What is a customer-centricity strategy?
Customer-centricity is a mindset, a culture, a mantra. It is only achieved when everyone within an organization is laser-focused on the customer and puts the customer at the center of every decision and action. Simply put, having a customer-centric strategy is the key to delivering better customer experiences (CX).
Taking a customer-centric approach to your business is no longer optional – it is required to remain competitive. Customers have more choices than ever before and can switch brands at the drop of a hat. In addition, competition is no longer limited to within an industry. Instead, businesses across industries are competing based on experiences. Both B2C and B2B customers want every experience to be as easy as a click – whether they are shopping for shoes, insurance, or healthcare services.
Data and business applications help create trusted and intelligent views of customer data across all sources and uncover insights that create personalized, authentic engagement across channels. Great customer experiences rely on great data and enable true competitive differentiation.
Companies that provide exceptional personalized experiences will set themselves apart. To get this edge, they need data in order to accurately and confidently identify customers at each step in the customer journey, build audience segments, and customize offers and interactions.
Customer data is often collected by accident without consistent governance, verification, authentication, or standardization across departments. There is a lack of confidence around its accuracy and compliance, making it difficult and potentially costly to use the data across teams.
Data-driven companies looking to support customer-centricity initiatives need to be concerned with the collection and support of high-quality data over the long haul. Only 16% of organizations think their data is of “very good” quality. Once bad data goes in, you can expect to get bad results out, limiting effectiveness and deteriorating the customer experience. Being data-driven means investing in your data, making sure you have the data you need when you need it, and using high-quality data to fuel your decisions and programs.
Some customer-centricity programs utilize big data technologies to help deliver the underlying set of requirements. Large amounts of customer data are loaded into data lakes or similar large-scale data capabilities such as a cloud data warehouse. Data is still data – regardless of how big, how fast, how frequent, how complex. The same underlying set of principles and capabilities are required to manage data regardless of the technology platform employed.
The shift to digital over the past decade has increased the variety and volume of big data significantly. Most companies are already collecting customer data across many systems and applications. However, to effectively deliver customer-centric experiences, companies need to do more than simply collect data. They need to eliminate data silos, connect and enrich data, and serve up actionable insights to those who need them. Companies need to know where to find the data, how to bring it together, and how use it to transform the business.
Over $2 billion a year — that’s how much the median Fortune 1000 company would boost revenue by, if it increased the usability of the data it already has by just 10%, according to research at the University of Texas. A customer-centric business model requires technology that allows organizations to effectively access, manage, and deliver the right data and information to downstream business and customer-facing systems, while reducing operational risks and cost for IT organizations.
Let’s look at four data capabilities that are critical to customer-centricity.
The first critical capability in a data-driven approach to customer-centricity is to identify what customer data you possess, where it resides, and in what category it belongs. Formally called “data discovery,” this step is the process of identifying, cataloging, and classifying customer and related data stored in all your different systems. The goal of data discovery is to understand what exactly has been stored, so that your brand can derive value from it.
Because data can reside in numerous places in your organization and potentially fall into multiple categories, this step requires help in the form of technical tools. Tools include data catalogs that enable you to discover, classify, protect, and share information. They should also help you meet regulatory requirements by identifying and securing unstructured data. And, today they are an imperative, not an option, as the volumes of data you’re now dealing with preclude taking a manual approach to data discovery.
The next key capability is to make sure the data you need is accurate and complete. Data cleansing is the process of improving the overall quality of data by removing or correcting inaccurate, incomplete, or irrelevant data from a system.
As with data discovery, what used to be done manually has now been automated with specialized tools and the help of artificial intelligence (AI). Data cleansing solutions attempt to find and remove or correct data that detracts from the quality – thus the usability – of data. The goal of data quality is to achieve consistent, complete, accurate, and uniform data throughout your organization.
Data cleansing leads to high-quality data. When data is of excellent quality, it can be easily processed and analyzed, leading to insights that help you make better decisions and provide customers with better experiences.
When your data is clean, it can be enriched from sources outside your company. Many external sources exist for enriching customer profiles. You can purchase or subscribe to enrichment data that tells you things like the following about your customers:
Knowing things such as your customers’ ages, gender, interests, and many more data points helps you find and retain more customers. You save on customer acquisition costs by delivering the most relevant communication at the right time with the right actionable offer. And, you can apply this insight to your existing customers to better tailor messaging in the time and place they prefer.
Now that your customer data has been discovered and cleaned, you need to manage it and integrate relevant data from different sources across the enterprise. The goal: to deliver a consistent view of customer data that results in seamless experiences across channels, regions, and lines of business.
Collecting the data from all these disparate sources and transforming it into a standard format is the job of a data integration tool. An integration platform should offer out-of-the-box connectors for a broad range of source systems to ensure data is delivered to the systems and applications where it is needed.
Keeping customer data, especially personally identifiable information (PII), private and secure is hugely important in a customer-centricity strategy. Failure to comply with industry or government privacy regulations such as GDPR, Know Your Customer (KYC) or HIPAA results in punitive fines, but more importantly run the risk of alienating your customers due to a lack of trust and confidence in your ability to manage and use their data.
With a foundation of trusted data and a single source of rich, reliable customer profiles, you can now start to capitalize on customer-centricity. A critical aspect of the data strategy needs to be about how to deliver this single view to the business and analytical applications that need it – and, eventually, to the employees who will use it to build out customer-centric programs, interactions, campaigns and more.
Applications that use these customer profiles includes CRM applications, order management applications, finance and billing systems, call center systems, HR systems, and marketing automation platforms.
To deliver the experiences your customers expect, it’s important that your customer data fuel target applications like point of sale, customer service help desk, campaign management, and marketing analytics. It’s the only way to make sure everybody is working with trusted customer data that’s come from a single source of truth.
When data is found, consolidated, cleansed, governed, and secure, it’s officially usable. However, it’s critical for companies to go a step further to ensure effective management of the data. Companies need to address data quality and reduce errors across multiple systems. By having a single master repository for all critical business data, companies can optimize business processes.
Here are a few concrete examples of organizations that delivered on their customer-centricity vision by implementing data-centric capabilities and building a trusted view of their customer data:
Once data is clean, enriched, and accessible, it can support new, personalized customer interactions. Customer-facing roles, including those in marketing, sales, and service/support, have varying data needs and challenges. Ultimately, you need to connect the right people with the right data.
For many decades, marketing had taken a “spray and pray” approach to acquiring customers and focused even less on retaining and growing existing customer relationships. But, as consumer behavior has shifted and digital channels become the norm, this strategy is less and less effective.
By taking a data-driven approach to marketing activities, lead generation is more targeted, campaigns benefit from segments informed by data, and website and content is personalized to be more authentic and create an emotional connection with customers that ultimately result in greater loyalty.
Customer-centricity strategies have evolved sales teams from being organized by product areas to being organized by customers. To sell the best product to the right customer at the right time, sales needs a complete view of the customer across all interactions and touchpoints. They need to understand whether a customer has clicked on marketing offers, has open service requests, or has provided positive or negative Net Promoter Scores (NPS), so they can understand the current state and adjust their sales strategies accordingly.
With a broad view of the customer, sellers can make more informed product recommendations for better cross- and up-sell results, identify the next best action (which may be to do nothing), and gain navigate complex organization hierarchies (B2B) for better account penetration or households (B2C) to understand influencer networks.
Most contact center staffs have very limited access to customer data. They are mostly limited to what customers tell them at the time of the call. By connecting data and providing them with real-time insight into such basic things as transaction history and reasons for past calls, contact center professionals have a much fuller picture and can help the customer more proactively.
Informed interactions lead to better experiences for the customer, along with allowing the call center representative to think customer first, be more confident, and take more informed actions without requiring escalation.
With better data comes better approaches to customer-centricity due to an increase in visibility and understanding about the customer. Customer-focused areas of the business will benefit from a data-centric approach to marketing, sales, service and IT. Here’s a quick summary of the benefits:
Customer-centricity is an art, not a science. It requires a corporate culture that incorporates the customer into every decision and action. Data and technology have huge potential to help executives ensure their customer-centricity vision is experienced by both internal and external stakeholders – from each employee to every customer.
By breaking down data silos, improving data quality and governance, and building a complete and trusted view of the customer, marketers, sellers, and service teams can deliver meaningful experiences that keep customers coming back.
Are you getting the most from your customer data? Take this Customer 360 maturity assessment from Eckerson Group to assess and improve your organization’s customer data management strategy.