The world has changed. The number of data initiatives has exploded, with new programs to shift from descriptive to prescriptive analytics, investment to build and embed recommendation engines, and even new AI teams to train large-language models.
All together, this puts data availability, or rather the lack of it, as a top priority for most companies. SaaS vendors selling into enterprises should take advantage of this trend and lean into data offerings as a way to increase revenue and customer stickiness.
Data, not dashboards
Here’s what happened:
All companies beyond early-stage startups now have their own data team. In the last decade, the number of data jobs in the United States tripled, driven by the insatiable need to be more data-driven. These data professionals have their sights set on the wealth of data locked in their company’s SaaS systems (CRMs, ATSs, ERPs, Accounting, Marketing automation, etc.).
SaaS reporting dashboards just aren’t cutting it. Think about the SaaS tools you use. Would you rather use the reporting / analytics portal within each separate app, or just get access to the underlying data to do your own analysis?
Data needs to be somewhere where customers can actually work with it. For most modern data work, this equates to a finite set of destinations, namely the dominant data warehouses powering Business Intelligence: Snowflake, AWS Redshift, Google BigQuery, Databricks, or Azure Synapse.
APIs and file-based transfers only go halfway
What’s the most common answer when a client asks a SaaS vendor to export their data?
“Here’s our API documentation, have at it!”
Unless the client is using the API for a real-time integration, for most analytical needs, APIs only go halfway. Clients are forced to accept the API and build the other half: API scrapers, ETL pipelines, and other scripts to load the data into their data warehouse.
Other SaaS vendors may offer data delivery via S3 buckets or SFTP sites but once again, almost by definition, this is a halfway solution since clients and their data engineering teams are then responsible for picking up the files and loading it into their data warehouse.
Not only is this a bad experience for clients, it’s inefficient, requiring significant investment in time and resources from both parties.
The opportunity at hand
70% of a data professional’s time is spent on data integration and preparation, and their time is not cheap. It’s no surprise that the data integration industry is now $11B and growing fast. Clients want to offload as much of the integration as they can and are willing to pay a lot of money to third-party tools like Fivetran and Informatica to scrape SaaS vendor APIs on their behalf and load the resulting data into their data warehouses.
This setup is far from ideal – each additional SaaS tool a company adopts requires a new connector, integration tool, or pipeline, and companies are willing to pay to break free from this cycle. In fact, from our conversations, 4 out of 5 data leaders are willing to pay up to 20% more to their SaaS vendors to get ready-to-query data directly from them.
Leading SaaS vendors like Salesforce and Stripe have already begun to lean into this trend and capture the value that is otherwise going to the integration players.
The benefits of direct data delivery
Based on our experience thus far, by loading customer data directly into client data warehouses, SaaS companies stand to gain:
Up to 20% higher ACV. Clients are willing to pay to cut out the integration step and get the data where they can directly use it. Additionally, enterprise clients are increasingly starting to make this a key feature requirement.
Improved client stickiness. If you sell CRM software, you sell into Sales. But if you offer data delivery as well, suddenly you’re working with the data team and expanding your reach to the rest of the org. Your data starts to power internal dashboards, AI models, and even board decks, leading to strong stickiness.
Reduced overhead. As with any process, the fewer the number of steps, the lower the overhead. By cutting out the middle step and leveraging native cloud sharing protocols, both parties can go back to their day jobs and shift out of integration mode.
By delivering data on the consumers’ terms, SaaS vendors can gain a unique competitive edge and start tapping into their clients’ data budgets - especially relevant in today’s volatile market conditions. That being said, developing and maintaining these features in-house can prove to be it’s own challenge. Fortunately, embedded data delivery solutions like Amplify can drastically reduce the time to value, enabling quick and efficient data service deployment. Book a call with us to learn more about how other SaaS companies are launching direct data delivery in days.