28 May 2025

What Are the Advantages of Data-Driven Marketing

Data-driven marketing is gaining popularity. Consumer data is becoming increasingly important. It helps to personalize advertising. According to statistics, 40% of brands plan to increase budgets for marketing based on Big Data.

Modern technologies provide various ways to gather information about target audiences: from loyalty programs to engagement in relevant discussions on social networks. One of these tools is Big Data.

In this article, we explain how data-driven marketing allows successfully setting up advertising campaigns and increasing promotion effectiveness.

What is Data-Driven Marketing

Data-driven marketing is an approach in which the development of advertising campaigns is based on large volumes of data and analytics. This allows creating personalized offers and improving conversion rates.

Big Data in marketing is formed from numerous sources:

Telecom operators’ data: information about visited websites, movements, calls, and SMS messages.
Banking analytics: transaction data, receipts, profiles of consumer behavior.
Mobile applications: user behavior, in-app actions, session frequency.
Online sources: cookies, pixels, website logs, CRM data, social networks, and tracking systems.

These data are combined, cleaned, and used to build accurate audience profiles and enable effective targeting.

According to an Ascend2 study, nearly one-third (32%) of respondents consider their marketing strategy based on Big Data very successful. 63% of respondents rate data-driven marketing as a moderately effective tool. This indicates that many organizations have significant potential to improve Big Data analytics.

The survey also shows that email marketing (47%) and customer journey mapping (46%) are the main areas where data-driven marketing brings the greatest benefits. These results have been consistent for three consecutive years. It emphasize the key role of personalized communication with consumers.

Areas of Big Data Application in Marketing

Advantages of Targeting Based on Big Data

Big Data in marketing opens new opportunities for interacting with audiences.

Deep Customer Understanding

Big Data is a tool that helps companies study their audience in detail, identify their needs, interests, and behaviors. This allows data segmentation. Dividing the audience into categories is important for creating more precise advertising campaigns.

Categories that can be identified through Big Data analysis include:

Gender/Age
Income Level/Standard of Living
Lifestyle, presence of children/pets, leisure activities, interests
Visits to competitors
Internet and TV behavior
Purchasing behavior, interest in products
Location
Other custom events

There is also predictive analytics of Big Data — analysis of customer data that helps forecast trends and future consumer behavior. Thanks to this, marketers can create advertising offers in advance, even before visible demand arises.

Data-driven marketing allows tracking and analyzing user behavior across different platforms. This provides a holistic view of the customer journey.

Additionally, Big Data is a tool for optimizing communication timing and channels. Thanks to analytics, marketers learn when and where it is best to contact the customer. For instance, email, push notifications, phone calls, in-app advertising, etc.

Big Data in marketing helps determine the stage of the funnel the customer is at. For example, whether they have just started showing interest, are comparing products, or are ready to purchase. If the consumer has doubts, behavioral data and feedback help identify where difficulties arise.

How Data-driven Marketing Helps Better Understand Customers

Personalization in Targeting

Data-based targeting allows showing ads only to interested users. This improves promotional results and ROI.

The combination of targeting and personalization makes advertising campaigns more relevant and effective. It strengthens brand awareness, increases customer loyalty, and boosts revenue.

How Big Data Helps in Targeting:

Precise sociodemographic targeting. Data on gender, age, income, family status, and presence of children is used to show ads only to relevant segments.
Geolocation. Big Data shows where the user lives, works, and frequently visits. Ads can be tied to specific districts, cities, or even routes.
Behavioral targeting. User actions are taken into account: what they searched for, which sites they visited, what products they viewed, and how they interacted with content.
Interests and lifestyle. Analysis of apps, content, subscriptions, views, and purchases allows targeting by interests: sports, cooking, travel, automobiles, etc.
Targeting by device context. It is possible to consider which apps or at what time the user sees the ad — for example, in the evening, on the road, or at work.
Targeting by device type and connection. Data is considered about the device the user uses (mobile, tablet, desktop) and the connection type (Wi-Fi, mobile network), affecting ad format and volume.
Look-alike targeting. Based on characteristics of loyal users, Big Data finds users with similar profiles.

Improved Budget Optimization

Thanks to Big Data, mobile advertising can be targeted at audience segments that bring the highest returns. This allows reducing non-targeted expenses and increasing ROI.

One of the key mechanisms is reducing costs on ineffective advertising. Analysis shows which campaigns lead to conversions and which do not. By excluding or adjusting low-performing channels, marketers save budget and redirect resources where they generate profit.

Additionally, based on user behavior and conversion probability, algorithms automatically adjust bids to increase conversions.

Big Data helps prevent budget overspending. Tracking ad frequency allows limiting impressions to the same users.

How Big Data Helps Optimize Marketing Budget

Programmatic advertising offers advanced targeting methods based on Big Data. This allows automatic analysis of user behavior and showing ads only to those interested in the product.

At BYYD, we select audiences and promotion channels based on deep analysis of Big Data. This approach reduces customer acquisition costs and increases campaign effectiveness.