Google does not reveal exact figures and data regarding its daily search volumes. However, recent studies reveal that Google processes around 99,000 searches per second, which roughly makes it 8.5 billion searches every day and about 2 trillion in a year.
With this much drive among users for knowledge and solutions to personal and professional queries, the ability to capitalize on data is set to determine the future of businesses from all sectors, especially small and growing ones.
To that effect, most small businesses are seeking data analytics services and solutions to get a keener and more updated vision of market trends and stay ahead of their competitors.
Table of Contents
1. An Overview of Data Science
Before we dive into the advantages and use cases of data science for growing businesses, it is essential to have a clear idea of data science itself and its role in business development and growth.
1.1 What is Data Science?
Data science refers to the detailed study and evaluation of big data to obtain relevant and actionable insights for business or organizational growth. Big data, in simple terms, consists of larger and more complex sets of data that traditional data-processing systems cannot go through and utilize to the fullest.
Data science involves a multifaceted approach that fuses practices and principles of statistics, mathematics, computer programming, and artificial intelligence to access and analyze vast amounts of data.
Data scientists aim to study large volumes of information and answer questions such as “What happened?”, “Why it happened?”, “What can be expected in the future?”, and “How can the present results be improved upon?”.
1.2 Data Science and Small Businesses
While large companies and brands such as Apple, Nike, or McDonald’s can reach global customer bases due to their widespread popularity among the masses, small businesses have to rely on word-of-mouth publicity, organic search traffic, and online and offline marketing efforts.
This is where data science is emerging as a major game-changer for growing companies without a lofty brand image or huge funds to support celebrity endorsements or expensive advertising campaigns.
More and more small businesses are investing in data science solutions and services to make the most of user data and spot patterns in their behavior that can be acted upon. Data scientists aim to enhance your Business Intelligence (BI) and convert unstructured data into result-driven conclusions you can implement in your business strategies and decisions.
Small businesses can benefit from various types of data science and analytics, the most prominent ones being:
Text Analysis (Data mining) – Data Mining is the careful study of textual information to identify patterns that provide knowledge on user preferences, market trends, and demands.
Statistical Analysis – This method involves evaluating the numbers, facts, and figures in large volumes of data with the practices of:
- Data description
- Correlation of data with the underlying user bases
- Summarizing the information collected into a workable model
- Testing the usefulness and validity of the model, and
- Predicting and foreseeing trends of the future.
Diagnostic Analysis – This form of analysis tries to explain the causes of an event or business performance over a specific duration. Diagnostic testing consists of methods such as data discovery, data mining, and drill-downs that help small businesses determine the causes and effects of market demand for a certain product, customer behavior, supply chain issues, and so on.
Predictive Analytics – Data scientists use historical and current data to predict business performance, opportunities, and challenges that might come in the future.
Prescriptive Analytics – Prescriptive analytics aims to evaluate data and provide recommendations and roadmaps to follow for improving your business performance. It involves various methods like graph evaluation, complex event processing, simulation, neural networks, and a lot more.
2. Benefits of Data Science for Small Businesses
Big data and advanced analytics services can work wonders for small businesses with their ability to transform terabytes of data into workable knowledge. Leveraging user data can help growing companies streamline their working processes, identify financial threats, and make data-driven decisions.
The most significant advantages of utilizing data science for startups and developing enterprises include:
2.1 Manage Finances and Reduce Costs
Financial stability and viability are vital for small businesses that often operate on tight budgets and resources. Constantly analyzing data can help you stay in full control of your finances and conduct flawless internal audits. This helps you break down complex data and present you with the relevant facts and figures.
Artificial intelligence (AI) and machine learning (ML) are facilitating major breakthroughs by completing these audits and evaluations within seconds, instead of relying on traditional methods that would involve days and months.
For instance, suppose you have a high number of tax invoices because of suppliers on a particular date where the total amount will be higher than the due income from them. In such cases, AI-powered systems can be trained to automatically divert funds and provide you with plans and suggestions for the future.
This is why every successful startup is working closely with an artificial intelligence development company to introduce new levels of speed and accuracy in its financial surveys and audits.
2.2 Identify and Address Problems
By analyzing big data, you can use the results to answer critical questions such as “Why do customers abandon their carts”,” When customers are likely to make a purchase”, and “What products or services do customers tend to opt for over others”.
Data evaluation tools can give you crucial insights into customer behavior and demands as they navigate through your sales funnel. Apart from observing customer actions, you can also address issues related to suppliers, clients, and investors. With real-time information, you can get a comprehensive overview of how your business is performing and make better decisions as it grows.
2.3 Improve the User Experience
User Experience (UX) refers to the level of satisfaction or lack thereof of the user while interacting with your digital platforms like your website, mobile apps, or social media pages. The first few seconds of interaction are instrumental in deciding if the users find value in your product and whether they are willing to pay for it.
Employing the latest data science procedures provides you with up-to-the-minute intelligence on user actions and behavior on your online platforms. After understanding how your customers think and behave, you can make modifications and improvements to your sales funnels.
By utilizing authentic and relevant information, you can make both your online and brick-and-mortar stores more intuitive and engaging for existing and prospective customers and form deeper connections.
2.4 Efficient Team Management
Big data also boosts small businesses by smoothening the process of employee and team management. You can easily identify staff members who offer more productivity and those who require more resources or training.
Data science and analytics help you to manage employees better by assessing the correlation between engagement and retention. You can answer questions like how and why individuals are interacting with what they do, how it translates for your business performance metrics, and what areas you can improve to retain them.
You can create a vibrant team culture that drives engagement and encourages collaborative progress. You can assign each separate task to the employee best suited for it and enhance both the quality of work and the productivity of your personnel.
2.5 Drive Revenue
If you are a small business owner, data science consulting services help you increase conversions and sales in several ways. With an in-depth knowledge of the customer’s lifecycle, you can devise new ways to engage with customers and boost revenue.
Sound and accurate data on market demands fills you with the confidence required to launch a new product or service and diversify your revenue stream. Recent market surveys reveal that companies that have incorporated data science and big data analytics into their workflows have increased their profits by 8% in the first three quarters of 2023.
We have listed down some of the major use cases of data science that help small businesses grow, in the following section.
3. Data Science for Small Businesses – Use Cases
Data science isn’t a one-way road. It is more of an information-packed multi-lane highway that can be utilized in different areas and aspects of your business processes.
Data analytics companies are helping small businesses grow their operations by facilitating existing workflows and identifying new ways of self-evaluation and improvement.
3.1 Informed Pricing Decisions
You can study big data and make sound decisions regarding the price of your services or products. If your product is priced higher than the competition, customers will turn to other companies for a better deal, lowering your sales and revenue.
Using data science methodologies allows you to compile the prices of a large number of items and their prices from similar businesses. Once you know what your rivals are charging, you can arrive at an optimum price that is both competitive and financially viable.
3.2 Enhance the Customer Service
Getting a user to visit your online or physical stores and make a purchase is only half the battle won. Actual success lies in satisfying customers with your before and after-sales support and having them come back to make more purchases.
Several factors make customers leave a store or website including a slow site, higher prices, or a lack of proper customer support. Small businesses can track exactly where people lose interest and make sure you can engage with them at crucial points.
Higher customer retention rates help lower the costs of customer acquisition and provide new growth opportunities. You can examine every step of the customer journey and identify the pain points and challenges that are holding them back from making purchases.
Today AI-based customer service chatbots are offering new levels of speed and relevance in dealing with customer issues and queries. With the ability of natural language processing (NLP), these bots can understand what the customers want and can offer solutions in human-like and conversational language.
By learning how users think, behave, and make purchasing decisions, chatbots can create more personalized and engaging experiences for existing and potential customers. In most cases, AI bots tackle the initial few queries and resolve trivial issues, while human operators take charge as the issue progresses or in the case more critical matters.
3.3 Effective Inventory Management
Issues with your inventory can take a massive toll on your time and resources, setting your business back by significant margins. Not having a well-defined inventory management strategy, not maintaining clear inventory records, and over or under-ordering can cause considerable damage to your business.
Thanks to advanced data science solutions, you can now tackle these issues without having to burn a hole in your pocket. By carefully examining each step of your inventory and supply chain, you can enhance your operational efficiency and set proper stock levels, reducing the risk of stockout.
You can determine appropriate stock levels, authorize order fulfillment, provide accurate product descriptions, and lessen unwarranted warehouse deficits and surpluses. You can gather and analyze data to streamline your business workflows and develop a foolproof inventory management system.
For instance, you can optimize your supply chain and stock based on market trends, weather forecasts, geopolitical conditions, and consumer demands. By studying exact market conditions, you can get only the most relevant products or raw materials to avoid stock overload.
3.4 Market and Competitor Analysis
By utilizing user data to its fullest, you can draw workable insights about similar businesses and their niche. Data analytics services help you understand the demographics of the customers your rivals are targeting, what products they are purchasing, margins of profit, and a lot more.
Such information can help small businesses adapt themselves faster to market demands, reduce expenses, and increase their customer bases by offering relevant products and services.
Studying and assessing your competitors helps you to
- Understand the market better
- Get to know your own business well
- Estimate the strengths and weaknesses of your peers
- Forecast market trends
- Identify your business’s vulnerabilities
- Know what drives the customers’ interests and desires for a product
- Learn from your competitor’s mistakes, and
- Choose the best strategies and plans for the future.
3.5 Enhance Your Marketing Efforts
With an in-depth knowledge of how the market works and how your competitors win over their customers, small businesses can foresee where the present market trends are headed, the demand for particular products, and so on.
Making data-driven decisions eliminates the need for assumptions and guesswork and provides you with accurate facts and figures to base your marketing strategies upon. Data science helps you spot what exactly your users want and let you identify them and promote products from their wishlist.
Drawing insights from big data allows you to:
- Evaluate your website and app’s performance
- Adjust your marketing campaigns
- Choose the best most relevant digital marketing tactics
- Use the best-suited channels, and
- Set up promotional campaigns.
You can measure and evaluate all of the user data down to the most minute details such as how people navigate your online store, how they interact with your products or services, how much time they spend on specific pages, and a lot more.
3.6 Improve Cybersecurity
Cybersecurity ranks pretty high among the list of key concerns for small businesses around the world. Companies often need to collect user data to provide tailor-made products and solutions. This includes sensitive information such as NAP (name, address, phone number), bank details, medical history, social media accounts, and so on.
Cybercriminals can infiltrate systems with poor security, access such high-risk information, and use it for unlawful and nefarious activities. Working closely with data science and advanced analytics services, you can create, manage, and analyze vast amounts of diversified data sources including proprietary and transactional data.
Cybersecurity data analysts scan digital platforms for security risks and gain insights from previous incidents. Businesses can use this information to tighten their security aspects and shield their data from cyber attacks in the form of DDoS (distributed denial of service), phishing, malware, ransomware, injection of malicious code, and the like.
The primary applications of cybersecurity data science include:
- Monitoring the security of various online platforms
- Detecting security risks and threats
- Development of compliance policies and regulations
- Enhancing cloud computing security
- Security audits and analytics
- Risk assessment
- Data privacy and protection, and
- Immediate response to incidents of security breaches
4. Closing Remarks
Data science and advanced analytics are destined to shape the future landscape of businesses from all niches. This growing trend is especially beneficial to small businesses and startups as it levels the playing field to a considerable extent.
Growing companies can leverage data science not only to evaluate business-related information but also to identify what is working and what isn’t and provide actionable knowledge on how to base their future decisions and marketing strategies.
If you are a business owner in search of a web development company to capitalize on big data and market analytics and launch a business-specific stunning website, reach out to us at Webgen Technologies. We have been providing top-notch web and software solutions that are bound to take your business ahead of the curve.