Trends & Insights

A Guide To Marketing Intelligence For A Modern Marketer

Published On: 29 Jan 2024

By:Lifesight

A Guide To Marketing Intelligence For A Modern Marketer.webp
Unlock the power of Marketing Intelligence with our comprehensive guide. Learn the pillars, components, and technology driving effective decision-making. Leverage Lifesight for actionable insights, increased ROAS, and intelligent recommendations. Elevate your marketing strategies today!

Marketing decision-making is a complex and nuanced process, often challenging due to the multitude of factors that influence each decision. It's not easy to find your way through different types of data, figure out what market trends mean, and understand how customers act.

When marketers don't have enough data, they often have to deal with the risk of operating in the dark. This tendency to overlook the 'intelligence' aspect can lead to decisions that are not fully informed or grounded in the realities of the market and customer needs.

To combat this, it's crucial for marketers to embrace a more analytical and data-driven approach, shedding light on the shadows of uncertainty and assumption. With the right set of marketing intelligence tools, visualizing the performance of your marketing campaigns and decoding the underlying patterns is not rocket science anymore.

In this guide, we will take you through all the concepts and frameworks related to marketing intelligence to plan your marketing initiatives better.

The Pillars of Marketing Intelligence

Marketing intelligence helps you answer questions like - who engaged with your store, how they engage, and the possible next steps to optimize your marketing campaigns.

Marketing intelligence is a vast concept with no tool to help with end-to-end marketing visualization. You must know the structure and components of marketing intelligence to identify the right set of tools.

Structure of marketing intelligence

Marketing intelligence is the compilation of four different types of intelligence:

  • Market intelligence -refers to all the specific information about a particular industry and its standard metrics. When a brand enters a new market, it is essential to set benchmarks and KPIs depending on the market standards and opportunities. Market intelligence reveals the scope of success and potential risks
  • Customer intelligence - focuses on understanding the target audiences in a particular industry, inside out. Customer intelligence shares insights like client demographics, typical purchase patterns, and common pain points, giving you a fair idea of what to expect from potential customers.
  • Competitive intelligence - gathers data on leading players and competitors in the same market. These datasets can be competitors' strategies, their roadmaps, their organic data, and so on.
  • Product intelligence - focuses on existing products in a market, their features, how they solve customers' pain points, what features they are lacking, and so on. These insights help product teams understand what sort of product they want to develop to satisfy potential customers' needs.
  • Pricing Intelligence - analyzes the pricing strategies of products and services in the market. It looks at how different pricing models affect customer behavior, market demand, and competitive positioning. This intelligence helps businesses in setting competitive yet profitable pricing strategies, ensuring they stay relevant and appealing to their target audience while maintaining healthy profit margins.

Components of marketing intelligence

The significant components of any marketing intelligence tool are the data collector, analyzer, visualizer, and execution.

  • Data collector - The data analyzer identifies data points that align with your business goals and integrates with these data sources to collect different data types like marketing, conversion, and non-marketing data. You need these datasets to establish your marketing campaigns' KPIs and track data better.
  • Data analyzer - The built-in data analyzer performs a simple yet meaningful analysis of all collected data to identify the underlying patterns and how these datasets are correlated. For small businesses with limited datasets, simple data analysis is fairly easy using spreadsheets. For large enterprises, since a large volume of data is involved in the mix, you need advanced machine learning algorithms to perform regression analysis.
  • Data visualizer - Analyzing a large data set is insufficient for decision-making. Marketing intelligence tools have a built-in data visualization dashboard showing real-time data patterns. With data visualization, marketers develop a concrete idea of how their marketing initiatives are performing across multiple touchpoints to
  • Execution - The execution element in a marketing intelligence tool is related to decision-making. It is about clearly showing the current marketing scenario and planning future steps.

The Role of Technology in Marketing Intelligence

Technology is the foundation of modern marketing intelligence initiatives. Marketing intelligence is slowly shifting its focus towards strategic decision-making, and technology is the critical driver for this shift as it makes marketing insights actionable.

Here is how technology plays a crucial role in marketing intelligence:

Artificial Intelligence (AI) and Machine Learning (ML) - AI redefines different aspects of a business, and there are no exceptions when it comes to market intelligence. The integration of AI in marketing intelligence helps brands:

  • Process qualitative insights from a large volume of data through sophisticated natural language processing
  • Use predictive analytics to process structured and unstructured data and uncover the underlying patterns between data attributes
  • Forecast future data trends and next steps based on historical analysis of past data

With increasing digital data footprints, the volume of data available on the internet is inexplicable. The power of big data lies in analyzing this large volume of unstructured datasets and converting them into actionable steps. The primary application of big data in marketing intelligence is creating sample attributes that brands leverage to understand target customers' behavioral patterns.

Gathering and Analyzing Market Data

One of the significant steps in the marketing intelligence process is data collection. Knowing what data to collect and manage makes a lot of difference in the marketing intelligence process.

Here are some of the most effective data-collection strategies for businesses:

  • Surveys - Surveys include a series of questions related to customers' experience with a brand, purchase barriers, objections, and so on. The answers to these questions will help marketers derive critical insights regarding your campaign messaging and marketing mix.
  • Social listening - Tracking the sentiments of social followers and community members through their posts, comments, and engagements helps you gauge their perception of your brand. Social media marketing tools like Hootsuite gather all this information to help you make conclusions related to target audience's emotions, and accordingly, decision-making becomes more accessible.
  • First-party user data - First-party data involves data related to online consumer behavior, like user interactions, purchase history, scrolling data, and saved items. These datasets give you an overview of users' interests and browsing behavior to plan your marketing campaigns efficiently.
  • Competitor research - Analyzing your competitor data also helps in marketing decision-making. Analyzing competitors' marketing, pricing, distribution, and product strategies often helps a brand uncover valuable insights that later contribute to its marketing initiatives.

Consumer Insights and Behavior Analysis

Once you have the necessary datasets, the next step is to analyze them to derive critical insights.

Some of the methods to analyze collected data using marketing intelligence tools are:

  • Statistical analysis - The purpose is to decode what the collected datasets tell you about the customers. While quantitative data can be analyzed directly for statistical significance, qualitative data requires segregation and assigning themes.
  • Exploratory analysis - Behind a marketing intelligence campaign, there should be a distinctive set of questions that marketers want to address. For example - why is conversion not increasing? Why was there a dip in organic impressions last month?

In exploratory analysis, marketers develop hypotheses based on these questions and identify data patterns that might help them find the answers.

Integrating Marketing Intelligence into your Organizational Strategy

After you analyze all the datasets, integrate the insights into your marketing strategy. This process involves two steps - compiling all your findings and preparing the next steps.

  • Compiling all your findings - Create a detailed report involving charts, numbers, and a proper explanation of all your findings. The goal is when a marketer comes across this dashboard, they will be able to conclude easily.
  • Preparing the next steps - If marketing intelligence helps you derive clear conclusions from the collected data, planning the next step is straightforward. All you have to do is convert the findings into actionable steps. For example, if the marketing intelligence dashboard shows that Facebook is the most poorly performing marketing channel, the actionable step will be to reduce Facebook's marketing budget.

However, if the marketing intelligence report doesn't provide all the necessary information to plan a roadmap, you will need to collect more details or perform data analysis again.

Ethical Considerations in Marketing Intelligence

Marketing intelligence is entirely dependent on data. But how you collect these datasets makes a lot of difference. Your data sources must be ethical, and you must ensure that you have users' consent when using first-party user data. Brands like Apple have solid data policies related to third-party provider integrations when collecting user data.

If you are also using a third-party marketing intelligence tool, you must be aware of the following data protection frameworks:

  • General Data Protection Regulation (GDPR) - This framework explains how brands should handle confidential data of the EU member countries. GDPR went into effect on May 25, 2018.
  • Health Insurance Portability and Accountability Act (HIPAA) - This US regulatory framework is focused on protecting medical data and applies to healthcare service providers and healthcare brands.
  • California Privacy Rights Act (CPRA) - CRPA has been in effect since January 1, 2020. It adds a layer of data protection for all businesses dealing with sensitive data related to California residents.

Overcoming Challenges in Marketing Intelligence

Even seasoned marketers don't have it all figured out when marketing intelligence is questioned. Marketing intelligence is associated with multiple challenges that you must address:

Challenge 1: Collecting competitor data

There are multiple small, medium, and big competitors for a new brand starting. It is a challenge to collect appropriate data for each competitor. Even though you are using a marketing intelligence tool, some of the concerning factors are:

  • The volume and variety of the data
  • Confusion related to which data points to select
  • Limited access to competitor platforms

Solution

Use an AI-powered data intelligence tool that collects and streamlines competitor data collection processes based on pre-defined instructions. For example, tools like SEMRush Ahrefs help marketers collect critical competitor data related to a brand's organic performance.

paid competitor analysis through SEMRUSH

Source

Challenge 2: Turning intelligence findings into actionable steps

Despite using an intuitive marketing intelligence dashboard, it is not always easy to turn the findings of the intelligence tool into actionable next steps. This is mainly because the insights you get from the marketing intelligence tool are diverse. For example, if you get insights around websites, paid campaigns, and social platforms - how will you prioritize which platform to target first?

Solution

Invest in an all-in-one marketing measurement tool like Lifesight to help you derive valuable insights from marketing dashboards along with the level of prioritization. Additionally, collaborate with analysts who have prior experience in decoding such patterns.

Make the most of Marketing Campaigns with Lifesight

Choosing the right marketing intelligence tool is a pivotal decision that significantly influences the success of your marketing campaigns. Lifesight stands out as an essential tool in this realm, offering a host of features and benefits designed to enhance your marketing strategies effectively.

Lifesight's automated marketing intelligence platform excels in:

  1. Increasing budget efficiency with improved Return on Ad Spend (ROAS): Lifesight provides deep insights into campaign performance, enabling marketers to allocate budgets more effectively. By analyzing and identifying the most profitable channels and strategies, Lifesight helps in optimizing ROAS, ensuring that every dollar spent contributes meaningfully to the overall campaign success.
  2. Understanding factors that drive incremental profits: Lifesight goes beyond surface-level analytics to delve into what really drives profits in your marketing endeavors. Through detailed analysis, it uncovers the underlying factors contributing to incremental profits, allowing businesses to focus on strategies that deliver tangible financial returns.
  3. Providing intelligent recommendations for simplified Decision-Making: The platform offers actionable recommendations based on data-driven insights, simplifying the decision-making process for marketers. These intelligent suggestions are tailored to align with your specific campaign goals, ensuring that each decision is informed and strategic.

Ready to try out Lifesight's unified marketing measurement platform?

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