How SaaS companies can power their AI features with integration data (6 examples)

Aside from recruiting talented developers to build AI features in your SaaS product, you can leverage the data you collect from your customer-facing integrations. 

Integration data provides information that’s specific to individual clients, which helps your AI features deliver personalized experiences more easily. Integration data can also come from the systems of truth—like a CRM for client data or an HRIS for employee data. This allows your product to collect accurate, comprehensive, and up-to-date information over time that keeps your AI features useful and impactful.

So how, exactly, can integration data support AI features? We’ll break this down by covering how 6 SaaS companies use product integrations to power their AI features.

1. Deliver AI-generated insights to employees

Assembly, an employee management platform, uses file storage data from integrations to fuel their AI-powered intranet’s search functionality. 

Rather than needing to search through individual documents in your company’s shared file storage platform, Assembly’s customers can simply ask the AI-powered search (coined “Dora AI”) their question and, in just a few seconds, get an answer back.

2. Provide intelligent prospecting recommendations 

Telescope, a sales automation platform, leverages CRM integrations to power their lead recommendations. 

When users connect their CRM platform, such as Salesforce or Hubspot, to Telescope, their prospect and customer data begins to train and enhance Telescope’s AI model. Telescope can then generate an optimal customer profile and recommend high-fit leads.

In addition, as Telescope’s clients update their CRMs over time (e.g. marking opportunities as “closed-won”), Telescope’s models will receive further training, all but ensuring they improve over time for each client.

Related: A guide to integrating SaaS applications

3. Analyze and prioritize customer feedback

Kraftul, a customer feedback platform, trains its model with feedback data that’s collected in various forms (via integrations), such as tickets, transcripts from user interviews, and surveys. 

Based on its training for a given client, Kraftul can analyze the customer feedback and provide the product improvements that need to be prioritized.

4. Identify opportunities to improve employee productivity

‍PeopleLogic, an end-to-end people intelligence platform, uses HR integrations to automatically pull and track key employee-related metrics, such as tenure and time-off. These metrics fuel AI-driven insights that PeopleLogic’s customers can use to enhance their employees’ performance. 

For example, using time-off, time spent in meetings, and other sources of data, PeopleLogic can generate a score that represents how likely an employee is to stay at a company—StayFactor™.

5. Streamline expense submissions

Ramp, a spend management platform, integrates with over 1,000 platforms, including banks, accounting systems, and HR systems, to automate their users’ expense workflows. For instance, Ramp Intelligence, Ramp’s AI feature, automates parts of the user workflow, such as generating receipts and categorizing expenses. 

Ramp Intelligence also leverages thousands of transactional data points to let you know if you are paying too much for software.

Related: A look at the top integration trends in 2024

6. Hyper-personalize your outbounding 

Apollo, a sales intelligence and engagement platform, uses data from clients’ CRM and marketing automation tools to generate subject lines and email bodies that are most likely to receive engagement (i.e. get opens and click throughs). And, equally important, it can do this for a range of personas (e.g. executive buyer) and scenarios (e.g. a competitor objection).

Also, since Apollo’s AI model gathers email performance data across scenarios and personas over time, it’s able to offer increasingly better copy for each client.

Related: What you need to know about marketing automation integration

Final thoughts

SaaS companies, including the ones listed above, use Merge to power their product integrations instead of building them in-house. This enables them to get their AI features to market faster and, because of the large amounts of data these integrations sync into their product, offer best-in-class AI capabilities.

You can learn more about how our clients use integration data to fuel their AI features and how your platform can too by scheduling a demo with one of our integration experts.