Where Does Customer Data Reside? Key Storage Solutions
With the growing emphasis on digitization, large volumes of data are generated exponentially from sources like social media, online transactions, IoT devices, and mobile applications. Collecting and utilizing this data can be crucial to your organization’s success. It helps you thoroughly understand how the market is responding to your products and services and identify the areas for improvement.
Your departments are most likely leveraging marketing, e-commerce, and payment platforms to capture the influx of customer data effectively. The article comprehensively explains these storage solutions and answers a commonly asked question: ‘Where does customer data usually live?’
What Is Customer Data?
Customer data is any information that you gather about your customers when they interact with your brand. It includes demographics, purchase history, and online interactions that can provide a peek into their preferences and needs. This data is essential for delivering personalized user experiences, enhancing customer service, and performing predictive analytics.
7 Common Places Where the Customer Data Lives
Customer data can be scattered across various systems and platforms within your organization, making it difficult to use for reporting and gaining stakeholder buy-in. By relying on modern tools and technologies, you can streamline big data management and other downstream tasks. This section will explore seven common locations where customer data is typically found.
Marketing Platforms
Marketing platforms are centralized hubs for gathering customers’ reactions to your email and social media campaigns. By consolidating these data records, you can develop comprehensive customer profiles, segment the audience, and create targeted marketing strategies.
Some popular marketing tools include HubSpot and Mailchimp. These tools allow you to fetch details like search history, engagement metrics, and behavioral patterns. You can also track customer interactions over several touchpoints, including website visits, email opens, and social media comments. With these insights, you can make data-based decisions to amplify your marketing efforts and improve customer outreach.
Sales Platforms
Sales platforms empower you to manage customer progress throughout the sales funnel. They help you track leads and oversee your sales pipeline while keeping a detailed account of customer activities. With these platforms, you can store important information like contact numbers, communication history, purchase intentions, and the status of deals.
Two well-known examples of sales platforms are Pipedrive and Nutshell. They make the entire sales process—from lead generation to deal closure—smooth sailing. You can capture potential buyers from multiple sources, optimize your acquisition and retention techniques, and increase conversion rates.
E-commerce Platforms
You can use e-commerce platforms to collect customer data related to online shopping, such as browsing patterns, product reviews, ratings, and cart abandonment rates. This enables you to tailor your recommendations based on the feedback you receive and improve the overall customer experience.
Shopify and WooCommerce are renowned platforms for managing product listings, identifying checkout problems, and tracking inventory. The former provides native templates, while the latter facilitates integration with third-party tools to generate in-depth reports on website performance. You can use metrics like page load speed, bounce rates, and click-through rates to pinpoint issues that could potentially interrupt user journeys.
Customer Relationship Management (CRM) Platforms
CRM platforms are designed to facilitate a single-page view of all your customer data analytics. Your teams can use them to integrate information from sales, marketing, and customer service interactions. CRMs also increase operational efficiency by automating data entry tasks, appointment scheduling, and follow-up communications, freeing your staff for more strategic activities.
Salesforce and Zoho CRM are examples of CRMs that can help you foster stronger customer relationships by offering support ticketing systems for faster complaint resolution. Additionally, these platforms equip you with all the necessary data to identify and capitalize on cross-selling and upselling opportunities, increasing profitability.
Analytics Platforms
Analytics platforms are crucial for storing and analyzing customer data for marketing, product development, and sales. You can combine the capabilities of these platforms with data enrichment tools and effectively discover, validate, and merge third-party data with your existing datasets. This enriched pool of data provides actionable insights about upcoming market trends to expand your user base.
Two popular choices for analytics platforms include Looker and Mixpanel. While Looker focuses more on complex data analyses and customization, Mixpanel is preferred for user behavior tracking and event analysis. Both tools have a dashboard feature that you can use to visualize and explore your data thoroughly.
Payment Platforms
Payment platforms enable you to store transaction information, such as payment methods, transaction history, and billing details. You can leverage this data to understand your customer’s purchasing behavior and spending patterns and optimize payment processing. Based on average transaction volume and purchase frequency, you can also narrow down any suspicious activity and take appropriate security measures to prevent potential fraud risks.
PayPal and Stripe are some examples of payment platforms that handle payments securely and give you stats to refine your pricing strategies. They are PCI-complaint and can manage credit card credentials according to the strictest industry standards. Both platforms are also equipped with encryption, two-factor authentication, and tokenization features, enabling you to protect your customer data for reliable reporting and decision-making.
Data Lakes
Data lakes are centralized repositories where customer data usually lives. These flexible and scalable storage solutions can accommodate raw, unstructured, semi-structured, and structured customer records. Since they don’t have a restrictive schema, it is easier for you to load the data first and then access it later for further analysis.
Amazon S3 and Google Cloud Storage (GCS) are some of the popular choices when it comes to data lakes. You can integrate these tools with data enrichment services to retrieve high-quality, relevant data from external sources and create complete and reliable datasets.
How Airbyte Helps You Unify Customer Data from Various Platforms to Make Sense Out of It
With customer data fragmented across various systems, it is extremely challenging to obtain a holistic view. Therefore, to streamline this process and create a single unified repository of your customer profiles, you can leverage Airbyte, an AI-enabled data movement and replication platform.
With Airbyte, you can consolidate your customer data using its extensive catalog of 550+ pre-built connectors. These connectors let you extract data simultaneously from diverse sources, such as CRM systems and social media platforms, to your preferred destination. This single source of truth (SSOT) offers a comprehensive understanding of your customers to deliver personalized services.
Below is a detailed guide on how to use Airbyte's native connectors and build pipelines connecting your source and target systems. For this tutorial, let's assume BigQuery is your destination and PayPal, Shopify, and Facebook Ads are your data sources.
#1 Configuring the Source
- Click on the Sources tab on the left side of the dashboard. You will see a text field.
- Enter PayPal and click on the respective connector.
- Fill in all the mandatory fields, such as Client ID, Client Secret, and Start Date, and click on Set up source.
- The platform will run tests and validate your source setup. Once it passes all the tests, PayPal will be configured as your data source.
Similarly, you can set up Facebook Ads and Shopify as your data sources. The next stage is to set up the destination part of your pipeline.
#2 Configuring the Destination
- Click on the Destinations tab just below the Sources tab.
- Type in BigQuery in the search bar and tap on the respective connector.
- Input all the necessary information like Project ID, Dataset Location, Default Dataset ID, and Loading Method. Then, click the Set up destination button.
- The platform will run tests again; once all tests are cleared, your destination will be set up.
If you can’t find the required connector, you can use Connector Development Kit (CDK) or Connector Builder to develop a customized one. The AI assistant functionality in Connector Builder scans through your preferred API documentation and auto-fills the required fields, significantly reducing the development time.
#3 Creating a Connection
The last stage of building a data pipeline is creating a connection. This is a four-step process. The first two steps involve adding sources and destinations you previously configured, and the third step is selecting streams you want to replicate.
- Click the Replicate Source button and select the streams you want to synchronize.
- Click on Next and proceed to the last step, where you have to enter the connection’s name, replication frequency, and other necessary details.
- Once you are satisfied with your configuration settings, you can tap the Finish and Sync button.
With this, you have successfully built end-to-end data pipelines for customer data integration.
Key Features of Airbyte
Some of the features of Airbyte that can help streamline the transfer, storage, processing, and analysis of your customer data are:
- Flexible Pipeline Development Options: Airbyte provides an interface for all your production workflows. It caters to your staff with technical and non-technical backgrounds by providing user-intuitive UI, PyAirbyte (Python library), APIs, and Terraform Provider.
- Custom Transformations: You can integrate Airbyte with dbt Cloud to run custom transformations and convert raw data into a format best suited for analysis and reporting. Airbyte also lets you integrate it with LLM frameworks like LangChain or LlamaIndex to perform RAG transformations, such as chunking, indexing, and embedding.
- Data Orchestration: Airbyte empowers you to automate your data pipelines using popular data orchestrators, such as Dagster, Airflow, Prefect, and Kestra. This integration lets you manage complex workflows and streamline data processes effectively.
- GenAI Workflows: You can directly store your semi-structured, structured, and unstructured data in vector databases like Milvus, Chroma, and Pinecone. This simplifies your GenAI workflows and smoothens the outcomes of LLM-based applications.
Additionally, Airbyte has announced the general availability of its Self-Managed Enterprise edition. It offers large-scale data ingestion capabilities and gives you complete control over the confidentiality of your customer data by using PII masking.
To learn more about Airbyte and its use cases, you can contact the experts at Airbyte.
Learn How KORTX Uses Airbyte to Streamline Customer Data Ingestion
KORTX is a digital marketing company that provides customer data marketing analytics services to enhance client’s business outcomes. The firm’s major pain point before turning to Airbyte was inefficiencies in collecting data from multiple sources and loading it into the BigQuery warehouse.
After utilizing Powered by Airbyte, KORTX can now swiftly perform customer data integration by instantly adding hundreds of data sources to their product. This helps the team avoid tedious tasks like maintaining ELT (extract, load, transform) pipelines. With Powered by Airbyte, the company can quickly gather data from Facebook Marketing, Google Ads, Google Analytics, and more and load it into BigQuery with just a few clicks. This has saved them from the trouble of building custom connectors for every tool, saving significant engineering time.
Airbyte’s resilience, reliability, adaptability, and flexibility have helped KORTX simplify the data ingestion process and effortlessly meet its evolving data requirements. Depending on Airbyte has improved data accuracy and timeliness, boosting the firm’s ability to deliver valuable insights to its clients. Click here to learn more about how Airbyte is empowering the data engineers at KORTX.
Wrapping It Up
If your organization uses data to personalize and improve customer experience, the first question you should answer is, “Where does customer data usually live?” Once you know this, you can easily optimize your data management and gain a 360-degree view of your customers.
Data integration tools like Airbyte can simplify such processes. Airbyte helps you consolidate your scattered customer data and gain a unified view to draw valuable insights for improved customer engagement and analysis. By leveraging its robust features, such as pre-built connectors and data orchestration capabilities, you can build automated pipelines and efficiently utilize your resources. This will save time, money, and effort in the long run.