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Today’s modern business world thrives on data. From the earliest stages of design and manufacturing to later media outreach and customer engagement, raw data is an invaluable resource. Over the past decade, various data analysis tools have come along to provide cutting-edge business intelligence and actionable insights to organizations of different industries sizes. The best analytics tools handle data mining through large volumes of data sources for consumer trends, while also transforming that information into quantitative data and analytics for better business decisions.

But what are the most popular and universal uses for data analysis? While that may depend on the organization and its needs, any business entity can benefit from the machine learning aspects of predictive analytics in marketing campaigns or sentiment analysis for creating a greater customer experience.

Big Data and Pre-launch Strategies

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In the beginning, you may ask yourself “what is data analysis and why is it beneficial?” To best understand the importance of data analysis, perhaps it’s a good idea to consider the valuable insights that statistical analysis can yield toward future outcomes. Regardless of its industry, every organization eventually plans a structural expansion or faces the public launch of a new product or service.

Each of these common initiatives requires separate teams to oversee the design, manufacturing, customer engagement, media outreach, and, ultimately, customer service. Statistical analysis can aid in the prediction of success or failure for each of these key initiatives. Additionally, proper analysis can provide the members of each team with the insights to make better business decisions.

When it comes to assisting your preliminary teams, big data analytics can enable product designers and marketing strategists to better understand the demands of consumers, as well as recognize needed improvements in existing competition. Depending upon the type of data analysis and data analytics techniques used, the algorithm-based platforms can consolidate new data for targeting the correct demographics and assist in predicting the behaviors and trends in product success. With that in mind, related predictive analysis can assist marketing campaigns in adjusting their own outreach methods, recognizing the appropriate websites and influencers for optimal success.

Post-launch and Improved Workflow

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The benefits of data analysis don’t end once your new product or service has been unveiled. During your future marketing campaigns, a data analyst will most likely oversee your online presence, as well as the advanced analytics behind your company’s various social media profiles. But where data visualization helped your organization in the earlier stages of production, data trends represented by historical data and other business analytics can now enable ongoing success both with future outcomes and customer service.

Largely due to the shared popularity of online shopping and social media influencing, garnering valuable insights into customer needs has never been easier. Likewise, customer outreach and engagement are improved, allowing your company to directly receive valuable customer feedback. For small businesses, the integration of data analysis and “voice of the customer” software (VoC) together can present an appearance of round-the-clock customer service, allowing you to retain customer information and previous purchases and communications.

With this data at your side, your service team can ask the key questions needed to provide a customized, personalized customer experience. Through sentiment analysis, all progress made during the customer journey can be retained for future communications, which only deepens the customer relationship and ongoing brand loyalty.

Ultimately, a good analytics tool can prove to be the most important facet in your entire business process. If knowledge can empower your organization to better meet the needs of its demographic through improved products or services, as well as personalized customer experiences, then analytics is imperative for business intelligence and insight.

Kathy Heckle