Unleashing the Power of Data Analytics for SMEs: A Guide to a Better Decision Making

Data analytics is a discipline that revolves around examining large and varied data sets to uncover hidden patterns, correlations, and other insights.

With our Data Analytics course, your organization can learn how to use insights gained from data analytics to make informed decisions, improve business operations, and drive innovation.

However, data analytics technology companies often overlook small and medium enterprises (SMEs).


Maybe because they’re too small to have the resources, or influence to make their voices heard in these spaces. We can only speculate for now. Fortunately, today’s article seeks to discuss the potential powerful benefits and application cases of data analytics for SMEs.

Elements of Data Storytelling

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How many businesses use data analytics?

In 2020, only 45% of SMEs were actively using data analytics tools, according to a SCORE Association survey. Furthermore, Allied Market Research projects that the business analytics market will steadily grow by 13.5% from 2021 to 2030, peaking at an estimated $684.12 Billion.

These optimistic projections are powered by the fact that more data is being generated every day, with the emergence of more Data-as-a-Service(DaaS) companies offering affordable subscription-based services for SMEs.

Also read: “Business Intelligence Statistics to Watch for in 2023”

Why do SMEs need data analytics?

The process of data analytics typically involves several steps.

First, data is collected from various sources, such as databases, social media platforms, and sensors.

Next, the data is cleaned and pre-processed to remove any errors or inconsistencies. Then, statistical and computational methods are applied to the data to uncover patterns and insights.

Finally, the results are visually presented in a way that is easy to understand and can be used to inform decision-making.

Understanding the role of data analytics in decision-making for SMEs can provide valuable insights into how this technology is shaping the business landscape.

Data analytics is not just a paradigm for large businesses. SMEs need data analytic capabilities to improve their overall business performance in countless ways. For example, to gain a competitive advantage to improve customer experience by using predictive modelling or machine learning techniques.

Data analytics also provides SMEs with the right tools to understand their customers’ needs and preferences as quickly as possible.

This, in turn, improves their ability to expand their market share by identifying new opportunities in the market. Thus, it helps them stay ahead of the curve whilst dynamically adapting to changing market conditions.

Also read: “What is data analytics: A complete guide

How can SMEs use Big Data?

SMEs can leverage Big Data in four key ways:

  1. To make informed and accurate decisions based on data insights, rather than relying on intuition or assumptions. This may foster more effective and efficient operations, improved customer satisfaction, and increased profitability.
  2. To mitigate financial and regulatory risks or vulnerabilities by providing insights into potential problems before they occur.
  3. To improve competitiveness as SMEs typically face tough competition from larger companies. Big Data can help level the playing field.
  4. To gain a better understanding of customer preferences and behaviour, in order to tailor products and services and provide a more personalised customer experience.

Data analytics metrics to track for SMEs

Customer retention rate

Customer retention rate simply refers to the percentage of customers that an SME has been able to retain over a specified period. For SMEs, this metric is directly related to the success and sustainability of the business. Addressing it may increase revenue, customer loyalty, and positive word-of-mouth referrals.

Customer acquisition cost

Customer acquisition cost (CAC) measures how much it costs on average to acquire a new customer. This metric can help SMEs determine the return on investment (ROI) of their marketing and sales efforts.

Lead drop-off rate

Lead drop-off rate is essentially the percentage of leads that enter a sales funnel but don’t complete the intended action. Also known as the abandonment rate, this is an essential metric for SMEs to track as it provides actionable insights into how well their sales funnel is performing and where potential bottlenecks are occurring.

For context, high lead drop-off rates can indicate problems with the sales process, like a lack of clarity for users, or difficulties navigating the funnel. Or even a disconnect between marketing messages and the product or service being offered.

Cash flow

Cash flow is fundamentally the amount of cash and cash equivalents that are coming in and going out of the business over a specific period of time, for example, a month or a quarter.

Cash flow is an important metric for continually tracking the financial health of SMEs as it provides insights into operational areas that require reduced expenditure. This insight can be employed to make strategic decisions to improve the financial health of the business whilst ensuring its long-term sustainability.

Churn Rate

The churn rate fundamentally measures the percentage of customers who stop doing business with an SME over a given period of time. By tracking churn rate, SMEs can accurately identify which products or services aren’t meeting customer needs and take steps to improve them.

How does data analytics benefit small businesses?

1. Informed business decision-making

SMEs can leverage data analytics to guide business decisions and minimise financial losses. For example, they can exploit predictive and prescriptive analytics to anticipate risks and prescribe actionable reactions to address them.

2. Better understanding of customers

Analysis of data associated with a business can help SMEs to create a complete picture of their customer’s journeys.

For example, in the context of eCommerce, analytics can help to understand how most customers get to know the brand, what they particularly buy with repeated frequency, how they shop, at what time, and from which technology devices. Or even, why they frequently abandon the carts.

3. Enhanced inventory management

Data analytics can enhance the operational efficiency of an SME’s stock management processes. By analysing data, SMEs can avoid overstocking and stockouts, empower order fulfilment, and eliminate excessive warehouse deliveries and errors.

inventory management

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4. Financial process clarity

With the help of data analytics, SMEs can programmatically track how much money they spend on onboarding new consumers, for instance. This enables them to avoid guesswork when designing promotions and marketing campaigns. Thus, adding financial clarity to an SME’s operations.

Types of data analytics techniques used by small businesses

The most common data analytics technique employed by SMEs are:

Text analysis

Text analysis helps uncover patterns in large data sets leveraging databases or data mining tools. Also known as data analysis, this technique revolves around transforming raw data to identify patterns and relationships and then interpreting the data to make informed business decisions.

Diagnostic analysis

Diagnostical analytics is an advanced analytics paradigm that entails iteratively examining data to answer the question of “Why did it happen?” Techniques like drill-down, data discovery, data mining and correlations typically characterise it.

This technique can be deployed across a number of use cases, like examining market demand and analysing customer behaviour.

Predictive analysis

It is employed to make projections about future outcomes based on historical data and statistical modelling, data mining and machine learning techniques.

Prescriptive analysis

It revolves around examining business data to provide actionable recommendations on the steps to take to resolve a business issue. This form of analytics employs graph analysis, simulation, neural networks, complex event processing, recommendation engines, etc.

Statistical analysis

It is essentially the process of collecting, exploring and presenting substantial amounts of data to uncover repeated patterns and trends.


Data analytics has become increasingly important in today’s digital age. With the vast amount of data being generated every day, SMEs need to be able to analyse and make sense of it in order to stay competitive.

As we have seen, data analytics can help SMEs to identify trends, predict future outcomes, and gain a deeper understanding of their customers. This can lead to better decision-making, increased efficiency, and improved customer satisfaction.

As technology continues to appreciably advance, the field of data analytics is expected to grow and evolve in tandem.

One area of particular interest for SMEs will be machine learning, which involves the use of AI algorithms that can learn from data to make predictions or decisions without being explicitly programmed.

This paradigm has the potential to revolutionise how many SMEs operate. However, as with any new technology, there are also concerns about privacy, security, and ethical implications.

In conclusion, data analytics is a powerful tool that can help SMEs make informed decisions, improve operations, and drive innovation. By understanding the process of data analytics and staying up-to-date with the latest advances in technology, SMEs can stay ahead of the curve and reap the benefits of this exciting field.

Reach out to us for more information on how to get started with your data analytics journey in Singapore.

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