Did you know that 40 % of organizations aimed to increase data-driven marketing budgets in the coming year?
And it makes a lot of sense. Data-driven marketing presents some of the most explicit advantages for businesses, such as:
But before we learn how to run data-driven campaigns and achieve these jaw-dropping benefits effectively, let's understand what data-driven campaigns are.
Data-driven marketing campaigns are defined as marketing campaigns that use detailed customer data to make accurate predictions about customer behavior and use it further to optimize the campaign's performance.
Over 64% of global marketing leaders agree that data-driven strategies are vital in today's economy. So this article will explore four effective strategies to run data-driven marketing campaigns.
Demographic data is an undermined source of information and an excellent strategy to run data-driven campaigns for marketers. Demographic data of your customers, such as age, gender, income, and relationship status, open a pool of opportunities for you to run intentional, intelligent, and effective campaigns.
Let's take age as an example. After analyzing your demographic customer data, you realize that 75% of your key target audience belongs to the millennial generation. This helps you understand their interests, likes, dislikes, habits, opinions, relatable factors, and catchphrases!
Getting critical insights into the customers' psyche helps you build a more relevant and personalized campaign. You can use the data to:
Knowing the demographic data of your target audience is an excellent strategy for social media campaigns. Social media platforms such as Facebook, LinkedIn, and Instagram allow you to build a campaign audience using such data. This makes your campaigns more specific, targeted, and destined to get better results.
Another great strategy to run data-driven campaigns is to use data from different marketing channels - using data from social media to drive email campaigns, website data to create podcast campaigns, etc.
Every marketing channel has a distinct collection of data based on its features. The email marketing channel gives you insights into a customer's working hours and business priorities. The social media channel gives you insights into the interests and preferences of customers beyond their work. The website provides you with insights into the online behavior of customers.
You can hone your campaign design, messaging, and content using data from different channels.
For example, your social media campaign data shows that most of your target audience is interested in an upcoming music event. So, you plan an email campaign for these prospects and offer a few free tickets to the music event. This campaign is bound to get you a lot more traction than other campaigns since the event catches the attention of your prospects.
A/B tests are a great way to run data-driven marketing campaigns. A/B tests are run to test the performance of an element in your campaign.
For instance, you like two different subject lines for an email campaign. Instead of assuming which one will perform better, you use A/B testing to determine the winner. In this case, your email tool will randomly send the email to the sample database with both subject lines. The subject line with more opens is the clear winner, and now you can use it for the rest of your database.
A/B testing is a technique that collects information through the testing and then gives you accurate estimates for you to run data-driven campaigns. Use A/B testing in your marketing campaigns such as social media, web pages, advertisements, and content marketing to make them more effective.
This is one of the most important and yet underrated strategies to put in place for running data-driven marketing campaigns.
If you have been running data-driven campaigns for a while now and still not seeing results, there are chances that your data is not entirely accurate.
For example, your social media campaigns are planned based on your collective analytics data, but they are not converting as expected. This means you rectify your data collection tools and check for any inefficiencies in the tool or the process. To audit your data collection and analytics process, you must assign time, effort, and resources.
Here is a method you can use to improve your data collection and analytics process:
If you have been doing data analytics and collection for a long time, the chances are that there are a lot of gaps you need to fix.
So first things first, sit down with your team and analyze every detail of your current process. Understand the different sources from where your data is collected.
This helps you discover your current process clearly, so you can work on improving it.
You have now discovered the exact process your team follows. After realizing the inefficiencies in this process, you can start putting together a process that optimizes your workflows.
It can be better tracking codes, effective visualization reports, brainstorming insights, and communication of the data correctly within your team.
Upgrade your data analytics process to focus on the end result - more campaign conversions.
The next step is to align your existing or new platforms to support the improved data collection and analytics process. Redefine your marketing analytics platform, change your cookie policies, or build a new workflow for data modeling.
After fixing your process gaps and systems, build detailed documentation of the improved and enhanced processes. This acts as your go-to guide for future process references in case of training, re-assessments, and changes in the team. We know it is boring, but it is necessary!
I know this is a mundane process that requires more time and resources than you already have. But that should not stop you from building better data for your data-driven campaigns.
At Processology, work with teams like you to give your processes intentional direction to accomplish intended results. Talk to our expert Processologists to streamline your data analytics process.