5 Ways Data Analytics Can Help Startups

data analytics startup

The world is a startup frenzy today. Each startup emerges with the belief that their idea can change the world but gathering facts and figures to convince their audience becomes much easier with an effective data strategy in hand. The digital wave has hit every industry by storm and they have been flooded with numbers and figures. The motto today is to build-measure-optimise and repeat.

The Essential Role Of Data Analytics In Startups

SETS KEY PERFORMANCE INDICATORS: Firstly, data analysis help startup set goals. Without metrics, it would be difficult to layout goals and measure the progress which allows a startup to constantly improving and pushing forward. Sharing updates with your teammates would ensure a motivated, informed and focused workspace. 

ELEVATE DECISION MAKING: Data can be used by everyone within a company to increase productivity and enhance decision making. It aids the entrepreneurs to make smart, calculated and informed decisions about their startup. It helps them in identifying trends and patterns, conflict areas and successes, uncovering hidden opportunities and potential next steps. 

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TARGETED CONTENT: Knowing the requirements of customers beforehand makes marketing campaigns more customer-oriented. It empowers companies to customize their advertisements in order to target an entire segment of the customer base. It also helps them in determining which segment of customers will respond efficiently to the campaign. 

OPERATIONAL EFFICIENCY: Data analytics help startups in identifying other potential opportunities to streamline operations and maximize profits. It helps them in recognizing problems, eliminating the process of waiting for them to occur and take necessary actions for the same. This allows them to see which operations have yielded best results under various conditions and pinpoint which operational areas are error-prone requiring improvements. 

ANTICIPATING THE ANALYSIS: Owing to a large amount of structured and unstructured data, it would be difficult to manage and infer relevant information from them. Data analytic tools like Tableau, Power BI and Logi are capable of handling heterogeneous data and provide insights out of them. It allows decision-makers to realise connections between multi-dimensional data sets and provide innovative ways to interpret data through graphical representations. 

Outlook

When you’re at the top of a roller coaster waiting for the drop, you would want to be sure the coaster is well built and well maintained. This is where data analytics come into play. In an unpredictable world, they can help you make calculated decisions towards progress. Moreover, it saved you from the drops most startups fail to recover from. 

To climb to the top of the ladder we must make sure the base is durable and strong. Data Analytics is that asset which helps galvanise a derailed business back on track with sharp objective insight which further can be used creatively in executing a call for action. The idea is to inculcate a culture of data-driven mathematical decision making which renders a steep learning curve for any business venture.

This article is a part of the AIM Writers Programme. If you wish to write for us, email us at info@analyticsindiamag.com

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Yasir Wani
Yasir Wani is a part of the AIM Writers Programme. He is a multipotentialite who craves for brain-stimulating problems faced by digital consumers. He has a knack for Consumer Centricism keeping a close eye on what data has to say. Previously worked at an organisation where he built the BI and Web Analytics team from scratch creating huge business impact and shaping a data-driven culture in the organization. This achievement helped him work closely with C-level executives of the company ranging from Managing Director, Chief Finance Officer, Chief Product Officer and Marketing Director. The main areas of work included: Data-Driven product strategy, Setting of Success KPIs for new features, benchmarking, Web Analytics strategy, Enterprise-wide Data Dashboards, Hypothesis Testing using A/B & Multivariate Tests, Customer Behavior analysis, Visual Analytics, UX & Content Auditing and Product change management.

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