Elevate good GTM strategies to great with business-aligned data: Snowflake’s Kaushal Veluri

If a product is good, it will sell itself. Many companies take this approach when launching a new product, rebranding a product, or approaching a new market. Unfortunately, in today’s cluttered and crowded market, good - even great - products can sink without a data-driven Go To Market (GTM) strategy. 

Crafting an effective, data-driven GTM strategy can make or break your chances of success. It can boost brand recognition, increase revenue, improve customer relationships, and give companies that coveted competitive advantage. 

A typical GTM strategy will cover a variety of components, including market definition, an outline of the customer, distribution model, messaging that covers a product’s value proposition, an identification of competitors in the field, and pricing strategies.  

This is where data makes a difference; it can take a GTM strategy from ordinary to extraordinary. GTM strategies, very often, are intuition-based. Founders opt to go with a gut feeling or make decisions based on assumptions - a risky approach in today’s complex marketplaces. Data helps companies craft strategies that are as targeted and accurate as possible. It is the first and foundational step in building a comprehensive plan.  

The GTM strategy was the focus of a fireside chat at YourStory’s DevSparks Hyderabad 2024. Kaushal Veluri, Head of RSI Partners, Snowflake India, and Rishabh Mansur, Head, Community, YourStory, discussed the essential role of data in creating truly effective GTM strategies. Snowflake provides data storage, processing and analytic solutions that enable companies to identify trends, mine insights, and create targeted, personalised messaging to appeal to prospective customers. 

Veluri shared insights on building a data-driven culture in organisations, data collection processes, and examples of data-rich GTM strategies.

Intuition or information: what makes a great GTM?

Should companies rely on intuition or information to create a GTM strategy? While the new consensus leans towards data-driven decision making, Veluri offered a different perspective: intuition and information as two sides of the same coin. 

Data from a variety of sources - internal databases, customer feedback, and market research - contribute to a comprehensive dataset. Historical data can offer a retrospective view of a company’s performance. Past GTM strategies and sales data illuminate what product demos, presentations, and value propositions are ideal for converting different prospects. Visualisation tools like dashboards and reports can help companies understand conversion rates, revenue growth, customer acquisition costs, and more. Predictive and descriptive analytics can mine insights or identify patterns in the data.

The importance of data in crafting a GTM strategy cannot be overstated, but relying solely on a data-heavy approach has its downsides. In the fireside discussion, Veluri discussed the tendency to over-analyse data, splicing it into increasingly narrow segments until the value of the data is lost. He said intuition does play a role in decision making, where founders should attempt to align it to a business objective. 

“If you take the data-driven approach, I strongly believe that the process becomes focused solely on analysis. Companies begin to slice and splice the data, until analysis becomes paralysis. You have to have that balance; you have to take a leap of faith. If you have an intuition that there is potential in a particular market, let's try and validate that with data,” he said.

The challenge of data collection

Data collection is the first step in building a comprehensive GTM strategy. It is also one of the biggest challenges. Given the volume of data generated today, understanding what the right data is and where to get it can take time. Apart from multiple sources such as websites, mobile, and social media platforms, data is also generated in different formats. Various datasets need to be integrated, including CRM, market, sales, product and financial data. Additionally, these datasets are often locked in a database, and teams are ill-equipped to access and analyse the data. How can companies gather that data in one space? One Single Source of Truth (SSOT), where it gets a visual representation and comprehensive analysis of this data.

Veluri cited an example of this challenge by discussing a Snowflake customer, who had identified a unique value proposition. The company works with farmers, sharing critical information regarding their farm land and offering carbon credits that they could sell in the market as an additional revenue source. To streamline the vast amount of data, they first set their end goals in place, which helped them determine what data to collect. Once they had the data, they could begin to build a dashboard to help them visualise the data. 

Integrating and understanding what data needs to be leveraged for a GTM plan is half the battle won. Veluri advised aligning the data to the company’s business objectives. “Data will always make sense if it is aligned to a business objective. If you have aligned it to a business objective, then the collection of data takes a life of its own, because then you are measuring it on Key Performance Indicators (KPIs),” he said.

Creating a data-first culture

Data-driven GTM strategies reflect an organisation that has built a data-first mindset. Veluri said this culture has to be built from top down, where every employee at every level understands the value of data collection, cleaning, and analysis. Large organisations have volumes of untapped and unorganised data that can be leveraged for innovation. Smaller organisations can start collecting data from external sources. The true challenge is how organisations can weave data into their GTM strategies after that.