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Understanding what’s working and what isn’t in your marketing strategy can help you refine future marketing campaigns. That’s where marketing analytics comes in. 

You can use marketing analytics to acquire more specific insights about your customers, the kinds of products they buy, and their interactions with your marketing. This guide shares how to use that information to maximize your sales.

What is marketing analytics?

Marketing analytics is the process of measuring, managing, and analyzing marketing performance to get a higher return on investment. It uses data from different marketing channels, such as email, social media analytics, and your online store. 

You should use marketing analytics to determine the most impactful marketing tactics, predict future trends, and increase sales. It can also help identify which marketing initiatives are working, allowing you to more effectively allocate marketing resources like time and budget.

Why marketing analytics matter

With marketing campaign analytics, you can track the sources and behavior of traffic to your site in far greater detail. This can help your business in a number of ways.

Stand out in a saturated market

It’s now easier than ever to start an online store. You need to do everything you can to not only create a product that stands out, but insulate your business with marketing strategies that attract customers. 

Instead of relying on data alone, marketing analytics help you uncover what messages resonate with your target audience. If your highest-converting Facebook ads and landing pages both talk about your commitment to sustainability, for example, it makes sense to run with this messaging on other channels. 

By focusing on something that your target market connects with, as opposed to the technical specifications of your products (which are easily comparable to competitors), you have more chance of standing out against the competition.

Make educated decisions about where to invest marketing dollars 

Marketing analytics let you track not just sales from Google Ads, but sales from specific search engine keywords you have bid on. Not just email clicks, but clicks on a specific link in an email. Not just Instagram traffic, but visitors from a link in your bio.

This data helps figure out what is (and isn’t) working, allowing you to readjust budgets and marketing efforts and get the most out of your investment. 

You can also group traffic to your site based on the source, target audience, content type, links clicked, and other details, as well as group traffic across multiple channels and landing pages that belong to the same campaign. This allows you to analyze and compare the online marketing performance and customer behavior of specific traffic segments.

Improve the customer experience

The brands that win are those that deliver faultless customer experiences. Consumers can buy similar products from hundreds of other retailers, but seven in 10 will spend more with the one that makes the purchase experience enjoyable. 

Marketing analytics helps you figure out what customers want so you can proactively deliver on (or exceed) their expectations. If your data proves that digital marketing campaigns that show the products a potential customer has abandoned in their online cart have higher conversion rates, for example, it makes sense to assign more budget to these ads over other retargeting campaigns. 

By providing customers with what they want, you’re reducing the risk of losing them to a competitor. 

Key components of marketing analytics

  • Data sources
  • Marketing attribution models
  • UTM parameters

Data sources

Data collection is the first step in marketing analytics. However, consumers are generating more information than ever before. It’s projected that in 2024, internet users will generate 147 zetabytes of data, almost double the amount from only three years ago. Determining which metrics are important and identifying their sources can be challenging. 

When collecting data about your marketing strategy, you can source:

  • Zero-party data. This is information that your customers have voluntarily provided, such as answers to a quiz or product reviews. 
  • First-party data. This is data you have about your customers, but that hasn’t come directly from them. Examples include website analytics or social media marketing reports.
  • Second-party data. This is information you’ve collected about your customers from another source, such as survey responses collated from another company.
  • Third-party data. This data is gathered from someone else, such as industry reports or social listening tools.
A question to get first-party data from customers, asking about their skin.
Jones Road Beauty collects first-party data with its “Find your perfect match” quiz.

Marketing attribution models

You must determine how much weight to give each data point—particularly when reporting on goals such as conversions or sales. This is known as marketing attribution.

If you’re an online retailer with a digital marketing strategy, you might have customers who’ve interacted with your brand on several channels. They viewed your post on Instagram, went to your website, opened an email, then clicked a Facebook ad before buying. How do you determine which channel should get the credit for the sale? 

The answer varies depending on your attribution model:

  • First-click attribution. The first time someone interacted with your brand. In the example above, Instagram would get the credit using this attribution model.
  • Last-click attribution. The final time someone interacted with your brand before converting. In this case, it would be a Facebook ad. 
  • Multichannel attribution. This model spreads out the credit for every touchpoint. It’s one of the most popular because it recognizes someone might not have converted if they didn’t work through each stage of the marketing funnel

UTM parameters

UTM parameters are pieces of information that can be added to the end of any URL that give search engines more information about that particular link.

The UTM parameters highlighted on a LinkPop URL.
UTM parameters on this Linkpop URL.

The part after the “?” is a UTM parameter. Each parameter describes something different about the context of the link, and an “&” separates each parameter. When someone clicks on that link, Google Analytics for that particular website will read and record that parameter information.

There are five UTM parameters that can be used for tracking various pieces of information in Google Analytics:

  • Campaign source (utm_source): This is generally used to describe the website or main source in which the link will be placed. For example, the name of the website displaying your ads.
  • Campaign medium (utm_medium): Medium is used to describe the marketing activity. For example, you may want to call this “ppc” if you’re using the link for a pay-per-click campaign or “review” if you’re using the link to track traffic from a product review on a blogger’s site.
  • Campaign name (utm_campaign): Campaign name refers to the overall campaign you’re running. For example, it could refer to a product launch, a summer campaign, or a particular sale, and be used to group traffic from multiple sources and mediums in the same campaign.
  • Campaign term (utm_term): Campaign term is an optional parameter used for tracking particular keywords if you’re running a Google Ads campaign.
  • Campaign content (utm_content): This optional parameter is helpful if you’re testing variations of the same ad in a campaign to see which one drives more traffic. 

5 marketing analytics tips

Now that we know the types of data you might want to collect, here are five tips to turn marketing data into actionable insights:

  1. Understand which metrics to track
  2. Make sure you’re collecting high-quality marketing data
  3. Compare marketing analytics against competitors
  4. Supplement analytics with marketing trends
  5. Use predictive analytics

1. Understand which metrics to track

Your key performance indicators (KPIs) are the metrics that matter to you most. The KPIs you use will depend on your business and your overall marketing strategy.

For many ecommerce businesses, that might include:

2. Make sure you’re collecting high-quality marketing data

Data can never be 100% clean or accurate. There are always blind spots and gaps. However, you can increase the quality of your marketing datasets by proactively using tracking parameters to track your KPIs.

Your insights will remain shallow without campaign tracking in place and your marketing analytics can quickly become a mess without a logical methodology for grouping traffic.

For example, if you use the parameter “utm_medium=IGstories” in an Instagram Stories link, and then “utm_medium=insta-stories” in another, your analytics will separate the traffic into two groups, even if you intended to group all Instagram Stories traffic together. That’s why it’s important you’re highly intentional about tracking your marketing campaigns.

3. Compare marketing analytics against competitors

Raw data doesn’t mean much. It’s only when you compare data against other benchmarks that patterns emerge and you see whether your marketing strategy is performing well. 

Paint the bigger picture by comparing your marketing analytics against competitors’ data. Tools like Mention and Ahrefs can help lift the lid on other brands’ data.

Let’s say you’re analyzing marketing data to see how effective your search engine optimization strategy is. You want to know how many keywords you’re ranking for, so you enter your URL into Ahrefs. The software collects data about all keywords and websites. You can type your competitors’ website address and see the same data, which helps you make a

Ahrefs report showing traffic acquisition sources for Mailchimp URLs.
Ahrefs’ data analysis report for MailChimp.

4. Supplement analytics with marketing trends

Some brands get hung up on zero-party data—words that come from your customer’s mouth. They can express your target market’s wants, needs, and demands from a brand. But they can’t always tell you exactly where the market is heading in the way that second- or third-party data often can. 

Supplementing your own information with this data gives you a competitive advantage. You might be collecting the same information as your competitors when you rely on externally collected data but by comparing it against your private data (like survey responses from your customers) it paints a bigger picture. This is a smart way to spot emerging trends and predict where the market is heading.

5. Use predictive analytics

Data doesn’t just have to tell you what’s happened in the past. Historical data can signal what’s about to happen in the future. 

Predictive analytics is the final piece of the marketing analytics puzzle. It uses statistical methods and machine learning to identify trends, patterns, and insights in your marketing data. 

The most obvious use case of predictive analytics in marketing is personalized product recommendations. If historical data shows that people tend to buy a phone case with their charging cable, you can create product bundles that offer both items at a discounted price. 

It’s a win-win for everyone involved: you increase your average order value and conversion rates, while customers get a better experience since you’ve proactively catered to their needs—without them having to match the two products themselves. 

Marketing analytics software

If you’re ready to start tracking your marketing analytics, here are three of the best ecommerce analytics tools to rely on. 

Shopify Analytics

A Shopify Analytics dashboard using a line graph to show Instagram performance data.
Shopify Analytics dashboard is free for all merchants.

Shopify’s built-in reporting and analytics helps you make faster, better decisions. Choose from more than 60 pre-built dashboards and reports or customize your own to spot trends, capitalize on opportunities, and supercharge your decision-making. The free marketing analytics software is available for any Shopify store owner. 

Still Life Story is one brand that maximizes the value of Shopify Analytics. Founder Ruby Friel opened the brick-and-mortar store amid a pandemic shortly after becoming a new mom. She invested all profits back into the store, but needed to make data-driven decisions on how that investment would be best spent.

Ruby used Shopify Analytics to monitor the store’s weekly sales by product type. The Sales by product variant report showed some SKUs were more in-demand than others. This allowed Ruby to prioritize which products she should invest in and promote on social media.

Google Analytics

Google Analytics is the most popular analytics tool. You can embed tracking codes on any website and monitor how people interact with your website. 

Amongst its standout features is the ability to segment visitors. Filter data from people who visited from a traffic source, use a specific device, or are located within a certain geographic region to see how these factors contribute to your marketing results. 

Triple Whale

Triple Whale dashboard with the title “Make better decisions with data you can trust.”
Triple Whale’s data visualization tools.

Triple Whale is a marketing analytics tool that pulls together data from a variety of sources. Use the Shopify app to sync your Shopify Analytics with marketing data from platforms like Facebook, Google Ads, Klaviyo, Amazon, and Google Analytics. 

Triple Whale is known for its data visualization features. Choose the metrics that matter most to your marketing team and present them in a report—without switching tabs and importing data into a spreadsheet.

What you do with the marketing data you collect matters most

Marketing analytics help you determine where to invest your budget and attention to get the most out of your marketing efforts. But it’s ultimately up to you how you use your marketing data. Data analysis can be open to interpretation but marketing campaign analytics with an ongoing effort to preserve the quality of your data makes it easier to read.

Luckily, Shopify also makes it easy to track the most important data for your online store. Dive into Shopify Analytics for digestible, real-time insights about your traffic, products, customers, and more.

Marketing analytics FAQ

How can marketing analytics help bring in more sales?

Marketing campaign analytics let you track and monitor behavior from users who interact with your marketing and visit your online store. You can then visualize that data in reports, tables, and dashboards to help you find answers to questions you have that could help grow your business.

How does marketing analytics improve decision making?

Marketing analytics helps you make better decisions because you’re basing your marketing strategy on historical data that can inform future campaigns, instead of a hunch or gut feeling. This allows you to better allocate resources, including time and money, to get the most out of your marketing investment.

What are the challenges in implementing marketing analytics?

  • Lack of data science skills
  • Poor data quality
  • Improper data attribution
  • Ineffective data storage
  • Not using the right marketing analytics tools

How can marketing analytics be used in ecommerce?

  • Prioritize inventory
  • Adjust product prices
  • Identify upcoming trends
  • Hone in on your best-performing channel
  • Adjust your content mix
  • Upsell and cross-sell products

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