3 Ways Harnessing Data And Leveraging Analytics Can Put Your Business Ahead

These days, 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, harnessing the right data can catapult an unknown operation into a household name. At the very least, leveraging accessible information can make a company more efficient and responsive to customers’ needs.

But data is also complex, making it easy to get confused about what it all means. Uncovering actionable insights requires knowing how to use information while filtering out the nonsense. In data analytics, biases, misinterpretations and insufficient methods can lead a business down the wrong path. When done correctly, though, data analytics has the power to put a company ahead of its competition. Here are three ways it can.

1. Shaping Strategies

Businesses rely on well-conceived strategies to stay ahead of the game. While business strategies aren’t a guarantee of success, they’re a road map to what company leaders hope to achieve. Ideally, those in the C-suite aren’t designing these blueprints based on intuition alone. They’re also using data to determine which direction to go.

Relational data models are examples of sources leaders can use to formulate their game plans. These models reveal not-so-obvious relationships between different variables. While correlation doesn’t always mean causation, uncovering connections between variables can lead to more well-informed strategies.

Say a company’s customer survey data shows an inverse relationship between loyalty and satisfaction. In other words, the longer clients stick around, the lower their overall satisfaction becomes. Intuitively, this doesn’t seem to make sense. But the data points toward the need for a different customer retention strategy. To figure out what the potential fix should be, leaders would need to plug in more variables.

DevX, a leading provider of tools and services for the tech sector, highlights the scalability of relational data models. These models are relatively easy to understand and scale according to a company’s needs. The number of variables can increase or decrease as leaders look to solve problems of various complexity. For example, the company seeking to solve its customer satisfaction problem may need to add agent empathy and language alignment data points to traditional response time and first-contact resolution metrics.

2. Predicting Consumer Behavior

Predictive analytics comes as close to a crystal ball as companies can get. With these tools, employees can identify patterns in consumer behaviors. Predictive analytics bring businesses closer to the customer’s mind by revealing how a client will likely react to market developments and company tactics. The tools predict the future by looking at past data to identify patterns and preferences.

For instance, historical data shows people cut back on spending when prices go up. But not all market segments bear the brunt of a slowing economy equally. In 2023, inflation and rising interest rates have caused consumers to pull back on new cars, home appliances and furniture. Yet they’re still spending money on restaurants and hotels despite increasing prices.

As with any forecast, predictive analytics aren’t always on the nose. However, businesses that use these tools can better anticipate consumers’ needs. Given the current climate, budget-friendly hotel chains like Comfort Inn may broaden their appeal to additional consumer segments. But that doesn’t mean more upscale brands like the Four Seasons will have to offer steep discounts to compete.

Predictive analytics tools customize outputs based on a company’s target market and external variables, indicating how customers will likely respond to a new product, service or promotion. If both ends of the hotel chain spectrum continue to appeal to clients despite inflation, each chain will pull ahead. However, predictive analytics may lead them to provide offerings as distinct as their customer bases.

3. Enhancing Online Experiences

​When people want to buy something, they start their search online. More telling is how many shoppers check out a company’s digital presence to help guide their decisions. About 81% of consumers search for companies online, with 55% checking out reviews and 47% browsing businesses’ websites.

If a website isn’t up to snuff, it won’t convince people to move forward in their purchasing journey. Technical problems and confusing content will lower potential customers’ confidence in a business. Even longer load times and complex checkout processes will lead to higher bounce rates or abandoned carts. With website analytics, companies can enhance digital customer experiences and increase conversions.

Everything from SEO data to scroll depth can show whether a website is performing to expectations. Low organic traffic could indicate a problem with content and keywords. Less-than-ideal conversion rates might reveal the need for design changes. And too many abandoned carts could 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 boost company profits.

What It Takes to Compete
Beating the competition is how businesses stay in the game. But winning strategies don’t appear out of thin air. Leaders need reliable data analytics to guide, predict and improve what their companies do. Attempting to lead a modern business without data is like leaving everything up to chance.



Source: www.forbes.com
Image: Pexels

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