understand and engage with its customers. The bank wanted to create a single view of the customer and use that information to provide more competitive offerings. It realized that a siloed data structure was hindering its progress, so the bank decided to use a centralized decision strategy to tap into more data sources and extract value from that data, garnering more intelligent and precise customer insights. What’s more, it now has access to real-time intelligence to enable strategic decisions within minutes -- not months.
Three Tips For Creating A Customer Centric Strategy
- To be customer-centric, digital businesses need to rely on digital decisions -- ones that leverage the power of machine learning, are automated and happen in real time. To start, businesses should instill a culture of digital decisioning that correlates to business outcomes. This means the organization focuses on the most critical elements in the customer journey and ensures that all teams are working toward data-driven and analytics-informed actions to deliver the best outcomes.
- Next, organizations should focus on getting quick wins under their belts. What key decisions can impact the business and be measured to demonstrate the value of centralized decisioning? For this example, let’s look at customer churn. Knowing when a customer might unsubscribe from a service, and then combining that data with business rules to decide what personalized action to take, could result in an improvement in customer retention. Businesses can measure churn and retention to show that centralized decisioning had a material impact.
- And finally, it’s important to explain the decisions to outside parties such as regulators, executives and even customers. Demystifying the process with clear explanations of how the decision was made goes a long way in demonstrating transparency and building trust in the system and your brand. To extend that idea even further, don’t forget to help executives to better understand how machine learning models work, how they are governed and how they self-adjust to changes to create better outcomes.
Originally published on Forbes.com.