5 Principles of Data-Driven Marketing

by Jones David

For many, the transition to data-driven marketing is often unclear and therefore lengthy. What are the principles to be followed in this transition?

1. Data is a strategically important resource.

In fact, data is a raw material for decision-making. The purity, reliability, freshness, and quality of data for any marketer are crucial in choosing sources and tools for information management. There can be nothing worse than building an entire advertising campaign based on false data.

Given the importance of “right” data for business, try to structure marketing processes so that they work for you. To do this, you need to create a clear system for managing key constants.

Okay, checklist:

Do you know where your data comes from and where it is stored?

Are you sure that the data collected is clean and accurate?

Do you have a business glossary of basic data terms so that every employee can understand what is going on? — Magento advanced reports may help you

2. Build a strong team to handle the data.

Don’t be afraid to involve extra specialists. The truth is, you can’t do it quickly on your own. Ask for help from qualified workers who have been working on data issues for years. Thus, you expand your opportunities in the market and significantly save time and money.

Form teams to solve problems in different areas – from communication with clients to audience segmentation.


Have you already hired a data science manager?

How well have your operating teams been selected? Can they create a consistent model to track all marketing costs?

Can your teams make informed decisions based on the data?

3. Build a database for data storage.

Data will flow to you from all communication channels – network, email, mobile devices, different data platforms. Sooner or later, you will need a single system of information organization, with which you can get the right data at any time.

Three steps to organizing a data warehouse:

Find all relevant information.

Systematize it into the proper format.

Upload the received data to the storage system.

The third step can be interpreted differently. You can form either an EDW (enterprise data warehouse) or a data lake.


Do you know where your data is stored?

Have you already started integrating different data platforms into one?

Do you have a system to store your data? What is its size and what data formats can it store?

Discuss the feasibility of switching to a data lake for your company.

4. Connect all data sources into one system.

Fragmentation of user data is one of the major jungles. The point is that the information is collected by different platforms, from different sources, and in different formats. This affects the degree of brand identification of the user. In order to determine whether the same person bought a product from you and then called the support team with a comment on the service, apply the practice of “mastering the data”. In this case, a master record is created (a record about the client), with which you can identify this person at any stage of the user’s path.


How many platforms do you have working on data collection?

Can you build a business case for master data management?

5. Clearly define your operational leverage.

The revenue generation mechanism is based on modeling and tracking the consumer’s path – from getting to know the brand to re-purchasing.

To begin with, it is important to identify the key steps in the consumer’s journey. What makes a potential customer become real? Track the level of interaction with the brand at each stage, evaluate it and make conclusions, improvements, and changes. In this way, you can identify the working levers of influence on the consumer.


Do you track the key leverage that leads to revenue generation?

How confident are you of the accuracy and timeliness of the data collected in the user’s path?

Can you confidently predict the level of revenue from the cost of a particular communication channel with the user?

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