How to consolidate scattered marketing metrics for one dashboard?

Spotlight

PAGE: https://alison.com/course/diploma-in-marketing-analytics

PROMISE: Turn scattered marketing data into clear decisions on where to focus time.

WHO: Small business owners formalizing their understanding of marketing data.

WHYNOW: This beginner level course offers a low cost path to structure scattered marketing information.

DESC: Learn about marketing analytics, R programming, and other marketing mix models, as well as the recommendation engines and filtering marketing analysis.

BEFORE: Marketing metrics are scattered across separate reports.

BEFORE: It is unclear which posts or projects deserve time.

BEFORE: Decisions rely on gut feel rather than data.

AFTER: Metrics are viewed through a unified analytical lens.

AFTER: Clear criteria exist for prioritizing projects.

AFTER: Data informs decisions on marketing mix.

GAIN: Clearer segmentation of customer bases

GAIN: Better understanding of retail analytics

GAIN: Improved identification of churn risks

STEP: You wonder why some campaigns fail without a clear data explanation. || Identify the influence of key marketing concepts in marketing analytics || You link campaign results to specific marketing drivers before spending more.

STEP: You guess which customer groups matter because data is siloed. || Analyze the concept of customer segmentation and target positioning || You isolate high value groups and stop broad reach tactics.

STEP: You cannot predict which products customers will buy next. || Explain the recommendation engine and retail analytics || You apply logic to predict purchases and direct traffic to likely items.

STEP: You lose regular customers without knowing why they left. || Describe the importance of the customer-churn approach in marketing analytics || You spot warning signs early and intervene with targeted retention offers.

NOTFOR: Those needing a full R programming certification

NOTFOR: Experienced data scientists requiring advanced algorithmic depth

FACT: Average duration: 15-20 Hours (Contains Video)

FACT: CPD-accredited certificate available

FACT: Beginner level

COVERS: Identify the influence of key marketing concepts in marketing analytics

COVERS: Explain the utilization of R programming in marketing analytics

COVERS: Analyze the concept of customer segmentation and target positioning

COVERS: Identify the marketing mix models in analytics

COVERS: Explain the recommendation engine and retail analytics

COVERS: Describe the importance of the customer-churn approach in marketing analytics

COVERS: Analyze the applications of text mining in marketing analytics

COVERS: Explain the concept of sentiment analytics and the use of Naive Bayes classifiers for sentiment mining

COVERS: Identify social network analysis to create connections between people and their business decisions

COVERS: Marketing

COVERS: R Programming

MODULE: Introduction to R Programming || Understanding R programming and Installation | Functions and their Syntax | Matrix and Data Frame | Data Manipulation | Handling Basic Data Analytics | Creating a Bar Plot

MODULE: Consumers Wants || Wants, Needs and Demands in Marketing | Conjoint Analysis in Consumers Wants | Rating-Based of Conjoint Analysis | Pricing in Conjoint Analysis | Choice Modeling Method | Choice Based Conjoint

MODULE: Segmentation, Targeting and Positioning || Segmentation, Targeting and Positioning Methodology | Segmentation, Targeting and Positioning Concepts | Steps in Segmentation, Targeting and Positioning | Solving a Problem with Clustering Methods | Application of Multiple Techniques

MODULE: Demand Focusing and Pricing || Demand and Sales Forecasting | Bundle Pricing | Using Analytics to Forecast a Demand | Technology Adoption Model

MODULE: Understanding Pricing || Pricing and Skimming | Power Block Pricing | Solving Pricing Problems | Price Base Segmentation | Markdown Pricing and Dynamic Pricing | Price Bundling | Price Sales Promotion

MODULE: Marketing Mix Models and Advertising Model || Micro Level Analysis | Linear Model | Impact of the Advertising Model | Advertising Models Equation | Media Data

MODULE: Recommendation Engine and Retail Analysis || Recommendation Engine | Collaborative Filtering | Hands-On Item Collaborative Filtering | User Collaborative Filtering | Application of Recommendation Engine | Working with Sparse Datasets

MODULE: RFM and Market Basket Analysis || Recency Frequency Monetary Technique | Recency Frequency Monetary Analysis in R | Market Basket Analysis | Data Mining Technique | Market Basket Analysis Hands-On

What you are probably seeing

You open multiple browser tabs and different apps to check how a side project is performing today.

You manually copy numbers into a spreadsheet because the source data is trapped inside separate platforms.

Why it happens

Most web and mobile projects use different tools for traffic, revenue, or user engagement, and these tools rarely talk to each other.

Without a central standard, it is hard to compare a new idea against an old one because you are looking at different definitions of success.

What changed recently

2026-10-07 · is marketing analytics worth it
SidePop addresses that gap:
• Single dashboard replaces scattered tabs for project decisions.
• Tracks multiple web and mobile side projects.
• Identifies which specific project actually deserves time.
Source: autocomplete

Step by step

1. List every platform where you currently store data for each of your active side projects.

2. Pick a single metric that matters most to each project, such as revenue or active users, to define its health.

3. Export or copy the weekly data for each project into one simple shared spreadsheet.

4. Create a visual summary row for each project to show its total value or growth trend at a glance.

5. Delete any project that fails to meet your minimum time requirement based on its performance data.

Ways to go further

Start here: An Introduction to Marketing For when you are new to marketing and need foundational theory. Open the free course on Alison ↗

Better fit: Online Marketing With Google Analytics For when you need to learn how to set up tracking for digital campaigns. Open the free course on Alison ↗

Best when: Diploma in Marketing Analytics For when you want to formalize your understanding of marketing data. Open the free course on Alison ↗

Affiliate links: CHEAPUNO may earn a commission if you buy through them, at no extra cost to you.

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