Big data is everywhere. No matter the size of your business, you’re probably collecting data somewhere. Your lead generation forms, your website analytics, and even the metrics provided by your social media accounts are all data that you use to optimize your business.
As your business grows, so will the volume of data you collect. More web pages, loyalty programs, app downloads, social media activity, transactions, email data… It adds up quickly. It won’t be long before you start collecting more data than you can reasonably review yourself.
As we often say, data on its own isn’t valuable. You need to ask smart data questions and share your findings with your team to turn that data into smart decisions. That’s where business intelligence comes in.
In this post, we help you understand business intelligence, why it’s important, and how to implement it in your organization.
Data on its own isn’t valuable. You need to ask smart data questions and share your findings with your team in order to turn that data into smart decisions. That’s where business intelligence comes in. Share on XBusiness Intelligence Defined
Business intelligence is when companies use technology and data to improve strategic decision-making. If used correctly, business intelligence creates a better customer experience and provides the company with a competitive advantage.
Business intelligence refers to a big category of data collecting and processing activities. Some organizations track one or two metrics and review them monthly with their small team. Others track thousands of data points, review them daily, and employ teams of data scientists to collect, process, analyze, and report on it all. Your organization probably falls somewhere in the middle. But in order to get the benefits of business intelligence, you must formalize and standardize the process.
Business Intelligence Techniques
Business intelligence isn’t a single process. It’s a complex web of different techniques that vary depending on the nature of your business and your company’s needs. You might use one, several, or all of the following methods.
Keep in mind that these techniques are NOT a linear process. Instead, they occur in a continuous cycle, all happening at once.
Data Mining
Data mining is collecting, sorting, and segmenting large data sets. For some organizations, it involves using machine learning to identify trends and relationships.
Querying
This is the process of searching data sets for specific information. For instance, you might query your data set for a list of customers who make a particular purchase.
Data Preparation
Data prep will structure data to prepare it for analysis. For instance, you might use several data points to calculate a conversion rate or time-to-sale.
Data Reporting
Data reporting shares data, analyses, and conclusions with stakeholders and decision-makers so they can organize and implement strategies.
Data Visualization
Data visualization is a technique that turns hard data into visual representations for analysis, such as charts and graphs. This technique is key to helping people in your organization understand the data.
Benchmarking
Benchmarking establishes performance standards and compares data to those standards. The goal is to track performance changes.
Descriptive Analytics
With descriptive analytics, you’ll look at historical data to draw interpretations to understand better what has happened in the past.
Statistical Analysis
Statistical analytics applies statistics to the results from descriptive analytics to identify trends and relationships.
Predictive Analytics
Using predictive analytics, you’ll use statistics and modeling techniques to forecast future events and predict future performance based on current and historical data.
The Benefits of Business Intelligence
Business intelligence becomes more important every year. As more business, entertainment, and other tasks occur online, an ever-increasing flow of data challenges us. We must extract as much value from this data as possible to stay competitive. Below are just a few benefits BI offers.
Identify Ways to Increase Profit
An increase in profit is the most obvious benefit and the primary reason many companies take business intelligence seriously. By exploring and analyzing your data, you can uncover new methods to make existing products and services more profitable, reduce expenses and overhead, or create new products and services for your customers.
Analyze Customer Behavior
A keen understanding of how your customers behave is a powerful way to generate more revenue. For instance, tracking the performance of different pricing models can help you maximize the amount you can charge your customers.
Identify Market Patterns and Trends
There are profitable opportunities in your industry that, in many cases, aren’t obvious. BI can help you identify patterns that you might exploit. For instance, if you notice that customers prefer to buy small amounts of a product more often, you might explore a subscription option.
Optimize Your Operations
BI isn’t just for selling more products and services. It can also help you reduce expenses and make your operations more efficient. For instance, data collected in a manufacturing facility might show managers the benefit of rearranging equipment.
Predict Future Performance
Will a new product sell? Will signing with a new vendor reduce expenses? These questions are hard to answer, but your existing data can provide clues. With the right models, BI can use historical data to make future predictions. This kind of information is enormously helpful for making long-term strategic decisions.
Discover Problems
Often, you aren’t aware of the minor problems your customers encounter in your business because they don’t complain. They simply do business with another company. Resolving these problems could represent a lot of revenue if only you could find them. BI can help illuminate these issues so you can fix them promptly.
How to Use Business Intelligence
There’s no one-size-fits-all approach to business intelligence. The specific steps you take to use business intelligence will depend on the nature of your business, the types of customers you serve, and your company’s needs.
Your BI needs may be small and straightforward. For instance, you may not have a formal process that employs the business intelligence techniques we explained above. You might explore your data intuitively without the help of statistical models or predictive analytics.
GFChart, for example, plays a role in the BI process. As a data visualization tool, GFChart helps you create attractive charts and graphs from your Gravity Forms data. You can turn your form data into meaningful information for your readers, leaders, coworkers, and stakeholders.
Or your BI needs might be exceedingly complex. You may decide to use a sophisticated business intelligence platform like Sisense, Power BI, or Qlik that integrates with all of your other tools. You might have dedicated teams of data scientists and engineers who analyze your data and create models.
Here are some classic examples of how organizations implement business intelligence:
- Operations. Streamline the supply chain, improve distribution routes, optimize logistics and labor, and ensure service level agreements are met.
- Marketing. Track campaign performance, gain visibility into overall performance, identify most profitable avenues, and predict future performance.
- Sales. Focus on key performance indicators, monitor sales pipeline performance, and identify profitable customer types.
- Finance. Look at the financial impact of any company activity or campaign and forecast finances in the future.
- Product development. Identify consumer demand, predict product rollouts, and determine pricing models.
Take Business Intelligence Seriously
If you’re thinking, “I don’t need data – I just go with my gut,” we strongly encourage you to reconsider. Your competitors use business intelligence to make smart and actionable decisions based on the real world, not their feelings. If you don’t take business intelligence seriously, the competition will leave you behind.