Data Analytics Beginner's Guide

At its core, data analytics means looking at information you already have and using it to make better decisions.

You don’t need advanced business knowledge or technical skills to get started. In fact, many small business owners already use data without realizing it.

Some examples include:

• Noticing that weekends are your busiest days.
• Remembering which products sell the most.
• Tracking which customers come back regularly.

That’s data analytics.

Data analytics helps business owners be more intentional and consistent in tracking and using that information.

Example: Muri Lelu Skincare Brand

“Data analytics gave us a clearer understanding of how customers shop, which products drive repeat purchases, and how subscriptions contribute to long-term revenue. By combining website, subscription, and email data, we identified our most valuable customer groups, uncovered opportunities to stop losing customers, and developed more targeted marketing strategies for one-time buyers, repeat customers, and active or former subscribers.

These insights helped us establish realistic growth goals, prioritize retention alongside acquisition, improve email segmentation, and make more informed decisions about where to invest our marketing resources."

Muri Lelu, client of MOBI contributor ModFox Consulting

Using data in your business can help you:

• Make more informed decisions.
• Save time and money.
• Increase sales.
• Improve customer satisfaction.
• Identify problems early.

Instead of guessing what might work, you can rely on real information from your business. You can also make changes if you notice problems.

You likely already have access to valuable data. Here are some common types:

Before you begin, download the MOBI KPI Workbook to help you identify and organize the information that matters most to your business.

Data is most useful when you know which numbers deserve your attention. Key performance indicators, often called KPIs, are specific measurements that help you understand whether your business is making progress toward its goals.

A KPI is more than a number you happen to track. It should be connected to an important business objective and help you decide what action to take.

For example, if your goal is to increase sales, useful KPIs might include:

• Monthly revenue.
• Number of new customers.
• Average order value.
• Sales conversion rate (the percentage of prospective customers who make a purchase).
• Percentage of customers who make a repeat purchase.

If your goal is to improve customer satisfaction, you might track:

• Customer satisfaction ratings.
• Number of complaints or returns.
• Online review scores.
• Customer retention rate (the percentage of customers a business keeps over a specific period).
• Average response time to customer questions. 

How to Select the Right KPIs

Small business owners often have access to more data than they can realistically use. Tracking too many numbers can become overwhelming and make it harder to see what is important. Begin by identifying your most important business goals. Then choose a small number of KPIs that show whether you are moving closer to those goals.

Ask yourself:

1. What is my main goal?
2. What measurement would show progress toward that goal?
3. Where will the data come from? (Example: sales, email sign ups, etc.)
4. How often should I review it?
5. What action could I take if the measurement improves or declines?

For example, imagine that a retail business wants to increase monthly sales. The owner may choose to track website visitors, sales conversion rate, average order value, and repeat customer rate. Together, these KPIs can help explain not only whether sales are increasing, but also why.

A good KPI should be:

• Relevant: It is connected to an important business goal.
• Measurable: You can collect the data consistently.
• Easy to understand: You know what the number means.
• Actionable: The result can help you decide what to do next.
• Time-based: You review it over a defined period, such as weekly or monthly.

Avoid choosing a KPI simply because the number is easy to find. For example, social media followers may be interesting, but they may not be a useful KPI unless growing your audience supports a specific business goal. Website purchases or inquiries may provide more meaningful information.

Leading and Lagging KPIs

Some KPIs show what has already happened. These are called lagging indicators. Examples include monthly revenue, profit, number of completed sales, customer retention rate, etc.

Other KPIs can provide an early sign of what may happen in the future. These are called leading indicators. Examples include number of sales inquiries, website visits, appointments booked, proposals sent, email click rate, etc.

Both types are useful. A lagging KPI tells you the final result, while a leading KPI may help you identify a problem or opportunity before the final result appears.

For example, if monthly sales have declined, that is a lagging indicator. If the number of new customer inquiries began declining several weeks earlier, that leading indicator may help explain the change.

Not every KPI needs to be reviewed every day.

Looking at long-term measurements too frequently can lead to unnecessary changes before there is enough information to identify a meaningful trend. The right review schedule depends on the type of business, the KPI, and how quickly the information changes. 

Create a regular schedule for reviewing your KPIs. Consistency makes it easier to compare results, recognize patterns, and respond early when something changes. Here are some examples to help you get started.

Look for Trends, Not Just Individual Numbers

One number does not always tell the full story. Compare results over time and look for patterns.

For example:

• Are sales increasing or decreasing each month?
• Do certain products consistently perform better?
• Are customer complaints becoming more frequent?
• Is advertising generating more leads but fewer sales?
• Are expenses increasing faster than revenue?

You should also consider the context behind the data. A decrease in sales may be related to seasonality, a temporary closure, a change in pricing, or reduced marketing activity. Data can show you what is happening, but you may need additional information to understand why it is happening.

Example: MOBI KPI Workbook

Start Small

You do not need a complicated dashboard or expensive software to begin tracking KPIs. A spreadsheet, accounting system, ecommerce platform, customer relationship management system, or point-of-sale report may provide the information you need.

Start with three to five KPIs that are closely connected to your current goals. Review them consistently, record what you learn, and adjust your actions when necessary. As your business grows, you can add or change KPIs to reflect your new priorities.

The purpose of data analytics is not to collect every possible number. It is to identify the information that helps you understand your business and make better decisions.

Why does data analytics often sound so complicated?

You may hear terms like artificial intelligence (AI), machine learning, or advanced analytics and feel like they are only for large or technology-focused businesses. The good news is that the core idea is the same regardless of your business's size. 

Data analytics means using information to make better decisions. AI is simply a tool that helps analyze larger amounts of data more quickly and identify patterns you might not notice on your own.

Many small business owners are already using tools that include AI without realizing it. For example, email marketing platforms may suggest the best time to send messages, social media platforms recommend content, and accounting software can automatically organize expenses. (You may also be using AI tools without realizing it if you use Waze, Google Maps, Grammarly, Siri, or Alexa!)

If you are just getting started, focus on simple steps like tracking your sales, understanding your customers, and reviewing basic reports. As your business grows, you can begin using tools that automate tasks, predict trends, or personalize customer experiences.

You do not need to be a data expert to benefit from these tools. The goal is not to understand complex technology, it is to use the information available to you to make smarter, more confident business decisions.

There are simple and complex ways to use data analytics for your business. Here are examples for basic, intermediate, and advanced uses for business owners.

Using a Superprompt for Data Analysis

A superprompt is a detailed set of instructions that tells an artificial intelligence tool exactly what role to take, what information and background data to review, what questions to answer, what constraints to consider, the objectives and audience for the instructions, and how to organize the results.

Unlike a short prompt, which typically provides a single instruction or question to give an AI one task, a superprompt provides context, objectives, definitions, analysis requirements, and a preferred output format, creating a framework for the AI to follow. This helps tools like ChatGPT, Claude, Gemini, and others to produce a more complete and useful analysis rather than a general summary of the information provided.

For a business data analysis project, the quality of the results depends heavily on the quality and completeness of the information supplied. Before entering the superprompt, the user should gather reports from the systems used to operate the business, such as an ecommerce platform, accounting software, email marketing platform, subscription platform, customer relationship management system, or advertising accounts.

Preparation activities may include identifying the questions the business needs to answer, selecting a consistent reporting period, exporting relevant reports, checking that files include clear dates and column headings, removing unnecessary personal information, and organizing files by source. The user should also prepare basic business context, including current goals, challenges, products or services, target customers, marketing channels, budget, and any operational limitations.

Once the data and business context have been prepared, the files can be uploaded to the AI platform along with the superprompt. The superprompt then guides the AI to review the available data, identify missing or inconsistent information, analyze performance, develop recommendations, and present findings in a structured format. The results should still be reviewed by the business owner, since AI-generated analysis may rely on assumptions when data is incomplete or unclear.

***Best Practice*** Before uploading business information into an AI tool, remove or anonymize sensitive information such as customer names, email addresses, payment details, employee records, passwords, tax information, health information, and confidential contracts. Review the privacy settings and data policies of any AI platform you use.

When Should You Start Using More Advanced Data Analytics Tools?

You don’t need advanced analytics right away. Focus on collecting consistent data first. This will help you identify areas where more detailed analysis is needed. You may want to use more advanced tools if your business is growing and becoming more complex, you are spending too much time analyzing information manually, or you want to improve efficiency or scale your business.

Here are some examples showing how data analytics can be used for different types of businesses.

Example 1: Party Store Owner

A party store owner tracks:

• Which items sell most (balloons, decorations, themed supplies).
• Busy seasons (holidays, graduation, birthdays).

Using data analytics:

• Orders more popular products before peak seasons.
• Creates promotions for slow-moving inventory.
• Adjusts store hours based on busiest times.

Advanced: Use point-of-sale (POS) software to predict inventory needs. 

Example 2: Residential Cleaning Business

A cleaning business tracks:

• Number of clients per week.
• Time spent per job.
• Types of services requested.

Using data analytics:

• Identifies the most profitable services.
• Adjusts pricing based on time and effort.
• Schedules jobs more efficiently.

Advanced: Use scheduling tools that optimize routes and bookings. 

Example 3: Graphic Designer

A freelance designer tracks:

• Types of projects (logos, websites, branding).
• Time spent per project.
• Client feedback.

Using data analytics:

• Focuses on the most profitable services.
• Improves pricing and turnaround times.
• Builds stronger client relationships.

Advanced: Use AI tools to speed up design drafts or analyze client preferences.

Example 4: Technology-Focused Business

A larger or tech-focused business might track:

• Website visits.
• Conversion rates (when a prospective customer becomes a customer it’s a conversion).
• Customer behavior online (time spent on page, most popular pages viewed, etc.).

Using data analytics:

• Improves website design.
• Optimizes marketing campaigns.
• Increases online sales.

Advanced: Use AI to personalize customer experiences.

You don’t need to be a data expert to use data analytics. Start with these simple steps:

Step 1: Decide What You Want to Improve

Ask yourself key questions to identify one clear goal to start: Do I want more customers? Do I want to increase sales? Do I want to save time or reduce costs? 

Step 2: Identify What to Track

With your goal in mind, choose two to five simple things to track, such as: daily sales, number of customers, most popular products/services, time spent on tasks.

Step 3: Track Your Data Consistently

Decide on a method to track your data. You can use a notebook, a spreadsheet (for example Microsoft Excel or Google Sheets), your point-of-sale system, simple apps or tools, or MOBI’s KPI Workbook. The most important thing in tracking your data is consistency.

Step 4: Review Your Data Regularly

Set aside time weekly or monthly to review your data. As you review the data, ask yourself key questions to analyze the information: What patterns do I see? What is working well? What needs improvement?

Step 5: Take Action

Take action based upon your analysis of the data. Here are a few examples of how data leads to action:

• If sales are highest on weekends → Increase staff or hours.
• If a service takes too long → Adjust pricing or process.
• If customers repeat purchases → Create loyalty programs.
• If marketing isn’t working → Try a new approach.

Common Tools for Small Business Data Analytics

You don’t need expensive tools. Start simple, or start with tools you already use. Here are a few ideas of common tools, and online searching can help you compare to find the best fit for your business needs.

• Spreadsheets. Great for tracking and organizing data. (Ex: Microsoft Excel, Google Sheets, etc.)
• Point-of-Sale (POS) Systems. Track sales automatically. (Ex: Square, Shopify, Toast, PayPal, etc.)
• Scheduling Apps. Track appointments and time. (Ex: Calendly, Google Calendar, along with other industry-specific and customizable solutions.)
• Social Media Insights. Show engagement and reach. (Provided within your profile of most platforms.)
• Accounting Software. Track income and expenses. (Ex: Intuit QuickBooks, FreshBooks, Xero, Zoho Books, Wave, etc.)

Data analytics means using the information you already have to make better decisions.

Data analytics doesn’t have to be complicated. Start simply by writing things down, looking for patterns, asking questions, and making small changes. By tracking a few key metrics, reviewing them regularly, and taking action, you can improve your operations, increase your revenue, and better serve your customers. Start small, stay consistent, and use what you learn to make your business stronger every day. Over time, you’ll become more confident and comfortable using data to guide your business.

Top 10 Do’s

1. Start simple. Begin by tracking just a few key numbers like sales, customers, or time spent on tasks.
2. Focus on your goals. Decide what you want to improve (sales, efficiency, customer experience) before tracking data.
3. Track your data consistently. Use a notebook, spreadsheet, or system you already have.
4. Review your data regularly. Set aside time each week or month to look for patterns.
5. Look for trends over time. Pay attention to what increases, decreases, or stays consistent.
6. Use data to make decisions. Let your information guide changes in pricing, scheduling, or inventory.
7. Listen to your customers. Feedback is valuable data that can help improve your business.
8. Use tools that are easy for you. Start with simple tools like spreadsheets or built-in reports.
9. Take small actions based on what you learn. Make gradual improvements instead of big, risky changes.
10. Stay curious. Ask questions about your business and use data to find answers.

Top 10 Don’ts

1. Assume data analytics is only for large businesses. Small businesses can also use information to make better decisions.
2. Try to track everything at once. Too much data can become overwhelming.
3. Ignore your data. Collecting information without reviewing it won’t help you improve.
4. Choose your KPIs without identifying your goals first. KPIs should help you evaluate whether you are getting closer to your goals.
5. Review data without considering the context. By looking at the context you can understand what is happening and why.
6. Forget to act on your findings. Data is only useful if it leads to action.
7. Be afraid to experiment with AI analysis. AI tools can provide analysis for larger amounts of data more quickly and help identify patterns you may not notice.
8. Ignore customer behavior and feedback. What customers do and say provides important insights.
9. Make decisions based on one data point. Look at patterns over time instead.
10. Track numbers just because they are easy to find. Be intentional about the information you analyze.

MOBI offers a wide variety of resources to help you. These include our Business Plan Template, worksheets, checklists, templates, infographics, and more. Note: Resources may download automatically or open in a new tab.