Your business should know the facts, right? Without facts, you might make important decisions on a whim, and the results may not be as powerful as expected. In all, there’s a higher chance of success from every angle by using data-driven analytics.
Businesses today are becoming more data-driven as technologies advance and data is widely available. Plus, being data-driven can transform an organization in an extremely positive way if done right.
Having said that, a business needs to know what it means exactly to be data-driven, the pros and the cons, and the keys to having a data-driven culture.
In this article, we’ll go over everything you need to know about being a data-driven business so you can decide if it’s the right move for you.
What Is Data Analytics in Business?
Data analytics can help companies understand their customers, analyze ad campaigns, personalize, develop products, and create content strategies. With that in mind, being a data-driven business has many benefits, mostly creating powerful strategies that boost bottom lines.
Where do the different sources of data come from?
Data collection can come from something as simple as a survey sent out to your customer database. Many businesses use data from historical research or new information obtained for a specific reason. Data can also be collected from customers and site visitors or can be purchased from other organizations.
The data a business collects from its customers is called first-party data. Data collected from a company (a competitor) that collected their own data is called second-party data. Finally, buying data from an enterprise that sells it is called third-party data.
Types of Insights Gained From Data Analytics
The amount of data that businesses can obtain thanks to technology is impressive. By checking your analytics, you can see your audience’s demographics, interests, psychographics, consumer behaviors, predictive analytics, and more.
But in general, consumer data can be broken into four sections:
1. Personal data: Personally identifiable information such as gender and social security numbers. It can also include your IP address, web browser cookies, and device IDs (both on mobile and desktop devices).
2. Engagement data: How customers interact with a business’s content. It includes the average order value, page likes, shares, and comments, how many people use your customer support system, etc.
3. Behavioral data: How much time customers spend browning your content, mouse movement, purchase histories, and product usage information such as repeated actions.
4. Attitudinal data: Key metrics on purchase criteria, customer satisfaction, product desirability, opinions, branding, and sentiments.
All of this information can help you hyper-target your ads to get the best results and create content around what your audience engages with most.
Where can you view your analytics?
Many data analytics tools offer a 360 view of all of your analytics sources combined. However, if you’re running a Google Ad, you don’t need to pay for and download a tool. Checking the analytics for your ad is as simple as logging in to Google My Business. From there, you can see all of your Google Analytics on your dashboard.
You can do the same on social media platforms like Facebook and Instagram.
How Businesses Use Data Analytics to Boost Their Bottom Line
Businesses can use data analytics to make timely decisions in different core areas needed for long-term success. Here’s a rundown of the places that data benefits the most:
Use of Data Analytics in Marketing
In the past, businesses have lost billions of dollars in ads and marketing because they simply weren’t running ads that caught the consumer’s attention. In fact, an estimated 611 billion US dollars are lost per year due to poorly targeting digital marketing campaigns.
Why was this happening?
It’s most likely they were skipping the research phase. With data analytics available, businesses can create hyper-focused marketing campaigns on their target audience, leading to much more effective campaigns.
The research involves observing online activity, monitoring point-of-sale transactions, and adapting to quickly changing consumer trends.
Netflix is a leading example of a use case of data analytics for marketing. They track their subscriber’s search and watch data to know which movies to suggest. Smart suggestions like these keep subscribers’ interest high, and in turn, they keep their memberships.
Innovations and Product Development
Every new product idea begins with establishing what exactly it is the customers need. Without analytics, product development is reduced to the basics of having a vision and implementing it with disregard to whether it appeals to your audience or not.
Data-driven businesses use analytics to analyze the following:
- Product viability: using data to verify and solidify product development concepts.
- Product progress measurement: analyze and inform your business about which features of a new product are appealing and which aren’t to make a more versatile final product.
- User experience insights: Data can be used to understand why customers buy the product and what purpose it serves in their life. Some businesses can use this data to see why a customer may opt for a competitor’s product instead.
- Product development inspiration: Analytics can inspire innovations or help existing ones stay relevant through changing consumer needs and trends.
Data is crucial to a product’s long-term success and its evolution to fit new trends and market changes.
Customer Service and Retention
No business can claim success without the establishment of a customer base. And with a customer base, a company can not ignore competition that may take those customers away. If a business is slow to learn what customers are looking for, the loss of clientele will negatively affect its survival.
Finding ways to please customers and keep up with their behaviors can be a shot in the dark if you’re just guessing.
That’s where a predictive analysis comes in. Using historical data and current facts, you can make super reliable predictions on your clients’ issues with your service or product.
Doing a prediction analysis to deal with customer problems provides different advantages to a business since you can pinpoint issues before the customer reaches out to you first. And by having more time to fix business problems, the customer will appreciate that your business is on the ball and proactively solving issues.
Run Operations More Efficiently
Most businesses plan to cut costs in their yearly reports, but many companies struggle with hitting their cost-cutting targets. It may be difficult to know where they are spending money on the wrong things.
How can you obtain sustainable operations that cost money without damaging the customer experience or the company’s ability to grow?
The most effective way to eliminate errors and external spending is by looking at data. Data analytics streamlines your process by improving your understanding of what your audience wants. Therefore, there’s no wasted time or money on efforts that don’t match your audience’s interest.
The Key to Constructing a Data-Driven Culture
“We’re not that much smarter than we used to be, even though we have much more information—and that means the real skill now is learning how to pick out the useful information from all this noise.”
— Nate Silver
A data-driven culture embraces data in decision-making by treating data as a strategic asset to the company. It promotes frequent experimentation to learn, grow, and improve. A data-driven business realizes that a strong foundation of data is critical, including artificial intelligence (AI) and machine learning (ML). It’s a culture made of a high level of data literacy and uses it to boost the company and everyone in it as a whole.
Data-driven companies make data accessible to employees so they can always refer to the facts before making decisions. At the same time, data-driven companies are transparent about data access restrictions and governance methods.
A business must know that data can only take growth so far — people are the real growth drivers in any data-driven business. Analytics leaders must find the employees with data skills, lead by example, and know when relying on data is a mistake.
So, how can you, as a leader, create a data-driven culture?
1. Target Your Leaders First
The senior leaders within your business should be the first ones to build a data-driven culture. These senior executives will set examples that trickle down throughout each management level and among employees, leading to lasting organizational transformation.
2. Implement a Change in Mindset
A key component of developing a data-driven culture is to change the way your employees view data. Data analysis shouldn’t be seen as another boring task they need to perform. Instead, it should be thought of as a focal point for every decision.
Your entire team needs to not only turn to data to answer questions but regularly analyze available data and create discussions around the findings.
3. Build a Team of Skilled People
Being a data-driven business requires technical people who are equipped to support a data-driven culture. These people are responsible for maintaining and building the company’s database. Their main focus is using technology and analytics platforms to organize data better (eliminating the excel spreadsheets and manual calculations) and make data more readable for the employees.
Your technical team will also be the people that reinforce the data-driven culture by lending support to other departments for structuring and understanding data.
4. Make Data Analysis a Standard Procedure in Decision Making
Your entire team needs to understand that no strategic decision should be made without analyzing the data first. On top of that, your team needs to know why data plays such an important role in business decisions.
Although the answer to why looking at data before anything may vary from business to business, some of the standard core reasons are because it creates decisions based on facts, increasing the possibility of a positive outcome while leading to more credibility for your business.
Once you implement these steps, your company will be on the right track to honing a data-driven culture. It’s important to note that you can only have a fully data-driven culture if everyone in your company is on board.
This change may be specifically difficult if your business has been using other methods for years. Shifts in company culture need to be practiced and are achieved over time.
That brings us to the challenges of having a data-driven business.
Challenges Companies Face When Transitioning to Being Data-Driven
As businesses learn the benefits of being data-driven, more are investing in the tools and people they need to make it happen. However, if being data-driven was such an easy thing to accomplish, there wouldn’t be so many doubts around the topic, and companies would do it without hesitation.
The challenges that hold companies back include:
1. Difficulty With Incorporating a Data-Driven Culture
Startups and new businesses are adapting to a data-driven culture because of the benefits it presents. However, a huge part of the industry doesn’t know how to take the first steps in leading a data-driven approach in their existing organizational culture.
Changing cultures can be more evident in certain types of businesses than others. Take a production and manufacturing company as an example. This type of company is familiar with traditional business methods and may have difficulty knowing how to utilize data.
2. Lack of Leadership in the Data-Driven Approach
As mentioned above, if your business is truly data-driven, everyone must be on the same page.
Having everyone on the same page is only possible if you have certain people who preach the business culture to everyone in the company. Most importantly, leaders need to consistently reinforce the culture and act as a leading example for everyone.
A lack of this leadership could cause a semi data-driven company, causing conflicts between different teams and unreliable results.
3. Distrust in Data
Did you know that 71% of people don’t trust data quality?
Most people looking at data don’t know where the big data analytics came from, when it may be useful, and how current it is. The confusion comes into play most when data insights contradict a long-standing norm.
A distrust in data often influences leaders to fall back on decisions they think they can rely on, leaving the data aside and following their gut instinct.
4. Translating Data Insights to Where They Will Drive the Most Value
You have the data. Now what?
Could this data drive better results for the marketing team, the customer service team, or the operations team? Knowing where to send the data can be tricky and often gets misused.
The best way to make sure the data is being sent to the right place is by making it accessible to every team in your organization. This way, the teams can share valuable insights and see where the data can fit in.
5. Finding and Recruiting Analytical People
Having everyone within a company be familiar with using big data and advanced analytics is unrealistic, especially if you have recently transitioned to being a data-driven business. Many businesses struggle with the imbalance of data professionals and non-techy employees because the professionals always end up getting the final say, creating downgrades in job positions and possible disputes in the workplace.
The interactions between the data professionals and the non-techy employees are key to avoiding issues. This simply implies good communication between teams during meetings and the analysis of data.
Your team should learn from one another and be open to discussions, no matter their knowledge level.
Final Thoughts
A data-driven business looks to data before making any big decisions. Everyone, from senior management to employees, should be on the same page. Companies who adopt being data-driven tend to see much better growth as every business decision taken has evidence to support its potential success.
While transitioning to being data-driven has major benefits, companies who choose to do so also face challenges that slow the transition or even bring it to a halt. When determining if being a data-driven business is right for your company, it’s important to analyze your business model first. Some businesses are better off following traditional methods while others have more possibility for change.
You must also see if you have enough knowledgeable staff or need to go through hiring and training all new tech personnel. Overall, the effort is worth it as being a data-driven company gives you a competitive advantage and amazing business opportunities.
