Get the Most from Your Business Data
Data & Analytics · Module 5
← Fundamentals of Digital Marketing - Google
Index
1. Digital Marketing Strategy and Data
Using data to inform and improve your digital marketing strategy in a structured way is essential.
A Robust Digital Marketing Strategy
A strategy outlines how to get from where you are now to where you want to be. For long-term success:
| Principle | Description |
|---|---|
| Set realistic expectations | Goals can take time to achieve. |
| Track your results | Understand what’s working and what’s not; make changes and improve. |
| Adapt to changes | Stay current with technology, AI capabilities, privacy regulations, and industry shifts. |
Performance Goals
Performance goals measure the actions customers take when they arrive at your website or store. They vary by business model.
| Business Type | Key Metrics |
|---|---|
| E-commerce | Add to cart, purchases, product page views, purchase value, return on ad spend (ROAS) |
| App | Installs, downloads, first opens, in-app events |
| Lead gen | Phone calls, form submissions; sales team follow-up; cost per lead (CPL) |
| Content / media | Page views, time on site, subscriber growth, ad revenue |
Advice: Understand how the client makes money first—profit margins, lead conversion—then give sound marketing advice. The data never lies when attribution is set up correctly.
What is an Insight?
An insight is a deep understanding from analysing data or experiences. It reveals non-obvious patterns and guides decisions.
| Data | Insight |
|---|---|
| Sales dropped 20% last quarter | Customer feedback shows a competitor’s new feature is attracting users → need for innovation |
An actionable insight identifies what to do next to improve.
2. The Data Cycle
Collect, analyse, and use data to guide decisions. The cycle: Plan → Do → Check → Act.
| Stage | Description |
|---|---|
| 1. Plan | Identify a realistic goal (e.g. +10% social followers). Use existing data (visits, sales, GA4 analytics) to check achievability. Define campaign goals that support main goals. |
| 2. Do | Implement: create and launch content across relevant channels. Design ads; target audience with engaging content. |
| 3. Check | Review data relevant to the goal. E.g. one social site gains more followers. Evaluate metrics (clicks, visits). Compare to goals. Give approaches 2–3 months before reviewing. |
| 4. Act | Adjust based on insights. E.g. change posting frequency, content type on underperforming channels. Optimise future campaigns. |
3. Top Tips for Gathering Data
| Tip | Description |
|---|---|
| Stay focused | Don’t collect everything. Focus on data relevant to your goals; capture the right information at the right time. |
| Stay up-to-date | Review data at regular intervals. Spot anomalies (seasonal spikes, drops). |
| Use the right tools | GA4 for web analytics, platform insights for social, Google Search Console for search performance. AI-powered dashboards (Looker Studio, Power BI) for automated reporting. |
| Review past data | Use historical data; compare similar datasets (apples to apples); watch for outliers. |
| Prioritise first-party data | With third-party cookies deprecated, your own data (email, purchase history, on-site behaviour) is your most valuable asset. |
Using AI for Analysis
AI tools can analyse large datasets quickly—reviews, sentiment, market research—to identify trends and insights. For AI analysis fundamentals and the T-C-R-E-I prompting framework, see 3. Using AI for Content Creation.
| AI Use Case | Example |
|---|---|
| Anomaly detection | GA4 AI insights automatically flag unusual traffic spikes or drops |
| Predictive analytics | GA4 predictive metrics estimate purchase probability and churn risk |
| Sentiment analysis | AI analyses customer reviews at scale to spot trends |
| Report generation | AI summarises key metrics into natural-language reports |
4. Analytics and the Customer Journey
Types of Data
| Type | Description | Source |
|---|---|---|
| Quantitative | Numerically measured (visits, sales) | GA4, social media analytics, ad platforms |
| Qualitative | Descriptive (opinions, sentiment, language) | Reviews, surveys, open-ended questions |
| Online vs offline | Combine in-store surveys with online reviews for a fuller picture | Both channels |
Choose by goal: Feelings → qualitative. Numbers (e.g. blog reads) → analytics. Combining both gives richer insights.
GA4 (Google Analytics 4)
GA4 is the current Google analytics platform (Universal Analytics was sunset in July 2023). Key features:
| Feature | Description |
|---|---|
| Event-based tracking | Every interaction is an event (page view, scroll, click, purchase) |
| AI-powered insights | Automated anomaly detection and trend identification |
| Predictive metrics | Purchase probability, churn probability, predicted revenue |
| Cross-platform | Tracks website and app in one property |
| Privacy-centric | Designed for a cookieless future; uses modelled data to fill gaps |
| Explorations | Freeform, funnel, path, and cohort analysis |
Analytics by Journey Stage
| Stage | What You Can Measure |
|---|---|
| Awareness | How people find you; which search engines; which pages they land on; AI Overview appearances |
| Engagement | Do they browse, sign up, or leave? Scroll depth, video plays, time on page |
| Conversion | Reservations, add to basket, purchases |
| Retention | Repeat visits; advocates sharing content; customer lifetime value (CLV) |
Getting Specific: Strategies
| Step | Action |
|---|---|
| Identify goals | Set clear, quantifiable goals per stage. E.g. Awareness: click from social; Engagement: sign up for free consultation; Conversion: first purchase; Retention: voucher code from newsletter. Revisit SMART goals from 02 - Build Your Digital Marketing Strategy. |
| Configure tools | Set up conversions in GA4. Configure events and mark key events as conversions. |
| Find actionable insights | Spot bottlenecks. E.g. only 2% of social visitors sign up; weekends see 6% vs 3% reservation rate; booking page visits but no appointments. |
| Make changes | Act on insights: offer 10% off for newsletter sign-up; boost weekend advertising; simplify booking. |
5. Managing and Presenting Data
Organising and Analysing
| Tool | Use |
|---|---|
| Spreadsheets | Google Sheets, Excel for manual data analysis. Functions, filters, pivot tables. |
| Looker Studio (Google) | Free dashboard tool. Connect GA4, Google Ads, Search Console, Sheets for automated reports. |
| Power BI / Tableau | Enterprise-level visualisation and reporting. |
| AI-powered summaries | Use ChatGPT, Claude, or Gemini to interpret data exports and generate narrative summaries. |
Presenting Your Data
Know Your Audience
Your audience = those reviewing the data (colleagues, stakeholders, investors). Ask:
- What roles do they hold?
- What level of knowledge?
- What decisions will they make from this data?
Choose Your Format
| Format | Best For |
|---|---|
| Tables | Smaller datasets; quick comparisons |
| Pie charts | Percentages; proportional data |
| Bar charts | Comparing related items; bar length = value |
| Line graphs | Data over time (e.g. traffic trends) |
| Heat maps | Performance by area (e.g. click hotspots) |
| Dashboards | Live, updating views for ongoing monitoring (Looker Studio, Power BI) |
6. Checklists
AI Data Analysis Checklist
- Identify a goal and relevant data
- Choose an AI tool (ChatGPT, Claude, Gemini, or platform-native AI)
- Check data isn’t confidential; review tool’s data usage policies
- Enter prompt using T-C-R-E-I framework; include the goal
- Verify AI output against raw data
Data Collection Checklist
- What qualitative data do you collect?
- What quantitative data do you collect?
- How frequently do you collect it?
- Are you building first-party data assets (email, CRM, on-site behaviour)?
Customer Journey Goals Checklist
- Identify one goal per stage: Awareness, Engagement, Conversion, Retention
- E.g. Conversion: 25% of basket-adders make a purchase
- E.g. Retention: Increase 4–5 star reviews over next 3 months
- Find insightful data for each goal
- Identify 1–2 bottlenecks preventing goal achievement
Dashboard Planning Checklist
- Note important metrics to track (e.g. clicks to website, conversion rate, ROAS)
- Identify links between data (e.g. content topic and clicks; social origin and purchase %)
- Choose a visualisation tool (Looker Studio, Power BI, spreadsheet)
- Set up automated reporting cadence (weekly, monthly)
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