Marketing analytics is the use of data to evaluate the effectiveness and success of marketing activities. By integrating marketing AI into your business strategy, you can gather deeper consumer insights, optimize your marketing objectives, and get a better return on investment.
Marketing analytics benefits both marketers and consumers. This analysis allows marketers to achieve higher ROI on marketing investments by understanding what is successful in driving either conversions, brand awareness, or both. Analytics also ensures that consumers see a greater number of targeted, personalized ads that speak to their specific needs and interests, rather than mass communications that tend to annoy.
Marketing data can be analyzed using a variety of methods and models depending on the KPIs being measured. For example, analysis of brand awareness relies upon different data and models than analysis of conversions. Some popular analytics models and methods include:
- Media Mix Models (MMM): Attribution models that look at aggregate data over a long period of time.
- Multi-Touch Attribution (MTA): Attribution models that provide person-level data from across the buyer’s journey.
- Unified Marketing Measurement (UMM): A form of measurement that integrates various attribution models including MMM and MTA into comprehensive engagement metrics.
The Importance of Marketing Analytics
In the modern marketing landscape, accurate data is more important than ever. Consumers have become highly selective in choosing the branded media they engage with and the media they ignore.
If brands want to catch the ideal buyer’s attention, they must rely on accurate data to create targeted personal ads based on individual interests, rather than broader demographic associations. This will allow marketing teams to serve the right ad, at the right time, on the right channel to move consumers down the sales funnel.
How Organizations Use Marketing Analytics
Marketing analytics data helps your business make decisions on everything from ad spend to product updates, branding and more. To give yourself a true 360 degree view of your campaigns and be sure you are making the right decisions, it's important to take data from multiple sources (online and offline). Using this data, your team can gain insights into the following:
Product intelligence involves taking a deep dive into the brand’s products as well as analyzing how those products stack up within the market. Typically done by speaking to consumers, polling target audiences or engaging them with surveys, organizations can better understand the differentiators and competitive advantages of their products. From there, teams can better align products to the unique consumer interests and problems that help drive conversions.
Customer Trends and Preferences
Analytics can tell a lot about your consumers. What messaging / creative resonates with them? Which products are they buying and which have they researched in the past? Which ads are leading to conversions and which are ignored?
Product Development Trends
Analytics can also offer insight into the types of product features consumers want. Marketing teams can pass this information on to product development for future iterations.
Analytics also helps uncover areas of the buyer’s journey that could be simplified or improved. Where are your clients struggling? Are there ways you can simplify your product or make the check-out process easier?
Messaging and Media
Data analysis can determine where marketers choose to display messages for particular consumers. This has become especially important due to the sheer number of channels. In addition to traditional marketing channels such as print, television and broadcast, marketers must also know which digital channels and social media networks consumers prefer. Analytics answers these key questions:
- What media should you be buying?
- Which are driving the most sales?
- What message is resonating with your audience?
How do your marketing efforts compare with the competition? How can you close that gap if there is one? Are there opportunities your competitors are capitalizing on that you may have missed?
Predict Future Results
If you have a thorough understanding of why a campaign worked, you’ll be able to apply that knowledge to future campaigns for increased ROI.
The Challenges of Data Analysis
The biggest challenge of the analysis process is understanding and utilizing the immense quantity of data marketers. This means that marketers must determine how to best organize the data into a digestible format to derive actionable insights.
Some of the biggest marketing analytics challenges faced today are:
- Data Quantity: Big data emerged during the digital age, enabling marketing teams to record every consumer click, impression and view. However this quantity of data is irrelevant if it cannot be structured and analyzed for insights that allow for in-campaign optimizations. This has left marketers grappling with how to best organize data to evaluate its meaning. In fact, research shows that experienced data scientists spend the majority of their time wrangling and formatting data, rather than analyzing it
- Data Quality: Not only is there a problem in terms of the vast information organizations must sift through, but this data is often viewed as unreliable. According to Forrester, 21 percent of respondents’ media budgets were wasted due to poor data quality. This means one dollar out of every 5 dollars was not being utilized effectively. Over the course of a year, these dollars can add up, resulting in $1.2 million dollars and $16.5 million dollars of wasted budget for mid-size and enterprise level firms. Organizations need a process to maintain data quality, so that employees can leverage accurate information to make the right decisions.
- Lack of Data Scientists: Even if companies have access to the right data, many don’t have access to the right people. In fact, according to a survey by The CMO, only 1.9% of companies believe they have the right people to fully leverage marketing analytics.
- Selecting Attribution Models: Determining the model that provides the right insights can be tricky. For example, media mix modeling and multi-touch attribution offer entirely different insights – aggregate campaign-focused data and person-level consumer data respectively. The models that marketers choose will dictate the types of insights they receive. Engagement analysis across so many channels can create confusion when it’s time to choose the right model.
- Correlating Data: In this same vein, because marketers are collecting data from so many different sources, they must find a way to normalize it to make it comparable. It’s especially challenging comparing online and offline engagements, as they are typically measured by different attribution models. This is where unified marketing measurement and marketing analytics platforms demonstrate true value, organizing data from disparate sources.
What is Marketing Analytics Software Used For?
Marketing analytics software combats the above challenges by collecting, organizing and correlating valuable data quickly, allowing marketers to make real-time campaign optimizations.
Modern marketing platforms are valuable for the speed at which they can store and process massive amounts of data. One of the major drawbacks of having access to so much data is that marketers cannot possibly parse through it all in time to make real-time optimizations. That’s where the processing power of advanced analytics platforms comes into play, enabling marketers to adjust creative or ad placement as needed before the campaign ends, enhancing potential ROI.
Additionally, many platforms including marketing Evolution, leverage unified marketing measurement, to normalize and aggregate marketing data from across various channels and campaigns, simplifying analysis.
Finally, advanced analytics platforms go beyond measuring consumer engagements to offer insights into brand equity and how certain audience segments react to creative elements. This helps marketers better determine brand-building ROI, as well as how to further personalize branded experiences.
Marketing Analytics Software - Features & Capabilities
When implementing a marketing analytics solution, consider these key features and capabilities:
- Real-Time Analytics and Insights
- Brand Measurement Capabilities
- Granular, Person-Level Data
- The Ability to Correlate Online and Offline Attribution Metrics
- Contextualized Customer and Market Insights
- Annual Media Plan Recommendations
Implementing Marketing Analytics Into Your Program
- Make A Plan: Set goals and create benchmarks for yourself so you can accurately and effectively report your data.
- Implement Your Plan: Focus on driving your data to the correct places in your business where you will get the most benefit out of it. Having the right team in place is key.
3. Optimize Your Plan: Once you implement your plan, make adjustments to your team or data flow based on your results in order to move leads down the sales funnel quicker.
Skills That Marketing Analytics Managers Need
As marketing teams seek to conduct quality analysis that lead to more engaging, profitable campaigns, they must focus on employing analytics managers who can:
- Conduct Quality Analyses: First and most obvious, an analytics manager must have experience evaluating large data sets to discern insights including buying patterns and engagement trends within the target audience.
- Make Optimization Recommendations: Once data insights are gained, the ability to come up with recommendations to improve underperforming campaigns based on trends is crucial. For example, data may show that one consumer engaged with branded content only in the evening, informing a strategy shift to serve the ad on the consumer’s commute home, rather than the morning commute.
- Understand Consumer and MarTech Trends: Analytics managers should also stay abreast of consumer and MarTech trends. Understanding consumer demands for a seamless omnichannel experience and how buyers are engaging with augmented and virtual reality will certainly play a role in determining next steps for optimization opportunities.
- Work with Analytics Tools: Next, analytics managers must be onboarded and comfortable with various automation tools and analytics platforms, because of the vital role these tools play in reducing the time from consumer engagement to consumer insight.
- Collaborate with Stakeholders: Finally, members of the analytics team must be able to use the data they work with to tell a compelling story to stakeholders, and demonstrate the ways other departments, such as sales or product development, can use these findings to drive engagement and conversions.
How to Start the Marketing Analytics Process
If you’re looking to enhance analytics capabilities, here are four steps to take at the outset of your program:
1. Understand What You Want to Measure
There are many aspects to a marketing campaign you can measure: conversion rates, leads captured and brand recognition, to name a few. Understand the problem you are trying to solve or insight you are trying to glean when beginning to analyze your data.
2. Establish a Benchmark
What does a successful campaign look like? This will determine the types of data and metrics marketers collect. For example, if the goal is to increase brand awareness – the success benchmark might be an increased percentage of brand loyalty demonstrated in a customer panel, rather than an online click or impression.
3. Assess Your Current Capabilities
What is your company doing today? What are your weak spots? Whether assessing offline campaign results or identifying media most likely to convert, understanding these weak points can help you strengthen your program.
4. Deploy a Marketing Analytics Tool
Marketing analytics tools will increase in importance as consumers become more selective and datasets grow. An advanced platform, such as our Marketing Measurement and Optimization Platform uses unified marketing measurement to help marketers identify the messages that resonate and the types of media that converts. This provides a holistic view of which campaigns are successful and which are underperforming in real time.
Having the right marketing analytics solution in place is key to a successful marketing program. By understanding where your audience is engaging and what is truly driving sales, you can make sure you are putting your money in the right place and improve ROI.
Additional Tips and Resources
- The Role of Marketing Analytics in Identifying Creative Needs
- Marketing Attribution Models: How Did We Get Here? A History of Measurement
- Inaccurate Attribution is…. Bad Attribution
- Why Marketing Analytics Software Must Be a Budget Priority to Achieve Goals