The word data has featured prominently in many business-related discussions over the past decade or so. From sales funnels to web analytics, data is spearheading the product development, sales, and marketing efforts of just about every business.
But data alone is not enough to help your business thrive. You need a functional data strategy to transform the data into value. A data strategy refers to the process which defines how you’ll collect, manage, and analyze business data so you can make well-informed critical decisions for the company.
However, there are different kinds of data with countless metrics you can use to track your data. As such, you need to be clear on what data strategy is valuable to your business, and why you should implement it.
To help you in this process, here are six examples of data strategies you can consider for your business.
1. Data Exploration
Data exploration involves manipulating data to find solutions to problems that managers might not have thought of before. This strategy leverages predictive model tools to predict customer behavior based on their previous business transactions.
By predicting emerging customer trends, the business can perform targeted actions such as upgrading the service or customizing marketing messages to stay ahead of the curve.
2. Decision Science
Decision science involves analyzing non-transactional data such as product reviews and consumer feedback to add more value to the decision-making process.
Key decision-makers will work with stakeholders responsible for collecting and analyzing community feedback. With this information, management can determine the value of the feedback provided and develop a roadmap that’ll dictate how they plan to act on the ideas.
3. Performance Management
Performance management involves multidimensional analysis of business transactional data such as inventory and buyer activity. For example, managers can use this data to create a clear picture of their customers and how to segment them.
The major issue with this strategy is ensuring the accuracy and quality of data entered into the system. But creating numerous databases can be an ideal solution to this challenge.
4. Social Analytics
A social analytics strategy involves analyzing data from social media platforms such as reviews and conversations related to the business. Social analytics measures brand awareness, audience reach, and engagement level among platform members.
5. Network Performance
Network performance analytics helps IT teams identify bottlenecks in advance by measuring website traffic, load times, user activity, and network uptime and downtime. Businesses that measure network performance use a software engine to access data from different sources such as servers and connected devices.
6. Employee Engagement
Data can also be used inward to provide insights into employee engagement and productivity at work. This data helps managers get a good sense of their employees’ work processes and how to help them become more efficient.
For instance, if your data insights reveal that the customer service team is spending too much time on the same queries, you can develop an FAQ section or a chatbot programmed to answer such queries in real-time.
The Bottom Line
The ability to manage and analyze data is critical to a company’s success more than ever before. However, the data you have is only as valuable as you use it. Consider any of the data strategies to discover trends and opportunities that will give you a competitive edge in the market.