Rapid innovation has driven high-growth companies to optimize their strategies to improve return on investment and achieve better business results. These companies have sought to adopt solutions to access real-time data and actionable insights to continually adapt to changing consumer and market needs. Given the positive growth this approach has brought, adopting dynamic data strategies is the way forward for the startup ecosystem.

Dell Technologies, in collaboration with YourStory, hosted a panel discussion to discuss the impact of data strategies on the future of the startup ecosystem and examine how high-growth startups can benefit from data analytics to fuel growth. A few ecosystem thought leaders, who have a wealth of experience promoting the use of data analytics to succeed in their industries, shared their insights and advice for companies looking to adopt of data.

Use data to improve business

For Credit Fair, a leading consumer lending startup, it’s very important to ensure that data is collected, stored and used correctly, said the founder and CEO Adithya Damani. Thus, data management and quick decision making are essential for them as they use AI/ML models for all their operations and to fulfill their mission of providing fair finance to every Indian.

Airmeet strongly believes in the power of data, says co-founder and CEO Lalit Mangal. He underscored the importance of first-party quality data generated largely from events. “I think it opens up huge opportunities to learn more about our customers and our geographies,” he said, adding that Airmeet uses data extensively in its business, especially the sales pipeline.

Suresh Rangarajan, Founder, Colive, believes that although data plays a very important role in all businesses, the real estate space has fallen behind, which is what they have addressed by using a transparent system. “By providing a rental exchange…I think we’re solving a huge problem that this country has,” he said. They have added so much data to the platform so that customers can make an informed decision, he added.

Vivek Pandei, co-founder and CTO of Ecozen Solutions, felt that data is very important to their business because it uses it at every stage of its operation. Their products are powered by three key technology elements – motor drives, thermal storage and IoT, all of which are driven by data. “We were able to optimize product design and reduce costs because we leveraged data,” he said, adding that it also plays a role in preventive analytics, predictive analytics, and more.

Bhupendra Khanal, Founder and CEO, Himalayan Natives, pointed out that their rapid growth and success was due to optimizing data during the pandemic. Himalayan Natives grew from one product to 84 products in six months, collaborated with online platforms and local stakeholders, and became a top three player in its category thanks to robust data solutions.

Why adopt a data strategy

“Most of your competitors are going to be pulling insights from data, so if you’re not, then your strategy is obviously flawed,” said Sudip K GoswamiDirector & GM – South India and Startups, Dell Technologies.

It asks four questions to guide companies looking to build a viable data management strategy. First, where do you put the data for analysis and action? Two, how long do you keep the data? Third, how do you use this data and extract it? Fourth, how do you secure your data? “As long as you think about those four things… two years later you would have scaled 3x, 5x, [or] 10x is what I would call your data management strategy,” he added.

Tips for adopting the right data strategy

Lalit said the key is identifying the metrics and questions the company wants to answer using data. For Airmeet, he said, there were several key drivers, such as revenue forecast, cost of acquisition and customer engagement, and added that they had invested in sustainable differentiation, which relies heavily on data.

Airmeet uses state-of-the-art technology to ensure security and privacy – one of the tenets of its data strategy – not only to focus on its internal processes, but also to serve several Fortune 500 companies, Lalit said.

Adithya said alternative data is important for Credit Fair to identify how they can better serve underserved populations in the lending industry. Their data-driven decision-making culture ensures that they collect different data points and perspectives to give them an edge over competitors, periodically review the data and use it to deliver a better customer experience, he added. .

Predictive analytics use cases

Ecozen uses minute-by-minute predictive analytics, Vivek said. Recounting his first experience with a customer, he emphasized that his strategy came from a predictive analytics perspective to minimize the time it takes to resolve a problem. “It’s been a driving force that greatly influences our product design and customer service,” he said, adding that they had algorithms running on the server to track the health of their systems so that the downtime can be avoided and money saved even in the event of an accident.

Suresh focused on the criticality of human participation in data analysis. In his view, one cannot ignore the person setting up the algorithms because the required data processing will not occur and create value even with the right data. Colive uses predictive analytics to create use cases where they can predict cash flow by looking at data to understand the nature of the tenant and give them a particular score, ultimately helping them get a better deal from the landlord.

Preparation for real-time personalization

Bhupendra advised against starting analysis early without enough data. At Himalayan Natives, he said, they focused on collecting and analyzing publicly available competitor data from online sources to create internal data before starting analysis.

For D2C companies to prepare for large-scale personalization, he suggested that they should first implement data practice from the beginning to collect data, then they should know what they want and how. they want to position themselves.

Data Protection and Privacy

Sudiip believes companies should talk about what they do with their data and what steps they take to protect it from a breach. Companies should adopt stable and widely used data policies and identify what stage they are currently in implementing them, which helps build trust and credibility among customers, he said.

“Like any relationship…trust is only built when you talk about what you are doing about it,” he said, adding that when companies assure others they are taking steps to ensure privacy is protected. data, customers will identify very much with them. After.

Tips for startups

Lalit stressed the importance of starting a data practice early to collect data and understand what works and what doesn’t. Adithya said startups need to invest in people, provide them with data visualization tools, and encourage them to make data-driven decisions.

For Vivek, it is very important to proactively determine the importance of data to your business, identify data needs and standardize data sets. “The rate at which startups are planning to grow today… it becomes very important early on that you move into a very professional environment,” he added.

Suresh emphasized the importance of capturing data in the chosen format and storing it correctly. You have to lay the groundwork right, he said, for everyone in the business to follow.

Based on his personal experience, Bhupendra believes that investment in data is crucial, along with adequate legal and financial investments. Sudiip agreed with Lalit on starting a data practice and added that engaging a consultant or other third party to plan the roadmap for the future would be the best step forward.