(BMB MK02) Unit 5: Social Media, Web Analytics Tools & Qualitative Analysis
Social Media & Web Analytics Tools
Introduction to Social Media & Web Analytics
Social media and web analytics help businesses understand audience behavior, measure campaign performance, and improve digital marketing strategies. Through analytics, companies can track who interacts with their brand, what type of content they like, and how engagement leads to conversions.
Facebook Analytics Overview
Facebook Analytics (now integrated with
Meta Business Suite Insights)
provides
data-driven insights about
user behavior, audience demographics, and content engagement.
It helps marketers
measure the effectiveness of Facebook pages, posts, and ads.
Key Metrics in Facebook Analytics
| Metric | Meaning | Business Use |
|---|---|---|
| Page Views | Total number of times your page was viewed | Measures visibility of brand page |
| Page Likes / Followers | Number of people following your page | Tracks brand growth and popularity |
| Reach | Number of unique users who saw your content | Measures audience size |
| Engagement | Total interactions (likes, comments, shares, clicks) | Indicates content quality and audience interest |
| Post Impressions | Total times posts appeared on users’ screens | Shows ad visibility and awareness level |
| Click-Through Rate (CTR) | % of people who clicked on your link or ad | Measures effectiveness of CTAs |
| Video Views | How many users watched your videos | Measures video campaign success |
| Conversion Rate | % of users taking desired action (buy, sign up) | Measures ROI of campaigns |
Facebook Demographics Analysis
Demographics data provides details about who your audience is.
| Factor | Explanation | Example |
|---|---|---|
| Age Group | Understand which age segment interacts most | 18–24 years = high engagement for trendy fashion |
| Gender | Identify whether males or females engage more | Male: 60%, Female: 40% |
| Location | Shows where followers come from | Lucknow, Delhi, Mumbai – top cities |
| Device Used | Desktop vs Mobile | Helps optimize ad format and size |
| Interests & Occupation | Shows hobbies, job fields, or lifestyle | Helps in targeting relevant audience |
📌 Business Use: Demographic analysis helps in creating personalized ads, selecting target segments, and improving communication tone.
Engagement Analysis
Engagement shows how actively your audience interacts with your content.
| Type of Engagement | Meaning | Example |
|---|---|---|
| Likes / Reactions | Show emotional response | “Love” reaction to a festival post |
| Comments | Reflects opinions & feedback | Customer queries or suggestions |
| Shares | Indicates content value | Memes or videos shared widely |
| Saves / Clicks | Shows intent to revisit or buy | Users clicking to shop now |
High engagement = strong brand connection.
Post Performance Analysis
Post performance measures how each post performs based on reach, engagement, and conversion.
| Post Type | Example | Best For |
|---|---|---|
| Image Post | Product image or quote | Quick engagement |
| Video Post | Tutorial or ad video | Higher watch time |
| Carousel Post | Multiple product images | E-commerce |
| Story / Reel | Short creative video | Awareness & recall |
Facebook Insights provides detailed performance reports so marketers can identify which type of post drives the best results and plan content strategies accordingly.
Benefits of Facebook Analytics
- Understand who your audience is (demographics)
- Improve content engagement
- Track ad campaign ROI
- Optimize posting time and content type
- Strengthen customer relationships
In short: Facebook Analytics acts as a digital mirror — it shows how people see, react, and connect with your brand online.
What is Social Campaign Analysis?
Social Campaign Analysis means measuring and evaluating how well your social media campaigns are performing across different platforms. It helps marketers understand whether the campaign has achieved its goals such as brand awareness, engagement, lead generation, or sales.
Example: A brand runs a Diwali offer campaign on Instagram and YouTube.
Campaign analysis helps find out:
- How many people viewed the ad
- How many interacted (likes/comments)
- How many actually visited the website or purchased
Goals of a Social Media Campaign
Every campaign starts with clear, measurable goals (SMART goals: Specific, Measurable, Achievable, Relevant, Time-bound).
| Goal Type | Example | Key Metric |
|---|---|---|
| Brand Awareness | Reach more people | Impressions, Reach |
| Engagement | Get users to interact | Likes, Shares, Comments |
| Lead Generation | Capture potential customers | Clicks, Form fills |
| Website Traffic | Drive visitors to website | Click-throughs |
| Sales Conversion | Turn followers into buyers | Conversion Rate |
| Customer Retention | Keep customers loyal | Repeat interactions |
Measuring Outcomes
After setting goals, outcomes are measured through analytics tools (like Meta Insights, Instagram Analytics, Twitter Analytics, YouTube Studio, LinkedIn Analytics).
| Outcome | Measurement Tool | KPI Examples |
|---|---|---|
| Engagement | Instagram Insights | Likes, Shares, Comments |
| Reach | Facebook/Meta Business Suite | Impressions, Follows |
| Traffic | Google Analytics | Referral Source, Clicks |
| Leads | CRM tools (HubSpot, Zoho) | Lead Forms, Signups |
| Conversion | Ad Manager | Cost per Conversion, ROAS |
Platform-Specific Analytics
Instagram Analytics
- Metrics: Impressions, Reach, Engagement Rate, Story Views, Saves
- Best Use: Visual storytelling, influencer marketing, brand image building
- Tool: Instagram Insights (inside business account)
Twitter (X) Analytics
- Metrics: Tweet Impressions, Retweets, Mentions, Profile Visits, Engagement Rate
- Best Use: Real-time updates, brand voice, trending topics
- Tool: Twitter Analytics Dashboard
LinkedIn Analytics
- Metrics: Post Views, Clicks, Engagement, Follower Demographics (industry, job role, location)
- Best Use: B2B marketing, professional branding, lead generation
- Tool: LinkedIn Page Analytics
YouTube Analytics
- Metrics: Watch Time, Views, Audience Retention, Subscribers, CTR, Engagement Rate
- Best Use: Video content marketing, education, entertainment, product demos
- Tool: YouTube Studio Analytics
Organic vs. Paid Traffic
| Type | Meaning | Example | Benefits |
|---|---|---|---|
| Organic Traffic | Visitors coming naturally (unpaid) through posts, shares, or searches | People finding your Instagram reel or YouTube video | Free, builds trust, long-term growth |
| Paid Traffic | Visitors driven by paid ads or sponsored content | Facebook Ads, LinkedIn Ads, YouTube Video Ads | Quick reach, targeted audience, measurable ROI |
Key Point: A balanced strategy uses both organic (brand building) and paid (performance marketing) for better results.
Benchmarking in Social Media Analytics
Benchmarking means comparing your performance with:
- Past performance (internal benchmarking) — Example: This month’s engagement vs last month’s.
- Industry standards (external benchmarking) — Example: Average CTR in your industry is 2%, your ad got 3.5%.
Benchmarking Metrics:
- Engagement rate
- Follower growth rate
- Conversion rate
- Cost per click (CPC)
- Return on ad spend (ROAS)
Purpose
- Identify strengths and weaknesses
- Set realistic goals
- Track progress over time
In Summary
| Element | Description |
|---|---|
| Goal Setting | Define campaign objectives (awareness, engagement, sales) |
| Platform Analytics | Measure KPIs using Instagram, Twitter, LinkedIn & YouTube tools |
| Traffic Type | Use both organic (free) and paid (ads) reach |
| Benchmarking | Compare performance against goals and competitors |
| Outcome Evaluation | Use insights to improve future campaigns |
Web Analytics Tools
A/B Testing
- Version A = Original (Control)
- Version B = Modified (Variant)
Purpose
- Improve conversion rates
- Test changes in design, content, CTA buttons, headlines
Example
- Original landing page has “Buy Now” button in blue.
- Variant page has “Buy Now” button in red.
- Measure which version gets more clicks or sales.
Online Surveys
Online surveys collect direct feedback from users to understand their preferences, satisfaction, or opinions.
Purpose
- Collect qualitative and quantitative data
- Measure user satisfaction
- Identify pain points and improvement areas
Tools
-
Google Forms, SurveyMonkey, Typeform
Example: After a website visit, a pop-up survey asks: “Did you find what you were looking for today?”
Web Crawling & Indexing
Web Crawling
- Automated software called web crawlers or spiders scan the internet and collect website data.
- Helps search engines discover new pages.
Web Indexing
-
Collected pages are organized and stored in a database (index) for quick retrieval during searches.
Example: Googlebot crawls a website → Index stores page content → Appears in Google Search results.
NLP Techniques for Micro-text Analysis
Natural Language Processing (NLP) is used to analyze text data from social media, reviews, or website comments to understand sentiments, opinions, and trends.
Applications in Web Analytics
- Sentiment Analysis: Detect if comments are positive, negative, or neutral
- Topic Detection: Identify common themes in reviews
- Micro-text Analysis: Analyze short texts like tweets, captions, or feedback forms
Example: Analyzing 1,000 tweets about a new product → NLP identifies 70% positive, 20% neutral, 10% negative.
Google Website Optimizer (GWO)
Meaning
Google Website Optimizer (now part of Google Optimize) is a tool for testing and improving website performance using experiments like A/B Testing, Multivariate Testing, and Split URL Testing.
Working
-
Select the web page or element to test
-
Create variations (different headlines, images, CTA buttons)
-
Split traffic between original and variants
-
Measure conversion metrics (clicks, purchases, sign-ups)
-
Determine the best-performing version
Implementation Steps
-
Set up experiment in Google Optimize
-
Add experiment code to website
-
Define objectives (e.g., CTR, sign-ups)
-
Run the test for a sufficient duration
-
Analyze results and implement winning changes
Benefits
-
Data-driven decision making
-
Increases website conversion rate
-
Improves user experience
-
Reduces guesswork in design changes
✅ Summary Table
| Tool / Technique | Purpose | Example / Use Case |
|---|---|---|
| A/B Testing | Compare two versions to improve conversions | Test button color, headline |
| Online Surveys | Collect user feedback | Satisfaction survey after purchase |
| Web Crawling & Indexing | Discover & organize website pages | Googlebot crawling pages for search |
| NLP for Micro-text Analysis | Analyze short text for sentiment & trends | Tweets or product reviews analysis |
| Google Website Optimizer | Test & optimize website performance | Optimize landing page for more clicks |
In simple terms: These tools help understand visitors, test changes, collect feedback, and optimize website performance scientifically, rather than relying on guesswork.
Qualitative Techniques & Advanced Web Analytics
Qualitative Techniques in Web Analytics
Qualitative techniques help understand user experience, opinions, and behavior beyond numbers.
A. Heuristic Evaluation
- Meaning: Expert analysis of a website based on usability principles (heuristics).
- Purpose: Identify usability problems such as confusing navigation, poor layout, or unclear content. Example: A usability expert checks an e-commerce website and notes that the checkout process is too long, causing drop-offs.
B. Site Visits
- Meaning: Physically or virtually observing users interacting with the website or store.
- Purpose: Gain direct insights on user behavior and workflow. Example: Observing users on an online learning platform to see which courses they explore first.
C. Surveys (Post-Visit & Online)
- Post-Visit Survey: Asked immediately after a website interaction or store visit. Example: “Was our website easy to navigate today?”
- Online Surveys: Collected via email, pop-ups, or forms. Example: Customer feedback forms for product satisfaction.
- Purpose: Collect user opinions, satisfaction, and suggestions for improvement.
Web Analytics 2.0 vs. 1.0
| Feature | Web Analytics 1.0 | Web Analytics 2.0 |
|---|---|---|
| Focus | Page views, hits, clicks | User engagement, conversions, customer behavior |
| Perspective | Technical / quantitative | Strategic / qualitative + quantitative |
| Data Source | Onsite only | Onsite + offsite + social media + mobile |
| Objective | Measure traffic | Understand user intent & optimize experience |
| Example | Total page views per day | Track which content drives repeat purchases |
💡 Key Idea: Web Analytics 2.0 is more holistic and user-focused, integrating behavioral insights and social data.
Competitive Intelligence (CI)
- Meaning: Collecting and analyzing information about competitors’ online strategies.
- Purpose: Identify strengths, weaknesses, opportunities, and threats (SWOT) and improve your own website strategy.
- Monitor competitor traffic (SimilarWeb, SEMrush)
- Analyze content & social media engagement
- Track ad campaigns, keywords, and SEO strategies
Website Traffic Trends & Overlap
- Traffic Trends: Tracking how visitor behavior changes over time (daily, weekly, monthly) Example: Increased traffic during festive season, lower on weekdays.
- Traffic Overlap: Shows shared audience between competitors or platforms. Example: Users visiting both Amazon and Flipkart → Indicates market overlap and competitive audience.
Purpose
- Identify peak traffic periods
- Understand shared audiences
- Plan marketing & content strategies effectively
Summary Table
| Topic | Key Points | Example / Use |
|---|---|---|
| Heuristic Evaluation | Expert-based usability analysis | Detect confusing navigation |
| Site Visits | Observing user behavior | Track course exploration on LMS |
| Surveys | Post-visit or online feedback | Customer satisfaction forms |
| Web Analytics 1.0 | Measures hits, page views | Count total page visits |
| Web Analytics 2.0 | Measures engagement & conversions | Track content that drives repeat sales |
| Competitive Intelligence | Analyze competitors’ strategies | Monitor Instagram and SEO tactics |
| Traffic Trends & Overlap | Track audience behavior & shared traffic | Peak season traffic, overlapping users with competitors |
In simple words: These techniques help go beyond numbers, understand why users behave the way they do, learn from competitors, and make data-driven improvements to website and digital campaigns.