The Art of Data-Driven Marketing in 2025

Vlada Malysheva

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Creative Writer

July 12, 2024

In 2020, and continuing when the whole world has been operating online for more than a year, it’s difficult to imagine marketing in the old way without using Big Data. Modern marketing experts and marketing teams are well aware of the importance and necessity of data-driven strategies. High demands, expectations, and, of course, instant results for customers require informed decisions and actions based on specific data.

Over 60% of marketers believe data-driven marketing is crucial to success in a hyper-competitive global economy. It’s this approach that helps businesses succeed and reach the target audience. Let’s look at exactly what data-driven marketing is and how a data-driven marketing strategy can help your brand achieve its business goals.

Note: This post was written in 2021 and has been completely updated based on the recent updates in July 2024.

What is Data-Driven Marketing?

Data-driven marketing involves the collection and application of data to guide marketing strategies and customize the customer data journey. This approach focuses on understanding consumer demographics and actions, allowing marketers to target audiences in the optimal location and at the most opportune moment.

As the name implies, data-driven marketing uses large amounts of data to obtain actionable insights about user behavior. With this information, experts can predict customer behavior, create marketing strategies, and promote new products in the market, considering user behavior and considering other parameters.

This approach also enables the creation of personalized messaging, which tailors experiences and communications to individual consumer preferences and behaviors. With a changing digital landscape, the advent of new technologies, and the growing amount of available customer data, it’s tough to imagine marketing without data analytics anymore.

The data-driven approach allows marketers to create an effective, personalized consumer experience. The main goal of data-driven marketing is to increase the marketing department’s productivity and customer experience with your brand. In other words, we’re trying to achieve the most cherished, highest ROI value.

The data-driven approach in marketing is like preparing for the birthday of a best friend. In our case, our client is our best friend. To avoid any mistakes with a gift, you need to know not only his gender and age, but also where he lives and what his preferences and hobbies are. This data is used to create the most efficient selling solution.

And, of course, let’s not forget about the sharp changes in user behavior connected with the pandemic. Restrictions and quarantine have accelerated the transition of most processes (especially in e-commerce) to online. Those changes that could take decades occurred in a year, and now marketers must live and work in a new normal, where you can’t do without data-based solutions.

As you can see from the GlobalWebIndex research, this new spending mindset is already here.

Build data-driven marketing with OWOX BI. The service automatically collects all marketing data in a single, convenient structure from your website, advertising services, and call tracking and CRM systems. Get up-to-date and unified data ready for further segmentation and reporting. No more spending time on data discrepancies and complex transformations.

Comparing Data-Driven Marketing and Traditional Marketing Approaches

Data-driven marketing not only streamlines the decision-making process but also personalizes the customer experience, making it more relevant and engaging for each user. Marketers can create more effective marketing campaigns that resonate with their target audience by analyzing consumer behavior and preferences, leading to higher conversion rates and customer loyalty.

Furthermore, the agility of data-driven marketing allows businesses to quickly adapt to market trends and changes in consumer behavior, maintaining a competitive edge.

In contrast, traditional marketing, relying on broader demographic data and less precise targeting, may struggle to achieve the same level of personalization and relevance. The absence of immediate feedback mechanisms in traditional marketing means that strategy adjustments are slower, potentially leading to missed opportunities and wasted resources.

Additionally, the cost and effort required to conduct market research through traditional means can be prohibitive for many businesses, limiting their ability to stay informed about their audience's evolving needs and preferences.

Data Collection

Data-Driven Marketing: Extensive, using digital tools.
Traditional Marketing: Limited, often manual.

Data Analysis

Data-Driven Marketing: Real-time, automated.
Traditional Marketing: Static, manual.

Decision-making

Data-Driven Marketing: Based on data insights.
Traditional Marketing: Based on past experiences and intuition.

Cost Efficiency

Data-Driven Marketing: Higher due to automation.
Traditional Marketing: Lower due to manual processes.

Adaptability

Data-Driven Marketing: High, with real-time data.
Traditional Marketing: General, based on broad demographics.

Targeting Precision

Data-Driven Marketing: Precise, based on detailed data.
Traditional Marketing: General, based on broad demographics.

Performance Measurement

Data-Driven Marketing: Direct and immediate.
Traditional Marketing: Indirect and delayed.

Benefits of Data-driven Marketing

Understanding the significance of data-driven marketing, here are some key benefits it brings to the table:

Enhanced Customer Targeting and Segmentation: Data-driven marketing allows for intricate analysis of consumer behaviors and preferences, facilitating the creation of highly targeted and segmented marketing campaigns. This precise targeting enables marketers to deliver tailored messages that resonate more deeply with each segment, improving engagement rates and conversion potential.
Increased Efficiency and ROI: By leveraging data, marketers can identify the most effective strategies and channels, allocating resources more wisely. This approach minimizes waste on underperforming tactics, maximizing return on investment by focusing on marketing efforts in the areas that yield the highest returns.
Improved Customer Experience: Data-driven insights enable marketers to understand customer needs and preferences more deeply, allowing for the delivery of personalized experiences. This personalization enhances customer satisfaction and loyalty, as consumers are more likely to engage with content that feels specifically designed for them.
Agility and Market Responsiveness: The real-time nature of collection and analysis allows businesses to adapt to market changes or consumer feedback quickly. This agility ensures that marketing strategies remain relevant and effective, even in rapidly changing environments.
Measurable Results and Insights: Unlike traditional marketing, data-driven marketing offers clear, quantifiable metrics that demonstrate the effectiveness of campaigns. This measurability provides valuable insights for future planning, ensuring continuous improvement in marketing strategies.
Competitive Advantage: Utilizing data-driven marketing strategies gives businesses a competitive edge. The ability to quickly adapt to consumer trends, understand market dynamics, and personalize customer experiences can set a company apart from its competitors, driving growth and market share.

Frequent Challenges in Implementing Data-Driven Marketing

The most common obstacles in data-driven marketing, as identified by Campaign Monitor, highlight that 81% of marketers view implementing a data-driven strategy as exceedingly complex. Here are the main challenges and solutions:

Challenge 1: Data Collection

Many marketers new to data-driven approaches find the task of collecting customer data daunting. Questions about where to find data, coupled with the overwhelming amount of available information, often lead to hesitation in pursuing data-driven campaigns.

✅ Solution: Utilize Existing Data Sources

The good news is that most organizations already possess a wealth of data through CRM systems, website analytics, e-commerce platforms, advertising tools, ERP systems, social media software, and more.

These tools offer valuable insights into customer data profiles, website interactions, and product engagement. While some data may not be immediately actionable, striving for broader data sets can enhance decision-making, especially as consumer interests evolve rapidly.

Challenge 2: Integrating Data

Having up-to-date data is crucial for effective decision-making. The difficulty lies in manually consolidating and refreshing this data, a process that can be labor-intensive and prone to error when done manually, especially if relying on spreadsheets.

✅ Solution: Implement a Marketing Dashboard

Adopting marketing analytics and visualization platforms can streamline this process by aggregating data from multiple sources into a single dashboard. This enables real-time syncing and organization of data from various marketing channels, simplifying the overview of campaign performance.

Challenge 3: Breaking Down Data Silos

A staggering 92% of companies do not store their data in a unified location, leading to data being scattered across different teams and departments. This fragmentation prevents a holistic view of the customer data and hampers the marketing team’s ability to understand their audience fully and evaluate campaign effectiveness comprehensively.

✅ Solution: Address Data Silos Strategically

Overcoming data silos is challenging and involves establishing common data standards, fostering a culture of data sharing, and leveraging marketing analytics platforms. This process requires a strategic approach to data management and culture change within the organization.

Challenge 4: Developing a Data Team

Effectively processing vast amounts of data often necessitates the formation of specialized, cross-departmental data teams. Various models exist for structuring these teams, including the center of excellence, distributed data teams, and the hub and spoke model, each offering different approaches to data management and support.

✅ Solution: Choose the Right Team Structure

Selecting the appropriate structure depends on the organization's specific needs and goals. Whether it’s centralizing expertise, integrating data specialists across departments, or combining these strategies, the key is to establish clear guidelines and support for data processing and analysis.

Real-life Examples of Data-Driven Marketing Implemented by Businesses

Here are some popular examples-

Tailored Marketing for New Movers: DirectTV's approach capitalized on the insight that moving to a new home often prompts people to reconsider their service providers. By targeting these individuals with a homepage tailored to their specific situation, DirectTV effectively captured the attention of a key demographic at a pivotal moment, increasing the likelihood of conversion.
Behavior-triggered Email Campaigns: These emails go beyond simple reminders; they're a form of smart engagement that shows users the next steps or benefits they're missing out on. This method not only improves user experience by providing timely, useful information, but also significantly increases the chances of converting users into active customers by reducing friction points.
Optimized Advertising Timing: The winter apparel retailer's strategy underscores the importance of aligning marketing efforts with customer data and external factors like weather conditions. By strategically timing their ads, they not only saved on advertising costs but also ensured that their products were top of mind for customers at the exact moment they were most likely to consider a purchase, thereby boosting sales and efficiency.
Weather-Based Website Personalization: By dynamically changing the website's content based on real-time weather data, Very.co.uk demonstrated an innovative approach to personalization. This level of detail in targeting shows a deep understanding of customer preferences and behavior, significantly enhancing the shopping experience and encouraging purchases by making them feel uniquely understood.
Leveraging Advertising Data for SEO: This strategy illustrates the adaptability of digital marketers in the face of changing search engine policies. By creatively using data from one channel to inform strategies in another, marketers can overcome obstacles and continue to drive targeted traffic. This cross-utilization of data exemplifies a holistic approach to digital marketing, where insights from one area are used to inform strategies across the board.
Behavior-Based Retargeting: This technique not only keeps the brand visible to potential customers but does so in a way that's relevant to their interests and past interactions with the site. By customizing retargeting ads based on specific actions visitors took (or didn't take), companies can address individual concerns or interests, making the ads more engaging and increasing the likelihood of conversion. This strategic focus on behavior highlights the importance of understanding and responding to customer actions in real time.

Steps to Implement a Data-driven Marketing Strategy

The marketing department is always a cost item for any company. The main task is to understand which part of the budget goes into the abyss and which part of the budget is correctly invested to help the company increase profits. Specifically, the data-driven approach helps evaluate which solutions work, test various hypotheses, and suggest useful product promotion insights.

To configure the data-driven approach, you have to go through the steps

Goal Setting.
Data collection.
Data processing and analysis.
Building the team from Diverse fields.
Using automation to improve the customer experience
Data usage (hypothesis testing).
Performance assessment.

Goal Setting

Start by defining clear objectives for the collection process. This foundational step is crucial as it influences every subsequent decision you make. Establishing a clear goal for utilizing data is essential, mirroring the strategic approach of successful companies highlighted earlier.

These objectives will direct which data to gather, the sources to explore, and the insights to extract. By setting these targets upfront, you ensure that every piece of data collected is aligned with your overarching goals, making your marketing efforts more focused and effective.

Data Collection

New touchpoints constantly appear between brands and buyers, both offline and online (mobile applications, social networks, etc.). New detailed information appears at each stage of the customer journey and allows marketers to create selling content for various audiences.

Collecting data can be compared with gathering grapes or apples — the more hands are engaged in collecting, the better. However, the ideal option is to set up automatic collection. To begin this process, you have to consider the following:

Define data sources
Set up data collection

Remember that the best approach is to collect data and check it for errors automatically. Thus, you receive the data you need in almost real-time and high quality. If you want to get all these in one service, you should try the OWOX BI Pipeline to collect, clean, and merge raw unsampled data.

Data Processing and Analysis

Gathering information is just the beginning. Now that you have your data from all the necessary sources (advertising services, CRM, website, and mobile applications), it must be processed and turned into something extraordinary. Grapes are taken to storage and processed into wine, and raw, unsampled data is collected in one data storage and analyzed.

We recommend cloud data storage, particularly Google BigQuery. All marketers use Google products, so it’s logical to use one that is part of the infrastructure and has native service integrations. Also, BigQuery has plenty of other advantages – no additional burden on the company’s servers, data protection according to Google standards, control over access to data, and much more.

Two things are extremely important for the marketing department:

Obtain analyzed qualitative data to get valuable insights
Avoid complicated technical solutions

The first point is understandable — the data should work for you, and with the help of high-quality data, you can build reports to improve work efficiency.

As for the second one — the more data, the more complex the system becomes, the more difficult it is to see and correct the error. To service various systems and services may require significant resources and different specialists. An ideal scenario is a platform or service that provides everything you need: processes data, builds reports, etc.

Building the Team from Diverse Fields

Based on your objectives, assembling a dedicated team becomes essential for analyzing and leveraging the data effectively. This might involve either strengthening your in-house capabilities or seeking external expertise. The choice between developing internal resources or partnering with external professionals should align with your specific goals and the complexity of the data tasks at hand.

Ensuring you have the right mix of skills and resources is crucial for transforming data insights into actionable strategies that drive your project or company forward.

Enhance Customer Experience Through Automation

Utilize the insights gained from data analysis through data-driven marketing automation to tailor the customer experience more closely to individual preferences. The deeper your understanding of your customers, the better you can meet their expectations regarding products, shopping experiences, and promotions. Achieving the finest results requires adjusting the shopping journey to cater to each customer's unique needs and desires.

As your collection of data expands, integrating marketing automation technologies becomes increasingly vital. For optimal outcomes, employ marketing automation tools capable of processing large volumes of data swiftly. These tools are essential for analyzing complex datasets effectively and efficiently, enabling you to make informed decisions quickly.

Data Usage (hypothesis testing)

After processing and analyzing the data, the next step is using the information received to change and/or improve the marketing strategy. With the help of data, the marketer becomes aware of where most of the traffic comes from, which channels and campaigns work best, and where the funnel’s narrowest part is located. Most importantly, through data tracking and analysis, a marketer can test various hypotheses to improve conversion and increase income.

Examples of hypothesis testing include:

Improving segments by the probability of conversion, profitability, behavior, etc., and bid adjustments.
Promoting products that may interest a particular customer.
Send automatic emails according to triggers as a result of certain customer actions on the website or in the mobile application.

Performance Assessment

The goal of any business is to generate income and maintain constant growth. Of course, evaluating the company’s performance requires constant monitoring. And without quality data and regular reports, it cannot be done properly.

It’s important to note that performance assessment depends on the company’s goals and, which parameters are key factors. The most convenient way to track changes in these metrics is by using automated dashboards. In this case, you can clearly see how successfully the sales plan is being implemented and quickly adapt your marketing strategy if necessary.

Among the most important KPIs for tracking in marketing are:

Profitability (ROI, conversion rate, etc.)
Website performance (traffic, sessions, etc.)
Traffic quality (trial and demo registrations, sign-ups and downloads, etc.)
Customer satisfaction and loyalty (CTR, bounce rate, etc.)
Brand awareness (impressions, mentions on social media, etc.)

If you want to boost your data-driven marketing and devote more time and effort to optimizing advertising campaigns, finding growth zones, and testing hypotheses, then you should use services that can help you save time and money resources. For example, you can use the OWOX service to analyze the effectiveness of campaigns from Google Ads, Facebook, and other advertising services on the same dashboard.

Popular Data-driven Marketing Tools

Choosing the right tool for work is extremely important, since it’s with their help that marketers can successfully fulfill their duties. Today, the market offers a growing variety of services that can be used for different tasks, such as data collection, merging, processing, and analysis, not to forget data visualization as well.

The first thing you should not forget about when choosing marketing tools is how appropriate and suitable they are for business. You should consider both the stages of development of your business (startup, medium-sized business, or large corporation) and the niche in which your business operates.

Criteria by which you can rate how appropriate a particular service is for business include:

Integrations: To build a functioning ecosystem, you must first ensure that all your tools can work in the same infrastructure. In other words, the more connectors, the better.
Data collection and processing: The ideal service tracks data quality, reports errors, and automatically merges, transfers, and updates data.
Limitations: To avoid unpleasant surprises in the future, don’t forget to check the services’ documentation for any restrictions.
Cost: Compare the prices and functionality of different services to make sure you choose the best one.

Let’s sort the most popular marketing tools according to two main work stages:

Data Collection and Analysis

Data collection and analysis tools are essential in today's data-driven landscape, enabling businesses to gather, process, and interpret vast amounts of information to inform strategic decisions.

Google Analytics 4: A cornerstone for digital marketers, Google Analytics 4 offers comprehensive insights into website traffic, user behavior, and conversion metrics. Popular for its depth of collection and analysis capabilities, it helps marketers understand audience interactions and optimize their digital presence accordingly.
OWOX BI: OWOX BI specializes in marketing analytics, enabling users to consolidate data from various sources into a single repository. It's known for its ability to facilitate complex data analysis, helping businesses make informed decisions by providing detailed insights into marketing performance across channels.
Funnel.io: Funnel.io automates data collection from over 500 sources and integrates with analytics tools, making it a go-to for marketers seeking to streamline their data workflows. It simplifies the process of analyzing marketing spend and performance, offering clear insights that drive strategic decisions.
Improvado: Improvado is a marketing data aggregation tool that excels in collecting data from multiple platforms and presenting it in a unified dashboard. It enables marketers to view and analyze performance across channels without the need for manual data processing, enhancing efficiency and insight accuracy.
Stitch: Stitch focuses on data integration, offering a simple platform to consolidate marketing data from various sources into a single data warehouse. Its ease of use and scalability make it popular among businesses looking to build a centralized data infrastructure for analysis and reporting.
Supermetrics: Supermetrics is renowned for its ability to pull data from a wide range of marketing platforms directly into analytics, spreadsheets, and data visualization tools. It streamlines the data collection process, allowing for efficient analysis and reporting, making it a favorite for data-driven marketers.
CRM Systems (e.g., Salesforce, HubSpot, Oracle): CRM systems like Salesforce, HubSpot, and Oracle are pivotal in managing customer relationships, offering robust tools for data collection, customer segmentation, and personalized marketing. They are essential for businesses focused on tailoring their marketing efforts and improving customer engagement based on data insights.
SEMrush: SEMrush is a powerful tool for SEO and digital marketing analytics, offering insights into keywords, competitor analysis, and website performance. Its comprehensive data collection and analysis capabilities support marketers in optimizing their online visibility and content strategies.
Kissmetrics: Kissmetrics provides behavioral analytics and segmentation tools that help marketers understand how users interact with their websites and products. It's particularly valued for its focus on conversion optimization and customer engagement through data-driven insights.
Weborama: Weborama offers advanced data management and digital analytics solutions, specializing in audience segmentation and targeted advertising. It's recognized for its ability to leverage big data for precise marketing personalization and effectiveness measurement.
Datorama: A Salesforce company, Datorama excels in marketing intelligence by integrating and harmonizing data from diverse sources, providing actionable insights through AI-driven analytics. It's popular among marketers for its comprehensive dashboard and reporting capabilities, enabling optimized campaign performance analysis.
AppsFlyer: AppsFlyer specializes in mobile attribution and marketing analytics, helping businesses measure and optimize their mobile campaigns. Its robust data collection and analysis tools are crucial for app developers and marketers focused on understanding app performance and user engagement.
Adobe Analytics: Adobe Analytics offers deep insights into customer journeys across digital touchpoints, leveraging advanced segmentation and real-time analytics. It's highly regarded for its detailed analysis capabilities, empowering businesses to create personalized, data-driven marketing strategies.

Data Visualization Tools

Data visualization tools transform complex data sets into graphical representations, enhancing comprehension and enabling insightful analysis for informed decision-making.

Looker Studio (formerly Google Data Studio): Now part of the Google Cloud suite, Looker Studio offers intuitive data visualization and reporting capabilities. It allows users to turn their data into customizable dashboards and reports for easy analysis, making insights accessible across organizations with seamless integration with Google and other data sources.
Tableau: A leading tool in data visualization, Tableau excels at transforming complex data sets into interactive and understandable visual representations. It supports data-driven decision-making with its robust analytics platform, catering to businesses of all sizes across various industries.
Smart Data: While not as widely recognized by a specific product name, smart data tools generally refer to solutions that apply AI and machine learning to transform raw data into actionable insights. These tools focus on enhancing data quality and relevance for more effective decision-making processes.
Power BI: Microsoft's Power BI is a business analytics tool offering comprehensive data analysis and visualization. It allows users to create dashboards, generate reports, and publish insights from data, facilitating a deep understanding of business metrics and trends across various departments.
Qlik: Qlik offers a suite of data analytics tools with a focus on user-driven business intelligence. Its associative model helps users discover data relationships across multiple sources, promoting intuitive exploration and insights without predefined queries.

Useful Links

Key Takeaways

The best and most effective way to make all marketing processes efficient and performance-oriented is to use data-driven marketing. With data-driven marketing, you can improve dialogue and interaction with your customers.

Also, don’t forget that to achieve this, companies should use high-quality, verified data to improve their decisions. Moreover, for ease of work, collect it in one place, for example, cloud data storage. Thus, the data will be available to all employees, no matter where they are. If you don’t know where to start — sign up for a demo meeting with our specialists!