An increasing number of startups across the world have joined the unicorn club over the years. The dynamic nature of modern entrepreneurs who possess a competitive mindset is a major aspect contributing to this promising growth. These entrepreneurs essentially understand the potential of new-age technologies like IoT, Big Data and Analytics, ML, and AI, and often seek the assistance of a digital analytics company to boost their operations and augment their processes. Ditching the traditional ‘guessing and assuming’ approach, many startups today are hacking their growth using data insights.
The new-age entrepreneurs are professionals with a distinctive global exposure, looking to explore agile, innovative and disruptive technologies. They desire to provide solutions to existing issues in the society, or even create a wholly new market category altogether. Pillars of such business organizations are largely developed with IP-driven innovation and new-age deep technologies. Big Data and Analytics assist startups to identify &Â discover unseeing business opportunities. This is made possible by reviewing expansive data sets and deriving actionable insights. Brand new products can be developed, or the existing ones might be improved to deliver superior business outcomes.
Data Analytics: Importance of quantity
The widespread deployment of Internet of Things (IoT) devices, computers and sensors have accelerated the rate of data production and collection across diverse domains, logistics, and manufacturing being the two major ones. Data collection and access is, however, just half of the story. As the vast majority of data collected is often difficult to interpret and obscure, its overall usefulness ends up diminishing. As a result, companies often deal with extensive swatches of data that are unfiltered and raw and have to be carefully structured, organized, and curated prior to being ready for interpretation.
To make this process easier, organizations of all sizes, including start-ups, opt to seek third-party data analytics solutions. The use cases of data analytics service in the startup landscape are several, including customer sentiment analysis, personalized recommendation engines, customer segmentation, and fraud prevention.
Leveraging Data Analytics To Gain Competitive Advantage
As an increasing number of companies are expanding their data budget after realizing its importance. Modern-day organizations desire to uncover emerging trends as fast as possible, to exploit and differentiate themselves from the crowd. A great number of firms today look forward to using data sets to capitalize on new strategic opportunities like mergers, acquisitions, and partnerships.
However, unfortunately, not all startups have the engineering resources needed for complex analytics or are not able to convert knowledge into action properly. Incomplete data sets have especially been a major pain point for several companies. Depending on insights sourced from obscure, unstructured, and outdated data can prove detrimental to any company, especially the ones on the verge of an important investment or startup acquisition. Conversely, corporate M&A teams and management consultants require real-time access to data and market intelligence in order to track potential opportunities and startup activities.
Advisory teams also have to swiftly identify important insights and metrics to provide their company with the needed competitive edge, and subsequently, stay ahead of the curve. Hence, having access to a high-quality, adequate, and varied range of analytical tools tends to be vital for each and every organization. Data analytics and science combined with Big Data go a long way in meeting this demand by competently converting ‘noisy’ data into metrics that are useful and meaningful.
Delivering superior customer experiences
Customers are the biggest asset of any startup company. Understanding their needs and retaining them essentially drives the first sale of startups and plays an important role in their growth. Thereafter, the changing customer tastes, behavior, as well as evolving purchasing trends, can be effectively captured with the help of Big Data Analytics.
Modern-day customers typically do extensive research prior to spending their money on any product or service. This includes going through reviews online, checking out social media posts, and discussing with peers. Their research makes modern, value-driven customers, more confident about making purchases from lesser-known companies and startups. In comparison to baby boomers and gen-x who majorly prefer items belonging to more established, traditional stores.
Modern customers hence typically have an extensive digital footprint. The data generated by their distinguished online touch-points can subsequently be used by startups to customize their efforts. Big Data and Analytics solutions make it possible to strategically develop promotional campaigns around customer behaviour, interests and buying patterns. Startups can easily search data analytics companies online that can help them in tailoring their campaigns and gaining better conversions.
Conclusion
By providing the ideal content to the target customers, startup organizations can competently connect and strengthen relationships with them. Targeted messaging and reduced disconnect between a startup and its patrons can go a long way in enhancing customer experiences. It can especially be helpful in enabling a startup to secure a group of loyal patrons.