How to Use Marketing Data Analytics to Make Better Business Decisions

The use of data analytics in marketing is becoming more and more essential. As you run campaigns, there are always things that you can learn about your customers from the clicks they make, as well as likes, opens, and shares.

Data is king. But true power lies in processing and analyzing the data to generate insights that ultimately lead to better decisions on future strategies.

This blog post explains what marketing data analytics is, its challenges, steps, and tools that lead to better sales and marketing intelligence. We’ll also explore how it works and how to use it to improve your business results. Let’s get going!

What is marketing data analytics and why do you need it?

Marketing poses its challenges, especially for newcomers embarking on new ad campaigns or experimenting with diverse strategies to engage prospective customers.

In the absence of analytics, assessing the efficacy of marketing endeavors becomes a daunting task, leading to inefficiencies and potential adverse outcomes.

While certain organizations may experience apparent triumphs sans analytics, comprehending the underlying reasons behind successful campaigns can remain elusive, often attributed to mere luck. Conversely, when marketing endeavors falter, the lack of insights into the root causes of failure exacerbates the situation.

Now, let’s delve into the provided definition.

Marketing and data analytics defined

Marketing data analytics involves the meticulous examination of marketing data to derive insights that can drive actionable decisions. This encompasses pinpointing pivotal marketing metrics, ensuring the acquisition of dependable data, monitoring these metrics consistently, and leveraging the findings to enhance forthcoming strategies.

While “marketing analytics” may sound confined to numerical data, it transcends mere figures. It constitutes a comprehensive process integrating human expertise, advanced tools, and technological resources to achieve marketing objectives effectively.

Employing marketing data analytics empowers you with the ability to comprehend the efficacy of your efforts and the underlying reasons behind it. Mastering this process enables you to fully harness its potential.

The Importance of Data Analytics in Marketing

Organizations utilize marketing data analysis in various ways. Let’s examine some common examples:

Product Intelligence

Analytics aid in tracking customer interactions with products, facilitating enhancements in areas such as pricing and features to better align with customer needs.

Customer Trends and Preferences

By comprehending customer trends and preferences, adjustments to the marketing mix can be made to better resonate with the target audience. Additionally, this information enables customer segmentation and the creation of targeted marketing campaigns.

Customer Support

Utilizing analytics improves customer support by pinpointing areas where customers face challenges or require assistance. This insight informs the development of training materials or enhancements in self-service options.

Messaging and Media

Data analytics provide insights into the most effective messages and media for reaching and converting customers. This knowledge drives the creation of more targeted and impactful marketing campaigns.

Competition

Marketing data analytics allows tracking of competitors and understanding their strengths and weaknesses. Businesses leveraging data analytics gain a competitive edge over those that do not.

Predict Future Results

Predictive analytics enable the creation of forecasting models, analyzing current and historical data to project future outcomes. This analysis aids in understanding the likelihood of lead conversion and their interest levels in specific content or promotions. By discerning the impact of offers on different segments, such as age groups, organizations can optimize budget allocation, enhance revenue, and improve the effectiveness of targeted ad campaigns for acquiring new customers.

Benefits of Data Analytics in Marketing

Data analytics is increasingly vital in today’s business landscape. Here are some reasons why:

Better marketing decision-making

Analytics provide an objective understanding of marketing campaigns, enabling informed decisions based on factual data rather than speculation. Employing analytics both before and after decision-making facilitates tracking campaign success/failure and optimizing future plans.

Increased revenue

Marketing analytics empowers understanding of customer needs, enabling targeted messaging at opportune moments, consequently bolstering revenue streams significantly.

Time and cost savings

Data analysis identifies the most effective marketing strategies, saving time on future projects and ensuring resources are not squandered on unproductive efforts.

Impact on other areas

Marketing analytics extends its influence to various facets such as enhancing brand recognition, elevating content quality, optimizing channels, and refining customer understanding.

The Challenges of Marketing Data Analytics

Creating an analytics process that effectively measures and tracks pertinent metrics poses complexities for many companies. The challenges encompass a wide array of factors. Let’s delve into some of the significant hurdles below.

The volume and variety of marketing data

In today’s multifaceted marketing landscape, the abundance of digital channels and diverse campaigns generate vast amounts of data consumed across numerous devices. While this wealth of data is advantageous, marketers often grapple with the overwhelming task of managing and extracting insights from this data deluge.

Lack of resources

An ongoing challenge is the necessity for additional resources to harness the potential of data analytics. Prioritizing the recruitment of adequately trained personnel skilled in analytics becomes imperative. Moreover, effective utilization of marketing data analytics demands substantial investments in terms of time and financial resources, a luxury many businesses may not afford, thereby limiting its efficacy.

Lack of knowledge and skills

Many marketing organizations encounter skill gaps hindering the proficient use of data analytics. Effective utilization of marketing data analytics necessitates expertise in statistical analysis, data visualization, technical proficiency, as well as a deep understanding of customers and products. These competencies are indispensable for deciphering data and extracting actionable insights.

Difficulty in identifying and tracking meaningful analytics

One of the most formidable challenges for marketers lies in identifying metrics that truly align with strategic objectives rather than relying on readily available metrics or conventional marketing processes. This necessitates a deliberate approach starting with a thorough understanding of the strategic goals pursued by marketing initiatives. The pursuit of optimal metrics often entails navigating complex data sets, amalgamating and refining data to derive metrics that accurately reflect performance.

Despite these challenges, marketing data analytics remains a potent tool for enhancing marketing strategies. For assistance with marketing analytics, consider engaging Coupler.io, a company offering comprehensive data analytics consulting services, data visualization, and more.

Data Analytics in Marketing — Examples

Marketing data analytics aims to monitor the performance of marketing channels, offering insights into lead generation, customer conversion, and other metrics. Successful applications include enhancing understanding of customer behavior, optimizing engagement and retention, and crafting personalized customer journeys.

An illustrative instance of data analytics in marketing is Tradezella’s experience, demonstrating how strategic marketing communication can bolster product adoption and drive revenue growth.

Initially, Tradezella tracked basic business metrics such as ARR and churn but lacked comprehensive insight into user activity from a marketing standpoint, hindering efforts to reengage inactive users effectively.

Coupler.io’s data automation and analytics specialists addressed this challenge by delineating distinct funnel stages and identifying markers for user churn, facilitating targeted marketing efforts at various stages. Consequently, this led to a significant increase in activation rates from 28% to approximately 65%.

How can data analytics improve marketing strategy?

Marketing strategy can be significantly enhanced through the utilization of data analytics. While some businesses may operate without a well-defined strategy or analytics framework, particularly startups and small enterprises with limited budgetary allocations for analytics, their chances of success are diminished. Analytics serves as a guiding beacon, providing consistency and direction to marketing endeavors. Operating without analytics is akin to navigating blindly, akin to driving a vehicle without a dashboard.

By implementing data analytics effectively, businesses gain insights into their current marketing performance and identify areas for improvement. Analytics serves as a compass, guiding strategic decisions towards achieving better outcomes.

Moreover, analytics plays a pivotal role in continually monitoring the efficacy of marketing strategies and facilitating necessary adjustments. This iterative process ensures a steadfast commitment to delivering superior results.

How to Use Data Analytics in Marketing

The marketing analytics process follows a continuous cycle of measurement, analysis, and improvement. The steps outlined below can aid in working efficiently and effectively.

Step 1: Identify Metrics

The initial step involves determining the metrics to utilize, which align with your marketing strategy. Different marketing organizations may rely on various metrics to support their processes.

Common Metrics Used in Marketing Data Analytics:

  • Website Performance Metrics

Examples include traffic, most visited pages, search ranking, unique visits, bounce rate, and conversions.

  • Digital Ads Metrics

Metrics such as impressions, click-throughs, conversion rate, LTV, ROI, and engagement rate are essential.

  • Social Media Metrics

Key metrics in this category may include total reach, likes, views, comments, shares, followers, and subscribers.

  • Email Marketing Metrics

This category encompasses measures like open rate, click-through rate, and bounce rate.

Optional Metrics:

  • Marketing Team Performance Metrics

These gauge the productivity of the marketing team and may include metrics like impressions generated, net profit, and ROI.

  • Lead Generation Metrics

Metrics here assess the effectiveness of marketing lead generation efforts. Examples include new leads by channel, new leads by campaign, new opportunities created, qualified leads created, conversion rates, and cost per lead.

  • Customer Metrics

Metrics in this category include customer lifetime value (CLV), customer satisfaction, customer retention rates, Net Promoter Score (NPS), and customer churn rates.

Step 2: Gather Marketing Data for Analysis

During this phase, you’ll gather data from various sources, each contributing different types of data.

Your website serves as a primary data source, as it’s often the initial touchpoint for customers seeking information about your product or service.

Additionally, data from sources like CRM systems and marketing automation tools may be necessary.

Implementing systems to capture metrics facilitates an understanding of your business’s current status. Tools like Google Analytics enable the monitoring and optimization of website performance.

Aggregating data from diverse sources can be labor-intensive. Automation streamlines this process, ensuring efficiency and accuracy.

Automated platforms facilitate the extraction and integration of marketing data from multiple sources, allowing seamless consolidation. This data can then be exported to various destinations, including data warehouses and visualization tools.

Creating dashboards and reports for web analytics, sales, finance, e-commerce, and marketing becomes more manageable with these automated processes.

Expert assistance is available for refining data management, analytics, and visualization strategies to suit specific business needs.

Step 3: Analyze

Now that you’ve gathered the data, the subsequent step involves analyzing and visualizing the metrics to extract correlations and insights.

Dashboards serve as visual summaries of metrics, offering an overview of performance. For more granular insights, reports can be utilized.

A well-designed marketing dashboard provides a comprehensive snapshot of the marketing team’s health and performance. Utilizing appropriate charts and graphs facilitates effective communication regarding areas of success and areas requiring improvement.

Expert assistance may be sought to optimize dashboard design, ensuring that desired insights are conveyed efficiently.

Various visualization tools can be employed to build marketing dashboards, offering concise summaries of metrics for quick reference and analysis.

Step 4: Take improvement actions

Marketing metrics offer valuable insights into the state of affairs and potential areas for enhancement. In this step, it’s crucial to identify actions and modifications likely to drive improvement. Regardless of the thoroughness of the analysis, its value lies in guiding actionable steps.

Is improvement always necessary?

Certainly!

In principle, any process can benefit from refinement. While some improvement actions may be readily apparent, others might require deeper consideration.

Moreover, this step isn’t solely about addressing underperformance but also about replicating successful strategies. By doing so, one can consistently achieve better outcomes in future endeavors.

Tools Used in Data Analytics for Marketing

Marketing analytics involves a multifaceted process, yet it can be simplified with suitable tools and technology.

Utilizing the appropriate tools can streamline tasks, enhance understanding of data, automate processes, segment audiences, and provide real-time, accurate insights, thereby fostering collaboration.

Let’s explore some of the most popular and beneficial marketing analytics tools, categorized as follows:

Website Analytics Tools

  • These tools enable the capture and tracking of various website metrics, including total page views, unique visitors, and time on site.
  • Notable examples include Google Analytics, Adobe Analytics, and Mixpanel.

Business Intelligence (BI) and Data Visualization Tools

  • BI tools facilitate the extraction, transformation, and loading of raw data from multiple sources to a destination, often presented in the form of dashboards or visualizations.
  • Prominent BI tools include Tableau, Microsoft Power BI, Looker Studio, Oracle Business Intelligence, and SAP Business Objects.

Cohort Analysis Tools

  • Cohort analysis tools assess how metrics evolve over time, aiding in improved customer retention and precise lifetime value estimates.
  • These tools encompass BI tools mentioned earlier, along with KISSmetrics, Heap, among others.

Social Media Analytics Tools

  • Tools in this category track various social media metrics, such as engagement, reach, and impressions.
  • Popular choices include Sprout Social and Hootsuite.

Marketing Automation Tools

  • These software platforms automate and measure marketing tasks and workflows, encompassing lead management, email marketing, campaign management, and analytics.
  • Examples include HubSpot, Marketo, Pardot, AWeber, and MailChimp.

Search Engine Optimization (SEO) Tools

  • A variety of SEO tools assist marketers in enhancing their website’s ranking in search engine results pages (SERPs), offering features like keyword research and link-building.
  • Common options are Ahrefs, SEMRush, Google Search Console, and Moz.

The list provided offers just a glimpse of the myriad marketing analytics tools available. Selecting the right tools involves defining your requirements, researching potential options, comparing features prioritizing ease of use, and reviewing pricing to make an informed decision.

Data Analytics for Enhanced Marketing Decisions – Closing Thoughts

Marketing data analytics serves as a crucial tool for making well-informed business decisions. By grasping the essence of marketing data analytics and its application, you can make decisions that drive revenue growth.

Although challenges exist in collecting and analyzing marketing data, Coupler.io provides a seamless solution. Their data analytics consulting service aids in initiating or elevating existing efforts to the next level.

For further insights on streamlining marketing analytics, explore our article on the top 12 marketing reporting templates.