Marketing Data Analytics: How to Build Your Source of Truth

Growth Intelligence
0 min read
March 21, 2021
Kenneth Shen
Chief Executive Officer

What story is your marketing data telling you? 

At Half Past Nine, we liken data analytics to the headlights of a car that is circuiting the ever-evolving road track of the customer journey. It allows you to see where you are and where you’re going so you don’t veer off track.  

And if marketing dollars are the gasoline of sales performance, we want you get around your customer journey track as fuel efficiently as possible. That’s why it pays to put that effort in with your digital marketing analytics. 

Digital marketing analytics can seem daunting when you have a number of active platforms in your marketing tech stack. There are a few things you’re contending with in order to optimize your analytics and decision-making processes: 

  • Accurate tracking of all digital marketing activity and consumer interactions. 
  • Interpreting data correctly to inform further decisions on customer acquisition and retention initiatives. 
  • Finding one source of truth in a sea of marketing analytics platforms. 

In this article, we will overview setting up a digital analytics infrastructure and data tracking, and using analytics platforms to interpret your data accurately. 

If you’re still looking at how to set up your wider marketing operation and process, learn more before diving into the technicalities of tracking and analyzing your marketing activity.

The Importance of Marketing Analytics & Data Integrity 

Achieving accuracy and clarity around data is the billion-dollar conundrum for digital marketing in this era. Trustworthy data you can confidently use for making effective decisions that grow your business is the goal.  

Understand Where Budget Is Spent - Your data should be able to provide a clear and detailed picture of where and how investments are made in your marketing. Reporting should allow you to drill down into specific business streams, audience segments, individual marketing channels, products, and so on. 

Measure Results Accurately – It's crucial to understand what the result of investments are, directly tying spending back to measurable results. That could be bottom line revenue in resulting sales, or other marketing goals such as improved brand awareness in target audiences. Your KPIs should guide what kind of results you want and need to report on as a priority. 

Improve ROI – High quality data gives you the ability to improve budget efficiency and ROI with precision by investing more in tactics that work best, and divesting in ones that don’t. Ultimately, good marketing data integrity allows you can scale your business and drive growth. 

Once you have this data, it’s also important to consider the use of data visualization to communicate the information across your business clearly and quickly. 

The true source of your data’s power is being able to make highly responsive and good quality decisions across your marketing operations and wider business. That won’t happen if people can’t easily understand what the data is saying.

Maintaining Marketing Data Integrity

Maintaining the integrity of marketing data can be a challenge in today’s digital environment. That’s down to the number of cross-channel touch-points brand typically have with users on a daily basis resulting in double attribution for conversions, coupled with the growing trend for enhanced user privacy. 

Does your business have a process for assessing how well marketing data gives a complete and accurate picture? If not, we’d recommend introducing one, because data integrity does require some proactive management. Learn more about managing your marketing data integrity and hygiene.

Now, let’s cover setting up accurate data tracking, as it’s not possible to analyze data that you don’t have!

Capturing Digital Marketing Data 

When capturing digital marketing and advertising data, it’s all about pixels, tracking tags, and tracking codes.  

If you haven’t come across these yet, they are small and unique pieces of code that need to be added to your website. Provided by analytics and advertising platforms, it’s your responsibility to add them to your website. Either your website developer can help you, or if you have access to do it yourself, instructions are always provided.  

The codes allow the platforms to follow users onto your website and track their subsequent activity. That’s how they know what a user has done after they have clicked on your website, and, for example, if an advert was responsible for a ‘conversion event’. First, you’ll need to set up the conversion events you want to be tracked. Depending on your business, that could include newsletter sign-ups, adding items to cart, making a purchase from your store, a form-fill, an account registration, a demo sign up or trial subscription, etc. 

You’re typically going to need the following tracking-codes: 

  • Analytics Tags - Google Analytics is the biggest platform in the website analytics space, allowing you to see and report on all user activity (anonymized) on your website for free. Create an account and you’ll be provided with the Google Universal Analytics Tag to link your website. You could also add the newer version called Google Analytics 4, which links with your main Universal Analytics account. This newer extension provides advanced functionality that works for both websites and apps (with a new Firebase SDK code). 
  • Advertising Pixels - Any platform you use for digital advertising will provide you with pixel codes, allowing user clicks on adverts to be tracked onto your website. You’ll need to set up the conversion actions or user engagement ‘events’ you want the pixels to track and report on, depending on the goal of your adverts and your sales funnel. The most common pixels are the Facebook pixel and Google AdWords pixels, or Klaviyo pixel for email and SMS marketing.  
  • Other Tracking Codes - Some other codes you may find useful include Google Optimize for free A/B testing of website pages, the Hotjar Tracking Code for using visual tools such as heat-maps to see how people use your website. 

Note that tracking codes can actually slow down your website if you have too many. That will impact your search engine marketing (SEM) performance and also detract from the user experience. It helps to either use a tag manager, or be selective about which advertising platforms work best for your audience so you can minimize the number of tracking codes on your site. 

Google Tag Manager 

google tag manager data


Google Tag Manager lets you manage all of your tracking tags in one place. So rather than needing to add all your various tracking codes directly to your website, only the Google Tag Manager code goes into your site. We recommend using it - it’s an incredibly helpful free tool. 

Not only does this tool stop your site being slowed down by too many tracking codes, it also has a great feature for Custom Events Tracking. That means you can track valuable user activity like clicks, scroll depth and form fills. This kind of data provides greater insight into how much user engagement and value that individual webpages are generating for your business. 

UTM Codes  

UTM codes are slightly different. They are custom URLs that work with your analytics platform to track where your users last came from when they clicked onto your website. It involves adding a little bit of specially formatted text to the end of your webpage URLs.  

Analytics platforms like Google Analytics or HubSpot use the URL tag parameters to report the exact location users came from, meaning you can see which individual pieces of marketing content were responsible. You can see how many users came from which source and medium, (E.g. Email, Email banner click), which campaign it was part of, right down to an individual social media post or link within an article.   

It’s an invaluable tool for understanding how much traffic individual pieces of content or adverts drive to your site. You can use it to assess the effectiveness of entire marketing campaigns, channels, online PR coverage, right down to individual Pay-Per-Click (PPC) adverts, etc. 

You’ll have to create these UTM codes yourself, depending on what you want to track and how you want to label the dimensions for unique pieces of content. URL builders are available to help you do this, such as Google’s URL builder. You can also find tools to help you keep track of all your codes too. Depending on how many you use, this can definitely be worthwhile.  

Understanding Marketing Analytics Platforms 

There are a number of marketing analytics platforms out there to choose from. All will require some degree of tailored set-up in terms of tracking conversion activity that’s specific to your website and marketing goals. It’s worthwhile investing this effort to fully utilize the analytical potential available to you. 

We’re going to take a deeper dive into using website analytics, and then in-platform analytics. But there’s something we want to note first. 

We’ve not found one analytics platform that’s able to offer a complete source of truth across digital marketing channels. Website data, in-platform advertising data (such as from Facebook), and email marketing data can’t all be captured by one single analytics platform. 

On one hand, data is often treated as proprietary to the platforms providing the ad or email service, although you can usually export it manually. Companies like Facebook offer their own in-platform analytics tools that they’d like you to use. And on the other hand, nobody has developed an analytics platform that can capture all the different types of data from across the various marketing channels and platforms. 

That means you’ll have a number of analytical platforms you need to extract data from to create combined reporting. You can work around this by using visualization tools and creating dashboards with multiple data inputs for a holistic overview and top-level reporting purposes. Read more about data visualization.  

But for now, let’s get back to your website and in-platform analytics.  

Website Analytics 

google analytics data


Google Analytics is still the king of website analytics platforms - an incredible product to have at your disposal for free.  

Set up your Google Analytics account so it’s tailored to your own unique website and marketing goals. The most important data you’ll need to set up includes: 

  • Reporting views - if you want to separately analyze distinct business steams on your website (including language versions), if you have more than one website linked to the same Google Analytics property, or if you also have a customer app. These filtered views give you the ability to instantly view sliced data, making reporting quicker and easier. 
  • Traffic sources dimensions - to see exactly which entry points users have to your website. You can see source/medium data automatically, but as already discussed, you’ll need to use UTM codes for more detailed data. For example, clicks from specific Facebook ads. 
  • Custom events - to track user interaction and engagement with your website content. For example, call-to-action button clicks or link clicks, how many times a video was played, how long a video was played for, etc. 
  • Goals - to measure how often your users complete events that you consider to be conversions. For example, making an e-commerce purchase, downloading a sales brochure or submitting a contact form. After you have set up goals, you will have access to view conversion reports

Pros of Google Analytics: 

  • You own the data on your website, so all information is available to you in terms of users behaviors and actions. 
  • Data is shown on a last-click basis by default, or the click that brought users to your site. You can accurately track advert Click-Through attribution if you use UTM codes.

Cons of Google Analytics: 

  • You don’t get the full attribution scope for the combined effect that multiple outbound marketing touch-points contribute towards website traffic and conversions. That’s because you only know when someone has clicked on an advert - not how many adverts they have seen to create familiarity with your brand or product before coming to your website.  

However, do note that there are several attribution models you can use within conversion reports - you don’t just have to go by the default last click. For example, you could go by first interactions, or specific conversion paths using event metrics. However, none can give a complete view of attribution for every customer on their journey to a sale conversion. 

Other Website Analytics Platforms

Google Analytics may be the biggest and best known website analytics platform, but that certainly doesn’t mean it’s the only one you should use.  

google search console marketing


Google Search Console is a free tool for diving into your organic search performance. It allows you to see and fix any indexing problems (things that stop Google from crawling your site) and request that Google re-index it when fixed. You can look into which search queries show your site in search results, how many clicks you get for those searches, review backlinks, mobile usability and more.  

Use it in conjunction with other Google tools like Analytics, Google Trends, and Google Ads

Bing Webmaster Tools is a surprisingly competitive (and also free) alternative to Google Analytics. It’s simpler and more user friendly, geared towards organic search engine optimization (SEO). The main platform offers additional functionality for SEO reports and recommendations, mobile-friendliness reports, plus research keywords and see inbound links analysis. 

Bing is the largest search engine platform after Google in terms of users, so it’s worthwhile not complacently overlooking it. Plus, any improvements you make for Bing can also help optimize your site performance on other search engines too.  

Third-Party Analytics 

Third-party analytics is data that’s reported on within the platform where you’re deploying paid marketing activity. The most common are Google Ads Manager, Facebook Ads Manager, and email providers like MailChimp or Klaviyo

data from klaviyo marketing

Pros of Third-Party Analytics: 

  • The analytics functionality provided by advertising or email platforms offer valuable information designed to help you get better returns from the unique channel. It is specific to the type of activity that happens on the platform, whether that’s reporting on users engagement activity such as likes, shares, comments, retweets, followers gained or open rates, plus click-throughs and conversion attribution. Facebook, for example, will let you set up 8 types of conversion events that will be tracked and reported on across all of a user’s devices. 
  • Data is mostly available immediately, meaning you can optimize live campaigns, amend landing pages, and make cost-efficiency decisions quickly. It gives you much more control and responsiveness when you can monitor live results. 

Cons of Third-Party Analytics: 

  1. Advertising channels are competing against each other and want to demonstrate higher conversion attribution than the others, encouraging you to spend more of your ad budget with them. If you use more than one advertising platform, double-attribution can be an issue, meaning more than one advertising platform claims full attribution for a sales conversion on your website. The extent of over-estimation will depend on how many ads a user has seen or clicked across different platforms within the set attribution timeframe - called View-Through and Click-Through attribution respectively. 
  2. The quality of advertising data declines by the day as more user privacy laws and tracking restrictions are introduced. Where users have opted not to be tracked, data modeling is used as a substitute, with its reporting delayed by a day or two. Facebook, as a prime example, now indicates in its ad reporting where modeled data is in use. Given the size of the user base that measures such as the Apple iOS 14 privacy update are impacting, the data accuracy for how effective your adverts are is hugely compromised.  

You definitely can’t rest on your laurels and trust the in-platform analytics to manage the integrity of your reporting data for you. The best way forward for is a combination of using in-platform data with your own website analytics data.

The Bottom Line

In a fierce digital marketing landscape where competitive edge is driven by continually leveraging data with razor precision, it pays to fully utilize the many free data analytics tools available to you. 

Our top tips are to honestly assess how well you currently report accurate ROI data across your marketing activity mix. Familiarize yourself with what data analytics functionality is available beyond what you’re currently using. Take no ROI data from paid marketing providers at face value. And make sure you really understand what the data is telling you so you can make decisions that drive market-leading results. Don’t get complacent, but continually keep your eye on things with regular reporting schedules and a continuous improvement loop. 

As always, the team at Half Past Nine are here to support you should you need us! Data analytics & visualization is our passion. We’ll happily confess to being full-on data geeks who get a kick out of showing our clients how much extra revenue they’ve earned thanks to our obsession with all things analytics. 

Feel free to get in touch anytime via email or our contact form. We’d be delighted to explore how we can help you harness the power of data analytics & visualization to turbocharge your marketing strategy and tactical delivery. 

What To Read Next:

Nate Lorenzen
Founder
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Kenneth Shen
Chief Executive Officer
Kenneth Shen
Chief Executive Officer
Kenneth Shen
Chief Executive Officer
Kenneth Shen
Chief Executive Officer
Jenner Kearns
Chief Delivery Officer
Kenneth Shen
Chief Executive Officer
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Jenner Kearns
Chief Delivery Officer
Kenneth Shen
Chief Executive Officer
Jenner Kearns
Chief Delivery Officer
Kenneth Shen
Chief Executive Officer
Kenneth Shen
Chief Executive Officer
Isla Bruce
Head of Content
Isla Bruce
Head of Content
Isla Bruce
Head of Content
Jenner Kearns
Chief Delivery Officer
Isla Bruce
Head of Content
Kenneth Shen
Chief Executive Officer
Isla Bruce
Head of Content
Isla Bruce
Head of Content
Isla Bruce
Head of Content
Kenneth Shen
Chief Executive Officer
Isla Bruce
Head of Content

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Google Ads has significantly evolved with the integration of AI, making advertising more efficient and effective. One of the most notable features is AI-driven search campaigns, which leverage machine learning to optimize bidding strategies and broad match types. This helps advertisers reach their audience more precisely and efficiently.

Another standout feature is the AI-powered chat function that simplifies ad creation. This tool allows users to generate ad texts and assets easily, making it especially useful for those setting up campaigns. By streamlining the creative process, the AI chat feature saves time and reduces the complexity of creating effective ads.

Understanding these AI features can provide substantial benefits for advertisers looking to stay competitive. From smart bidding to real-time adjustments, AI transforms how campaigns are managed and optimized. Readers interested in these capabilities can explore more about the capabilities of artificial intelligence in Google Ads to enhance their ad performance.

Automated Bidding Strategies

Automated bidding strategies in Google Ads use AI to help optimize bids during ad auctions. These strategies aim to maximize conversions and improve cost-efficiency.

Defining Bidding Strategies

Bidding strategies are methods used to manage how much you're willing to pay for each ad click or conversion. In Google Ads, smart bidding is a popular method that uses machine learning to optimize your bids.

There are several types of automated bidding:

  • Target CPA (Cost Per Acquisition): Focuses on getting as many conversions as possible at the target cost per acquisition.
  • Target ROAS (Return on Ad Spend): Aims to achieve the highest possible return on ad spend.
  • Maximize Clicks: Seeks to get as many clicks as possible within your budget.
  • Maximize Conversions: Prioritizes increasing conversion numbers.
  • Enhanced CPC (Cost Per Click): Adjusts your manual bids to maximize conversions.

Each strategy suits different campaign goals, from driving traffic to improving conversion rates.

How AI Enhances Bidding

AI in Google Ads makes bidding smarter by analyzing vast amounts of data quickly and accurately. It adjusts bids based on various factors like time of day, user device, and location. This leads to better performance and cost-efficiency.

Predictive analytics helps AI forecast the likelihood of a click converting into a sale. By examining historical data, AI can make informed decisions on how much to bid.

Real-time adjustments are another benefit. AI in Google Ads can modify bids on the fly, ensuring you're not overpaying for clicks that are unlikely to convert.

Ad Personalization with AI

Ad personalization using AI in Google Ads allows marketers to create dynamic ads, analyze performance, and customize ad content to target specific audiences effectively.

Dynamic Ads Creation

One of the key features of artificial intelligence in Google Ads is dynamic ads creation. AI-driven search campaigns use machine learning to create ad variations that match user searches more accurately. By leveraging AI, Google Ads can automatically mix and match assets like images, text, and videos to produce ads that are highly relevant to users' search queries.

Dynamic ad creation can significantly improve engagement rates by displaying ads that closely match user intent. This results in higher click-through rates (CTR) and increases the overall effectiveness of ad campaigns. It saves time for marketers, as they don’t have to manually create multiple ad versions.

Performance Analysis

AI in Google Ads also enhances performance analysis. By utilizing the vast amount of data collected from ad campaigns, AI provides insights that help optimize ad performance. For example, Google Ads AI can identify which keywords and ad formats are generating the most conversions, and adjust bidding strategies accordingly.

The ability to analyze performance in real-time allows marketers to make data-driven decisions. AI can continuously monitor and tweak campaigns to maximize Return on Investment (ROI). Additionally, AI's capability to predict trends ensures that campaigns remain effective even as market conditions change.

Ad Customization Techniques

Ad customization techniques are another critical element of AI in Google Ads. With features like Performance Max campaigns, marketers can upload various high-quality assets. The AI then mixes and matches these assets to create customized ads that resonate with different segments of the audience.

Using custom formats and specific targeting options, AI can tailor ads to fit the preferences and behaviors of individual users. This personalized approach not only enhances user experience but also increases the likelihood of conversions. Techniques include using dynamic keyword insertion and adapting ad copy to different user demographics, which ensures ads are contextually relevant.

Predictive Analytics in Audience Targeting

Predictive analytics uses AI in Google Ads to enhance audience targeting by making data-driven forecasts about user behavior. This helps marketers reach the right audience more effectively and tailor campaigns to meet their needs.

Understanding Audience Segments

AI in Google Ads classifies users into distinct audience segments based on their online behavior. These segments include demographics, interests, and past interactions. This process helps marketers identify and target specific groups that are more likely to engage with their ads.

For example, artificial intelligence can segment users who frequently visit sports websites into a sports enthusiast category. Advertisers can then create tailored ads for this group, increasing the likelihood of successful engagement. By understanding these segments, campaigns become more focused and effective.

Predicting Consumer Behavior

Predictive analytics in Google Ads leverages historical data to anticipate future actions. For instance, it can predict which users are likely to make a purchase soon or which ones might drop off. This allows marketers to craft strategies that target these behaviors.

For example, AI can analyze past purchasing trends and identify users with a high probability of buying specific products. Marketers can then serve ads that highlight promotions or related products to these users, increasing conversion rates. Predicting consumer behavior makes ads more relevant and timely, ultimately optimizing ad spend.

Smart Campaigns and Performance Insights

Smart campaigns in Google Ads use AI to automatically manage various aspects of your ad campaigns, ensuring optimal performance. These features offer detailed insights, enabling businesses to make data-driven decisions.

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Key benefits include:

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  • Performance Enhancements Continuously optimizes ad performance through machine learning.

Interpreting AI-Driven Analytics

AI-driven analytics in Google Ads offer valuable insights that can improve campaign efficiency. These analytics highlight customer behaviors and preferences, providing data that can refine targeting strategies. Performance insights like detailed demographics and budget pacing help businesses understand where to allocate their resources effectively.

Important features include:

  • Customer Value Mode — Focuses on high-value customers.
  • Retention Goals Helps maintain existing customer relationships.
  • Budget Pacing Ensures ad spend is distributed evenly across the campaign timeline.

By using these AI features, businesses can make more informed decisions, leading to better outcomes for their advertising efforts.

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Setting up an A/B test in Meta's Ads Manager is straightforward and can yield insightful results. This tool allows businesses to use an existing campaign as a template, making the process efficient and user-friendly. Ad campaigns should run for at least seven days to ensure reliable results, with a maximum duration of 30 days best practices for A/B tests.

When running an A/B test, it’s crucial to test only one variable at a time. This approach helps in accurately determining what drives better performance. For example, small businesses have found success by testing creative variables first, like different video formats or static ads A/B Testing Ads.

Executing A/B Tests on Social Platforms

Performing A/B tests on social platforms like Facebook and Instagram allows marketers to pinpoint which ads resonate most with their audience. By comparing different versions of ads, advertisers can optimize their campaigns for better performance.

Setting Up A/B Tests for Facebook Ads

To execute an A/B test on Facebook Ads, start in the Ads Manager. Use the A/B Testing tool to test different variables like ad images, text, audience, or placement. This tool ensures that each ad version is shown to different audience segments, preventing overlap.

Steps to set up A/B tests:

  1. In Ads Manager, choose your campaign and click on "A/B test."
  2. Select the variable you want to test. It could be an image, headline, or target audience.
  3. Define the duration of the test. Facebook recommends a minimum of 7 days for accurate results.
  4. Analyze the performance. Metrics such as click-through rate (CTR) and conversion rates help determine the winning version.

For detailed guidelines, refer to Meta's resources on A/B Testing Ads on Facebook.

Optimizing Instagram Ads through A/B Testing

Instagram also supports A/B testing within the Meta Ads Manager. Identifying the most engaging ad elements is crucial for maximizing reach and conversions.

Steps to optimize Instagram ads:

  1. Access Meta Ads Manager and create an A/B test for your Instagram campaign.
  2. Choose a single element to test, like the ad's visual content or call-to-action.
  3. Set up the test to run for a period that provides sufficient data, typically at least 7 days.
  4. Review specific metrics such as engagement rates, likes, and shares to evaluate performance.

For more insights, visit the Meta Business Help Center page on A/B testing.

Keep tests simple by changing only one variable at a time, ensuring cleaner and more precise results. This method not only refines your ad strategies but also provides valuable insights into audience preferences.

Analyzing A/B Testing Results

Understanding how to interpret and act on A/B testing results is crucial for improving ad performance on Facebook and Instagram. This section will cover how to read data and metrics from your tests and what steps to take based on the insights gathered.

Interpreting Data and Metrics

To start, locate your A/B test results within the Ads Manager, where you will see various metrics. Look for metrics like CTR, conversion rate, and cost per result. The CTR shows how often people who see your ad click on it. A higher CTR suggests that the ad is engaging.

Conversion rate indicates how many of those clicks lead to a desired action, such as a purchase. Cost per result helps understand the financial efficiency of the ad. High costs might indicate an issue with the ad's effectiveness or targeting. Be sure to compare these metrics between different versions of your ads to see which performs better.

Actionable Insights and Next Steps

Once you have interpreted the data, identify which ad version performed the best. For instance, if Ad A had a higher CTR but a lower conversion rate compared to Ad B, you may need to tweak the call-to-action or landing page of Ad A.

Use these insights to inform future campaigns. If a specific image or headline resonates more with your audience, incorporate similar elements in your next ads. Document these findings to create a knowledge base for future reference.

Making educated adjustments based on these results can lead to more effective ad campaigns and better return on investment (ROI). Check out the details on viewing A/B test results to refine your strategy.