|We are currently living in a data-driven world and we will get to witness an increased production of data as time passes / Photo by: ESB Professional via Shutterstock|
We are currently living in a data-driven world and we will get to witness an increased production of data as time passes, wrote Avery Philips of InsideBIgData, a news platform dedicated to the world of big data. Hence, it’s natural for us to look back at the data we recorded thus far to “see where we have been and where we would like to go.” However, businesses are taking this perspective seriously.
Data analytics is essential to businesses, facilitating growth and transforming them into large, formidable organizations. Rudgers, a university in New Jersey, said that IT and other professionals in innovative firms like Google, Tesla, and Uber are leveraging the power of data analytics to explore new, stronger relationships with customers, and streamline processes, as cited by Phillips.
How Can Data Analytics Help Businesses?
Companies want to keep their day-to-day operations running smoothly. To Phillips, “a business would cease to be a business” if the company does not have any degree of operational efficiency. Operational efficiency can be drastically enhanced with the “evaluation of data analytics.” Moreover, utilizing analytics tools can help businesses analyze raw data they produce, allowing them to identify and correct inefficiencies to provide risk management solutions. This can help companies plan for their growth.
Data can help businesses pinpoint where they are lacking in their operations. They can collate data to gauge whether their logistics department is ordering more or less than it needs. Data analytics can also yield results from forecasting customer demand, enabling the company to make the necessary adjustments in advance. Moreover, financial and accounting operations can use data analytics when budgeting and managing projects.
With data analytics, companies can confidently take larger financial risks while having the flexibility to adjust to the consequences of such risks. For businesses to grow, investing in an analytics professional is worth the ROI, granting firms peace of mind with regard to taking risks.
|With data analytics, companies can confidently take larger financial risks while having the flexibility to adjust to the consequences of such risks / Photo by: NicoElNino via Shutterstock|
2. Marketing and Customer Engagement
Measuring data has revolutionized marketing campaigns. With data, businesses can understand their audience and determine which marketing strategy will be the most successful. Hence, data analytics tools are leveraged to draw insights about a business’s potential and its existing customer base. From a marketing perspective, this data is a goldmine.
Organizations can understand how customers are talking about them, particularly what they like and what they don’t like. Firms can see who is commenting, sharing content, and mentioning a business through social listening, helping them identify who comments and shares the most.
Other metrics like click-through and bounce rate can notify a business on how successful their marketing and content campaigns are. The aforementioned metrics can also alert them if they need to recalibrate their marketing efforts to reach more customers. Click-through rates shed light on how much traffic a company’s website landing page gets.
This can be accompanied by analyzing a website’s bounce rate, helping businesses understand that a “certain volume” of traffic are accidental clicks or indications that their website needs to more user-friendly. By making an organization’s website user-friendly, it can rank higher in Google’s search engines, thereby reaching and engaging more customers, said web design and marketing company Websauce, as mentioned by Phillips.
Data Analytics As a Company’s Culture
1. Formulating a Data-Centric Strategy
Sonia Johnson of entrepreneur magazine Entrepreneur recommended that companies formulate a data strategy that is correlated to business results. Many organizations lose sight of the elements that make data work, even if they are already extracting information from their data and analytics.
Therefore, it is essential for companies to “demonstrate value early in a data and analytics project” and to ensure that any data initiative is tied back to business strategy and outcomes during the business scoping phase. Strategies should also “open up broader data use cases and unlock data collaboration and information sharing.” Most importantly, they should also account for data privacy legislation and compliance with various regulations.
2. Investing in Data Analytics Tools and Software
It’s a great idea to invest in machine learning tools, AI, and data analytics software, as these reduce the time spent on analyzing and correlating data sets. For example, LIME (Local Interpretable Model-Agnostic Explanations) can help businesses understand how machine learning algorithmic models arrive at a conclusion.
Further, machine learning tools can automate processes such as identifying and addressing data quality issues and “when potential customers are likely to leave.” Investing in a data platform like Microsoft Azure can help automate ELT processes across varied data types and overcome challenges related to siloed data.
3. Promoting a Data-Driven Company Culture
A data-driven culture allows digital natives to differentiate themselves from their counterparts. n Decision-making processes and initiatives should be data-driven, which requires effective communication and collaboration across all departments. Leaders, as well as the company’s culture, “must be ready to support the spread of data literacy, innovation and new ideas.” It is also important for companies to acknowledge that data and analytics are essential tools in their business operations.
Data analytics allows businesses to engage with more customers, gathering data about analyzing and drawing insights from them to improve or gauge the success of their marketing efforts. Investing in data analytics is a must, but companies should not forget to foster a data-driven culture that supports innovation and data literacy.