How To Monetize Analytics Insights With Stackless

The company

Stackless delivers the world’s only data readiness platform to its customers. They use the Stackless service to analyze and monitor data and derive granular, actionable insights — helping them improve product development and elevate marketing and customer experience.

Its solution, built on GoodData’s cloud-based analytics platform allows companies to focus on their core business while Stackless handles the provision of timely, trustworthy, and useful data. Stackless’s mission is to remove the need for companies to invest in a full data stack, thus saving them time and resources and reducing their overall data analytics costs.

Stackless provides its customers with an admin dashboard to manage all of their data source connections and installed data applications (DApps). It also allows them to monitor the status of their data warehouse in terms of capacity used, the number of data insights created and the current data refresh interval.

The challenge:

The challenge for most companies is the number of different data sources they work with and how to merge and model the data for reporting. Data from Sales, HR, Marketing, Finance, and so on, all needs to be synergized and accessible to different stakeholders — preferably in one tool. Even at the department level, multiple different tools produce large amounts of data. For companies to make fast and efficient decisions based on all of the data from disparate systems, they need a way to collect, structure, and visualize it from both a granular viewpoint as well as a high level.

The second challenge many organizations face, particularly SMEs, is being able to analyze and act on this data cost-effectively. The cost and expertise required for setting up a full data stack with the team to support it is not insignificant. This is where Stackless has established itself as a unique solution within the data and analytics industry.

To solve these problems for its customers, Stackless needed an analytics platform that could:

• Scale efficiently (in terms of performance, cost, and storage) as their business and the needs of their customers grew
• Support automation via APIs and SDKs in order to quickly roll out new insights to end-users on-demand.
• Provide trusted data outputs via a robust and transparent semantic data model.
• Offer advanced embedding features in order to deliver a seamless analytics experience to its customers as well as monetize the solution.

The solution

The beauty of the Stackless model is the ability for clients to simply pay as their data needs grow. Instead of incurring the employee or consulting cost of custom building new reports, customers who require more insights can simply add them to their cart and access them in a matter of minutes. This removes the need to talk to sales about ‘add-ons’ while promoting the self-service benefits of the platform. This has the knock-on effect of saving Stackless time and resources to better assist customers. This guided self-service aspect means customers can create their own insights with only minimal input from Stackless. Where manual assistance is required, it can be more strategic in nature.

This is similar to GoodData’s self-service and scalability attributes. With its workspace-based structure, as Stackless brings on more clients they simply roll out new workspaces. Not only does this make for predictable and affordable pricing it also ensures that customers like Stackless can always rest assured that the performance and storage capabilities of their analytics solution are always aligned with their company growth/growing analytics needs.

GoodData’s analytics-as-code approach enables Stackless to automate many of its processes and deploy data insights through the use of APIs. The extensive API support within the GoodData platform means when the customer requires a new view of the data, the system simply uses an API call to spin up the new insight or dashboard in next to no time.

Rather than customers needing several point solutions for different types of data (ie. for Accounts, HR, Marketing), Stackless enables its customers to mix data from different systems to get a clearer picture of what’s going on and then easily act upon it. This is facilitated by GoodData’s semantic (metrics) layer. The semantic data model transforms the data into business- friendly logic making it easy for users to understand. Moreover, the semantic layer acts as a single source of truth, ensuring that no matter how the data is presented, the outputs remain consistent.