Customer Data Platforms: The Heart of the Customer Journey
Modern technology enables the collection and storage of vast amounts of data and most consumer-savvy CPG firms have massive volumes of invaluable customer data. Yet few organizations can leverage that data to its full potential.Read the Blog
Note: This is the second in a two-part blog series on the value of Customer Data Platforms for CPG firms. The first blog, Customer Data Platforms: The Heart of the Customer Journey can be read here.
To truly connect to consumers, CPG firms need a Customer Data Platform (CDP) to capture, integrate, and analyze all types of data so they can target the right consumers in the right way. The challenge is finding the right CDP—one that fits your firm’s current needs and is flexible enough to scale and provide deeper, more segmented insights as your needs warrant.
Overall, CPG firms require a CDP that is capable of:
- Automatically building out detailed consumer profiles for granular segmentation and behavioral analysis
- Helping firms develop personalized and targeted experiences, product recommendations, cross-channel marketing campaigns, and customer service
- Supporting firms in efforts to deliver consistent (and seamless) brand experiences across in-person and digital channels and touchpoints
CDPs are prebuilt software systems that create a persistent database containing a comprehensive view of each consumer. It does so by capturing data from multiple systems, linking information from those systems related to the same consumer, and storing the information to track behavior over time. The CDP can be connected to other systems, including your CRM, and other BI and AI-based solutions for analysis and reporting.
That said, let’s look at the must-have features and top considerations when implementing a successful CDP.
Your CPG firm is most likely using dozens of applications, each containing data that is unique to a department but that would be useful to others. A CDP platform’s pre-built connectors allow you to seamlessly ingest data from a myriad of sources and integrate that data with all channels of consumer interaction — transactions, website, mobile engagement, email, or customer service calls.
A CDP should provide integration capability to commonly used systems, and not all do. Connectors should include any marketing, services, sales, operations, finance, and BI platforms you are currently using. Furthermore, a CDP should have the ability to leverage compute power, scaling effectively to ingest potentially billions of rows of data.
Data unification and standardization
The key to a successful CDP starts with the unification of consumer data, breaking down departmental barriers, pulling data from differing formats, and eliminating data isolation. The CDP should be able to bring in data from disparate sources and create a common data estate that includes multiple data sets, on an attribute-by-attribute basis, to create a more complete consumer profile.
CDPs build unified consumer profiles around the concept of a digital identity. A good identity resolution strategy should be able to link anonymous and identified traffic to complete a consumer. Identities can be represented in many ways across different lifecycle stages, for example, an anonymous web visitor cookie value vs. an identified email address. CDPs can vary in the methods they use to reconcile the different versions of a prospect or consumer, but the overall goal is the same: to create a single consumer view.
Because CDPs connect to all your tools and data sources, you can generate segmented lists on nearly any data point involving the consumer. These insights are important and go far beyond traditional demographics– ensuring that your campaigns can be extremely specific and targeted.
For example, you could use this data to create personalized digital experiences (for example, presenting specific offers during website visits) and take more informed risks to move consumers through the sales funnel. A good CDP should allow you to not only target your ideal consumers, but also suppress audiences you don’t want to include in a campaign, for example, advertising to consumers who just bought a similar product from you.
Brand and interest enrichment
Data enrichment allows organizations to merge data from other data sources with your CRM consumer data. This allows CPG firms to make more informed and targeted approaches toward nurturing and marketing to consumers.
For example, an organization that sells recreational vehicles and outdoor equipment can build marketing segments based on internal consumer engagement systems that identify consumers who would be interested in or are due for an equipment upgrade. However, what the organization might not know is which consumers prefer specific brands or types of equipment. By enriching consumer data with information such as brand affinities, you can create more targeted marketing segments of consumers who prefer brands of equipment that you currently have large quantities of in stock.
Security and compliance
With always up-to-date rich and adaptive profiles, organizations maintain an edge by gaining a deeper understanding of consumers—if the CDP is built with a privacy-first approach. Growing mistrust over data privacy has driven big changes in data reform. A future-proof customer data platform needs to be consent-enabled, allowing the organization to automatically honor consumer permissions and privacy.
To do so, the CDP should allow you to set data standards to make sure that website visitors have opted into your data collection. Once visitors have opted in, your CDP also needs to give you the ability to delete visitor data if a user asks you to do so. Suppose some consumers object to their data being stored or only want a portion of their data to be stored. In that case, you must be able to easily identify where certain data points are stored, and what’s being shared throughout your CDP pipeline.
Furthermore, if you are a global company, you are dealing with different compliance regulations, including GDPR, CCPA, CASL, and others. Each regulation has different requirements for capturing and storing consumer data and how that data can be used. Your CDP must be able to support these differing requirements.
Once data is standardized, a reliable CDP should be able to present insights in a range of data points such as behavior, experience, and demographics — all on a single platform. It’s critical that all the right people can get to the information, and better yet, work with it. The output needs to be consumable and actionable.
Most CDPs provide native reporting and dashboard services. Advanced reporting capabilities should include customizable reports that you can progressively modify or drill down on for deeper insights. For example, Customer Insights, Microsoft’s CDP platform, allows users to connect Customer Insights data with Power BI to further model and create visualizations with the knowledge they have gained about their consumers. These analytical visualizations can also be used for what-if analysis.
AI and predictive analytics
Most default reporting is about what already happened and not necessarily about what is likely to happen. Traditionally, metrics looked backward to unearth insights about past consumer behavior and measure the effectiveness of campaigns. With the advent of artificial intelligence (AI), real-time data from across the value chain is now being used to better predict future action.
With AI-infused CDP platforms, CPG companies can use predictive analytics to make predictions on how business actions will impact satisfaction and value measures like revenue, cost to serve, or churn. These predictions can be based on historical data, user behavior, and even live data. The system uses all these data points to predict a future outcome, such as whether a consumer is likely to buy or to recommend the next best steps within the customer journey.
Using AI in a CDP allows you to anticipate unmet consumer needs, identify opportunities you didn’t know existed, and reveal very subtle consumer pain points. Yet, to successfully use predictive analytics, firms will need to do their homework, and do it well. You will need to spend time thinking about what you want to be able to predict, and where and how to get enough data to generate and test the model that will drive the prediction. Some CDPs come with out-of-the-box predictive models that you can use, and some don’t. It’s a feature you’ll want to investigate.
As CPG companies move forward on their respective transformation journeys, it’s important to find a CDP with the right features to meet your needs. When the demand for better consumer experiences is high and companies are operating on razor-thin margins, a consumer data platform is becoming a valuable endeavor.
With over 10 years of experience serving brands in the CPG industry and nearly 20 years working with the full Microsoft stack, Hitachi Solutions has the right combination of industry and technical expertise to help your firm develop and execute a comprehensive consumer service and experience strategy.
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