Data-driven marketing harnesses the power of big data and machine learning (ML) analysis to come up with sound marketing strategies. It uses customer engagement information collected from social media, websites, newsletters, and other marketing channels. By looking at various channels, marketers spot emerging trends and gain more in-depth insights into their customers’ profiles, behaviors, demographics, and even likes and dislikes.

The goal of data-driven marketing is to enhance every customer’s experience by making content, recommendations, and offerings personalized. That allows marketers to improve brand awareness and obtain loyal customers that consequently translate to increased revenue.

To date, a study revealed that 63% of companies had invested more in data-driven marketing. Experts believe this figure will continue to rise in the future.

What is Data-Driven Marketing?

Data-driven marketing is a type of marketing that focuses on customer-centric communications and uses analytics tools and big data to craft targeted campaigns. Customer experience is the main driving force behind it. In some circles, data-driven marketing is known as “big data marketing” because it gathers and analyzes massive amounts of customer information to turn the insights into actionable plans. In a sense, the practice aligns marketing efforts with customer demands to generate huge returns on investment (ROI).

Big data marketing is not only applied to sending out personalized communications but also improving the overall customer experience when they visit your site and social media pages. Marketers can tailor the look and feel of their websites and pages to their customers’ likes and dislikes. Product favorites can figure in a featured section on your home page for one. Awarding discounts and freebies to loyal customers via email is another option.

To gather information, marketers ask customers for feedback through surveys. The responses allow them to discover areas for improvement. Almost half (49%) of the marketers surveyed in a study indicated using data-driven marketing in this manner. So, aside from crafting more personalized campaigns, data-driven marketing also aids in product development.

How does Big Data Marketing Work?

Four processes make up big data marketing. These are:

1. Data Collection

You can collect data using applications such as Google Analytics and other customer relationship management (CRM) software. You may need as many sources as possible to ensure the accuracy of your findings. But because each source may use a different format, which could complicate the analysis, you may need to structure all information the same way.

2. Data Analysis

After collection and structuring, you are now ready to make comparisons and form conclusions and recommendations. Keep in mind your organization’s goals when building insights, however. A considerable part of the analysis lies in sifting through what’s relevant. Only then can you start converting the insights into actionable strategies.

Data analysis lets marketers build accurate customer profiles. These profiles will guide them in crafting a content calendar and plan that responds to the customers’ requirements. The profile and calendar will be part of the marketing campaign. The campaign needs to include key performance indicators (KPIs) as well, so its success can be measured.

3. Campaign Launch

Marketing campaigns are specially crafted to encompass all the channels available within the organization. These channels include email, social media, websites, and even third-party sites. What’s important is that the campaign follows the content strategy that resulted from the data analysis.

4. Result Monitoring

A campaign launch is, however, not the end of the line. Marketing campaigns are often fine-tuned to address customers’ ever-changing behaviors and market trends consistently. For that, marketers need to use analytics tools to check if they met the KPIs. Monitoring results allows marketers to adjust their strategies by looking at what worked and what didn’t, so in the end, they would meet their targets.

Is Data-driven Marketing Helpful to Businesses?
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