Can we trust every bit of data we get?
Traditional Vs. data marketing
In its most basic form, marketing has always had two goals. First, determine what customers want and need — then leverage that knowledge to produce precisely what buyers desire.
In terms of practice, this has always meant:
First, gaining a thorough grasp of the target market, identifying and anticipating client demands, and finally, developing methods to produce items that would meet those needs.
On the other hand, data-driven marketing enables marketers to interact with customers at the right moment. And with the right deal.
However, the advantages of utilizing the data extend beyond simply boosting communications. Customer insights are used by modern marketing teams to:
- Personalize the customer experience, target specific marketing categories, and acquire new consumers.
- Brands may also use the data to measure and enhance their strategy in real-time.
Data-driven marketing is a strategy for improving brand messaging using consumer data. Customers’ wants, preferences, and future behaviors are predicted via data-driven marketing. Such knowledge aids in the development of tailored marketing strategies that maximize return on investment (ROI).
Do we trust our data?
You have a few weeks to make a critical choice, and you’ve recently discovered some new data that is potentially game-changing insights when paired with previous data. However, it is unclear whether or not this further information can be believed. What should you do?
Of course, there is no easy answer. Many people are suspicious of data, while others enthusiastically welcome them, and the more discerning people take a more balanced approach. They are aware that some data (perhaps the majority) is harmful and should not be utilized, while others are good and should be implicitly trusted.
They also recognize that some data is faulty, but it may be used with caution. They are fascinated by this data and are ready to push it to its boundaries in the hopes of uncovering game-changing insights.
Fortunately, you can work with your data scientists to determine if the data you’re evaluating is safe to use and how far you can go with data that isn’t perfect. Following a few simple procedures will help you continue with more confidence — or caution, depending on the data quality.
Consider where it originated.
When a high-quality data quality program prepares data, you can trust it. They include direct accountability for managers to accurately produce data, input controls, and attempts to identify and eradicate core sources of mistakes. You won’t have to guess if the data is excellent or not since statistics on data quality will inform you.
Independently assess data quality.
Much, if not all, data will fall short of the gold standard; therefore, proceed with caution and do your data quality review. Make sure you understand where the data came from and how it was characterized, not just how your data scientist got it. Determine which organization was responsible for the data’s creation. Then explore a little deeper: What do your peers say about this data and organization? Is it regarded as high-quality or low-quality? What are the opinions of others on social media? Make some inquiries.
Clean up the information.
Data cleaning is divided into three stages: rinse, wash, and scrub. “Rinse” replaces apparent errors with “missing value” or corrects them if the task is simple; “scrub” entails in-depth analysis, including making repairs one-by-one, by hand, if required; and “wash” falls somewhere in the center.
Ascertain that the data integration is of good quality.
Align your existing data with the data you can trust — or the information you’re carefully moving forward with.
Closure
More and more of our lives are being dominated by technology. Data and analytics, in particular, are increasingly determining how we manage everything from our businesses to our day-to-day operations.
The ability of marketers to obtain relevant consumer data and the utilization of data is critical to offering the sort of customer experience that allows businesses to stand out.
With new data privacy rules, more consumer awareness, and the impending phase-out of third-party cookies, marketers must earn consumers’ confidence and utilize their data to improve their experience.
Marketers must earn and maintain consumer trust by being transparent about how data is used and ensuring that customers understand the benefit of giving their information.
