What is Marketing Analytics?

    Do an internet search for “marketing analytics,” and you’ll find several lengthy articles about it. But what it boils down to is this:

    Marketing analytics is the examination of results to measure a promotional effort’s level of success.

    Marketing analytics zeroes in on statistics. It reveals how well the different parts of a promotional effort are working and even burrows down to the individual customer level. 

    Importance of Marketing Analytics

    Deep data exploration answers highly specific questions like: 

    • Who replied to what?
    • Who clicked on this version of our video?
    • Who bought this color umbrella on a Tuesday when it rained more than an inch?

    Marketing analytics answers both the big-picture questions and the granular-level ones. Marketers use those revelations to fine-tune a marketing push, resulting in a more efficient return on investment (ROI).

    How Organizations Benefit from Marketing Analytics

    Put simply, marketing is advertising. It promotes a good, service, person, or company. Usually, a positive goal is in mind: increase sales, boost reputation, generate leads, and so forth. And naturally, those efforts must be quantified.

    Let's consider a simple hypothetical. A grocery store owner gets a big shipment of fresh apples, so he puts a sign in the window saying apples are on sale. He’s just done a little bit of marketing. After a while, he notices that the apple bin by the cash register is empty, but the one in the back of the store is still full. When the next shipment comes in, he moves the second bin to the register as well. Both bins sell out. He used marketing analytics to make his sales grow.

    Our grocery store owner isn’t the only one. Organizations, large and small, use marketing analytics to find ways to improve their business. Here are a few ways marketing analytics can take companies to the next level:

    • Ad spend – Companies can see where their advertisements get the most views or clicks. They can see what imaging or messaging appeals to customers and what doesn’t. That allows them to stop spending money pushing the weak ads and move their investment to more successful spots. Renowned consulting company McKinsey has said that companies enacting an analytics effort will save up to 20% on their marketing budget.1

    • Trends and their place in the market – It’s not just about the company’s money; businesses use marketing analytics to see where customers spend theirs. Businesses use analytics to track how a product or service’s popularity is gaining or waning. It also tracks the competition’s success or what they are ignoring. This information can help a company set goals or defend its position in the market.

    • Planning for the future – Marketing analytics is also a powerful tool for predicting future market trends. Using analytics to anticipate what is coming puts the company in a good position and allows for data-driven decisions on subsequent marketing campaigns.

    • 360-degree view of the customer – There are so many channels for marketing promotions: in-store, on-site, web, email, instant messaging, in-app ads, sponsored social media posts, advice from doctors, word-of-mouth, and so much more. Anything that can inform a customer is a channel. A marketing analytics strategy can help create a complete picture of a customer based on these different sources. This picture, in turn, leads to an actual omnichannel experience in which you can custom-build a promotional strategy that is connected across several interaction points and is unique to the individual.

    Targets of Marketing Analytics

    All aspects of a marketing campaign can be measured through analytics:

    • Traditional – Advertising has been around since antiquity. The earliest-known ad printed in English was published by William Caxton around 1476 to promote a new book.2 Legacy media such as newspapers, radio, and television still survive because of ads.

    • Digital – Banner ads and quick videos that play ahead of the item a user wants to watch are examples of digital marketing. Or, in the modern-day form of a traditional ad, a company can purchase a “live read,” in which a content creator will talk about a product during their web show or podcast.

    • Email – Continuing with the digital theme, email ads are another big producer of marketing data. Offers sent directly to users can be tracked for their click-through rates.

    • Written content – Blog posts, thought leadership articles, and write-ups by product reviewers can teach a company what types of products interest customers.

    • Social – “Likes” on sites such as Facebook, Twitter, Instagram, and others can also reveal burgeoning market trends. Influencers who post about products and the comments on those posts, both good and bad, are also primary data sources.

    Other Sources of Marketing Analytics Data

    A company can send out surveys and hear directly from the customers themselves. It can gauge the response to proposed changes by performing A/B testing, where one group appraises the original item while another assesses an altered version. Companies can also share data with other businesses in the industry. Or it can go out and purchase data from aggregation firms.

    Promotional Measurement and Planning: Evolution and Future

    Marketing Analytics Implementation

    When a company decides to dive head-first into marketing data, it has a few points to check off its to-do list. First, it should create an overall marketing analytics system or framework. Choosing which flavor of analytics to run comes next. Only then can they take the final steps to implement the process.

    • What Makes Up a Marketing Analytics Framework?

      A Complete Database Naturally, a company should collect as much data as possible. But it needs to keep in mind that historical data is the key. So, it should start gathering its marketing data into a central repository as soon as possible. That historical data must include what was promoted, when it was collected, the cost, and which customers were targeted. If you’ve read this far, you know this is obvious: without historical data, you can’t do an analysis, and you can’t make informed predictions about the future. Analyzing historical data is also known as time-series analytics.

      Attribution Reporting – Companies need to know what specific part of a promotion was responsible for the intended action, whether it was a sale, a lead on a potential customer, or a click on a “find out how” link in an article. There are several different ways to attribute value, which we’ll discuss in just a moment.

      Simple, Yet Powerful Answers – The next part of your overall marketing analytics framework is to ensure you get easy and actionable insights from the analysis. You want your staff to be able to come up with a clear-cut question (i.e., “How many widgets did we sell in June?”). And your analysis should be able to provide a clear-cut answer quickly and truthfully. On top of that, it should reveal even deeper details (i.e., “We sold more widgets on the second Monday in June; here’s why.”). The process of asking these questions should also be simple, leading us to the next part of the framework:

      Easy-to-Use Interface – The people who use the analytics should have an easy-to-understand platform for examining the data and insights. Users, especially business users, shouldn’t have to learn code and how to build an algorithm from scratch; they’re not IT experts. That said, there are times when users want a deluge of statistics to back them up. So the platform should still be powerful enough to allow custom-styled reports with as much detail as the user wants to include.

    • Different Kinds of Marketing Analytics

      There are several analytical approaches from which to choose. Here are the options at a company’s disposal:

      MMx – Marketing Mix Modeling is the gold standard. We’ve touched on this throughout the article so far: MMx creates complex equations to calculate how each facet of a marketing effort affects the final outcome. It can even factor in external variables, such as economic conditions. What MMx does so well is analyze every single input and tweak those inputs until it reaches the best possible conclusion. Think of it like a chess computer that can branch out thousands of possible paths forward based on each move.

      How Should A Marketing Mix Analysis Influence The Next Best Actions?

      Channel Design and Management – This type of marketing analytics looks at customer preferences. As mentioned earlier, many channels are available, so companies would do well to implement a channel design strategy. Analyzing what customers want to see and what they ignore is paramount, especially in the life sciences industry, where physicians have strict preferences for interacting with pharmaceutical companies.

      Find out how Axtria helps companies design and manage their marketing channels.
      (LINK: https://www.axtria.com/marketing/channel-design-management/)

      Attribution Modeling – A marketing analytics framework needs to accurately attribute which parts of a campaign elicited which results. One of the most common models used is called single attribution. It simply assigns all value to either the first interaction that led to a sale or desired result or the last interaction that led to it. If a marketing project will be lengthy, this model can include previous campaign results to help predict revenue.

      Alternatively, companies may realize there were points in-between initial contact and the last interaction that produced a sale. To solve that, attribution modeling implements multiple-program or multi-touch attribution. This process essentially reverse-engineers the sale, analyzing it from end to beginning to find the point that impacted the decision most.

      Predictive AnalyticsA predictive analytics approach is useful when creating a new promotional campaign. It aggregates and analyzes past performance and uses that history to suggest key details for the new endeavor. For example, it will show how much better the results will be with a bigger budget, what markets need more attention, which channels can work in concert with each other, which advertising style would work better if placed in a different channel, and so forth.

      ROI AnalyticsHere’s one for the math and accounting whizzes. This approach calculates the revenue earned based on each part of a promotional effort. A simple formula of net profits divided by the investment cost will give you a quantifiable number. If the result is positive, the plan worked. For this approach to be practical, a company must have clean, trustworthy data that shows which touchpoint led to a sale or action.

      It may be a simple approach, but in the end, hard data on revenue is one of the most critical drivers of decision-making among company executives.

      Assessing Interaction Among Promotion Channels To Accurately Measure Marketing ROI
    • Steps to Take When Implementing a Marketing Analytics Program

      1. The first step might sound obvious, but it is necessary: make a plan. Have discussions about expected goals and what you want to measure. Do diligent research on the marketing analytics platforms available before committing your company to purchasing one.

      2. Next, make sure you have the right team in place. Large companies should consider hiring a Chief Marketing Officer (CMO) who understands how the data is coming in and how to ask the right questions to glean answers from the statistics.

      3. Next, get your staff on board. Create a culture where your team embraces the data process. Help them realize that there is value in every interaction, whether it results in a sale or not. You can learn just as much from an unconverted action as you can from a new client.

      4. Finally, keep pushing forward. Keep refining. Don’t stagnate. You’ve spent time, effort, and money putting a marketing analytics system in place. A well-designed system will tell you exactly what you need to do to optimize; don’t ignore it.

    Challenges in Marketing Analytics

    There are, of course, some challenges to be aware of in marketing analytics. First and foremost is the amount of data available. A proper system needs to be in place to sort the data instead of having data analysts do that busy work. The system should also collate the data to make actual apples-to-apples comparisons. Along those same lines, data quality is another serious issue. Your data must be usable. According to Gartner, companies lose an average of $12.9 million annually due to poor data quality.3

    Another challenge is finding the right data scientists. You may have the data, and it may be of good quality, but do you have the right people to analyze it? Forbes recently wrote that there is a serious shortage of available data scientists4, while the US Bureau of Labor Statistics predicts data scientist jobs will grow nearly 28% by 2026.5

    Another challenge that has escalated in recent years involves data privacy and the threat of breaches. In some regions, stricter regulations have been established on what data can be collected and how long it can be stored. Opt-out choices can also hinder data collection. At first glance, having less data to work with may be antithetical to marketing analytics. But savvy marketers will know that this provides an opportunity to focus on the most valuable data—first-hand information from the customer, provided with their consent.

    White Paper
    The Evolution, Future Challenges, And Innovations For Pharma Marketing-Mix Analytics

    Marketing Analytics Tools and Software

    Several marketing analytics platforms are available to guide this hefty but rewarding venture. All-in-one solutions offer search result optimization of content, distribution optimization, A/B testing, scheduling, and much more. Some of the most popular solutions include HubSpot, Sprout Social, MailChimp, Google Analytics, and Semrush.

    Careers in Marketing Analytics

    With so many data job openings, you may wonder what it takes to kick-start a career in marketing analytics. Here are the skills that successful marketing analytics professionals possess.

    Don’t be afraid of large data sets – Managers should be able to generate good-quality reports and not balk at the amount of information at the start of the process. The more data you have, the better your results and insights will be.

    Adaptability – There may be times when a company changes its marketing analytics platform. Good analysts should be able to roll with those shifts.

    Keep current with market  trends – This has double meaning: strong marketing analysts will stay abreast of advancements in marketing technology (MarTech). They will also know the latest buying and social trends and will know how to look for them in the analyses.

    Teamwork makes the dream work – It might be an overused phrase, but it is apt in this industry. Good marketing analysts will know how to collaborate with colleagues. More importantly, they will know how to talk to the C-suite when the time comes to interpret the results of the analyses.

    Case Study
    Marketing Mix Analysis For A Specialty GI Drug Contributed Significant Top-Line Growth For A Top-10 Pharma Company

    Conclusion and Takeaways

    It is not enough to run a promotion. In today’s digital marketplace, there is an ever-increasing din of advertising—too much noise and not enough signal. You have to know where your marketing efforts are making the most impact to cut through the crowd. A proper marketing analytics effort will go beyond the obvious cost-saving measures and ensure that you can reach the right customer when they choose and with the product or service they want. When you and the consumer work together, you will earn brand loyalty. And for a promotional effort, that can be one of its highest measures of success.

    This article is contributed by John Hanafin, Assistant Marketing Manager at Axtria.


    1. Bhandari R, Singer M, van der Scheer H. Using marketing analytics to drive superior growth. McKinsey. June 1, 2014. Accessed June 29, 2023.
    2. Open Learn. A brief history of advertising. Updated March 1, 2019. Accessed June 29, 2023. https://www.open.edu/openlearn/money-management/management/business-studies/brief-history-advertising
    3. Sakpal M. How to improve your data quality. Gartner. July 14, 2021. Accessed June 29, 2023. https://www.gartner.com/smarterwithgartner/how-to-improve-your-data-quality
    4. Janssen N. The data science talent gap: why it exists and what businesses can do about it. Forbes. October 11, 2022. Accessed June 29, 2023. https://www.forbes.com/sites/forbestechcouncil/2022/10/11/the-data-science-talent-gap-why-it-exists-and-what-businesses-can-do-about-it/?sh=1a6bb6fb2398
    5. Rieley M. Big data adds up to opportunities in math careers. U.S. Bureau of Labor Statistics, Beyond the Numbers; 2018: Vol. 7, No. 8. Accessed June 29, 2023. https://www.bls.gov/opub/btn/volume-7/big-data-adds-up.htm

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