Team discusses analytics at conference table
Today, data is the backbone of businesses. Employees debate the best ways to collect, analyze and use it behind the scenes at companies everywhere. In the digital age, leveraging the right data can catapult an unknown operation into a household name. By using accessible information, a company can at least become more efficient and more responsive to customer needs.
But data is also complex, making it easy to get confused about what it all means. To discover actionable insights, you need to know how to use information while filtering out the nonsense. In data analysis, biases, misinterpretations and inadequate methods can lead a company down the wrong path. However, when done correctly, data analytics has the power to give a company a competitive edge. Here are three ways it can be done.
Table of Contents
1. Shape strategies
Businesses rely on well-thought-out strategies to stay ahead. While business strategies are no guarantee of success, they are a roadmap to what business leaders hope to achieve. Ideally, the C-suite doesn’t just design these blueprints by intuition. They also use data to determine which direction to take.
Relational data models are examples of resources leaders can use to formulate their game plans. These models reveal not-so-obvious relationships between different variables. While correlation does not always imply causation, uncovering relationships between variables can lead to more informed strategies.
Suppose a company’s customer survey data shows an inverse relationship between loyalty and satisfaction. In other words, the longer customers stick around, the lower their overall satisfaction becomes. Intuitively, this doesn’t seem logical. But the data points to the need for a different customer retention strategy. To figure out what the possible solution should be, leaders would need to input more variables.
DevX, a leading provider of tools and services for the tech industry, highlights the scalability of relational data models. These models are relatively easy to understand and can be adapted to a company’s needs. The number of variables can increase or decrease as leaders try to solve problems of varying complexity. For example, the company trying to solve its customer satisfaction problem may need to add data points for agent empathy and language matching to the traditional metrics for response time and first contact resolution.
2. Predict consumer behavior
Predictive analytics is as close to a crystal ball as companies can get. With these tools, employees can recognize patterns in consumer behavior. Predictive analytics brings companies closer to the customer by revealing how a customer is likely to react to market developments and business tactics. The tools predict the future by looking at past data to identify patterns and preferences.
For example, historical data shows that people cut back on spending when prices rise. But not all market segments are equally affected by a slowing economy. In 2023, inflation and rising interest rates have pushed consumers to it pull back on new cars, household appliances and furniture. Yet, despite rising prices, they are still spending money on restaurants and hotels.
As with any forecast, predictive analytics isn’t always lurking. However, companies that use these tools can better anticipate consumer needs. Given the current climate, budget-friendly hotel chains like Comfort Inn can expand their appeal to other consumer segments. But that doesn’t mean more upscale brands like the Four Seasons have to offer steep discounts in order to compete.
Predictive analytics tools adjust output based on a company’s target market and external variables, indicating how customers are likely to respond to a new product, service, or promotion. If both ends of the hotel chain’s spectrum continue to appeal to customers despite inflation, every chain will move forward. However, predictive analytics can lead them to offer offers as diverse as their customer base.
3. Improve online experiences
When people want to buy something, they look online. More telling is how many shoppers look to a company’s digital presence to help them make decisions. About 81% of consumers search for businesses online, with 55% viewing reviews and 47% browsing business websites.
If a website isn’t up to snuff, it’s not going to convince people to move forward in their buying journey. Technical issues and confusing content will reduce potential customers’ trust in a company. Even longer loading times and complex checkout processes will lead to higher bounce rates or abandoned carts. With website analytics, companies can improve digital customer experiences and increase conversion.
Everything from SEO data to scroll depth can show whether a website is performing as expected. Low organic traffic can indicate a problem with content and keywords. Less than ideal conversion rates can reveal the need for design changes. And too many abandoned carts can be people’s way of saying they don’t trust the site. These data points lead to website improvements that create seamless customer experiences and increase business profits.
What it takes to compete
Beating the competition keeps companies in the game. But winning strategies don’t come out of the blue. Leaders need reliable data analytics to drive, predict and improve what their companies are doing. Trying to run a modern business without data is like leaving everything to chance.
