A customer engagement platform’s functionality relies on customer data from outside sources such as data warehouses, spreadsheets/CSVs, customer relationship management software (CRMs), and customer data platforms (CDPs). The data from these sources must be sent to the customer engagement platform for features like segmentation, personalization, and workflow triggers to function. Each data source has a different connection method and a distinct set of pros and cons. In this post, we’ll explore the major data sources, how they connect to customer engagement platforms, and why you should or shouldn’t use one over the other for various use cases.

Data warehouses such as Snowflake and BigQuery —which store columnar data traditionally associated with business analytics operations— have been growing in popularity as a place to store all customer data for use across all business applications (not just analytics). This trend is largely due to the advent of reverse ETL tools like Hightouch and Census which simplify the process of syncing warehoused data to customer engagement platforms and other non-analytics-based business software. There are a few advantages here. You reduce the amount of company data you store on 3rd party services, which can enhance security. You also avoid vendor lock-in and high costs associated with CDPs, the main customer data storage alternative. The big disadvantage of using a data warehouse is time. Reverse ETL data syncing can be slower than other options, complicating trigger campaigns that rely on immediate content delivery to customers.

Spreadsheets and CSVs are another option. Most customer engagement platforms have interfaces that allow nontechnical users to easily upload these files, saving engineering resources. However, uploading static files means that data changes won’t be auto-synced, so you’ll have to manually upload updated files in batches. If, for example, a customer unsubscribes from your newsletter and your spreadsheet email list still contains their email, the engagement platform will continue sending them unwanted emails until a manual batch update is performed. Although less than ideal for the newsletter scenario, CSV uploads can be useful in other contexts such as manually segmenting customers based on static and relatively static data like demography or historical customer actions.

CRMs like Salesforce and Zoho, on the other hand, can be configured to dynamically update demographic and firmographic information about leads. They also contain helpful tools like lead scoring to qualify which leads are most likely to convert to customers. Many CRMs come with out of the box integrations, which make it easy for engineers and semi-technical people to quickly connect data from the CRM to other tools like engagement platforms. If the CRM doesn’t already have the right integration, your engineers will need to build a custom integration. Additionally, most CRMs aren’t designed to store customer events like logins, purchases, and newsletter signups, so you’ll have to combine them with other tools that are made to house such data, like CDPs.

CDPs like Segment and Rudderstack collect, organize, and store all data about your customers’ attributes and actions across your products and marketing touch points. Good CDPs also make it easy to feed this data into any tool that needs it, whether that’s a CRM that needs lead enrichment or an engagement platform that needs to trigger a welcome email after a customer signs up on your website. This is usually achieved with webhooks or by using one of the CDP’s pre-built integrations. The downside of CDPs is that they make data portability difficult and can get extremely pricey as you scale.

In reality, growth teams will usually need to combine different methods of customer data storage to fit the needs of their companies. One common combination is Salesforce plus a CDP. Salesforce is a CRM that already acts as the source-of-truth and central data hub for many companies’ prospect and customer data. However, it can be difficult for growth teams to ensure each platform used to engage with customers (e.g., sales engagement, call tracking, form builders, etc.) is simultaneously syncing data to Salesforce. In this case, a CDP can be used as a kind of syncing hub that automatically collects data from every customer touchpoint at regular intervals via integrations, and syncs a 360 degree view of each customer back to Salesforce.

There are a large number of possible configurations for storing and updating customer data. Which one you choose will most likely be a factor of cost, data loading speed requirements, automated data syncing requirements, setup difficulty, and engineering resources at your disposal.