Improve Your Customer Data Management Process With an Enterprise CDP
Fifty percent of executives said improving customer data management (CDM) is their Number One priority for customer experience, according to a recent commissioned Forrester survey. The group of interviewed executives, marketing directors, and technology decision-makers say they recognize the vital role of integrated customer data systems in delivering personalized experiences to customers.
However, a single view of the customer still eludes many companies due to several challenges, including scattered data, and a lack of customer insights. In this article, we examine how an enterprise CDP resolves these pain points and improves the customer data management process.
Customer Data Management Process Pitfalls
Despite good intentions, a lack of both technological firepower and a clear roadmap to data integration hinders companies from fully utilizing customer data potential. The numbers are revealing:
- Companies want to provide an integrated and consistent omnichannel experience but 40% of enterprise CRM users find it hard to create a 360° view of the customer
- 34% say they have issues personalizing CX due to data issues
- 31% say they encounter barriers to integrating a legacy system with other crucial customer systems
A customer data management process that relies on legacy systems such as CRM and DMP are also plagued with data quality issues such as outdated and unverified data. (For example, customers who have changed addresses or give false information such as Guessmyemail@123.com.) Poor data quality generates inaccurate and often incomplete customer profiles. Without cleansing or verification capabilities in place, unusable information clogs up a customer data management process.
Another pitfall of the CDM process is an inability to find new leads due to lack of segmentation and valid audience insights. While these issues can be addressed piecemeal, the overwhelming volume of required manual tasks and processes can impede customer data initiatives.
An enterprise CDP smooths out these road bumps by unifying data collection, nurturing customers, and processing sales within a single platform.
A CDP Centralizes Data Collection
Unless data is collected and unified in a central repository, it will be hard for companies to piece together an accurate profile of customers. Data comes in from a range of touchpoints across different channels. Internal and external sources also compound the growing pile of information. When multiplied to the scale of thousands of clients, one can imagine the daily nightmare of customer data managers.
Only CDPs truly solve this pain point by unifying data collection from the outset. A CDP connects to first-party data sources and ingests real-time information. The platform also takes care of data hygiene—cleansing and enriching it to create high-quality datasets for accurate analysis and forecasting.
Without an automated tool for data collection and preparation, data management personnel can easily get bogged down with the manual tasks of validating information, deleting duplicate records, and standardizing data formats, among others.
After a CDP has done the legwork of omnichannel data collection, it unifies data points to resolve customer identities. First, the CDP analyzes each piece of information and correctly attributes it to the right person; it then assigns a customer ID for permanent identification. This way, a CDP creates a unified view of customers which can be used for meaningful engagement, and ultimately, conversion.
CDPs Inform Customer Nurturing Strategies
Businesses can add value to a positive customer experience through intentional actions that nurture relationships. Relevant offers, special occasion promos, or even a personalized follow-up after a significant purchase tells customers they are valuable. But without a customer data foundation in the first place, it’s hard to orchestrate a customer nurturing strategy.
Data silos are the main culprit. It’s hard to coordinate disconnected data collections with unsynchronized information. It’s even harder to deliver real-time, personalized offers to individual customers at scale when the customer data management process is built on information stored in separate data silos.
This is what makes CDPs instrumental in orchestrating effective customer nurturing strategies. A CDP can arrange the following automated tasks, thanks to its customer data foundation and machine learning-powered recommendations:
- Personalized messaging. A CDP uses demographic and behavioral data, among others, to determine client messaging. For example, Gen-Z shoppers might be more receptive to fun promotional messages while Millennials might be more brand-conscious.
- Timely communication. AI-derived insights can determine the optimal hours and places to best engage customers. Some shoppers like to browse in the morning, while others are more open to offers in the evening. Certain channels also perform better than others—CDPs can use these insights to drive conversions.
- Targeted marketing. A CDP can analyze customer profiles at the individual or segment level to deliver meaningful offers and recommendations. This way, businesses can better target customers and avoid repetitive or irrelevant offers.
CDPs transform the customer data management process to produce measurable results through better customer engagement, retention, and conversion.
CDPs Power Sales Processes
Streamlining a customer data management process requires the seamless integration of internal systems such as sales, customer service, IT, and marketing. But the truth is, systems are often incompatible, and customer data management systems such as CRMs or DMPs often prove difficult to integrate. Business leaders also encounter difficulties when working with IT to develop a roadmap for customer data management onboarding and integration. All these factors affect the sales process, which relies on accurate customer profiles and timely recommendations to help close transactions.
Again, CDPs resolve this pain point by centralizing information and unifying customer profiles in one place. AI-powered predictive analytics help qualify leads with a high propensity to purchase, as well as the potential for long-term relationships. Customer journey visibility helps determine where clients are in their purchase timeline, while Next-Best-Action (NBA) recommendations encourage them to make that decision.
Furthermore, a CDP can help sales teams retarget audience segments, follow up high-propensity leads, and build lookalike audiences.
Watch the video below to see how it all comes together with an enterprise CDP:
In summary, a CDP takes the customer data management process to the next level, thanks to its ability to collect, cleanse, and centralize customer data into a single foundation. CDPs address the pain point of incomplete customer profiles via unified data collection and enrichment capabilities. They also inform customer nurturing strategies through individual personalization at scale. Lastly, a CDP powers up the sales process by overcoming customer data integration obstacles and using predictive analytics for NBA recommendations, retargeting, and building lookalike audiences.
Turn Your Customer Data Management Process Around
Treasure Data offers an intelligent solution to the customer data management process that fits your data maturity stage and scale. We take your customer data and turn it into actionable insights that drive revenue and build customer relationships. Worried about integrations? Treasure Data has 170+ built-in connectors that work with your current stack to future-proof your customer data management process.