As Whatfix scaled both in terms of operations and employee size, the volume of data captured and stored increased exponentially. Due to this, the current data & analytics processes started showing cracks. Data existed in the form of disparate silos, which restricted analytics use-cases that require data from multiple sources.
Before 2018, the internal data analytics at Whatfix was close to non-existent. Our business users used to rely on the customer data generated by our platform. Since these numbers were not correlated with the business data, analytics was restricted to account-level data. This prohibited us from looking at the bigger picture.
For instance, answering a question like “What is the usage trend in the top 25% of our clients based on ARR?” required almost 2 months of data engineering time. Inability to timely answer questions like this, among other pressing bottlenecks, created the need to deploy a data pipelining framework to build a single source of truth.
Samvit and his team began to evaluate whether they should develop an in-house solution or go for an external tool. They concluded going ahead with a third-party tool as developing an in-house solution would occupy a sizable portion of engineering bandwidth and even then it wouldn’t be as robust. The only inhibition was data security standards.
Since our core-offering involves handling our clients’ data, we generally avoid using third-party tools. Compliance is a big deal for us and we can’t compromise on that. While evaluating Hevo alongside Stitch & Fivetran, SOC 2 compliance was among the most important parameters.
In addition to SOC 2 compliance, Samvit chose Hevo out of all other competitors because of these reasons:
- Support for python-based transformations
- Best price to performance ratio
- Seamless data loading with advanced features
While evaluating the data integration tools we were comparing the tools based on the speed at which they move data and we found Hevo to be the fastest. Additionally, its transformation capabilities far surpassed all other solutions that we considered.
Whatfix is currently using Hevo’s pre-built integrations to pull data from Salesforce, Zendesk, Amazon S3, and Google sheets data sources. They’re using web-hooks to pull data from ClientSuccess and SaaSOptics. All of this data undergoes a series of transformations ranging from simple transformations like date-stamping, JSON flattening to complex python-based transformations. The transformed data is then aggregated at Whatfix’s Amazon Redshift data warehouse and consumed by different team members in the form of reports created on Looker.
Before Hevo, all data integration processes were manual, and reporting used to take a few days. Though complete adoption is still underway, reporting time has come down to just a few hours. Both product & engineering teams track their KPIs on Looker without any data issues and take important business decisions without any delays.
The biggest advantage of Hevo is that Loading and Transformation are seamless. We rarely have to spend time on maintenance. Hevo does a lot of heavy lifting for us: Time Stamping, JSON flattening, Table Splitting among other transformations. Developing an in-house solution comparable to Hevo would’ve definitely required significant expenditure both in terms of time & money. Hence we’re extremely happy to have Hevo on our side.
Last year Whatfix claimed to have onboarded over 100 Fortune 1000 customers, almost doubled its revenues, and is poised to raise a Series D round of funding. Because of the pandemic, most companies have adopted remote working and this has increased the need for solutions like Whatfix. It’s helping companies train their new employees faster on new software and processes remotely, empowering them to drive digital adoption and prepare for the future of work. Hevo is thrilled to have played an essential role in their growth journey and is super excited to solve more data challenges together!
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