The Objective of Marketing Analytics
Obstacles to effective marketing analytics
- Too Much Data: Marketers often face an overwhelming amount of data, leading to confusion about which data is important and how to derive actionable insights.
- Key Questions: Common questions arise such as:
- Which data is important?
- Am I measuring the right things?
- How do I find insights from the data?
- How do I connect actions from the data?
- How do I know what to do?
- Lack of Formal Training: Many marketers lack formal training in digital marketing analytics, resulting in repetitive and ineffective reporting practices. They often rely on copying previous reports without truly understanding the data.
- Survey Insights: A recent survey highlighted that marketers often lack the proper training and knowledge to perform marketing analytics effectively. Key obstacles include:
- Inability to prove return on investment (ROI)
- Dealing with useless metrics
- Misalignment of KPIs: There is a discrepancy between the most important business KPIs (like ROI and customer lifetime value) and the most used KPIs (like CPM, CPC, unique reach, and site visits). This indicates a fundamental misunderstanding about data.
- Communication Barriers: Without a common vocabulary and accurate terminology, marketers struggle to communicate effectively with each other and with executive teams. This leads to the creation of reports that are cluttered with excessive charts and graphs, obscuring important information.
- Approach to Analytics: Matt Bailey emphasizes the need to understand and read the analytics map. He advocates for:
- Developing a data and measurement strategy aligned with business objectives
- Identifying and defining the necessary data based on business objectives
- Applying skills for effective measurement, comparison, and analysis
- Outcome: By following a structured framework, marketers can create shorter, more direct reports packed with persuasive and compelling information that the executive team will appreciate
Identify your business objectives for marketing analytics
- Purpose of Analytics: The first step in building an analytics strategy is to identify the purpose, which is the objective of your company or organization, typically set by the CEO or executive team.
- Examples of Objectives:
- New B2B Company: Increase customers.
- Established B2B Company: Decrease cost per lead.
- Direct to Consumer Company: Increase sales.
- Importance of Business Objectives: Understanding the business objective is crucial for both marketing and analytics. It sets the direction for your strategy.
- Measurement Plan Worksheet: Use the exercise files to download the measurement plan worksheet. The first column is where you define your business objective.
- Defining “Good Leads”:
- Quantity: Focus on the number of leads produced.
- Cost: Emphasize budget and cost per lead.
- Quality: High lead to customer conversion rate.
- Different Approaches Based on Goals:
- Number of Leads: Focus on channels and tactics that produce high numbers of leads, with less emphasis on cost.
- Cost per Lead: Emphasize financial aspects, evaluating channels and tactics based on CPM and CPC to reduce costs.
- Quality of Leads: Measure throughout the entire process, from lead acquisition to sales, to identify key factors influencing lead quality.
- Primary Business Objective: Defining your primary business objective is the first step. It sets the destination and reveals the paths necessary to achieve it.
Define objectives, goals, metrics, and KPIs
- Language Barriers: Different terminologies in marketing, analytics, and executive teams can cause confusion. Establishing a common language is crucial.
- Objectives: The overall business purpose, such as selling products, making money, or increasing profits.
- Strategy: The high-level plan to achieve the objective. Examples include digital marketing, inbound marketing, or content marketing. Strategies are not specific to platforms like Facebook or YouTube; those are tactics.
- Tactics: Methods to enact the strategy, such as gaining high-quality leads through content marketing using SEO, paid media, and social media distribution.
- Goals: Actions visitors can complete on your website or app that contribute to your objectives. These can include purchases, registrations, or subscriptions. Also known as conversion actions.
- Conversions:
- Macro Conversions: Directly impact objectives with financial impact (e.g., leads, sales, subscribers).
- Micro Conversions: Indirectly contribute to goals (e.g., page views, video views, PDF downloads, post comments).
- Metrics: Data points without context, such as page views. Metrics alone have no value without understanding their contribution to goals or objectives.
- Key Performance Indicators (KPIs): Metrics in the context of achieving goals and objectives. For example, the click-through rate in paid search ads indicates the quality and effectiveness of the ad in generating visits. KPIs provide feedback along the customer journey but not the entire journey to conversion.
- Importance of Context: Numbers like page views need context to be valuable. Without understanding their business value, they remain trivial facts.
- Application: Using the right terminology helps in effectively communicating and understanding analytics, making it easier to connect data to actionable insights.
Implement business objectives for strategy
- Initial Challenges: Marketers often feel overwhelmed by analytics interfaces filled with charts, graphs, and unfamiliar terminology. Common questions include:
- What is important?
- How do I find it?
- First Step in Analytics: Know what you are looking for by defining the business objective. This is the foundation for developing a marketing strategy.
- Example Businesses:
- B2B Company (Read30Tech): Increase revenue.
- Olive Oil E-commerce Company: Increase revenue.
- Developing Marketing Strategy:
- Objective: Increase revenue.
- How to Achieve It: Options include acquiring new customers, nurturing existing relationships, upselling, cross-selling, and developing a loyalty program.
- Primary Objective: Increase leads. This is the most important measurement data and will be the metric by which you are ultimately measured.
- High-Level Methods to Meet Objectives:
- Gain New Leads: Measure by the number of leads acquired.
- Optimize Lead Generation Process: Increase conversion rate, evaluate lead rate, and assess content influencing leads.
- Create Lead Referral Program: Build customer loyalty and referrals.
- Execution of Methods:
- Gain New Leads: Use content marketing and inbound marketing.
- Optimize Lead Generation: Evaluate customer experience and develop conversion optimization.
- Create Referral Program: Focus on customer loyalty and referrals.
- Shifting Objectives: If the objective shifts to increasing profitability, the strategy and data needs change:
- Gain New Customers: Measure cost per acquisition and target acquisition cost.
- Increase Customer Spend: Measure current average spend and target increase.
- Build Loyalty and Referrals: Use customer relationship management software to personalize communications, increase education, and drive more sales through recognition and rewards.
- Formulating Strategy: Define how to meet business objectives and set accompanying goals and KPIs to show success. This ensures clear measurements and specific, custom goals and KPIs.
A Clear Analytics Strategy Creates Clear Measurements
Create measurements that connect to objectives
- Clear Direction and Strategy: Without a clear direction or strategy, it’s impossible to have effective analytics. Mixed messages and unclear objectives can lead to confusion.
- Matching Objectives with Campaigns:
- Awareness campaigns are meant to build visibility, not sales. The performance goal is to increase awareness, not ROI.
- If ROI is the objective, campaigns should be designed to lead to financial outcomes like sales.
- Strategic Plan Development:
- Example: Acquiring new customers through content marketing to drive inbound leads.
- Methods and tactics are developed based on this strategy.
- Content Marketing Focus:
- Content marketing aims to answer questions and educate potential customers early in their decision-making process.
- This increases visibility and improves chances of acquiring leads or customers.
- Primary Methods:
- Search Engines and Paid Search Ads: Used to drive traffic to content that answers questions.
- Videos and Guides: Developed to showcase destinations, customer experiences, and decision-making guides.
- Driving Traffic: Content is distributed across platforms and channels to drive people back to the website.
- Objective and KPIs:
- If the objective is to gain new customers, the primary measurement is net new customers created.
- KPIs (Key Performance Indicators) are crucial as they guide and influence decisions and budgets.
- KPI Analytics:
- Leads from Various Sources: Organic search, paid search, social media, email, or combined sources.
- Profitability Objective: Includes cost per lead, revenue generated, and campaign costs for each channel.
- Comparison and Benchmarking:
- Establish target costs to compare each channel’s effectiveness.
- Identify cost-effective lead generation channels and avoid high-cost, low-production ones.
- Framework for Marketing and Measurement:
- Clear objectives lead to the development of strategy and KPIs.
- This framework provides a clear line back to the objective and improves marketing and measurement.
Focus on marketing tactics, not channels
- Shiny Object Syndrome: Marketers often get distracted by new platforms (e.g., TikTok) without strategic thinking. This is termed “shiny object syndrome”.
- Strategic Thinking:
- Focus on the content to be created, its purpose, target audience, and intended outcome before considering the platform.
- Platforms (e.g., Facebook, Instagram, YouTube) are tools to reach specific audiences with targeted messages.
- Platform Metrics:
- Metrics like impressions, views, likes, comments, and shares are activity metrics specific to platforms.
- These metrics often have different definitions across platforms and may not align with business objectives.
- Reporting Issues:
- Copying and pasting platform-generated reports can clutter important data with irrelevant metrics.
- Executive teams are interested in metrics that align with business objectives, such as leads generated and business impact, not just engagement metrics.
- Connecting Metrics to Strategy:
- Platform data is useful for evaluating campaign performance and comparing channel performance.
- Important to understand how each platform contributes to the overall marketing mix, customer journeys, and progression to value-based actions.
- Communication with Executives:
- Marketers need to present data that answers executive questions like “How many leads were created?” and “How much business did it generate?”.
- Avoid overwhelming reports with excessive engagement data that do not answer these key questions.
- Speaking the Executive Language:
- Learn to translate platform metrics into business-relevant insights.
- Focus on metrics that show the impact on business objectives rather than just activity.
Establish target outcomes and value for your analytics
- Monetary Value in Reports: Reports should show the business value or revenue created, not just activities and engagement metrics.
- Desired Outcomes:
- B2B: Generating leads.
- B2C: Generating new customers.
- The goal is to map these outcomes back to the primary objective of increasing revenue.
- Metrics to Use:
- Visits to conversion.
- Clicks or visits to conversion.
- Conversion by media type or channel.
- Number of leads generated and their value.
- Leads by channel, cost per lead per channel, and revenue generated by channel.
- Value of Leads:
- Know the value of a generated lead or a newly acquired customer.
- Example: If 10 leads result in one sale worth $2,000, each lead is valued at $200.
- Micro Conversions:
- Attach value to actions like video views, downloads, and registrations.
- These actions, known as micro conversions, provide value to visitors and financial benefits to the business.
- Goal Value Calculation:
- Adding goal and goal value to analytics reports helps in apportionment.
- Example: Channels bringing visits and conversions show goal completions and page value, representing the estimated value based on goal contributions.
- Speaking the C-Suite Language:
- Using monetary values in outcome reporting aligns with the language of the executive team, making reports more impactful and understandable.
Establish comparison and benchmark data
- Value Neutral Data: Data itself is neither good nor bad; it gains value through comparison.
- Importance of Comparison:
- Use averages, baselines, or goals to provide context for data.
- For example, average metrics at the top of a graph help in making value judgments.
- Steps for Effective Comparison:
- Look at the Average:
- Example Metrics:
- Bounce Rate: 79-80%
- Time on Site: 1 minute 20 seconds
- Pages Viewed: 1.5 pages
- Conversion Rate: 1.25%
- Example Metrics:
- Identify Outliers:
- Compare pages to find those performing above or below average.
- Example: A page with a 93% bounce rate indicates less engagement.
- Evaluate the Page:
- Understand the intended purpose of the page.
- Determine if low engagement is due to the page’s purpose or an issue.
- Look at the Average:
- Insight and Action:
- Insight identifies the problem and explains why it is a problem.
- Derive actions to improve or optimize based on insights.
- Using Baselines:
- Baselines can be past business performance, campaign averages, or industry averages.
- Use them to find and address tactics or processes that don’t measure up.
- Focus on Outliers:
- Look for substantial departures from the average.
- These areas are easiest to fix and can leverage success in other areas.
Implement Analysis Methods
Leverage the best analytics skill: Asking questions
- Critical Skill: The most valuable data skill for a marketer and analyst is the ability to ask questions, not math.
- Evaluating Goals:
- Before taking action, evaluate past performance.
- Ask questions about the goal:
- How many registrations are we to increase by?
- What is the timeframe?
- Is the goal realistic based on past performance, budget, and audience?
- Analyzing Performance:
- Assess average registrations and attendees.
- Determine the source of registrations (new or existing contacts).
- Identify primary and secondary sources of registrations.
- Evaluate advertising costs per registration and the best sources.
- Content Evaluation:
- Analyze past webinar content:
- Which subjects had the highest and lowest registrations?
- Which had the highest registered-to-attend ratio?
- Which resulted in the most sales conversions?
- Analyze past webinar content:
- Timing and Trends:
- Consider when past webinars were held.
- Identify trends in registration or attendance.
- Assess if webinars were around timely content or events.
- Deeper Analysis:
- Asking more questions about past performance helps define the necessary data.
- Analyzing data uncovers insights about campaign performance and audience value.
- Decision Making:
- Asking questions leads to better decisions about campaigns.
- Helps in understanding the influence of content and marketing strategies.
Apply question-asking frameworks
- Importance of Questions: Asking questions provides context and defines goals, making data meaningful. Without questions, data lacks context and purpose.
- Hierarchy of Data:
- Raw Data: Thousands of data points (e.g., visits) are meaningless on their own.
- Information: Adding context (e.g., average sessions per visitor) provides some insights.
- Knowledge: Answering specific questions (e.g., leads produced by a campaign) gives objective measurements.
- Wisdom: Understanding why events happened and applying analysis requires human reasoning.
- Question-Asking Frameworks:
- ABCs of Analytics:
- Acquisition: Where did people come from?
- Behavior: What did they do?
- Conversion: What was it worth?
- This framework helps analyze specific segments, such as those from a paid search campaign, and their journey from ad impression to conversion.
- The Three Cs of Analysis:
- Context: Identify common factors and build segments.
- Contrast: Compare behaviors to find differences and understand why they occur.
- Comparison: Align data with the intended purpose of actions or processes.
- ABCs of Analytics:
- Application:
- Use these frameworks to ask and answer questions that focus on economic and business value.
- Helps in reporting insights that are valuable to executive teams.
Connect measurement factors in marketing campaigns
- Customer Journey and Sales Funnel:
- Analytics help identify where customers abandon the process and where improvements are needed.
- The sales funnel stages are similar across businesses.
- Top of the Funnel: Cost per Mille (CPM):
- CPM is the cost for every 1,000 impressions or views.
- Example: $40 CPM means paying $40 for 1,000 impressions.
- Engagement Metrics:
- Engagement Rate: Total engagements divided by views, measuring audience interest.
- Cost per Engagement: Campaign cost divided by total engagement actions.
- Disaggregating Engagement Metrics:
- Different interactions have different values (e.g., shares are more valuable than likes).
- Applause Rate: Total likes divided by followers or impressions.
- Conversation Rate: Number of comments per post.
- Amplification Rate: Number of shares, which can also be a financial metric.
- Click-Through Rate (CTR):
- Measures the quality of the post/ad/email in moving someone to the next stage.
- Cost per Click: Provides financial context for campaign results.
- Conversion Rate:
- Measures the overall campaign quality from impression to conversion.
- Calculated by conversions divided by ad/post clicks or emails sent.
- Cost per Conversion: Can be cost per customer, sale, or lead, depending on the goal.
- Comparative Metrics:
- Metrics like shares and CTR can be averaged monthly, quarterly, or yearly for comparison.
- Helps identify high-performing and low-performing posts for analysis.
Apply KPIs to connect data to action
- Finding Actionable Data:
- Understand the process being analyzed.
- Use comparisons for context to make judgments.
- Sales/Lead Funnel Metrics:
- Impressions and CPM:
- CPM (Cost per Mille) is both a performance and financial metric.
- Factors affecting CPM: audience targeting and competition.
- Low impressions could be due to too many targeting factors or budget constraints.
- Engagement Metrics:
- Measures interest in your ad or post.
- Low engagement often indicates uninteresting content.
- Improve by changing the headline and image.
- Click-Through Rate (CTR):
- Measures the quality of your ad or post.
- Low CTR suggests the ad isn’t persuasive.
- Improve by refining the headline, image, call to action, and offer.
- Conversion Rate:
- Direct measurement of the landing page and campaign quality.
- Influencing factors: landing page relevance, call to action visibility, form fields, design, content, images, and loading time.
- Impressions and CPM:
- Nurturing Process:
- Similar steps apply to email campaigns: delivery, open rate, clicks, and landing page visits.
- More influencing factors closer to conversion, leading to actionable improvements.
- KPIs as Indicators:
- KPIs are like a car’s dashboard indicators.
- Connect KPIs to causal factors to recommend specific actions for campaign improvement.
Implement Analysis Methods
Leverage the best analytics skill: Asking questions
- Critical Skill: The most valuable data skill for a marketer and analyst is the ability to ask questions, not math.
- Evaluating Goals:
- Before taking action, evaluate past performance.
- Ask questions about the goal:
- How many registrations are we to increase by?
- What is the timeframe?
- Is the goal realistic based on past performance, budget, and audience?
- Analyzing Performance:
- Assess average registrations and attendees.
- Determine the source of registrations (new or existing contacts).
- Identify primary and secondary sources of registrations.
- Evaluate advertising costs per registration and the best sources.
- Content Evaluation:
- Analyze past webinar content:
- Which subjects had the highest and lowest registrations?
- Which had the highest registered-to-attend ratio?
- Which resulted in the most sales conversions?
- Analyze past webinar content:
- Timing and Trends:
- Consider when past webinars were held.
- Identify trends in registration or attendance.
- Assess if webinars were around timely content or events.
- Deeper Analysis:
- Asking more questions about past performance helps define the necessary data.
- Analyzing data uncovers insights about campaign performance and audience value.
- Decision Making:
- Asking questions leads to better decisions about campaigns.
- Helps in understanding the influence of content and marketing strategies.
Apply question-asking frameworks
- Importance of Questions: Asking questions provides context and defines goals, making data meaningful. Without questions, data lacks context and purpose.
- Hierarchy of Data:
- Raw Data: Thousands of data points (e.g., visits) are meaningless on their own.
- Information: Adding context (e.g., average sessions per visitor) provides some insights.
- Knowledge: Answering specific questions (e.g., leads produced by a campaign) gives objective measurements.
- Wisdom: Understanding why events happened and applying analysis requires human reasoning.
- Question-Asking Frameworks:
- ABCs of Analytics:
- Acquisition: Where did people come from?
- Behavior: What did they do?
- Conversion: What was it worth?
- This framework helps analyze specific segments, such as those from a paid search campaign, and their journey from ad impression to conversion.
- The Three Cs of Analysis:
- Context: Identify common factors and build segments.
- Contrast: Compare behaviors to find differences and understand why they occur.
- Comparison: Align data with the intended purpose of actions or processes.
- ABCs of Analytics:
- Application:
- Use these frameworks to ask and answer questions that focus on economic and business value.
- Helps in reporting insights that are valuable to executive teams.
Connect measurement factors in marketing campaigns
- Customer Journey and Sales Funnel:
- Analytics help identify where customers abandon the process and where improvements are needed.
- The sales funnel stages are similar across businesses.
- Top of the Funnel: Cost per Mille (CPM):
- CPM is the cost for every 1,000 impressions or views.
- Example: $40 CPM means paying $40 for 1,000 impressions.
- Engagement Metrics:
- Engagement Rate: Total engagements divided by views, measuring audience interest.
- Cost per Engagement: Campaign cost divided by total engagement actions.
- Disaggregating Engagement Metrics:
- Different interactions have different values (e.g., shares are more valuable than likes).
- Applause Rate: Total likes divided by followers or impressions.
- Conversation Rate: Number of comments per post.
- Amplification Rate: Number of shares, which can also be a financial metric.
- Click-Through Rate (CTR):
- Measures the quality of the post/ad/email in moving someone to the next stage.
- Cost per Click: Provides financial context for campaign results.
- Conversion Rate:
- Measures the overall campaign quality from impression to conversion.
- Calculated by conversions divided by ad/post clicks or emails sent.
- Cost per Conversion: Can be cost per customer, sale, or lead, depending on the goal.
- Comparative Metrics:
- Metrics like shares and CTR can be averaged monthly, quarterly, or yearly for comparison.
- Helps identify high-performing and low-performing posts for analysis.
Turn Data into Insight, Insight into Action
Apply KPIs to connect data to action
- Finding Actionable Data:
- Understand the process being analyzed.
- Use comparisons for context to make judgments.
- Sales/Lead Funnel Metrics:
- Impressions and CPM:
- CPM (Cost per Mille) is both a performance and financial metric.
- Factors affecting CPM: audience targeting and competition.
- Low impressions could be due to too many targeting factors or budget constraints.
- Engagement Metrics:
- Measures interest in your ad or post.
- Low engagement often indicates uninteresting content.
- Improve by changing the headline and image.
- Click-Through Rate (CTR):
- Measures the quality of your ad or post.
- Low CTR suggests the ad isn’t persuasive.
- Improve by refining the headline, image, call to action, and offer.
- Conversion Rate:
- Direct measurement of the landing page and campaign quality.
- Influencing factors: landing page relevance, call to action visibility, form fields, design, content, images, and loading time.
- Impressions and CPM:
- Nurturing Process:
- Similar steps apply to email campaigns: delivery, open rate, clicks, and landing page visits.
- More influencing factors closer to conversion, leading to actionable improvements.
- KPIs as Indicators:
- KPIs are like a car’s dashboard indicators.
- Connect KPIs to causal factors to recommend specific actions for campaign improvement.
Improve the user experience using marketing analytics
- Meeting Scenario:
- Marketing blamed IT for website failures.
- IT created a technically sound website, but the checkout process was unclear.
- Marketing had not tested the checkout process themselves.
- Role of Marketing:
- Marketing is responsible for measuring and optimizing the customer experience.
- Simple changes in the checkout process can significantly improve usability and profitability.
- Starting Analytics Program:
- Begin with processes and tasks users need to accomplish (e.g., website, app transactions).
- Measure how many people start and complete these tasks.
- Identify and improve drop-off points in multi-page processes.
- Conversion Optimization:
- Focus on improving existing structures rather than creating new campaigns.
- Small changes in processes can yield significant results.
- Example: Improving the visibility of instructions and the purchase button increased sales tenfold.
- Micro Conversions:
- Evaluate various micro conversions throughout websites and apps.
- Measure and optimize stages like account setup and checkout processes to increase conversion rates and revenue.
- Overall Impact:
- Enhancing user experience leads to higher conversion rates and happier visitors.
- Improved user experience encourages repeat visits and customer loyalty.
Establish a reporting framework for your analytics data
- Importance of Reporting:
- Reporting data is as crucial as analyzing it.
- Many marketers struggle with internal reporting, often creating lengthy reports with no clear insights.
- Common Pitfalls:
- Overloading reports with unnecessary data.
- Failing to focus on key insights and value, leading to ineffective communication with managers.
- Effective Reporting Strategy:
- Three Cs Framework:
- Context: Provide background information. Example: Campaign targeting mobile, tablet, and desktop users.
- Comparison: Compare performance across different segments. Example: Mobile vs. desktop conversion rates.
- Contrast: Highlight differences and identify issues. Example: Poor mobile conversion rates due to non-mobile-friendly website.
- Three Cs Framework:
- Simplified Reporting Format:
- Insight: Identify the primary insights. Example: Mobile site issues led to low conversion rates.
- Action: Recommend actions based on insights. Example: Propose a new mobile-friendly website.
- Impact: Quantify the business or economic impact. Example: Potential revenue increase by improving mobile conversions.
- Example Case:
- Campaign data showed:
- 0.07% overall conversion rate.
- Less than 0.01% conversion rate for mobile users.
- Generated 214 leads valued at $75 each, totaling nearly $16,000.
- Comparison with industry average conversion rate (0.75%) showed potential for significant revenue increase.
- Campaign data showed:
- Communicating with Executives:
- Use financial language and simple formats.
- Translate data into monetary values to make the impact clear.
- Example: Highlighting potential revenue loss if no action is taken.
- Key Takeaways:
- Focus on essential insights and actionable recommendations.
- Use clear, concise formats to communicate effectively with the executive team.
- Align reporting with business objectives to drive decision-making.
Implementing your marketing analytics strategy
- Starting with Questions:
- Asking questions is crucial for defining the data you need.
- Neil Postman emphasizes that question-asking is the best tool humans have.
- Defining Data Needs:
- Define the data required to answer your questions.
- Collect data that provides the necessary context for insights.
- Maintaining Focus:
- Always keep the business objective in mind during data exploration.
- Ensure every report ties activity back to a financial impact or business outcome.
- Reporting to Executives:
- Focus on telling a simple, clear story that the executive team can understand.
- Avoid overloading with data and metrics that don’t add value.
- Delivering Insights:
- Managers prefer fewer data points but more actionable insights.
- Translate data into insights, actions, and impacts that resonate with the C-suite.
These notes are from the LinkedIn Learning course ‘Marketing Foundations Analytics‘ by Matt Bailey. I highly recommend this course to anyone aspiring to become an Marketing Expert. To access this course and learn from industry experts, consider upgrading to LinkedIn Premium.
Please note that these notes were generated using LinkedIn’s AI tool, and I don’t claim ownership of the content. I’m sharing these notes solely for educational purposes and personal revision. If you have any concerns, please contact me at marketing@youthnet.in.