Written by Gaurav Agarwal |
Traditional on-premise enterprise BI solutions take 18 months to implement and deliver with bi-annual or annual refresh cycles. Adoption and engagement across the organization remains low in many of these delivered solutions delivering limited value. Having worked at a few large enterprise vendors in BI and other domains, one of the most frustrating aspects from a product development perspective is the lag in end user feedback to be able to provide increased value to them. Even after identification, iterations on the product take at least half a year to reach the end user.
Majority of the end users by that time have completely disengaged with the solution as its providing them little to no value. This user behavior has hit an extreme in recent times with tiny attention spans for end users who are using fast and easy-to-use consumer apps in their off-work life. From my experience in building consumer products, the only way to operate a successful experience is to enable experimentation and iteration at a rapid pace.
As you can imagine, this is non-existent in enterprise BI. Although we've seen other SMB and cloud enterprise domain players such as Zendesk successfully practice this. Moreover, in traditional BI, the end-to-end user experience is dependent on the quality of integrations between several technology vendors. An end-to-end cloud BI such as GoodData differentiates here by not only delivery increased time-to-value but also by providing a truly defined and seamless user experience for both the business and technical users.
Working on a cloud-based BI platform at GoodData, provides the following strategic competitive advantages in the overall BI industry from my perspective:
- Data-driven product development: Building a platform is never easy. In theory you can do everything, but successful platforms are ones that have a clear strategy and understanding of where it's going. This is based on multiple inputs including the market, customers and company strategy. But a key element in this is the ability to drive everyday decisions in product and engineering based on real data using your best judgement and experience. Many argue that data hampers creativity, but the way I think about it is that when used in the correct way it can focus your creativity on the problems that deserve to be solved by the best engineers.
At GoodData, we monitor and analyze everything (in our dashboards of course and respecting all privacy and agreements). The goal is not to advertise and target people, but to better understand engagement and adoption of our UX, volume and variety of our data loads, number of API hits etc. Having real-time access to this data combined with the experience of folks using this data everyday is our real competitive advantage.
- Rapid iteration and experimentation: When I built an ad-tech platform targeted at data scientist within a large software company, the only way to increase revenue was to increase the level of experimentation to understand what will increases relevance and CTR. In the rapidly evolving data landscape with different thesis around the definition of "data discovery", we have the ability to test several concepts in the market and select the one we need to invest in based on rapid feedback and adoption and engagement metrics. Sounds unreal in the BI domain? We do it every day.
- Deep understanding of our personas: User personas in the data domain are rapidly changing and are highly complex. Who is a data scientist and what is he trying to do? What's the difference between a Business Analyst and a Data Analyst? What's the best tooling for IT vs a data engineer? Who is using a specific feature and why? Our ability to analyze product usage through different lenses allows us to navigate this complex environment and build the right tools for the right personas.
- Delivering continuous value: From a product perspective there is nothing more satisfying than constantly delivery high value to your end users, whether business of technical. For a SaaS business like ours, this becomes even more critical as we need to "earn our revenue" every single day. BI products can get stale for end users especially when they interact with rapidly evolving consumer products every since day. The ability to provide new features and enhancements on a monthly or even weekly basis helps create ongoing end-user perceived value.
- Customer Satisfaction: Constantly monitoring how each of our customers are engaging with the platform enables us to identify early any issues that maybe product or otherwise. Having this data helps us have an informed discussion with our customers that is focused on problem solving rather than problem identification. Additionally our ability to ship rapidly, allows us to meet any urgent needs in real-time and also benefits the entire customer base. The perfect recipe for happy customers!
Written by Gaurav Agarwal |
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