Data-Driven Marketing – Developing data-driven marketing strategy
Data-driven marketing refers to strategies built based on insights collected through interactions with consumers to develop future behavior predictions.
It involves understanding what data a business owns and how to organize, analyze, and apply it to minimize marketing spend.
By having large volumes of data, marketers can take that information and analyze it to make decisions based on that previous analysis.
However, Decisions backed by large amounts of data allow companies to anticipate needs, mitigate risk, offer more relevant products and personalized services.
Role of data-driven marketing in decision making
- Today’s marketing leaders know that data-driven insights have become the long-awaited holy grail.
The importance of relying on robustness of customer data is increasingly recognized.
- But according to a recent Google study, less than 40 percent of marketers conduct consumer research to make decisions.
- Basically, Big data is more accessible than ever. Data has become a crucial technology tool for many companies.
- For marketers, data has the power to make marketing campaigns have that much more impact.
Data-driven marketing strategy
- Successful brands must use customer data to make marketing decisions.
- Ans also, Marketers must have a robust data-driven marketing strategy to ensure that they take advantage of the changes to meet customer needs.
1. Customer interaction strategy
- Firstly, understand the buyer journey, from the first contact to the end, through purchase and post-sale relationships.
- Secondly, identify the changes that may occur in your company through systems and data to transform and deliver a consumer engagement plan.
- Lastly, remember that your goal is to produce a consistent customer-concentric journey from multichannel.
2. Analytics strategy
- The three main categories of analytics are business analytics, predictive analytics, and prescriptive analytics.
- Since data and technology will drive analytics, you need to determine where your business currently stands.
- However, you must also determine what kind of analytics must compete in the age of digital transformation.
3. Data strategy
- Data-driven marketing requires credible data, so developing a data strategy that encompasses an entire company is critical.
- However, for your data strategy to be actionable, you must permeate the business through a partnership between IT, marketing, and other essential business functions.
4. Data-driven performance strategy
- Data-driven marketing is a discipline for acquiring, analyzing, and applying all information about customer and consumer wants, needs, motivations, and behaviors.
- However, establishing a data-driven culture is, therefore, a matter of data. You have to allow all your teams to have the necessary information and benefit their activities.
- Let us add that, another critical point in setting up a data-oriented organization is making data and its analysis easily accessible.
- Therefore, a data-driven company is an organization where all employees, whatever their skill level, have access to data and are autonomous in their operations.
Developing data-driven marketing strategy in a few steps
To guide you, here are the essential steps in setting up a data-driven strategy.
1. Identify your data
- Take all the data you have. All sales and transaction data, navigation data, operational data, machine logs, customer loyalty data, etc. can be used.
- And also, assess the history you have in your databases. This history will allow you to set up learning models on your data.
- You can set up predictive analyzes and predict, for example, the maintenance needs of your machines or predict the storage needs of your new product.
- Let us add that, every company has a lot of data that serves a data-driven organization.
2. Bring the experts together
- After identifying your data, bring together your company’s different departments and map all the additional data.
- However, Business experts and analysts are familiar with their business issues and their Customer data, logistics data, factory data.
- It is, therefore, necessary to identify all the data potential upstream.
3. Identify the external data that would allow you to enrich your current data
- There are many open data sites like Weather data, road traffic data, and demographic data to provide you with crucial data to enhance your analysis.
- However, You can correlate the attendance of your shops with the outside temperature. You can integrate this variable in the analysis and prediction of your stock.
4. Clean Database
- Your data to make it usable. A clean and harmonized database will speed up the availability of your analyzes.
- Software which includes advanced features for cleaning and preparing your data will make your job easier.
- This step is an essential step to be able to analyze your data.
5. Determine what you want to know
- When you are beginning, it may be interesting to look for a guideline for your analysis. Think about all of the unanswered questions so far and identify the data that might provide you with answers.
- However, this step is not mandatory because your data can also reveal lessons you did not anticipate.
6. Arm yourself with modern technologies
- The digital revolution we are living is a data revolution. Big Data and Artificial Intelligence are essential technologies to become data-driven.
- In addition, you don’t have to be a Data Scientist or have development and statistical skills to benefit from the uses of Data Science.
- However, Big Data and Artificial Intelligence technologies are a real advantage for your business because they allow you to predict and anticipate events.
- Let us add that, One of the characteristics of data-driven companies is their ability to instill a culture of data at all company levels.
- So make sure you have modern tools and involve business experts and operational staff as much as possible in your company’s digital transformation.
- However, Data analysis is no longer the prerogative of experts, thanks to the emergence of new analytical tools.
7. Make the data available
- We cannot repeat it enough: to become data-driven, all company skill levels must have access to the data and use it operationally.
- However, to make data analysis write for us accessible to your organization’s skills, you can rely on the automation of models and their translation into a dashboard.
8. Put data in your decision-making processes
- Being data-driven will allow you to explore all the treasures hidden within your databases. Harness insights and turn them into decisions that accelerate your business.
9. Test, learn and approve
- By introducing a data-driven culture in your organization, you will become agile.
- The insights you discover allow you to enter the virtuous circle of test and learn, optimize, and improve your methods, targeting, and performance.
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