The Salesforce platform is a business-critical system. This puts Salesforce Admins in the unique position of being both the gatekeeper and the enabler of your organization’s customer data strategy. With the digital universe evolving and the amount of data growing exponentially, it’s crucial to understand the changing landscape of data management – especially when it comes to data lakes and the creation of a ‘single-pane’ view of your customers.
To help you achieve this, we’re diving into the what, why, and how of data lakes – including how Salesforce data and industry tools can empower you to leverage your customer information where you want it, and when you want it.
What is a Data Lake?
At its core, a data lake is a vast repository designed as a raw data store for tremendous volumes of structured and unstructured data. Unlike the rigid framework of traditional databases, a data lake allows you to maintain data from disparate systems in its natural form.
This approach offers unparalleled flexibility and scalability, meaning businesses can store data from diverse sources and in various formats, all under one roof while eliminating data silos.
How Does It Work?
Data lakes are designed as a dynamic repository that collect, store, and secure a wide range of data types. At a high-level, here are the key processes:
- Data collection and storage: To fill the data lake, data is collected from a myriad of sources – including SaaS applications like Salesforce. Data is ingested and then stored using a flat architecture and object storage. With object storage, data is assigned a unique identifier and tagged with metadata tags for inventorying of data.
- Data distillation: This involves refining and transforming the data collected into a more usable format. It includes cleaning the data, enriching it with additional context, and consolidating disparate data sources to prepare for effective analysis.
- Data processing: With the unstructured and structured data in place, data lakes utilize powerful processing engines to analyze this data. Data processing focuses on transforming, aggregating, and analyzing distilled data to prepare it for practical use. This layer is about making sense of the data collected and stored in the data lake.
- Data consumption: This part of the process makes data available to the end-user tools where it will be consumed, such as for BI, AI, ML, etc. Once the data is accessible for integration, then you can set yourself up for data consumption to help your organization make decisions, inform strategies, and drive business actions.
From the initial collection and storage of diverse data sets to the intricate processes of data distillation and analysis, data lakes facilitate a seamless flow of information that transforms raw data into actionable insights.
What Does Customer 360 Have to Do With It?
A customer 360 data lake takes this data lake concept a step further by focusing solely on the customer and the customer journey over time. It integrates multiple types of data from every engagement, touchpoint, and interaction, giving you a holistic view of your customers’ behaviors, preferences, and feedback. With this view, you could:
- Personalize marketing campaigns: For example, a retail company could analyze purchased product history from Salesforce, pageviews from HubSpot, and social media interactions. By understanding patterns and preferences from these data sources, they can tailor email marketing campaigns to each customer, suggesting products they’re likely to buy.
- Enhance customer support: Imagine an automotive company utilizing its data lake to sift through vehicle telematics data, service records from dealership management systems, and customer support tickets from Salesforce Service Cloud. This integrated approach empowers service representatives to provide customized support responses, proactively address vehicle concerns, and significantly enhance customer satisfaction levels.
- Customize recommendations: Picture an insurance company leveraging its data lake by integrating data from historical quotes stored in their Salesforce org, driving records from public databases, and claim histories from their claims management software. This ensures that quotes are accurately tailored to each customer’s risk profile and history, across auto, home, and life insurance sectors – thereby increasing customer trust and retention.
The ultimate goal of merging your data into this unified data lake is to achieve this 360-degree view of each one of your customers. This isn’t just about collecting data from multiple sources; it’s about understanding your customers so deeply that you can anticipate their needs and tailor your interactions to exceed their expectations. It’s a lofty goal, but with the right strategy and tools, this is how you turn data into data-driven insights, and insights into better outcomes.
The need for an accurate customer 360 view is exactly why everyone is moving to a unified data lake. In many organizations, customer data is scattered across various silos throughout multiple teams, making it hard to get a complete picture. The move to data lakes is essentially a shift towards centralization and simplification. Having all this data together allows for more comprehensive data analytics and enables businesses to act on insights more rapidly and effectively.
The Role of Salesforce Data in this Data Lake
Salesforce data is often the heartbeat of customer interactions, containing everything from sales quotes to each customer support email. Integrating this information into your data lake is critical because it adds depth to your Customer 360.
For Salesforce Admins, this means ensuring your Salesforce data is not only accurate and comprehensive but also seamlessly integrated with other data sources in the lake. Only then can your organization be properly equipped to create a comprehensive customer profile with personalized experiences.
The Evolving Role of the Salesforce Admin
The journey into the world of data lakes heralds a new era for Salesforce Admins. Your role evolves from gatekeeper to pivotal strategist, as you navigate the integration of Salesforce data into the unified data lake. This transformation demands a deep understanding of both the technical landscape and the strategic business objectives that data serves.
You’re no longer just managing a CRM; you’re managing a primary dataset of your organization’s customer data strategy. This means overseeing the integration of Salesforce data into the unified data lake, ensuring data quality, and collaborating with other teams to help better understand the Salesforce dataset in order to drive precise insights that fuel customer-centric strategies. You become the architect of a data-driven future, ensuring that the flow of Salesforce data into the data lake is seamless, secure, and strategic.
How GRAX Can Help You
In order to have Customer 360 within a unified data lake, you need robust data management and a shift in your organization’s data culture, including your role within it.
GRAX helps organizations achieve this by enabling seamless Salesforce data protection, replication, and streaming into your data lake. This ensures a rich and accessible data repository, enhancing your organization’s Customer 360 initiative and facilitating data consumption in your preferred data tools – whether they’re Tableau, PowerBI, AWS SageMaker, Google BigQuery, or other business intelligence solutions.
In the customer-first digital age, mastering a unified data lake strategy is indispensable for Salesforce Admins. It not only enriches the Customer 360 view but also supports Salesforce Admins in evolving from operational to strategic roles. With a comprehensive data lake strategy aided by GRAX, you can achieve deeper insights, more effective strategies, and stronger customer relationships.
Watch our demo video to see how GRAX can help you go from data protection to strategic advantage.
Summary
Data lakes are a dynamic repository that collect, store, and secure a wide range of data types. Salesforce Admins are strategically placed to have a deep understanding of both the technical landscape and the business objectives that data serves.
By using a data lake to focus on your customers, you can obtain a 360-degree view of them helping you create more personalized experiences.