Fuel Your Startup With Big Data

Have you ever wondered how founders of successful start-ups get their initial ideas? These flashes of inspiration or hunches usually pop into a founder’s head seemingly from nowhere. That is a testament to the power of the human mind. However, start-ups flourish, flounder or fail depending on the entrepreneur’s actions after he or she has the idea. The success lies in the implementation.

Historically, those early steps were often as intuition-based as the initial idea itself. Trial and error were the order of the day and small focus groups did little to improve that. But Big Data is changing the game and is quickly bringing start-ups into the big league at a small price. This improved competitive footing gives savvy start-ups some serious traction in the race for funding and market prowess.

In the past, companies had to rely on polls and surveys to understand customers and prospective customers, which wasn't always the most effective way forward. Today however, smart companies are leveraging Big Data to gain a precise understanding of what their customers want. Companies that are ignoring data analytics are losing out as they continue to use guesses and estimates as part of their strategy or follow more winding, traditional paths. Founders of start-ups should note that these early steps will either make or break the company and view data analytics as a crucial decision-making tool.

Another thing leaders of start-ups should keep in mind is that they need to be dynamic, fast-changing and pivot quickly each time there are significant changes in their marketplace. Which is why, it is imperative for start-ups to use data analytics to understand market trends, and assess risks and opportunities dynamically, and not rely on the feedback they receive from their limited customer base.

Sure, they should analyse usage and engagement data from their early customers, product trials, and up-sell patterns in order to understand monetization. This can give start-ups clear visibility on which aspects of their marketing mix is working with their customers and where change may be needed. But they also need to combine this information with external data and unstructured data in the public domain to derive superior insight on their customer needs.

It is now possible for start-ups to evaluate the validity of their assumptions by tapping social data from Twitter, Facebook and other social networks through data re-sellers. 

For example, Facebook can provide a very reliable barometer/estimate for a market opportunity by analyzing public posts. A start-up focusing on young parents and parents-to-be, for instance, can get a quick estimate of the types of conversations and quantitative estimates on numbers of posts about specific categories (e.g. baby apparel). This kind of data can provide invaluable insights that can’t be gleaned from a focus group with a small sample size.

The increased availability of cloud-based on-demand resources also allows start-ups to create complex computing machinery that can process data for short periods, and at affordable costs. This dynamically scalable and often times virtualized environment fundamentally changes what a young company with limited resources is able to mobilize.

Here are some of the steps that start-up founders should follow in order to get valuable insights through data analytics:

• Step one: Get better data. The best way for start-up founders to improve their chance of success is by learning to make better decisions with the help of better data. How can start-ups afford access to better data? Consider using on-demand big data access services and publicly available data to further offset costs.
• Step two: Identify what you're doing right and areas where you may need to improve.
• Step three: Get the tools to extract information from publicly available sources, internal data sources, and/or partner resources, and use them to identify patterns, markets, and opportunities for your business. What are those tools? They range from data monitoring (noting changes in data) and aggregation (collecting data from multiple sources) to mining/interpretation tools. Big data tools are very affordable and are available from numerous vendors as an on-demand, pay-as-you-go service.

Finally, an entrepreneur should use data analytics insights to substantiate his/her pitch for investment funding. It doesn’t matter whether they are pitching angels, venture capitalists, or banks. If the idea is good, a strong set of insights from data analysis will provide the convincing argument a founder needs to bag that key round of funding.