"If you’re not innovating, you are going backwards.”
Innovation is the lifeblood of growth for all businesses no matter the size. Companies like Nokia learnt this the hard way when Apple launched the iPhone in 2007. Back then, Nokia enjoyed over 50% of smartphone market share while Apple was mainly known for its MacBook and iPods. Over a decade later, Nokia now owns a mere 1.1% of the market, adapting design ideas from Apple.
Savvy businesses today acknowledge the power of data and are effectively deploying analytics to grow their business. Well-resourced companies like Alibaba have even hired an army of in-house data scientists to develop custom machine learning tools to transform their big data into solutions for a wide variety of complex challenges.
Hacking Information Overload
In e-commerce, there is more data on consumer profiles, habits and preferences than humanly possible to process manually. Many companies have since started automating repetitive jobs like data consolidation, data cleaning and even analysis so that humans can focus on essential tasks.
One automation example is the merging data sets from different sources without human intervention. Data such as date of birth and age range is automatically identified and converted into the same format so that the files can be merged and analysed together. This results in a faster process for generating insights.
Automation – The E-commerce Secret To Scaling
Amazon is famously known for their innovative competitive streak. It is constantly finding new ways to generate higher revenues. Since 1998, Amazon has been leveraging on algorithms to automatically analyse its big data to understand shopping behaviours and personalize customer experiences. In 2013, 35% of Amazon’s total consumer purchases came from product recommendations based on such analysis algorithms – undoubtedly, that number would have grown over the years.
Today, e-commerce companies can even create 20,000 ad copies per second enabling humans to pick the most relevant ad copy for use. Combine this with personalized product recommendations and they create a powerful selling tool to target repeat customers.
SMEs can innovate with automation too (and they should)
Data analytics is no longer reserved for big corporates with deep pockets and a strong headcount. A growing number of smaller companies have achieved benefits of automated data analytics thanks to advances in data tools. Automated analytics tools can now perform much of the manual work in data preparation. The wide availability of affordable and intuitive analytics tools has changed the game of data analytics for small- to medium-sized enterprises. The even better news is, the results arrive fast - companies are recording a 40.38% revenue growth just 36 months after implementation of predictive intelligence.
To get started
Automation is the key to faster and more effective data analytics. However, many business owners are hardly using the data in their possession. By tapping into existing data, businesses can find new ways to sharpen their competitive edge.
Well-funded start-ups and corporates often have the skills and deep pockets to build entire full-stack infrastructure, but small companies looking to get started can consider using one of the many data analytics tools in the market or a SaaS product which often means lower upfront costs and more flexibility overall. These tools can start automating processes while also solving many of the headaches associated with infrastructure set-up and maintenance (i.e. backups and upgrades). Business owners, managers and executives can then focus on making data-informed strategic decisions.
DataVLT is an affordable, on-demand analytics platform secured by blockchain technology. It is designed to simplify the complexity of data science. Backed by artificial intelligence and machine learning capabilities, DataVLT empowers enterprises to make meaningful sense of their big data and scale cost efficiently. Essentially, it is an end-to-end data/information management platform.
Learn more at www.datavlt.com