Real-time Export of Data from Snowflake into Automated Workflows
Consumer expectations have changed as more businesses use data to offer more informed sales and customer support processes. However, not all businesses have been able to consistently keep up with consumer expectations. Gladly’s 2019 Customer Expectations survey notes, “Consumers today expect a seamless handoff from one experience to the next—so whether they’re switching from one channel to another (like phone to text), or an in-store experience to a contact center one, they expect not to have to repeat their stories again.” In fact, according to the survey, “86% expect the next agent they communicate with to know their previous interactions. But only 24% experience this. 76% expect agents to see their simultaneous interactions across channels (like if they sent a text while on the phone with an agent). But only 19% experience this. 66% expect contact center agents to know about their in-store interactions (and vice versa). But only 22% experience this.”
Multi-channel support is just one example of how real-time business insights are imperative in today’s fast-paced world. SalesOps and Support teams are better equipped to offer an informed and personalized customer experience when they have customer data available to them during their interaction. Integrating data real-time data updates into customer sales and support workflows can be transformative to the consumer experience, and help businesses to stay competitive as expectations rise. Having data analysts generate SQL queries and .pdf reports is a process that can only move so fast, and client-facing teams need comprehensive insights delivered in real-time.
Snowflake and Workato are now partnering to do just that. Snowflake is a cloud-native platform that offers ease and agility of access, and scalability, to generate greater value for its data warehousing clients. Workato is a cloud-native iPaaS solution, known for having a uniquely large number of connectors and an easy-to-use drag-and-drop interface that make automating processes, using codeless business logic, easy and immediate. As two companies aiming to futurize work and create ease-of-use and scalability for business users, the partnership is a natural match.
Putting the data into the hands of the end-user
Snowflake Technology Alliances Director, Tarik Dwiek, noted that Snowflake’s enterprise customers often use a range of SaaS applications in conjunction with databases and on-prem applications, and that Workato for Snowflake makes it possible for customers to integrate these disparate applications to move data into and “more uniquely, out of” Snowflake and incorporate it seamlessly into automated workflows. In an increasingly data-driven business landscape, this agility of access to the Snowflake cloud data warehouse could lend businesses the edge they need to stay competitive.
Now, business teams can derive real-time insights from Snowflake using Workato and make them available in the apps they use everyday, such as Slack, Salesforce, NetSuite, and many more.
These in-context insights enable:
- Sales to have product usage and customer 360 data in Salesforce to drive sales, upsells, and prevent churn
- Marketing to get data from Ad platforms, landing pages, and other lead touchpoints right inside of hub apps like Marketo to build customer journeys and develop ROI/Performance models for their paid campaigns
- Support to have customer 360 data, RMA status, and more in support apps like Zendesk
- Teams across the business to derive various company and departmental key metrics via alerts in Slack or MS Teams
Integrating Business Intelligence Into Automated Workflows
So how might this work in practice? Let’s say a customer has reached a product usage limit – they’ve added 10 out of 10 users to their account. In real-time the Account Executive on that account would get a notification in Slack letting them know that Account X has reached the user limit with a link to their Salesforce profile. In Salesforce, the rep could view how many times the customer has logged in, if they have engaged with any marketing materials, and other indicators of the customer’s intent. This arms the rep with the context they need to best serve the customer and potentially upsell. Another use-case might be generating a responsive, personalized marketing campaign by automating customer data analysis from the cloud database and auto-triggering marketing steps.
Basile Senesi, Head of Sales Operations at Fundbox elaborates: “With Workato and Snowflake, we’re able to do things much faster by using our sales ops resources to tackle issues that before required a developer or analyst, thereby allowing us to scale. Workato is becoming the cornerstone that powers all of our client facing teams that use Salesforce and is really the data pathway that we’re now using to intelligently get information from Snowflake into Salesforce.”
Having access to actionable business intelligence insights and business data allows businesses to make more accurately predict potential outcomes, and optimize workflows for success. Cloud-native platforms make data analysis tools and AI / ML (machine-learning) enabled data analysis increasingly accessible and scalable for businesses, without the costs of infrastructure development that may have in the past been inhibitive.
Snowflake Cloud Data Warehouse Reimagines Data Warehousing
If your data lake is more like an aquifer, that takes time-intensive drilling to dredge to the surface, consider looking instead to the cloud. With Snowflake and Workato, you can access it as easily as reaching out a mittened hand and seeing an organized, crystal-clear, structured form land on your fingers.
Workato’s operating system is unique for offering intelligent automation to integrate applications and automate workflows without compromising security and governance. To learn more about integrating business intelligence insights from the Snowflake cloud data warehouse into automated workflows, and to see how Workato’s drag-and-drop recipe editors work, request a demo with our team.