Customer Data Platform Use Cases That Are Obsolete

Last Modified: December 29th, 2022

Customer Data Platform Use Cases: Featured Image

Consumers are generating more data and digital footprints than ever before. It is everywhere, from geographical, transactional, and behavioral data to data from ad impressions, and product usage. Companies gather this data in three different ways: directly through customer contact, indirectly via tracking consumers, or by using third-party customer datasets and combining these data sources with their own.

Customer Data Platform (CDP) has emerged as a packaged software customer database system that helps business users (most often marketers) to create a persistent, unified customer profile from multiple systems. CDP solution was born out of marketing and advertising needs. It can link information related to each customer and store it to track customers’ behavior over time.

While CDP is great for targeting, customer profile unification, segmentation, and personalization, it doesn’t serve other department needs. Product, engineering, and support teams don’t have access to customer data, which could otherwise help businesses provide a better customer experience.

Moreover, with CDPs, your source of truth resides in a third-party solution, not in your own storage like a cloud data warehouse. Third-party storage solutions come with their own set of risks – data breach, loss of control, non-mature data governance policies, and lack of traceability.

To get a 360-degree view of the customer, provide a better customer experience, and secure long-term growth, business users across a company require a new system that could collect and standardize customer data in one location.

This requirement has sparked the development of reverse ETL – a technology that syncs centralized customer data from diverse sources into a single intelligent environment, resulting in a synced, well-integrated image of the customer. Teams can now access the trusted definitions of activated users through common operational tools they use.

This article will provide you with an outline of the use cases where customer data platforms are failing and why switching to reverse ETL should be your next step.

Table of Contents

What is a Customer Data Platform?

Customer Data Platform Workflow: Customer Data Platform Use Cases
Image Source: Smart Insights

A Customer Data Platform (CDP) is a database software application that produces “golden records” or “unified customer profiles” of all your customers – using their qualities and their data. A good CDP should be easy to link with your existing data stack and should make it simple to retrieve the data it stores.

A typical CDP platform provides its users with the ability to:

  • Collect customer data from multiple sources
  • Create 360-degree customer profiles
  • Connect to other third-party marketing automation solutions
  • Execute target marketing
  • Segment audiences
  • Generate predictive insights

On an individual level, CDP creates a complete picture of your customers. It takes first-party customer data (transactional, behavioral, and demographic) from various sources and systems and associates it with the customer who produced it. This way, CDPs create a single version of the truth on any particular customer or account.

This also generates a 360-degree customer profile, often known as a single customer view. Such insights can subsequently be utilized by third-party marketing automation solutions or built-in marketing automation tools to execute personalized messaging, automate segmentation, and create targeted campaigns to ultimately boost efficiency for your business.

What are the Capabilities Offered by a Customer Data Platform?

  • Single View of Customers: A CDP allows you to understand your clients on a one-on-one basis i.e., you can detect micro-trends, make precise product and content suggestions, and manage your customers’ journeys using information from every single consumer.

    A CDP creates a meaningful unified perspective of the consumer in real-time, whether via interactions in the physical shop or through visits to your website or app. You can take action on data from all channels and customer touchpoints and manage your customer relationships.
  • Get Rid of Data Silos: Customer data can comprise anything from behavioral, psychological, or demographic data. With each customer touchpoint, a new department might be be involved that will gather relevant data in their own application. Your marketing might choose to go with one set of customer touchpoints while sales might pick another set.

    Such separate storage has the potential to create data silos. Isolated data can impede your efforts to scale personalization or understand who your consumers are and where they originate from.

    CDP allows teams to make use of consumer data across departments and applications, breaking down data silos that hold back your growth and openness.
  • Data Privacy: The General Data Protection Regulation (GDPR) and other data privacy standards have made it more essential than ever to protect your customers’ data privacy. CDPs help your organization increase data protection, privacy, and compliance with particular data privacy legislation.

Customer Data Platform vs Data Warehouse: Which is the Better Option?

Essentially, having a CDP in your organization can only benefit the marketing and customer experience teams by providing customer data from relevant platforms, channels, and devices, including marketing, product, sales, and support systems.

But the warehouse approach is more than that.

When you employ a data warehouse, it provides every team – marketing, product, sales and customer support, and others with complete business data (including customer data) which can be queried easily using SQL programming language.

With the advancement in technology, data warehouses are becoming more robust than ever. All your critical data is stored inside a warehouse and organized using data models that are required by the companies. Today companies are turning from CDP to data warehouses having reverse ETL technology, not just because of the faster processing of the warehouses, but because of the time to value and actionable insights that reverse ETL provides to operational teams.

Why We Think Data Warehouses Stand Out

In addition to the essential features that data warehouses share with CDP platforms, there are many other areas where data warehouses outshine CDP:

  • Provides a Single Source of Truth: Data warehouse contains all your data, no matter what sort of business you run. Data warehouses also provide you the flexibility to use BI tools, since BI tools allow you to use SQL to visualize the right data.
  • More Flexibility: As compared to the CDP, data warehouses offer far more flexibility. CDP offers you only two core objects i.e., users and accounts. Furthermore, a person can only belong to one account. But users can be present in multiple accounts or sub-accounts. CDPs lack in querying and modeling arbitrary relational data. But with a data warehouse, you can easily use SQL to query the data.
  • Better Data Access: CDPs provide limited access to your customer’s data, and disclose very specific actions on top of your customer data. A data warehouse provides unlimited access to the customer’s data and allows you to take a competitive edge over the others.

You can see how Customer Data Platforms (CDPs) fall short in the following use cases.

Customer Data Platform Use Cases That are Obsolete

With more emphasis on data and the use of data warehouses coupled with reverse ETL, companies require a platform that can be used by the majority of their departments. Having CDPs in your organization allows your sales and marketing teams to get benefitted, but it can’t be used by finance or customer success teams. Here are some of the compelling customer data platform use cases that are outworn:

Businesses Looking for Scalable Options

When a company’s client base develops drastically, CDPs might face challenges to scale. When these smaller-scale CDPs have to handle significant amounts of data or more complicated sets of information, the processing speed drops significantly, and redundancies occur. On paper, this may not appear to be a big deal, but wasted opportunities and unmet client requirements eventually expose a company’s flaws.

Not all CDPs offer the same functionality and features. Most CDPs do not provide advanced analytics capabilities like Artificial Intelligence or Machine Learning. As a result, some businesses settle for less diversified customer data platform use cases to keep themselves within their budgets.

Businesses Needing to Extract Data from Heterogeneous Sources

When a CDP solution fails to collect data from different source systems, businesses then struggle to create a “single profile” of their consumers. This demonstrates a lack of critical technological components that should be available to the employees. Despite their lack of functionalities, vendors who provide customization tools but lack integration capabilities may market themselves as CDP suppliers.

In such circumstances, the IT team is tasked with ingesting structured and unstructured data from many sources. Data professionals may opt to design bespoke code for data ingestion or create customized frameworks for information extraction. Hence, it becomes a time-consuming process and requires a lot of effort.

Businesses Requiring Delivery of Actionable Insights

Failure to obtain proper findings from studied data eventually leaves businesses with ineffective insights. These flaws, once again, result in missed opportunities and delayed responses to crucial customer/market developments. This circumstance may require hiring outside analysts or using different techniques to assess incoming data.

Without the actionable insights, your company may bear a lot of loss. However, by having actionable insights into your organization, you can achieve the following:

  • It allows you to make informed decisions that drive activities resulting in excellent company impact and long-term success.
  • Today’s continuously changing competitive landscape allows for faster response times. Insights that prompt unprogrammed choices, driven mainly by predictive and prescriptive analytics, can help you gain a competitive advantage.
  • Aids businesses to improve operational efficiency by uncovering actionable insights in the tools of their choice, leading to process improvements.
  • Improves resource utilization by determining where you should invest and concentrate next to drive future development.

Case Study: How Loom Benefitted by Shifting to Reverse ETL from CDP

Loom Logo: Customer Data Platform Use Cases
Image Source: Crunchbase

Loom is video messaging software that allows users to communicate with coworkers, employers, and even students and instructors in a more productive way. They were using a CDP platform that didn’t allow them to share information other than “pure event data”.

With the help of reverse ETL, Loom was able to send all its relevant data to Zendesk, which they could not do while using a CDP platform. Sending data to Zendesk helped them to prioritize tickets and provide seamless customer service, helping boost their top line.

What is Reverse ETL?

Reverse ETL is a technology that allows you to synchronize data from your data warehouse to SaaS applications like CRM, Customer Experience, and so on. It aids in operationalizing your data.

Traditionally, businesses were interested in preserving data at a single source of truth and creating business reports using Business Intelligence technologies. However, these insights are even more powerful if they are used to drive the everyday operations of your sales, marketing, and finance teams using solutions like Hubspot, Salesforce, Marketo, Zendesk, and others.

Operationalize Your Data Through Reverse ETL: Customer Data Platform Use Cases

The aggregated data from your data warehouse must be integrated with applicable technology so that your marketing or sales team may get it automatically in the most appropriate location at the correct time. This is when Reverse ETL comes into play.

The data warehouse acts as a “single source of truth” in the reverse ETL process, keeping the most accurate, up-to-date data and duplicating it to numerous third-party systems. Reverse ETL provides your data and business teams with the data and insights they require for their day-to-day applications and proactive decision-making.

Reverse ETL vs CDP: What’s the Difference?

Here are some of the key differences between reverse ETL and CDP:

  • Functionality: In reverse ETL, all your data is available in a single data warehouse. With more data from various sources, you can get more insights and undertake data modeling, whereas CDP gives you access to customer data, restricting the kind of studies you can run.
  • Technology: In reverse ETL, batch APIs are typically used to obtain real-time data. On the other hand, CDPs frequently use event-driven APIs to get new data. When more information becomes available, a trigger is sent to the system, allowing the ingestion process to begin and access new data.
  • Motive: Reverse ETL transfers data from warehouse to SaaS applications and can be used by marketing, sales, customer support, finance, etc. On the other hand, CDP collects data from multiple sources and can be used by marketing and sales teams alone.

Why is Reverse ETL Better than CDP?

Below are the reasons why a Reverse ETL platform is better than CDP:

  • Reverse ETL takes care of all your data preprocessing needs and lets you focus on key business activities.
  • Reverse ETL gathers data that has already been structured in data warehouses and helps in saving your team’s bandwidth and efforts.
  • With reverse ETL, you can gain more insights as you get access to more data from various sources as compared to CDP.
  • Reverse ETL could be used by any team, such as marketing, sales, finance, support teams, etc., for their day-to-day operations, whereas CDP is mostly used by marketing and sales teams.
  • The cost of reverse ETL is based on the number of SaaS applications rather than the number of visitors per month, so you have more transparency.

Modern Way to Operationalize Your Data: Reverse ETL

The use of reverse ETL will allow you to open a lot of opportunities for your organization. You may make use of several benefits provided by reverse ETL. The three main advantages reverse ETL brings are as follows:

  • Operationalize Your Data: By providing relevant data to SaaS apps, reverse ETL systems enable you to operationalize and sync your data from multiple applications into a common application. For example, Hubspot, MailChimp, and Marketo data can be replicated to a data warehouse and synced to Salesforce to better the sales process.
  • Reduce Dependencies: Because of the no-code, plug-and-play ease of reverse ETL solutions like Hevo Activate, marketers and sales professionals no longer need to rely on data/IT teams for their working needs.
  • Improve the Customer Experience: Reverse ETL platforms make it easy to transmit data in real-time from a data warehouse to a SaaS application. This enables businesses to provide their clients with the most effective services possible at the right moment.

Activate Your Data Warehouse With Reverse ETL!

Hevo Activate syncs data from your warehouse – Snowflake, Redshift, BigQuery – into Business Applications – HubSpot, Salesforce, Zendesk, Google sheets, and many more. Check out our growing list of integrations.

Hevo Activate features –  SQL Query Editor, Custom Data Synchronization, Incremental Updates, Intelligent Data Type Conversion, and many more – help your business teams get accurate data without writing complicated Python Scripts. 

You can make faster and wiser decisions by operationalizing your product and customer data together – analyzing user journeys, and creating truly personalized experiences for your customers.

Enrich your applications with trusted data in your warehouse. Get started with Hevo Activate for reverse ETL today!

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Reverse ETL Use Cases

Here are some of the use cases of reverse ETL in different teams:

Reverse ETL in Marketing

Customers today demand an outstanding level of customization. As a marketing team, you may use reverse ETL to ensure that you send hyper-personalized and data-driven consumer engagement across various marketing channels to the right individuals.

How Imperfect Foods Increases Reactivations Using Reverse ETL

Imperfect Foods Logo: Customer Data Platform Use Cases
Image Source: PR Newswire

Imperfect Foods is a premier online grocer at the forefront of reducing food waste and creating a more sustainable food system. 

Imperfect Foods, a Certified B Corporation, works directly with farmers and producers to rescue food and deliver it straight to consumers’ doors. It gets tons of consumer data due to hundreds of thousands of customers and an ever-increasing number of data sources. They were facing issues in identifying what characteristics lead to high-value consumers or what circumstances motivate customers to order.

By utilizing reverse ETL in their organization, Imperfect Foods achieved the following:

  • Since deploying reverse ETL, the marketing team no longer needs to download ad hoc data sets from Snowflake to perform marketing campaigns across many channels.
  • Marketing has lowered the Customer Acquisition Cost (CAC) by 15% and increased customer reactivations by 53% by using reverse ETL to sync bespoke audiences driven to Snowflake by various ad platforms.

Reverse ETL in Sales

Using reverse ETL, the sales team may utilize the CRM lead score to rank leads in Salesforce or Hubspot.

How Reverse ETL Helps Culture Amps Speed Up Their Sales Team

Culture Amp Logo: Customer Data Platform Use Cases
Image Source: Crunchbase

Culture Amp is an employee analytics platform specializing in staff surveying and analytics. For years, Culture Amp battled with an in-house reverse ETL solution. They were facing issues in sending data to the applications they use at the desired speed.

By using a reverse ETL platform, they were able to achieve the following:

  • Data from operations flows effortlessly into downstream technologies that teams use regularly.
  • Due to less waiting time, teams were able to work faster.
  • Teams were receiving notifications, allowing them to resolve synchronization issues as they arise swiftly.

Reverse ETL in Customer Success

Reverse ETL allows the customer support team to automatically categorize inbound tickets by priority order based on the customer health score metric.

How Blend Reduces Success and Finance Team Reporting Time

Blend Logo: Customer Data Platform Use Cases
Image Source: PR Newswire

Blend is a digital lending platform that supports and facilitates mortgage, consumer loan, and deposit account applications. The primary challenge Blend faced was that they were finding difficulty sending data out of the data warehouse.

By using reverse ETL, Blend was able to achieve the following objectives:

  • Blend’s finance department could close off service team books four days sooner, lowering the team’s financial reporting time in half.
  • Their operations team could combine data sources to deliver robust, enterprise-wide data analysis.
  • Reverse ETL facilitated team and tool alignment, resulting in improved collaboration and a positive effect on Blend’s bottom line.

How to Operationalize Your Data Using Hevo Activate?

Hevo Activate Workflow: Customer Data Platform Use Cases

Hevo Activate syncs data from your data warehouse to the business apps you love – CRM applications like Salesforce, Marketo, Zendesk, and others. The data warehouse tables may contain information imported from various sources, including SaaS programs like Facebook and LinkedIn, webhook sources like SendGrid, etc.

You may use Hevo Activate to build complex SQL queries that offer a unified picture of this fragmented data, and then change it for use by your CRM application.

Hevo Activate Steps to Reverse ETL: Customer Data Platform Use Cases

Using Hevo Activate is relatively easy. It is a three-step process that consists of:

  • Step 1: Connecting data warehouse and destination applications.
  • Step 2: Writing a query to get relevant data.
  • Step 3: Mapping output to the destination object.
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Using the best-in-class reverse ETL solution like Hevo Activate gives you the following benefits:

  • Intelligent Data Type Conversion: During the mapping action, Hevo Activate automatically converts the field types of synced data.
  • Smart Error Handling: Hevo Activate notifies you of sync errors. If there are persistent issues, you can stop sync, resolve them and continue.
  • Secure: Hevo Activate’s fault-tolerant design ensures that your employees can handle data securely and consistently without data loss.
  • Live Customer Support: The customer support team of Hevo Activate is available round the clock to provide you assistance via chat, emails, and support calls.
  • On-Demand Data Sync: Hevo Activate allows customers to resume the sync or run sync immediately to perform data sync on demand.
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Final Thoughts

One of the essential duties of any organization is to gain meaningful insights from data and make better decisions. Analytics must be integrated directly into business applications by organizations. To uncover new possibilities, reduce attrition, and deliver improved service, go-to-market teams want actionable data that they can trust. Such a situation may be solved via reverse ETL.

Reverse ETL tools should be used if your organization wishes to operationalize data to allow data-driven decision-making for various teams such as marketing platforms, sales platforms, customer support, finance, and so on. If your company is primarily active in marketing, CDP is a better option.

There are a lot of customer data platform use cases that are outworn. Still, you can take advantage of emerging technologies such as reverse ETL, which allows you to get actionable insights from your data and take advantage of scalability and capability.

Reverse ETL using modern tools like Hevo Activate helps your data and business teams to extract data from multiple sources and sync the insights from your Single Source of Truth (SSOT) to downstream SaaS applications. This ultimately improves customer experience through real-time analytics and helps you foster a healthy and efficient data-driven environment in your organization.

Saket Mittal
Former Marketing Content Analyst, Hevo Data

Saket is a data analyst who has implemented different marketing strategies for Hevo. He has authored numerous articles covering a wide array of subjects in data integration and infrastructure.

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