Are you struggling to make sense of all the data analytics available to you? Do you feel overwhelmed by the amount of information you get every day?
Data analytics has become a crucial part of modern marketing. The ability to analyze customer behavior and trends allows marketers to better target their audience and improve sales conversions.
Research shows that 54% of companies that extensively use marketing analytics end up with higher profits than average. Without the right approach to marketing analytics, an organization may be unable to measure marketing performance accurately and, as a result, encounter more marketing challenges.
In this guide, we will walk you through the basics of marketing data analytics, explain why it matters, and provide you with the most important tips and tricks to master the art of data analytics.
Marketing analytics is the act of monitoring, collecting, and analyzing data for evaluating market success and guiding future business decisions.
What is Marketing Data Analytics?
A better term for marketing analytics would be “marketing data analytics.” It refers to the art of using data to evaluate the performance (or lack thereof) of marketing activities.
It is the combination of traditional business processes and data analytics to answer questions that drive better business results.
A study by Ruler Analytics has shown that most marketing departments face the greatest challenge when trying to prove and track their ROI and offline conversion rates.
Data quality management is among the top six challenges marketers face today. According to a recent survey by Forrester Research, 77% of business-to-business (B2B) marketers say they lack the skills necessary to effectively leverage data and analytical insights for making strategic business decisions.
Who should be thinking about Marketing Data and Analytics?
There are hundreds of different types of marketers, so you may wonder, “Who needs data? Who can benefit most from data?’ In short, the answer to this question is everybody — even people who don't necessarily use "marketing" in their titles. Here's a short checklist of the roles that should be watching marketing analytics closely:
CMO: The Chief Marketing Officer manages the performance of the marketing department, so they should be collecting data from their efforts to see if they're making an impact on the business.
Marketing Director: The marketing director is responsible for developing and executing marketing plans and budgets. They should track data to determine how well their campaign is doing and whether or not the budget is being used efficiently.
Analytics director: The analytics director is responsible for collecting data from every department within an organization, so he/she needs to know which metrics marketing is currently using.
CRO: The Chief Revenue Office should care about marketing analytics because they can help them determine how their new business and revenues are coming directly from their lead generation program.
Marketing Analyst: Marketing manager: Arguably, the role of a marketing manager is most relevant to the marketing function, because they are responsible for making strategic decisions related to the marketing data.
A Chief Business Intelligence Officer (CBIO): The CBIO ensures that business intelligence is used effectively by departments within an organization. They work closely with departments such as Marketing, Sales, Product Development, Customer Service, Human Resources, Finance, Legal, etc. to ensure that they're making good decisions based on accurate data.
Marketing Data Analytics is essential for Inbound marketing success
Inbound marketing is all about attracting customers through content creation and distribution. This means that your company must have a solid understanding of what its customers want to hear about, and then create content that will attract those customers.
This is where marketing data analytics comes into play. You need to understand what your customers want to read about, and then create compelling content that will draw them in.
You also need to know what kind of content your customers prefer to consume. If they like long-form articles, you'll need to write longer pieces. If they like videos, you'll need to create more video content.
You'll also need to know what topics your customers are interested in. If you find out that your customers are interested in travel, you might start creating blog posts about destinations around the world.
If you're looking to increase sales, you'll need to know what products your customers are buying. If you notice that your customers tend to buy certain items over others, you'll need to make sure that you're promoting the right products at the right time.
When it comes to customer service, you'll need to monitor what your customers are saying about your brand online. If you notice that people are complaining about slow delivery times, you'll need to improve your shipping process.
Why Marketing Data Analytics is Important
Marketing technology, data, and analytics is the most important thing for marketing departments, beating out branding, marketing channels, and ROI.
If your company isn't already using data analytics, it's time to start. There are many reasons why companies need to adopt data analytics, but here are the biggest ones:
1. Improves customer service
Customer service is one of the most important aspects of any business. If customers aren't happy, then they won't come back. And if they don't come back, then they'll tell others about their bad experience. This is where data analytics comes into play.
By analyzing customer interactions, you can identify trends and patterns that will allow you to better serve your customers. You can also find ways to increase conversion rates, decrease churn, and reduce customer support costs.
2. To make more informed decisions
Data analytics allows you to make more informed decisions. It helps you understand what works and what doesn't when it comes to your marketing campaigns.
For example, if you're running a Facebook ad campaign, you can use data analytics to figure out which demographics respond best to your ads.
You can also analyze the results of your email marketing campaigns to see which messages get opened and clicked on. With all of these insights, you can create more effective campaigns and ultimately grow your business.
3. Drives growth
Data analytics can be used to measure the effectiveness of your current marketing efforts. Once you have this information, you can adjust your strategy accordingly.
For example, if your sales team has been struggling to close deals, you might want to change your approach. Or if your website traffic has been stagnant, you could try different types of content or even redesign your site altogether.
4. More time for productive work
Marketing data analytics takes up less of your time than traditional methods. Instead of spending hours manually entering data into spreadsheets, you can spend just minutes doing it with data analytics software.
Some tools can do much of the heavy lifting for you. All you need to do is enter the basic details, and the tool does the rest.
But marketing data, according to Lyndsay Weir, allows you to free up time for more productive tasks. In her role as Global Data and Analytics Manager at Nestlé, Lyndsay uses marketing data analytics software to consolidate, analyze, and visualize the wealth of data available across different channels.
She says that she sees real-time insights into how people are interacting with products and brands. This helps her make better decisions about where to spend money and what to focus on next.
It had huge time-saving benefits—Nestlé's marketing department was able to save 80% of their time by using insight to fine-tune their marketing campaigns and produce the results they needed.
Data streamlining and optimizing your marketing strategy means knowing which resources and strategies best suit your target market.
5. Provides powerful insights
Data analytics gives you access to powerful insights that would otherwise take months or years to gather.
For example, if you were trying to determine why your website wasn't converting visitors into leads, you'd probably need to hire an expert to conduct a study. But with data analytics, you can quickly pinpoint the problem yourself.
You can also use data analytics to predict future outcomes based on past events. If you know that most people who visit your website are likely to convert, you can design your website so that it looks like a lead generation page.
Marketing campaigns come with a set of KPIs that measure success. But how do you know whether those KPIs are achieving their goals? You need to analyze and benchmark each metric against others. This helps you identify areas where your efforts aren't paying off, and adjust accordingly.
Once you've identified these metrics, compare them to other important business KPIs such as revenue or churn. If you're working with a client or your CEO, they'll probably want to see the data behind marketing recommendations that are being proposed. They want to see the value of marketing.
6. Helps you stay competitive
With data analytics, you can gain valuable insights into your competitors' marketing tactics.
This will help you decide whether or not you should follow their lead. For example, if one company starts offering a new product, you might be tempted to jump on board.
However, if you find out that this competitor has been testing the same product for over a year without any sales, then you may decide to wait until they start making a profit before jumping in.
7. Improves return on ad spend
Marketing data gives you the power to make better decisions about how much to spend on advertising. You can use it to target specific groups of people based on demographics, interests, behaviors, and even location. This helps you find the best way to reach your audience and ultimately increase revenue.
Let's take a look at some real-world examples. For example, let's say that our gut instincts tell us that women aged 20–40 are most likely to buy our product.
However, previous advertising research has shown that most people who buy cosmetics are between the ages of 18 and 25.
You could end up wasting money on advertising because you've ignored the majority of potential buyers. Or worse still, you could miss out on making a sale because you didn't target enough people.
To help prevent this, marketers often rely on gut instinct to decide where to place ads. Gut instincts are great, but they aren't always reliable. And sometimes, they lead us astray.
3 Types of Marketing Data Sources to lean on
There are three main types of data you can use to evaluate your strategy. Let's go through each one and see how you can get them.
There are three main ways marketers measure success: Zero-party data, first-party data, and third-party data.
Zero-party data is information a customer gives voluntarily. Some marketers consider it the best, most accurate source of marketing data because potential customers voluntarily share their preferences, interests, and behaviors directly with the brand.
Source zero-party data through:
First-party data includes any information that was obtained by a business from its customers. Examples of first-part marketing data available include:
- Website: number of visits, bounce rates, and page views per visit.
- Mobile application: notification open rates, monthly active users, and retention rate.
- Ecommerce platform: order value, products purchased, or the number of purchases.
- CRM: such things as deal sizes, sales cycles, or preferred communications channels.
- Social media profile: engagement rate, website clicks, or time active.
- Point of sale system: preferred payment method, purchase location, or sell-through rate.
While this kind of marketing data can help you understand who your target market might be, you'll need to explain exactly what you're collecting and why. Data privacy laws, such as GDPR (General Data Privacy Regulation), require companies to inform their customers about what data they collect from them.
Apple's iOS 14.5 update was one of the earliest of its type to ask brands not to track user data for advertising purposes.
Third-party data is information obtained through external sources.
Brands are responding to privacy concerns by increasing their transparency, asking users for less data, and reducing the intensity of tracking. Data from third-party sources is used to fill in any missing gaps.
- Research studies: Like the number of hours people spend on social media, or their preferred payment method.
- Demographic statistics: such as job titles, ages, or incomes sourced from the Census or the Bureau of Labor Statistics.
- Big data aggregation companies: such as Oracle or Adobe.
According to Statista, $22 billion was spent on third-party data in 2021, with $13.3 billion spent on data itself and $8.7 billion on audience data activation solutions. This spending on third-party data is because of Apple’s recent iOS updates, GDPR, and consumers' growing concern for their data.
How to make the most of your marketing data
Marketing data is everywhere. From customer reviews to social media posts, there are plenty of ways to collect information about your customers. But what does that mean for your brand? What can you learn from it? And how do you turn that into actionable insights?
The answer lies in understanding how to make the most out of your marketing data. Here are how to make the most of your marketing data:
1. Organize the data
You shouldn't be surprised if you feel overloaded by the sheer volume of marketing research out there. There are currently over 7,000 marketing research tools in use today, making it an extremely fragmented and manual space.
Collecting data is the easy part. It’s analyzing the data. Businesses are challenged by the fact that they have so much raw marketing information lying around but don't know how to turn it into useful insights.
Data delivery solutions (like HubSpot) streamline the secure transfer of data between sales and marketing platforms. You can focus on understanding the insights without worrying about gathering data for your analysis.
2. Establish data governance
Who is responsible for maintaining, collecting, and storing customer information? The statement “Too Many Cooks Can Spoil Your Broth” applies here. You don't want too many people dipping into and out of your database, creating inconsistencies, and wreaking havoc with your reporting.
You need to establish a team member who is responsible for keeping your repositories tidy, such as a database administrator or a marketer. The member is responsible for:
- Integrating your data delivery solution with third-party software
- Maintaining the integration by checking each tool is functioning correctly
- Working with marketing strategists to segment data
3. Define your north star metrics
A north star metric is the driving force behind your campaign and is a key performance indicator (KPI). They’re usually aimed at specific business goals, such as decreasing churn, increasing customer satisfaction, or generating new revenues.
All marketing metrics must be benchmarked against this north star. When reporting, if the ultimate goal is revenue, then focus on financial metrics, including average orders per day (AOD) and return on investment (ROI).
If the goal is to increase customer satisfaction, then look at customer retention rates.
4. Slice and dice marketing data
Data alone doesn't always tell the whole story. Use data analytics to dig deeper into your data to see if there are any marketing patterns or benchmarks that could be used to improve your business.
Don't rely solely on metrics provided by Facebook when evaluating the success of an ad campaign. Because platforms may be known to artificially inflate their metrics, you might end up pivoting your strategy unnecessarily.
To check whether your page looks good, compare your metrics with data from other sources, including:
- Your CRM
- Google Analytics
Instead of using spreadsheets and complicated formulas, use a data visualization tool like HubSpot. Create custom reports automatically by pulling data from multiple sources into one place without having to manually enter the data.
5. Relay data back to consumers
It is important to remember that when you collect data, you're not just doing it for the sake of it; you're doing it because you want to use the data to learn things about your business and figure out ways to become more successful.
You should relay any data you find back to customers and send them personalized messages they find appealing.
The most common data points used for retargeting include:
- Campaign source
- Products purchased
- Email clicks
- Pages viewed
If you're a software company selling an online accounting tool, for example, historical analytics show that a potential customer has recently visited your "tips" page. They've clicked through from there to your features and pricing pages.
These prospects are clearly at the beginning of their buying cycle. They need some kind of incentive to get them to engage with you. Offer them a 10% discount code for using your product. That's the hook they were initially interested in.
6. Report regularly
You'll only be able to spot trends if you report regularly. When planning future marketing strategies, consult your repositories to see where improvements could be made.
By basing future goals on historical data, we improve our chances of setting realistic goals.
For example, if you're currently converting 2% of your emails into sales, then a reasonable target for increasing conversion rates might be to double that rate to 4%, over six months.
If you fail to consider your current baseline when setting goals for the next six months, you may set an unrealistic and unattainable goal that will likely deflate your marketing team if they cannot meet it within the unrealistic period.
Ongoing collection and analysis of user behavior make it easier for companies to run A/B testing.
Make sure you use current data as a benchmark for measuring and switching up the marketing messages, forms, and channels used by your customer engagement teams.
Make sure that you monitor the difference between key performance indicators (KPIs) such as conversions or revenues generated. A small percentage increase every day will compound over time.
How to Make Data-Driven Marketing Decisions
As a marketer, making data-driven decisions can help you achieve greater business results over time. Instead of trying to predict what will work in the future, you can use analytics to help you decide which marketing tactics to use, where to allocate your budgets, and more.
Here is a framework for making marketing decisions using analytics:
Gather your data from every channel
The first step is for you to get your data from every platform (Facebook, Twitter, etc.), including Google Analytics, CRM, etc.
You'll ideally want to use a tool called HubSpot Operations Hub to aggregate your customer service metrics into one central location. You can also do it manually in Excel, but doing so is quite time-consuming.
Store and leverage your data
You'll need to save your information somewhere before you begin enhancing it. A CRM, such as HubSpot or Salesforce, can help you do this. If you aren't already working with a CRM, consider finding one that works best for your business.
Then, you can start to enhance it using artificial intelligence and machine learning to pull out key trends and important insights.
Create a dashboard
The final step is putting all of that stored data together into one place so you can easily access it. You can view your information in real-time, reducing the amount of time you spent manually reviewing the numbers.
The best thing about an online dashboard is that they're easy to set up and doesn't require any technical knowledge or skills. Even beginners can create a basic dashboard without any experience in data analysis.
Once all your data has been imported into the Dashboard, you can begin making data-based business choices.
For example, you could look at which marketing campaigns were most successful during the past three months, and then allocate more resources toward them next month.
You could even take a look at the performance of different types of content (e.g., blog posts vs. videos) to determine which type of content performs best.
Leverage the power of Marketing Data Analytics
In conclusion, data analytics has become a huge part of marketing today. With the amount of information available online, you must use your data to gain insights into consumer behavior. This allows you to create targeted campaigns that reach consumers where they spend their time online.
Data analytics is also used to help companies improve customer service and increase sales. It can help leaders understand strategic and operational decisions better and uncover new questions and opportunities they might not have thought of before.
The key is to spend time investing in the people, tools, and infrastructure required to create and execute an organization’s data strategy roadmap.
At Fine Media, we are certified in HubSpot software, the best for any size of business. If you are ready to make data-driven decisions and grow your business, contact us today!