Why is it important for eCommerce business to make Data-Driven decisions?

Why is it important for eCommerce business to make Data-Driven decisions?

Ever since doing business went digital, the amount of data it has been generating on the side continues to get bigger and bigger every day. Even the simple act of buying and selling something online involves multiple data points, such as

    - The customer’s name, email address, physical location, and phone number

    - The process the customer follows on the website to reach checkout

    - Potential drop off points along the buying journey

    - How coupons, discounts, and external factors like festive sales periods drive buying decisions

And that’s just skimming the surface. This data can translate into actionable insights that businesses can indeed utilize.

However, this data is often bulky, unstructured, and sometimes difficult to process. The challenge of too much data but very few insights is all too real. Omnichannel or eCommerce companies, for one, stand to benefit a lot if they are able to unify their data sets and extract real value out of the data. Data, in fact, can form the crux of decision-making in business.

Often, data tends to get stacked in information silos of its units, departments, or divisions. This is where technology comes in as an ally to pull real value out of these data banks and silos.

Data is a goldmine. When harnessed right, technology-driven data analysis in eCommerce can help drive the following business insights or strategies:

  • Quantifying demand for the service or product
  • Getting realistic estimates on future demand
  • Understanding the buyer journey and buyer behavior
  • Gathering competitive business intelligence
  • Visualizing responses to marketing campaigns
  • It all boils down to how accessible the information is within the data mountain, and what tools you need to mine it. The answer lies in technology in the form of the right data analytics tools. These tools can help sift through vast amounts of noise and pick up on the precise signals that can help facilitate data-driven decision-making.

    Why use data to make decisions?

    Not only does data analytics afford a look at the big picture, but it also looks at relationships and patterns among several of its components, before delivering insights. One way of achieving this is through unified data analytics. Unified data analytics is basically a process that merges data processing with cutting-edge artificial intelligence to deliver business insights and outcomes. It is data science and engineering at its best.

    Data scientists who handle vast amounts of data to separate the signal from the noise find that the best place to begin is with a holistic view. In other words, it is necessary to have an idea of the big picture, or the environment, before diverting intense focus on one particular problem area.

    What happens if you don’t harness data analytics for business?

    If businesses skimp out on using data to make decisions, they miss out on valuable opportunities for growth. Certain types of data have a limited shelf-life. They are actionable only up to a point, or else the data will degrade and decompose, so to speak.

    For example in eCommerce, the type of purchases that happen online during a holiday flash sale, the segment of customers who respond quickly to SMS prompts, how timed notifications and messaging contribute to the online traffic, are all things worth knowing in planning marketing campaigns.

    Data-driven decision-making is also referred to as DDDM or information-based decision-making. Data-driven decision-making examples include the grouping of historical data or information to analyze trends in the past and using those insights to make strategic decisions or plan future campaigns.

    Decision-making, when backed by data, is vastly more reliable than any decisions you make based on your gut feeling, experience, or personal opinions. With data analytics and insights, you take more calculated risks and reduce the vulnerability factor in your business growth practices.

    Making It Simpler: Which Tools Should You Use For Your eCommerce Business?

    Data analytics companies are continually developing newer and more efficient tools and techniques for business analytics to help companies pull useful, actionable insights from their data sets. Analytics tools help collate the data, analyze it, create models, extract insights and present them in a format that is easy to consume.

    The typical mix of contemporary business analytics tools that companies deploy nowadays is in the form of business analytics software bundles that combine data mining tools, statistical tools, and predictive modeling tools. These tools provide enterprises with a unified, “big-picture” or holistic overview as well as vital insights. Together, they boost productivity and profitability, advise short-and long-term growth, and improve everyday efficiency for organizations.

    Customer insight tools are designed to track emerging trends by monitoring conversations on social media, digital channels, as well as more traditional ones. They help the organization divide its audience into segments or personas on top of standard demographic data. They offer a unique insight into the mindset of the customer.

    As complex as it sounds, data analytics tools are everywhere! The insights offered by tools such as Google Analytics, or social media platforms, are a simple yet everyday example of analytics that we are all exposed to. Likewise, eCommerce platforms such as Shopify offer several plugins that can help you measure basic aspects of your eCommerce business.

    Likewise, the Shoptimize Growth Platform is designed for eCommerce businesses to help them mine richer data and garner better insights from this data. In a saturated market, access to good insights and being able to act on these recommendations is often the difference between a sustainable eCommerce business, and one that fails.



     
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