Digital Analysis Flashcards
[Funnel.io]
What is marketing analysis?
Management and analysis of data to improve the performance of marketing efforts.
[Funnel.io]
Why is marketing analytics important for marketers?
Marketing analytics uses data from various parts of the sales funnel to create broad picture of the sales funnel performance.
[Funnel.io]
What is the process of marketing analytics? (4 STEPS)
- COLLECT AND MANAGE
Collecting and managing marketing data. This means measuring the performance of your marketing efforts, then collecting and preparing the data that’s produced. - ANALYSIS AND INSIGHTS
Extracting insights and learnings from past activity, trying to understand what happened and why. - STRATEGY AND PLANNING
Decide what direction to take your marketing strategy, which is your way of telling the right story to the right potential customers at the right time, so they buy a product or service. - REPORTING
Report on your analysis, findings and plan strategy to your managers, boards or clients.
[Funnel.io]
What stages include in Marketing Analytics Maturity Framework? (4 steps)
- WHAT HAPPENED?
You need to somehow produce data to see what happened with your marketing activity. This would be something like showing you how much you spent on a channel like TikTok or Facebook. What it resulted in and how many clicks or how many video feeds. - WHY IT HAPPENED?
This will be understanding why a lot of people viewed your videos on Tik Tok and why you got more clicks on Facebook. Looking for correlations and trends, then trying to prove causation. - WHAT WILL HAPPEN NEXT?
What will happen when we spend $1,000 a month on Tik Tok or $100,000 a month? Will spending more affect the return on investment? It is having enough data to map out what could happen based on what has happened. - WHAT SHOULD BE DONE?
Make predictions, then take actions as a result. This will be knowing TikTok will drive more video views, but Facebook will drive more clicks, so you should optimize TikTok creatives for views and Facebook creatives for clicks.
[Funnel.io]
How to determine marketing budget? (4 steps)
- What you’ve spent across each platform.
- Map that together with web data from Google Analytics and conversion data for CRM to understand what you got in return.
- Determine an average order value for each platform.
- Analyze how each platform work for you to plan a budget
[Funnel.io]
What is the first step of marketing analytics?
You need to organize data, before you can analyze it.
[Funnel.io]
What is Data transformation in Marketing Analytics?
Data transformation = organizing data = preparing data.
How would you organize a library, so that books are easy to find?
[Tom Peyton]
What are 3 core data analysis metrics?
- Business Performance metrics
- Website metrics
- Ad/Social media metrics
[Tom Peyton]
What are 2 Business Performance metrics?
CPA (Cost Per Aqcuisition) and LTV (Lifetime customer value)
[Tom Peyton]
What Website traffic tells you?
Awareness state
[Tom Peyton]
What are 5 key metrics to track on website?
- Sessions
- Unique visitors
- Bounce rate
- Session duration
- Conversion rate
[Tom Peyton]
What are the key Ad/Social media metrics?
- Impressions (how many times your post is seen)
- Reach (how many indivituals saw your post)
- CTR (Click Through Rate)
- Frequency (how often your post is seen)
- CPC (Cost Per Click)
[Tom Peyton]
You have great CTR and small CPC, but low conversion rate. What could be the problem? (2 options)
- TARGETING
Targeting is too vague and broad so wrong people are clicking. - WEBSITE OPTIMIZATION FOR CONVERSIONS
People just clicking out of curiosity because they don’t really understand what your ad is about or the offer isn’t positioned in a way that’s compelling enough for you to stand out from the noise.
[Dale Pearson]
What are 12 tips to design better dashboard?
- Know the purpose
- Include only important content
- Consider data ink ratio
- Round your numbers
- Use the most efficient visualization
- Group related metrics
- Be consistent
- Show hierarcy
- Give numbers context
- Use clear numbers
- Remember it is for people
- Keep evolving
[Google Cloud]
What are 3 ways to use Google Cloud for marketing analysis?
- Marketing Insights
- Audience segmentation
- Customer experience
[Funnel.io]
What data inputs are crucial for Marketing Mix Model (MMM) projects?
- Weekly sales data (both online and offline)
- Weekly media spend
- Brand tracking data.
Typically, three years of data are used for larger companies.
[Funnel.io]
What does the process look like for the many MMM projects?
- Agree on business questions
- Identify data needed
- Visualisation of media data
- Modelling
- Outcome and implementation
[Funnel.io]
How is Marketing Mix Modeling (MMM) different from attribution modeling, and what are its advantages?
Marketing Mix Modeling is different from attribution modeling as it considers long-term sales activities and is less sensitive to regulatory changes like GDPR. Its advantages include the ability to optimize long-term and short-term strategies and consider the impact of various external variables.
[Mo Chen]
What technical skills data analytist need?
Excel and SQL + one programming language, such as Python
[Mo Chen]
What soft skills data analytist need?
Communicate clearly and shortly, use structured messaging in emails, and be able to adapt communication style for different audiences.
[Mo Chen] What does Mo Chen recommend as one way for wannabe-data analysts to showcase their skills and gain experience?
Working on coding challenges, creating own data projects, and uploading them to sites like GitHub to showcase skills and gain experience.
[Mo Chen]
Describe the importance of industry knowledge for data analysts?
Understanding the industry landscape in which a company operates is crucial for data analysts to ask the right questions and perform deeper analysis.
The document explores the criticisms of buyer personas in the era of online analytics and introduces the concept of data-driven personas, which are based on real insights about users and address some of the traditional persona challenges.
[Joni Salminen]
What are the major criticisms of using buyer personas in the era of online analytics?
- Online audiences are more complex
- Buyer personas are too focused on superficial demographic information
- Buyer persona describes, but does not predict
The document explores the criticisms of buyer personas in the era of online analytics and introduces the concept of data-driven personas, which are based on real insights about users and address some of the traditional persona challenges.
[Joni Salminen]
How do data-driven personas help to understand both big groups and individual customers?
Data-driven personas are using calculatory techniques to create accurate persona profiles based on real insights about users, allowing for advanced purposes such as prediction.
The document explores the criticisms of buyer personas in the era of online analytics and introduces the concept of data-driven personas, which are based on real insights about users and address some of the traditional persona challenges.
[Joni Salminen]
What are the potential benefits of using calculated techniques and data sources in the creation of data-driven personas?
- Accurate persona profiles
- Persona validation
- Consistency
- Faster development times
