What is data-driven marketing in 2023?

Data-driven marketing is the method that optimizes message-media mix based on several data points. Marketer leverage to understand the following:

  • What are the needs of the customers? What customer problem does their product solve?
  • How can the product solve it? How do they frame the message, and through what media mix reach out to the customer?
  • When to communicate?
  • Where to communicate?
  • Why should customers believe their message?


“2023 is about data-driven approaches in digital marketing. And, if you still underestimate marketing attribution importance, read this post.”


Any seasoned marketer would recognize the above as 4 or 6 or 8 Ps of marketing. It is equally applicable to traditional marketing as well.


What is data-driven marketing?

Data-driven marketing is an approach to marketing that utilizes data and analytics to make informed decisions about targeting, messaging, and optimizing campaigns. It involves collecting, analyzing, and interpreting various types of data related to consumer behavior, preferences, and interactions with a brand or product.

If you were to scrutiny a data-driven marketing approach with that of a few years ago, you’ll probably be amazed that things have been replaced. From tracking visits per page, bounce rates, and cost per click, today companies have grown to masticate tons of complicated data. Although for many, the goal is to endeavor customers. The actual possible data-driven marketing can also help meet another purpose.

If we were to select the top three objectives of data-driven marketing, we’d look for:

  1. Exposing the customer journey and where Purchasers locate at any point in time.
  2. Mapping and scaling marketing ROI.
  3. Coordinating the marketing and sales teams.


Digital marketing today is all about data and analytics. And, the ability to properly track consumers behaviours and analyze data will drive marketing performance.


How is data-driven marketing different from traditional marketing?

Traditional marketing too relied on gaining an understanding of the customer needs and problems. The only difference lies in the sources traditional marketers used and the depth of understanding those provided. 

Until the dawn of digital marketing, market research studies were the only source of data. Marketers used it in combination with a healthy dose of assumption. Understandably, this was a trial and error method, which had its fair share of hits and misses. Consequently, the process was neither cost-effective nor efficient all the time.


Digital marketing helps fix the inefficiencies of traditional marketing at two levels:

  1. Campaign planning
  2. Measuring impact

At the campaign planning level, digital platforms and ad networks like Google Ads, Facebook Ads, and others provide insight into consumer behavior and segments. 

Using a combination of consumer personas and segment sizes, marketers can target the right audience with a relevant message-media mix.

Once you run the campaign, you can also track the impact on various parameters. For instance, if you are running a brand awareness campaign, your brand-related searches go up. If you are running a sales campaign, your product sales improve. Numerous tools help you track the improvement on your baseline.


Read Also: What is Data-Driven Attribution and Why it Matters More Than Ever



Advantages of data-driven marketing

Data-driven marketing is the order of the day because of the advantages it offers. Following are its most common benefits:


1. You get to know more about your consumers

Even as you start with a hypothesis about your audience, data-driven marketing helps you validate it. Suppose you hypothesize that your customers are price sensitive, you can run a test where the control group sees no price change, but the test group gets a considerable discount. If the test group shows significantly better traction, with everything else constant, your hypothesis is valid. If not, you can reject it. You can have the results within a week without having repercussions on the brand value.

2. Helps you personalize messaging and connect with your customers better

Knowing customer needs and understanding their stage of the journey helps you personalize and time the message better. 


3. You can choose and focus on a few channels

In traditional marketing, most small and mid-size companies find marketing channels cost prohibitively expensive. Not knowing whether a channel works for them makes media purchase decisions more difficult. 

Data-driven marketing helps reduce these uncertainties. Marketers can start with a few channels, and they can continue to focus on one work. Say, if you are not sure whether Google Display Ads or Facebook Ads work best for your consumer brand, you can start with equal spending on both. Once you have the data coming in, you would know which ones are working better for you. You can distribute your budget accordingly.



What are the challenges in Data-driven marketing?

If your organization is new to data-driven marketing, you will find challenges at three levels.


1. Collecting data scattered at various levels and locations

Collecting data and deciding what’s relevant is the number one problem for most businesses. It might be distributed across sales channels, the marketing department, and the customer support team. The C-suite could have some of it. 

Moreover, most of this data would be in an unstructured form such as pdf, social media comments, call recordings, and so on. Collecting all of it and structuring it takes time and effort.


2. Single-point view of all data

Marketers often find it difficult to pull and compare data from various sources. It gets more challenging when you are running a big-budget multi-channel marketing campaign. Each of the platforms would have different names for the metrics. A few may use varied calculated fields too. That’s where Windsor.ai comes in.

Windsor.ai connectors help integrate multiple data sources into a BI tool of your choice – Looker Studio, Power BI, Tableau – you name it. It also provides you with customizable templates to track metrics relevant to your business.


3. Building a team and data-driven culture

The culture of a company often decides whether a positive change sustains. As you move to become a data-driven company, overcoming the hunch or intuition-based decision-making processed would be a challenge.

With the right set of tools, like Windsor.ai, you can bring transparency into the system to accelerate the transition.


Try Windsor.ai today

Access all your data from your favorite sources in one place.
Get started for free with a 30 - day trial.

Start Free Trial


3 Stages in transitioning to data driven marketing

The stages can roughly be categorised in

  1. Non-data driven marketing and decisions
  2. Awareness and transitioning phase
  3. Data driven marketing decisions and experiments

Where a company is depends a lot on the industry, how important marketing is for the company and multiple other factors. E-commerce and online travel tends to be more in stage 2 and 3 where-as some more traditional industries are more in stage 1. Some industries can be very heterogenous. Financial services is a an example of an industry with companies in all different stages. Some of the smaller companies are in stage 3 running a very effective marketing machine. Some of the incumbents still doing things the way they have always been done.

Characteristic for the different phases.


Stage 1: Non-data driven marketing and decisions

In this phase the company is continuing to operate the way it has been operating before. Characteristics for this phase is:

  • The company relies on agencies and uses metrics the agencies are providing them with. The company does not really have well defined KPI’s or its own independent source of data for  of the KPI’s. The agency can pick out numbers to highlight its own performance.


The result here is that the company is reliant on the reports its given by the agency but cannot really verify them and cannot steer or control its own KPI’s. Decisions therefore are not really done on numbers but more on how things have been done before and more based on internal relationships and feelings.


Stage 2: Awareness and transitioning phase

The catalyst to start the move towards a data-driven approach usually comes from external business pressure. It can be that the profit margins are eroding or the industry is going trough change which puts pressure on the company. A new competitor might have entered the space which forces everyone to up their game.

The transition in our experience is fastest if at the same time new marketing directors are brought in. They are not used to the old ways of doing things, not bound to the old relationships and can question everything.


Characteristic for this phase is:

  • Numbers are given more attention, however numbers are still looked at in isolation in every platform separately. This leads to double-counting conversions and other issues like misalignment. However the awareness of data and numbers start to be there. There are much more discussions around metrics and KPI’s.
  • Some teams might still look at vanity-metrics and easy-to-fake-metrics like impressions, clicks etc. But there is anyways now more discussion about the numbers and data. Teams might still look at entirely different KPI’s, eg. social team looks at impressions and search-team at revenue generated.
  • There is not yet a full helicopter view of all marketing channel performance and spend. The realisation that all teams need to work towards the same KPI’s starts to be there.
  • In this phase also work towards improving the data-pipelines and infrastructure is done. For example Cognita Group went through connecting the marketing channels, analytics and CRM.


Some organisational tension might arise in this phase as teams that have not been measured before on numbers start to be measured. These teams or agencies naturally shun transparency. It is important to not let these tensions derail the process as it otherwise might hurt the entire organisation. Discussion about data and metrics is always good to have so that the company and teams can agree on the metrics they want to work with.


Stage 3: Data driven marketing decisions and growth experiments

Some e-commerce companies are in this phase and online travel. Every campaign is run as an experiment, it has an expected impact and it is being measured. Results are being measured and discussed.

Ebay is the company I have seen with the most advanced infrastructure and culture for testing and experiments. All campaigns and experiments are automatically created and measured. The audiences are automatically randomly selected. There is lots of discussion around the metrics, the results and the cause-impact relationships as there always is. But its centered around KPI’s, experiments data and results.


This phase is characterised by:

  • The company has independent data-source for numbers and can control the metrics and KPI’s themselves.
  • There is one view of the KPI’s, performance and spend
  • Usually there starts to be expertise in-house that know both the business domain and the marketing data better than an external ever could.



Incorporating data-driven marketing into a marketing strategy is crucial for businesses looking to make informed decisions, engage their target audience effectively, and ultimately drive higher levels of success and customer satisfaction.


Windsor.ai gives a better way to integrate your data for analysis, visualization, and reporting. With Widsor.ai, you’ll get:

Interestingly, Windsor.ai is very easy to use and does not require you to code. It also has a 30-day free trial.

However, if you are not yet with us, book a free demo today, to see the power of Windsor for improving your Marketing Performance and ROI.


Try Windsor.ai today

Access all your data from your favorite sources in one place.
Get started for free with a 30 - day trial.

Start Free Trial



What is meant by data-driven marketing?

Data-driven marketing refers to the practice of making marketing decisions based on data analysis and insights, rather than relying solely on intuition or assumptions. This approach is about delivering value to customers based on their preferences and behaviors, fostering loyalty and driving business success.


What are benefits in data-driven marketing?

You’ve provided a comprehensive list of benefits associated with data-driven marketing. Here’s a summary:

  1. Budget Allocation: Enables more effective allocation of advertising budget by identifying which strategies yield higher returns on investment.
  2. Understanding Buyer’s Journey: Provides insights into user behavior, helping to optimize landing pages and calls to action to improve conversion rates.
  3. Audience Analysis: Allows for a deeper understanding of a diverse customer base, enabling the prediction of behavior and the creation of tailored selling scenarios.
  4. Relevant Offers: Facilitates the segmentation of users for targeted messaging, leveraging previous experiences to create campaigns that resonate with specific groups.
  5. Improved User Experience: Identifies and addresses pain points in the customer journey, leading to an enhanced overall user experience.
  6. Increased Sales: Enables the creation of targeted offers for different audience segments, resulting in more relevant marketing campaigns and ultimately higher sales.


Why Data-Driven Marketing Should Be Part of Your Marketing Strategy?

Here’s a breakdown:

  1. Informed Decision-Making: Data-driven marketing is based on real-world data, providing concrete information to guide marketing decisions, as opposed to relying on assumptions or theories.
  2. Targeted Engagement and Higher Conversion Rates: By leveraging data, marketers can create highly targeted campaigns that are more likely to resonate with specific audience segments. This leads to higher conversion rates as the messaging is more relevant to the recipients.
  3. Precise Audience Targeting: Data-driven marketing enables businesses to identify and target the right audience with the right content or offer, capturing their attention and providing them with what they need at the most opportune moments.
  4. Comprehensive Customer Understanding: It empowers businesses to have a thorough understanding of consumer behavior, from initial interaction with the brand to the final purchase. This knowledge helps in tailoring marketing efforts to meet customer preferences and needs effectively.


What are the data-driven marketing trends in 2023?

Content is still a King. Content creation is still the main SEO approach to reach your audience. 

The future is AI. Marketers will use AI in software products and services to analyze consumer behaviour and search patterns, using data from different sources. 

Influencer marketing. Influencers help brands get noticed or skyrocket thanks to a word-of-mouth approach. And, in 2023 this trend will just increase.

Voice searches and smart speakers. Due to increasing usage of voice speakers like Alexa, marketers need to put smart speakers ‘on the map’ of their marketing strategy. 

AR and VR to stand out. These tools will be more useful for marketers, especially for retailers and e-commerce, engaging its users more innovatively. 

Marketing technology tools. Marketers will use more software and digital tools to boost marketing efforts, automatize the process, and track data.

Marketing attribution will take precedence. As you can see from the list of digital marketing trends, there are many of them, and most of the marketers will use. This means that they need to track all marketing actions and customer journey using marketing attribution tools.