The Ultimate Guide to Data-driven Marketing Strategy Development
Data-driven marketing is a set of tactics and techniques that make extensive use of data obtained through customer interactions. Let us explore what data-driven marketing is and how you can develop a data-driven marketing strategy for your company. We recommend exploring and following the five steps detailed in our article for your data-driven marketing strategy as well as investing in marketing technology that will increase your efficiency and ensure that you reach the right buyers.
What is data-driven marketing?
To summarize, Data-driven marketing is a set of tactics and techniques that make extensive use of data obtained through customer interactions. This data enables them to develop effective marketing plans by better understanding customer behaviors, preferences, and purchase motives.
This valuable data is critical for all types of businesses because it helps them improve their marketing strategy and customer experience, resulting in increased revenue. Marketing professionals can predict their customers’ goals and future actions using customer data, allowing them to develop personalized data-driven marketing strategies with the highest ROI.
How to develop a data-driven marketing strategy?
Even in the absence of external factors such as a global pandemic or innovative technology, customer purchasing habits are constantly changing. While some marketers become frustrated with these changes and return to mass marketing techniques. Businesses that stick with their data-driven marketing strategy often can see double-digit increases in sales.
To develop a data-driven marketing strategy for your company. Follow the below steps and invest in marketing technology that will increase your efficiency and ensure you reach the right buyers.
- Collect and centralize information about current customers
- Look for trends and patterns in the data
- Divide your target audience into groups
- Create distinct marketing campaigns for each target demographic
- Data-Driven Marketing Relies on Real-Time Insights
Let us have a detailed look on each point to know how it works.
Collect and centralize information about current customers:
Because you have already succeeded with them, your current customers are one of the best sources of information about how to convert future customers. Gather as much information about them as you can, including demographics, location information, and the steps they took during their purchasing process. Web analytics software and customer surveys can assist you in gathering this data.
With the rise of cloud applications, you may have client information stored in multiple locations. To best understand and use the data you have, you must first centralize it.
Look for trends and patterns in the data:
Once the data has been collected and centralized, it can be analyzed for trends and patterns. For example, Is one of your products more popular in the southeast than in other areas? Before making a purchase, most of your customers will read articles and information to help them determine what product is suitable for them.
You can improve your marketing campaigns and encourage those patterns in potential customers as you identify buying patterns in your current customers.
Artificial intelligence (AI) can help you spot patterns and correlations that you might have missed otherwise. It can analyze more data in less time than human analysts. AI is used in many BI platforms to improve data insights.
However, even the best AI cannot replace human expertise. You need to ensure that you have experienced data scientists on staff to interpret the AI algorithms and validate the insights.
- Divide your target audience into groups:
As you learn more about your target audience, you will be able to categorize them. The groups you form will be determined by the trends discovered in your data analysis. You could make groups based on gender, location, or previous site behavior.
Many web analytics tools include predictive analytics to assist you in determining what actions potential customers are most likely to take. These are based on previous interactions with your brand. Google Analytics 4, for example, can even create groups based on these predictive metrics to assist you in encouraging leads to take the actions you desire.
To make this collaboration work, the entire marketing team must commit to investing in a data-driven strategy. It is not something that can be implemented overnight, so both leadership and individual contributors must be willing to put in the effort. While mass marketing is less time-consuming, it does not produce the same results as targeted marketing.
Create distinct marketing campaigns for each target demographic:
Once you have identified your customer groups, you will need to develop separate marketing campaigns for each one.
Because messages only resonate with a small portion of the audience, mass marketing is ineffective. However, by tailoring messages to each group, you can create more personalized campaigns that are more likely to resonate with a larger proportion of each group. It makes no sense, for example, to send an abandoned cart email to customers who have never added anything to their cart. Cart abandoners should be treated as a separate group so that you can encourage them to complete their purchase.
Data-driven marketing relies on real-time insights:
A successful data-driven marketing strategy is dependent on real-time insights to ensure you are working with the most up-to-date data. If a customer bought something last week but you just found out they visited the product page the week before. You will send them targeted messages that are not relevant to their current needs. Real-time data enables you to deliver the right message to the right customers at the right time.
The future of data-driven marketing looks promising. Data-driven solutions are becoming an important part of successful marketing campaigns with Artificial Intelligence marketing. This is heavily dependent on the growing needs and expectations of customers for more personalized experiences.
A data-driven marketing strategy is all about learning to love your failures. To a growth drudge, failure is a sign of progress; you are iterating towards success. Analytics and experimentation enable you to fail quickly, learn quickly, and improve quickly. You can now combine your learning with action to drive growth through data with the right marketing toolset.
Blog by: Hassan Ahmad
Image source: Shutterstock (1901819071)