Marketing Analytics

What is marketing analysis? Tips and tools

What is marketing analysis? Tips and tools

Marketing analytics is the study of data obtained through marketing campaigns to distinguish patterns between things, such as how the campaign contributes to conversions, consumer behavior, regional preferences, creative preferences, and more. The goal of marketing analytics as a practice is to use these patterns and results to improve future campaigns based on what has been successfully done.

Marketing analytics benefits sellers and consumers. This analysis enables marketers to achieve a higher ROI on their marketing investments by understanding what works in increasing conversions, brand awareness, or both. Analytics also ensures that consumers see more targeted and personalized ads that respond to their specific needs and interests, rather than mass communications that tend to be annoying.

Marketing data can be analyzed using a variety of methods and models depending on the KPIs being measured. For example, brand awareness analysis relies on different data and models than conversion analysis. Some common analysis models and techniques include:

  • Media Mix Models (MMM): Attribution models that analyze data collected over a long period of time.
  • Multi-Touch Attribution (MTA): Attribution models that provide person-level data throughout the buyer’s journey.
  • Uniform Marketing Measurement (UMM): A form of measurement that integrates various standard models, including the MMM and MTA, into overall engagement measures.

The importance of marketing analytics

In the modern marketing landscape, accurate analytics is more important than ever. Consumers have become very selective in choosing which brand media they engage with and which media they ignore. If brands want to capture the attention of the ideal shopper, they must rely on analytics to create personalized and targeted ads based on individual interests, rather than broader demographic associations. This will allow marketing teams to deliver the right advertising, at the right time, in the right channel to move consumers down the sales funnel.

How organizations use marketing analytics

Marketing analytics data can help your business make decisions about things including product and brand updates, and more. It is important to take data from multiple sources (online and offline) to avoid fragmentation. With this data, your team can gain insight into the following:

Product intelligence

Product intelligence involves delving into the brand’s products and how those products compare in the marketplace. Typically, by talking to consumers, surveying target audiences, or engaging them in surveys, organizations can better understand the trade-offs and competitive advantages of their products. From there, teams can better align products with unique consumer interests and issues that help drive conversions.

Customer trends and preferences.

Analytics can tell a lot about your customers. What messages/creations resonate with them? What products are they buying and which products have they researched in the past? Which ads lead to conversions and which ones are ignored?

Product development trends

Analytics can also provide information about the types of product features that consumers want. Marketing teams can pass this information on to product development for future iterations.

Customer Support

Analytics also help reveal areas of the buyer’s journey that can be simplified or improved. Where do your customers struggle? Are there ways to simplify your product or make the payment process easier?

Customer Support

Analytics also help reveal areas of the buyer’s journey that can be simplified or improved. Where do your customers struggle? Are there ways to simplify your product or make the payment process easier?

Messaging and media

Data analysis can determine where marketers choose to display messages to specific consumers. This has become especially important due to the large number of channels. In addition to traditional marketing channels such as print, television, and broadcast, marketers must also understand what digital and social media channels consumers prefer. Analytics answers these key questions: What media should you buy? What generates more sales? What message resonates with your audience?

efficiency

How do your marketing efforts compare to those of your competitors? How would you bridge that gap if there was one? Are there opportunities your competitors are taking advantage of that you may have missed?

Anticipate future results

If you have a deep understanding of why a campaign is successful, you will be able to apply this knowledge to future campaigns to increase your return on investment.

Data Analysis Challenges

While marketing analytics are essential to successful campaigns, the analytics process poses significant challenges due to the vast amount of data marketers can now generate. This means that marketers need to determine the best way to organize data in a digestible format to gain actionable insights.

Some of the biggest marketing analysis challenges we face today are:

  • Amount of Data – Big data emerged during the digital age, allowing marketing teams to record every consumer click, impression, and view. However, this amount of data is irrelevant if it cannot be organized and analyzed to obtain insights that allow for improvements within the campaign. This has left marketers struggling about how best to organize the data to assess its meaning. In fact, research shows that experienced data scientists spend most of their time discussing and formatting data, rather than analyzing it.
  • Data quality: Not only is there a problem with the huge amount of information organizations have to examine, but this data is often seen as unreliable. According to Forrester, 21 percent of respondents’ media budgets were wasted due to poor data quality. This means that $1 out of every $5 has not been used effectively. Over the course of a year, those dollars can accumulate, resulting in a budget loss of $1.2 million and $16.5 million for mid-size companies and at the enterprise level. Organizations need a process to maintain data quality so that employees can benefit from accurate information to make the right decisions.
  • Lack of Data Scientists – Even if companies can access the right data, not many of them have access to the right people. In fact, according to a survey by CMOs, only 1.9% of companies believe they have the right people to get the most out of marketing analytics.
  • Choosing the Reference Models Determining the Model Getting the correct statistics can be a challenge. For example, the multi-touch attribution models and media mix offer very different perspectives: aggregated data focused on the campaign and consumer data at the individual level, respectively. The templates marketers choose will determine the types of ideas they receive. Correlation analysis across many channels can lead to confusion when it comes time to choose the right model.
  • Linked Data – Along the same lines, since marketers collect data from many different sources, they need to find a way to normalize it so that it is comparable. It is particularly difficult to compare online and offline publications, as they are usually measured according to different criteria. This is where standardized marketing measurement and marketing analytics platforms show real value, coordinating data from different sources.

What is a used marketing analysis software?

Marketing analytics software combats these challenges by quickly collecting, organizing, and correlating valuable data, allowing marketers to make campaign improvements in real time.

Modern marketing platforms are valuable for the speed with which large amounts of data can be stored and processed. A major drawback to accessing a large amount of data is that marketers cannot analyze it completely in time to make real-time improvements. This is where the processing power of advanced analytics platforms comes in, allowing marketers to adjust ad design or placement as needed before the campaign ends, maximizing potential ROI. .

In addition, many platforms now take advantage of standardized marketing measurement to normalize and aggregate data across channels and campaigns, simplifying analysis.

Finally, advanced analytics platforms go beyond measuring consumer interactions to provide insights into brand value and how specific audience segments interact with creatives. This helps marketers better determine the ROI for brand building, as well as how to further personalize brand experiences.

Marketing Analytics Software: Features and Capabilities

When implementing a marketing measurement solution, consider these key features and capabilities of your marketing analytics software:

  • Analysis and information in real time
  • Brand scaling capabilities
  • Accurate data at the person level
  • Ability to link online and offline reference metrics
  • Contextual customer and market insights
  • Annual media plan recommendations

Skills Needed by Marketing Analytics Managers

As marketing teams look to conduct high-quality analytics that lead to more engaging and profitable campaigns, they need to focus on hiring analytics managers who can:

  • Performing quality analytics – First and foremost, the analytics manager must have experience evaluating large data sets to differentiate insights, including buying patterns and engagement trends within the target audience.
  • Make recommendations for improvement – Once you have insights from the data, it is critical to be able to create recommendations for improving poorly performing campaigns based on trends. For example, data may show that a consumer interacts with brand content only at night, informing a change in strategy to display advertising on the consumer’s way home, rather than in the morning.
  • Understanding Consumer and MarTech Trends Analytics managers must also stay on top of consumer and MarTech trends. Understanding consumers’ demands for a holistic, multi-channel experience and how shoppers interact with virtual and augmented reality will certainly play a role in determining next steps for improvement opportunities.
  • Working with Analytics Tools Next, Analytics Managers need to collaborate and get comfortable with different automation tools and analytics platforms, given the vital role these tools play in reducing time from consumer engagement to customer insight. consumer.
  • Collaborate with stakeholders – Ultimately, analytics team members need to be able to use the data they work with to tell a compelling story to stakeholders and explain ways other departments, such as sales or product development, can use it. These results to increase participation. and transfers.

How to start the marketing analysis process

If you’re looking to improve your analytics capabilities, here are four steps to take at the start of your program:

Understand what you want to measure

There are many aspects of a marketing campaign that you can measure: conversion rates, leads, and brand awareness, to name a few. Understand the problem you are trying to solve or the idea you are trying to gather as you begin to analyze your data.

Create a standard

What does a successful campaign look like? This will determine the types of data and metrics that marketers collect. For example, if the goal is to increase brand awareness, the criteria for success might be to increase the percentage of brand loyalty that appears on a customer’s dashboard, rather than clicking or appearing online.

Evaluate your current capabilities

What is your company doing today? What are your weaknesses Whether you’re evaluating the results of offline campaigns or identifying which media are most likely to convert, understanding these weaknesses can help you strengthen your program.

Implement a marketing analytics tool

Marketing analytics tools will become increasingly important as consumers become more selective and data sets grow. Advanced platform, such as marketing measurement and optimization. The platform uses standardized marketing metrics to help marketers determine which messages resonate and what types of media are converting. This provides an overview of which campaigns have been successful and which are not.

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