Data-Driven Marketing: 4 Key Steps To Improve It

Data Driven Marketing

Patrick Singer creates and publishes practical experiments that enable marketers to develop digital marketing and increase ROI. In this article, Patrick shares his insights on building a good foundation for managing data-driven marketing operations.

Leading digital marketers are using consumer data and digital tools to achieve accurate results in new and thoughtful ways.

To get you down to business as soon as possible. Here are four ways to start devising the best short- and long-term data-driven strategy.

1. Establish A Robust Database

Marketing data is spread across many sites, from the ad server or the search bidding tool to the data management platform or media platforms such as YouTube or Facebook. To simplify such a fragmented environment, all sources must be consolidated in one place, such as a web analytics tool. Unifying data sources makes it easier to identify campaign performance trends or user behavior. Allowing for more efficient and effective decisions.

Look at indicators of success beyond the classics, such as units sold, also consider all the beneficial interactions of the website and the application that add value to the company. Next, consider each of those interactions from an economic point of view and assess the full impact on your business.

Example: If a customer solves a problem using the FAQ section instead of contacting an advisor, how much money does the company save? Considering both the duration of calls, emails, instant messages, and the related costs, you can assign a value to user visits to the Frequently Asked Questions section. Taking all of these interactions into consideration will allow you to determine all website and application resources’ total value.

2. Use Automation To Save Time

If data-driven digital marketing is not automated, its effectiveness is limited. The speed and efficiency that automation brings are essential in everything from finding valuable audiences to enabling role deployment.

For example, automating bids in real-time allows you to adjust them on the fly, which is immensely valuable in marketing activities and often achieves incredible results. Automating workflows enables teams to stop wasting time on repetitive tasks and spend time deciding their strategy and moving forward.

3. Create Audience Segments

By creating audience segments, you can start publishing content geared towards the needs of each part. One of the ways to build features is to divide your audience into “leads,” “qualified leads,” and “current customers.” Then, consider each segment’s needs and the role it plays in your marketing strategy. Details can be further subdivided, for example, separating “current customers” into one-time shoppers and repeat customers.

Audience segments can be created using three types of data sources: platform data (such as search queries), third-party data (such as weather information intended for insurance companies), and proprietary data (such as data from a CRM, from the website, or apps).

4. Interpret Complicated Customer Journeys

Understanding the relationship between the different touchpoints of your brand is essential to creating an effective attribution model. For example, if a customer views one of your ads on mobile and later purchases on your website from their laptop, you need to match the actions and attribute the asset to the mobile phone ad.

Customer journeys can be even more complex, spanning weeks, going through various devices and including purchases in brick-and-mortar stores. By identifying how these touchpoints interact. You can use the information to invest in the most valuable channels or make automatic bidding strategies even brighter.

Conclusion

Data-driven marketing is about using the information to inform actions. Think about how you can apply these first four rules to your marketing strategy and develop a roadmap. Choose who is in charge of each task, set a calendar, and see yourself achieving quick victories to demonstrate to interested people with more experience than data-based marketing brings a clear added value to the company.