4 Ways to Use Data Analytics to Grow Your Business

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The modern business landscape has more options regarding customer outreach and product development than ever, largely thanks to the integration of insights garnered through data mining and data analysis. No matter the industry, team members from every level of conception, production, and strategic marketing can benefit from the pragmatic use of innovations regarding analytics, making data scientists as integral to outreach strategies as sales and marketing teams.

Here, we will look at four of the most beneficial ways that you can use data analytics to grow your business, while also fostering customer relationships and ongoing brand loyalty.

1. Market and Demographic Research

While the use of data mining and the statistical analysis of that raw data has long been among the best practices of major companies, the past decade has seen new functions of machine learning and data analysis assist smaller organizations to grow with faster success and accuracy. You may ask yourself what is data analytics? The answer is not overly advanced, although the many uses of the gathered analytics can prove invaluable to your business in numerous ways.

When looking at typical organizational workflow, data science can prove its worth as the first step during the earliest stage of development, allowing a company to find its correct target demographic. Additionally, you can gain insights into those potential customers’ needs and preferences by using the same valuable insights.

With the aid of a data mining platform and skilled data analyst, the information gathered from such sources as social media, customer feedback forums, and available user preferences, via historical data can all be gathered for proper data analysis. Ultimately, this now-structured data set can provide you with the information you need for future product development, as well as marketing strategies to meet high demand.

2. Product and Service Development

As mentioned, the next phase of a typical manufacturing workflow will include the structural design and development of a given product or service. In this instance, the big data gathered from the same sources can positively influence the consumer demands and preferences of an in-progress product.

While making crucial design and business decisions, you can apply algorithm-based platforms to comprise both predictive analytics to better understand customer outreach from previous product launches and marketing tactics, and statistical models to observe the success rate of specific similar goods or services. Before your own product launch, the product can be tweaked accordingly, leading not only to faster decision-making throughout the development stage but also better business decisions during the entire marketing process.

3. Customer Outreach and Engagement

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When it comes to applying big data analytics to customer outreach and engagement, the information gathered from online sources can turn valuable insights into actionable insights. For example, applying data analytics techniques to the preliminary stages of a marketing and business strategy can enable you to see the success rate of competitors’ own outreach tactics and campaigns.

Likewise, the use of data analytics can analyze the behavior and trends associated with overall customer satisfaction. This can give you the needed information to structure your own outreach strategies when the time comes for your product or services to meet the public.

4. Customer Feedback and Overall Growth

The use of data analysis is especially ideal for customer feedback and company growth. Remember that the use of unstructured data made into predictive models can benefit both you as the organization but also as the customer.

During a product’s launch and public unveiling, customer service and “voice of the customer” (VoC) data can streamline company feedback to meet consumer inquiries and demand. In addition, the use of data mining on third-party review websites and social media influencer sites can be studied through exploratory data analysis for better product and business performance.

By gaining a uniquely personalized understanding of your product and company’s perceived success rate, your services will improve, as will the customer experience.

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