In this sense, focusing on optimized strategies can help generate performance and provide the results that every business seeks. By observing the data, we can extract structured information about how digital marketing works.
This vision is essential for planning a correct strategy.
See the importance of data analysis:
Using a data model may seem complex, but it becomes simple as we understand the information that the data generates. From there, it is possible to observe, generate hypotheses, perform experiments, analyze the data manufacturing email list generated and share the results.
Understanding these concepts is important to show the direct connection of each of them with the marketing area, especially when we talk about digital marketing.
Working on digital channels generates a high volume of data. Therefore, only a well-structured process can be used to analyze and extract concrete information. Furthermore, to analyze relevant information in the digital world, it is important to always be up to date with global digital market trends for business.
We have separated for you: 7 tips for using data analysis
1- Analyze data by funnel stage
The sales funnel is made up of several stages, which are:
Customer approach;
Customer needs;
Be the solution to the problem;
Close the sale;
Complete the sale and follow up
Each of these steps requires the company’s knowledge to get the consumer through them all as quickly as possible.
Therefore, good data analysis transforms the average consumer into a loyal customer and defender of your brand, in addition to identifying flaws in the process. It is very common for customers to see a need, but not give your company a vote of confidence.
There are many factors and specific cases, and there are ways to make the consumer skip stages of the funnel. All of this is done through data collection and analysis.
2- Acquisition channels
Where to get new customers? How to find them? Acquisition channels are the paths your company must take to find new consumers. This is done with the highest level of knowledge of your target audience.
You can quickly answer simple questions such as your consumer’s age, when they buy, and what they do to find your product. However, some more in-depth questions need to be asked to locate these channels.
For example: why does a customer abandon a purchase? What triggers my customer to become interested in the company? Who are the visitors to my company's website? These questions can be answered with data analysis, especially when the information is specific to a given niche.
