To succeed, you need to know as much as possible about your customers and your markets. In the modern economy, the process of accessing those insights represents a challenging endeavor. Yes, there is plenty of data available – too much in some circumstances. But you also need to know the right techniques to uncover useful insights from those numbers.

That's where data analytics can help. Your small business or startup can learn how to find customers, improve productivity, and identify potential growth opportunities. This article will detail the four types of data analytics and outline how you can use them to your advantage.

What is data analytics?

You've heard that we live in the age of Big Data. The largest companies in the world – name like Apple, Amazon, Google — thrive on their ability to collect seemingly endless troves of information about their customers and about the world in general. These corporate behemoths can then use those numbers to understand their markets and make pinpoint decisions about how to drive the bottom line.

That's great for trillion-dollar companies. Can it work for your small business or startup?

The short answer: yes. Data analytics can help your business, even if you're still at the one-person-toiling-away-at-the-kitchen-table phase.

At its heart, the strategy centers on the use of information. It involves gathering statistics about your market and your customers, then using those numbers to determine the optimal next steps. You attempt to learn lessons about your target audience based on past behavior, and then apply those lessons to the future.

What are the 4 types of data analytics?

Data analytics represents a complicated field. However, the process can be organized into four basic categories. Understanding these types will help you narrow your goals as you consider this endeavor.

By understanding what you can accomplish with the various forms of data analytics, you can better shape your strategy. You can choose the level investment that makes sense for your current stage of development. With that in mind, here are the four types of data analytics:

Descriptive Analytics

This is the basic form of analytics. It's the first step in identifying (and eventually fixing) any problems, and a crucial entry point for making meaningful improvement in your business. However, it's also limited. Without the other forms of analytics, this process does little more than give you a snapshot of the current situation.

At its heart, descriptive analytics will let you know what is happening. It provides the basic statistics you need to understand your business. The process involves gathering information about your operations (things like website pageviews or total sales) and using these to gain an understanding of your performance.

Diagnostic Analytics

Think of it like a doctor's office. You have a fever. Descriptive analytics lets you know that your temperature is running to 101 degrees. Diagnostic analytics would take it a step further — a series of tests identifies the virus, so the doctor can better understand how to treat you. Using diagnostic analytics will help you understand why something is happening.

For instance, applying descriptive analytics might let you know that pageviews are falling on your website. Diagnostic analytics will let you know why this is happening. You'll learn the details of the decline, pinpointing the conditions that are dragging down performance. In this way, diagnostic analytics digs deeper, giving you insight on why a change is occurring.

Predictive Analytics

Here, we turn the power of analytics into the future. Predictive analytics looks at historical data and lets you build a reliable model. The goal is to anticipate what will happen, so you can properly position your organization.

Let's return to the website example. Rather than waiting for your pageviews to begin declining, predictive analytics can tip you off ahead of time. The process will identify market conditions that have turned against you, throwing up a warning signal of an imminent drop.

This gives you the foresight you need to react before changes affect your bottom line. By leveraging these techniques, you'll see the impact of trends. You'll go beyond understanding the forces impacting your operations, uncovering a good idea of how those forces will continue to influence your business outcomes.

Predictive analytics looks at historical data and lets you build a reliable model. The goal is to anticipate what will happen, so you can properly position your organization.

Prescriptive Analytics

Once you've developed a model for predicting the future, you want to use those projections to develop a winning game plan. Successfully applying predictive analytics will let you anticipate the impact of certain actions. This, in turn, leads to the next step: prescriptive analytics.

This form of data analytics lets you choose the right course. You'll get the information you need to intelligently select among possible ways forward. You can evaluate your options and select the best steps to improve your business.

In the website example, this means you'll know what steps to take to improve your traffic. You'll have the information you need to identify possible responses you could take to changing conditions. What's more, you'll have the tools necessary to choose the option with the highest probability of success.

What are the benefits of data analytics in small businesses and startups?

Now that we've outlined the four types of data analytics, let's take a step back. It's time to consider the project in broad terms. What upside can you expect from an investment in this strategy?

To answer that question, here are some of the most common benefits that companies receive when they become more proficient at data analytics:

• Improve understanding of your markets: Data analytics will let you discover insights about the conditions impacting your business.

• Optimize your website and marketing efforts: Make the best pitch possible. A keener understanding of what works and what doesn't will let you hone every aspect of your communication.

• Identify growth opportunities: What new products should you launch? Which new markets should you explore? Data analytics can point you in the right direction.

• Foster better relations with customers: Data analytics lets you learn about your customers, opening the door to a tighter connection.

• Upgrade your team: Don’t just rely on data analytics on the sales and marketing front. You can use these techniques for recruitment, retention, and upskilling. Over time, you’ll significantly improve your workforce.

• Maximize efficiency: Eliminate waste. With the right information, you can optimize your distribution of resources.

• Open up your ability to experiment: Try new things through an organized process, learning as much as you can along the way. Data analytics lets you test fresh ideas and discover which ones hold the most promise.

• Cut dead-end ventures as early as possible: Don't waste time and money on endeavors that are destined to fail. Learn as soon as possible whether a project lacks potential.

• Avoid getting duped by business fads: Are the latest trends and buzzwords worth your attention? Data analytics gives you a scientific way to find out.

How to get started with data analytics in your small business or startup

If you decide that you want to dive more into data analytics, there are a few factors to keep in mind. You want to get the most out of the process. As such, here are a few tips to help you get started:

Discover what you know (and what you don't know)

As we've seen by looking at the four types of data analytics, the field involves multiple levels of complexity. Meanwhile, your business has unique requirements, based on your market, customer base, development stage, and a long list of other factors. As such, it's important to gauge the data analytics expertise you have available on your current team and judge the additional help you might need.

Get buy in from your team

If data is going to play a bigger role in your organization's decision making, you need to prepare your team for the change. Take time to explain the goals to your staff. At the same time, make everyone aware of the specific KPIs you will be using and let them get familiar with their roles in the process.

This communication effort will pay off in the long run. You'll see higher engagement from your team. Long term, this will lead to better implementation, both of the data analysis and of the initiatives conceived as a result of your number-crunching.

Get expert advice

Don't be afraid to seek out help with this endeavor. Successful data analysis requires a level of technical skill, which might not be available within your organization. Expand your personal knowledge base as much as possible, but supplement that with outside experts who can guide your efforts.

Master data collection and maintenance

Your analysis won't be reliable if it doesn't start with good data. As such, perfecting this process should be your first step. Learn how to gather as much data as possible. At the same time, get adept at storing the information correctly and having the proper tools to parse it effectively.

Define your goals

Create clear objectives for your data analysis. In other words, know what questions you want answered. The more specific your queries, the more refined your analysis can be. That way, you can discover the actionable insights you need to push your small business or startup forward.

Find the right tech

Along with expert advice, you'll need the proper tools. Research the best software solutions to enhance your data collection and analysis. With the right tech backbone in place, you have a better chance of getting the results you need.

How can your small business or startup use data analysis?

More and more small businesses are using data analytics. A strong foundation in this field can improve your decision making in areas like marketing, finance, and HR. Still, you need to consider how to handle data analytics for your organization, finding the best approach for your situation.

Use the information provided here to get started. You can determine if your company could benefit from allocating time and resources to data analysis. From there, you can begin the process of evaluating the four kinds of data analytics and see how best to apply them to your small business or startup.