Introduction
As a marketer, you’ve got two ways to create marketing strategies for your business. The first way is intuition-based. You go for some hunches, develop strategies around them, and then wait to see if they work or not. The second one involves data. You make informed business decisions based on accurate data findings, aka a data-driven marketing strategy. Which way would you choose? The latter one— like any savvy marketer would do, right? Businesses that leverage data-driven marketing strategies drive five to eight times as much ROI as businesses that don’t. This is why a whopping 40% of brands plan to increase their data-driven marketing budget.
In this article, we’ll explain everything you need to know about data-driven marketing and how to utilize it for your business.
What is Data-Driven Marketing?
A data-driven marketing strategy leverages data—harnessed through customer interactions and third parties. The data gathered helps better to understand customer motivations, preferences, and behaviors.
However, data-based marketing isn’t just about collecting and analyzing data. It requires interpreting that data and using it to extract meaningful insights that could help to make well-informed decisions leading to business growth.
It’s also crucial that you have the right data to be successful with your marketing efforts. This means carefully selecting the most relevant metrics for your business and then collecting, transforming, and analyzing those metrics regularly.
If you aren’t tracking the right metrics, then it will be impossible to know whether or not your efforts are paying off. After all, if they’re not paying off, you need to modify your strategy to get better results.
How’s Data-Driven Marketing Different From Traditional Marketing?
Any marketing strategy is focused primarily on two objectives. The first is to identify the needs and wants of ideal customer profiles. And then using that insight to fulfill the needs of the customers.
To put it in marketing terms, it means:
- To understand the target audience in-depth.
- Identifying and anticipating the issues or needs of the customers.
- Creating strategies to develop products to solve the issues or fulfill the needs.
Traditional marketing
In order to achieve these objectives, traditional marketing teams have only two resources-
- Available market studies.
- Assumptions about the target market.
Unfortunately, this approach requires a lot of trial and error. Before finding the right blend of strategies, companies would need to launch several strategies. This, in turn, leads to unnecessary loss of time and money.
Data-driven marketing
On the contrary, with data-driven marketing, businesses can make informed decisions, saving time and money in the long run. Moreover, this allows companies to connect to the customers at the right time with the right offer. They could target a specific audience, use personalization to improve customer experience, and acquire new customers in real-time. This means there’s no need to launch multiple campaigns just to identify the best marketing blend.
The Benefits of a Data-Driven Marketing Strategy
Reach the Right Audience
Data-driven marketing can determine who your ideal customer is and where they spend their time online. You can leverage this information and put your marketing effort in the right direction to reach the right people.
For example, a data-driven marketing strategy can help you reach out to people who have actively shown interest in your product. These people have higher chances of converting.
Identify the Right Channel and Create Relevant Content
Knowing your target audience and their interests are extremely helpful to provide them with a clear, relevant message. Thus, users can act on it, especially while they’re on the channels where they spend most of their time.
You can then use this data to create a content strategy that delivers the right message, on the right channel, at precisely the right time. This will help you get your message in front of potential customers who are most likely to convert.
Improve Customer Experience
Data-driven marketing campaigns provide customers with the exact information they need rather than bombarding them with irrelevant offers.
Marketers can use customer value analytics to shorten the sales cycle without sacrificing personalized service. By providing a consistent omnichannel experience, marketers and customers alike can reap the benefits of a strong relationship that lasts.
In a world where customers are more sophisticated than ever, it’s important to provide a seamless experience across every channel. By using a data-driven marketing strategy, marketers can create customized campaigns for each customer segment and provide them with the information they actually want.
Attribution Optimization for Budget Management
Marketers often struggle to determine which portion of their advertising budget is being wasted and what is being put to good use. Data-driven marketing, with the help of analytics tools, allows marketers for better marketing attribution modeling and to discover the portion that yields the greatest ROI. That informs future decisions about where and how much money should be spent on advertisements without wasting resources on efforts that aren’t likely to succeed.
How to Make your Marketing Strategy Data-Driven?
Set a Goal
Data is everywhere. From customer demographics to product catalogs to user behavior on your website or mobile app— all these kinds of data can be used for marketing. But to create a highly effective data-driven marketing strategy, you need to figure out what data you need. You should set a goal for your strategy: What do you hope to accomplish by implementing it?
Create your own Digital Measurement Plan
There’s no point in setting a goal if you don’t have a strategy to measure the results. This is why creating your own team’s digital measurement plan is important. Below are the 5 points to take into account while developing your own digital measurement plan:
Step 1
Start with a plan of action by identifying the objectives and setting broad guidelines, i.e., what you want to achieve from your digital marketing activities. For example, if your product is quite new to the target audience, then you need to find a way to reach potential customers and spread the word.
Step 2
For each objective, identify one or more specific and measurable goals. Referring to the example above, you have a clear goal to reach new customers, raise awareness and drive traffic to your website.
Step 3
Next, write down your specific key performance indicators (KPIs). In our example, our KPIs would be:
- The number of new customers acquired from a digital marketing campaign.
- Increase in website traffic and the number of new visitors.
- Online search ranking for specific keywords.
Step 4
Set the parameters for success upfront by identifying targets for each KPI. For example, if you have a goal of reaching new customers, define how many new customers you need to acquire from the campaign. What are the benchmarks for success? For example, you may want to set targets like a 5% increase in sales or a 10% growth in recurring revenue.
Step 5
Lastly, identify the segments of people/behavior/outcomes that you will analyze to understand why you succeeded or failed. At the end of your campaign, you will have a good idea of how it performed. You can then use this data to plan for future campaigns and make adjustments to improve performance.
A well-documented digital measurement plan is a critical step in any marketing initiative. It ensures that everyone is on the same page data-wise and knows exactly what they’re working towards. It’s also essential to have a documented measurement plan so you can compare your results with other marketing initiatives and understand how effective each campaign was.
Gather the Data
Here comes the most crucial step— gathering the data. As a marketer, you must be aware of all the multiple data sources available to you. After setting your goals, you need to identify all of the available sources and identify which of them can provide data relevant to your business. For example, you may want to look at data such as the number of sales transactions and average order value, but this information won’t help if you sell services instead of products.
You also need to consider how frequently this data is updated. For example, if it is only updated once a year, it probably isn’t relevant to your day-to-day marketing activities. Once done with this, you need to figure out a way to access the data.
Store and Organize your Data
A marketing strategy must integrate multiple data sources into one cohesive and actionable plan to be effective. If you have multiple sources of data such as email lists, social media followers, website visitors, Google Analytics, CRM data, or even offline transactional data, you’ll need a platform that can handle all of these details and provide you with a clear and easy-to-understand view of all the critical data. Once you have a single dashboard where all your data is stored securely, it becomes much easier to manage and analyze.
The next step is to organize your data to easily find what you need while making reports or analyzing the data. A good marketing platform will allow you to create custom segments of information that makes sense to your team and enables effective reporting and analysis at all times. This means that whatever type of information you’re collecting needs to be organized in such a way that everyone can easily find the required data whenever they need it. Now, this can be challenging when the organization doesn’t have a central hub for data. In the absence of such a hub, users waste time and effort collecting data from multiple sources and end up creating duplicate reports.
This is why most organizations choose to build a Marketing Data Warehouse (MDW) as a central repository for marketing data. Read more about designing a marketing data warehouse in our comprehensive guide.
Turning Data into Actionable Insights
The right process of ingesting data, turning it into valuable insights, and taking required actions on that knowledge can drive superior business outcomes. While it’s very common to have analytics and testing practices, organizations often lose sight of the vital importance of acting on the data when they don’t have an efficient system for turning data into actionable insights.
A data-led marketing strategy is distinguished by its ability to conduct ongoing analysis and optimization rather than relying solely on the results of one-time tests.
The Challenges of Data-Driven Marketing
Finding High-Quality Data
We’re all about good data-driven tactics— but only when quality data back it. First of all, high-quality data needs to be consistent and up-to-date. The timeliness of marketing data is key to a business’s ability to respond quickly and efficiently to customer needs. As an example of how important timeliness is to your business, consider the following: If you’re selling a product that consumers purchase only when they need it—a new car or a house, for instance—how long would you have to wait before learning that someone was interested in what you had to offer? If the answer is “several weeks or months,” then you don’t have a data-driven marketing strategy. You’re probably just guessing at what customers want.
Moreover, high-quality data needs to be complete. Data that is missing a critical piece of information, such as the customer’s location or purchase history, can make it impossible for you to deliver a relevant experience. If your marketing strategies aren’t based on complete and accurate data, then they won’t be very effective.
Data Modeling and Normalization to Extract Useful Information
Data is an objective measurement of something that exists. But data can be riddled with errors and inconsistencies, especially when it comes from various sources that normally do not co-exist. Normalizing data involves ensuring that each piece of information in your database is consistent with other pieces, such as creating a standard format for addresses and phone numbers.
Once you’ve collected and organized your data, interpreting it and creating actionable insights is vital for the growth of your business. With the right data, you can make better-informed decisions, predict future trends, identify patterns, and build new revenue streams.
For example, if you’d like to monitor your spending on CPC campaigns, you would need a clear query-level view that could give you the full gist from all the data sources (Google Ads, Bing Ads, Search Console, etc.) in a unified format catching all misspelled words, query variations, or even intent. That is why in Maya, you can segment all the available information into meaningful categories so that your reports are always as clear and insightful as possible. You can learn more about working with Clusters and here.
Breaking Down Silos
Here’s a fact— marketing data is not just big; it’s also fragmented. It’s messy, and finding the exact information you need isn’t always easy. Marketers have made it easier to collect, harmonize, and analyze data, but most of the information still exists in multiple data sets- often referred to as silos, rather than being integrated seamlessly across the organization.
Using tools that can handle the whole data pipeline process, such as ETL (extract, transform, load), harmonization, and visualization of their metrics, marketers can reap the benefits of a single, unified view of their data. This gives them the power to make better decisions that drive higher ROI and create more personalized experiences for consumers.
The Fear of Intrusion
With the right data, marketing teams can easily track, analyze, and even predict their consumers’ behaviors to provide them with personalized experiences and content that drives higher engagement.
However, people don’t like that companies know too much about them. Organizations should consider providing value to consumers when creating tailored messages or personalized tactics, as consumers want complete data transparency. Users are willing to provide their data only if they see an obvious benefit and value in doing so. They definitely won’t like it if they learn their personal data is collected and used without their knowledge.
How to Build a Data-Driven Stack Using the Right Tools?
Marketing teams are at the forefront of data science. While they may not have the same formal training as data scientists, they are charged with collecting, analyzing, and applying the insights that drive marketing success.
The challenge is that many marketers lack the tools to execute these tasks promptly, which means they’re working with incomplete or inaccurate information. Moreover, they waste a lot of time on manual processes instead of focusing on driving growth.
There are numerous tools that can help marketers implement a data-driven marketing strategy, including those that help them collect, analyze, and visualize data from various sources. These tools can also provide marketers with an understanding of how their customers interact with the brand’s digital properties, which helps them to identify opportunities for optimization. Below, you can find information on how Maya Insights can help your business switch to a data-focused approach.
How can Maya help your team?
Maya is an all-in-one marketing intelligence system that automatically collects, combines, and analyzes your data to provide business-ready metrics and dashboards. The best thing about Maya is that it undertakes all of the data pipeline steps, starting from data extraction, transformation, and loading, to data visualization and meaningful insights.
Connecting your advertising, analytics, and CRM accounts is quite easy, as it requires just a few clicks and not a single line of code. Plus, you don’t need to select manually the fields and tables that you need because Maya already did, so you can get the most out of your analysis. Plus, it keeps your data fresh on a daily basis to get the latest picture anytime, anywhere, for any stakeholder.
In terms of the analysis capabilities available, with Maya, your teams have full control over your cleansed data, as they can segment it in a way that makes sense to your business and can create custom dashboards and visualization in seconds, using the extended capabilities of Microsoft Power BI.
Last but not least, you get direct access to Maya’s database and API to perform more advanced analyses with predictive analytics or machine learning or even implement it to your existing business infrastructure.
Conclusion
At the end of the day, a data-driven marketing strategy is about learning to love your failures. Failure to a growth hacker is a sign of progress; you are iterating towards success. Analytics and experiments allow you to fail fast, learn quickly, and improve rapidly. With the right marketing toolset, you can now combine your learning with action to drive growth through data.
Get started today with a free 30-day trial to see how Maya can help your business implement a data-driven marketing strategy, or book a demo with one of our experts to show you around! Finally, we have prepared a complete and comprehensive guide about Maya’s awesome features to give you a full picture (Spoiler alert!).
Frequently Asked Questions
Data-driven marketing gathers data, through customer interactions and third parties to better understand the target market and drive actions.
Marketing teams used to rely on gut feeling and experience to make decisions and design a strategy. Nowadays, marketing teams need to drive actions that are based on their data and KPIs, in order to implement a data-led marketing strategy.
To make your marketing strategy more data-driven you need to:
- Set a clear objective
- Figure out the key metrics that you need to track
- Collect your data from various sources efficiently
- Store & organize this information in a secure DWH
- Make decisions relying on those data, not on opinions