Analytics Vidhya
ASO Keyword Dashboard
Tracking 123 keywords for Analytics Vidhya in Apple App Store
Analytics Vidhya tracks 123 keywords (no keywords rank yet; 123 need traction). Key metrics: opportunity 70.0, difficulty 36.8.
Tracked keywords
123
0 ranked • 123 not ranking yet
Top 10 coverage
—
Best rank — • Latest leader —
Avg opportunity
70.0
Top keyword: path
Avg difficulty
36.8
Lower scores indicate easier wins
Opportunity leaders
- 66.8
path
Opportunity: 73.0 • Difficulty: 40.4 • Rank —
Competitors: 83
- 67.2
case
Opportunity: 73.0 • Difficulty: 40.5 • Rank —
Competitors: 63
- 67.7
calculate
Opportunity: 73.0 • Difficulty: 40.8 • Rank —
Competitors: 44
- 68.1
started
Opportunity: 73.0 • Difficulty: 41.2 • Rank —
Competitors: 113
- 63.7
largest
Opportunity: 73.0 • Difficulty: 38.8 • Rank —
Competitors: 103
Unranked opportunities
path
Opportunity: 73.0 • Difficulty: 40.4 • Competitors: 83
case
Opportunity: 73.0 • Difficulty: 40.5 • Competitors: 63
calculate
Opportunity: 73.0 • Difficulty: 40.8 • Competitors: 44
started
Opportunity: 73.0 • Difficulty: 41.2 • Competitors: 113
largest
Opportunity: 73.0 • Difficulty: 38.8 • Competitors: 103
High competition keywords
time
Total apps: 192,044 • Major competitors: 1,611
Latest rank: — • Difficulty: 53.4
help
Total apps: 149,169 • Major competitors: 1,295
Latest rank: — • Difficulty: 52.4
easy
Total apps: 142,894 • Major competitors: 1,125
Latest rank: — • Difficulty: 52.1
using
Total apps: 115,865 • Major competitors: 808
Latest rank: — • Difficulty: 51.2
simple
Total apps: 97,962 • Major competitors: 754
Latest rank: — • Difficulty: 50.4
All tracked keywords
Includes opportunity, difficulty, rankings and competitor benchmarks
| Major Competitors | |||||||
|---|---|---|---|---|---|---|---|
| top | 69 | 100 | 48 | 78 47,156 competing apps Median installs: 75 Avg rating: 4.2 | — | — | 631 major competitor apps |
| artificial intelligence | 72 | 100 | 36 | 61 4,173 competing apps Median installs: 50 Avg rating: 4.1 | — | — | 17 major competitor apps |
| right | 67 | 100 | 50 | 82 82,702 competing apps Median installs: 50 Avg rating: 4.2 | — | — | 941 major competitor apps |
| easy | 65 | 100 | 52 | 86 142,894 competing apps Median installs: 50 Avg rating: 4.1 | — | — | 1,125 major competitor apps |
| easy steps | 69 | 100 | 29 | 46 571 competing apps Median installs: 75 Avg rating: 4.2 | — | — | 8 major competitor apps |
| support | 67 | 100 | 49 | 82 73,987 competing apps Median installs: 50 Avg rating: 4.2 | — | — | 550 major competitor apps |
| learn | 67 | 100 | 49 | 81 72,877 competing apps Median installs: 50 Avg rating: 4.2 | — | — | 581 major competitor apps |
| scientist | 69 | 100 | 26 | 44 399 competing apps Median installs: 100 Avg rating: 4.2 | — | — | 2 major competitor apps |
| scientists | 70 | 100 | 29 | 49 821 competing apps Median installs: 75 Avg rating: 4.1 | — | — | 5 major competitor apps |
| using | 66 | 100 | 51 | 85 115,865 competing apps Median installs: 50 Avg rating: 4.1 | — | — | 808 major competitor apps |
| time | 65 | 100 | 53 | 88 192,044 competing apps Median installs: 50 Avg rating: 4.1 | — | — | 1,611 major competitor apps |
| help | 65 | 100 | 52 | 87 149,169 competing apps Median installs: 50 Avg rating: 4.2 | — | — | 1,295 major competitor apps |
| video | 69 | 100 | 47 | 78 46,056 competing apps Median installs: 75 Avg rating: 4.0 | — | — | 476 major competitor apps |
| tree | 71 | 100 | 35 | 57 2,704 competing apps Median installs: 75 Avg rating: 4.1 | — | — | 24 major competitor apps |
| path | 73 | 100 | 40 | 67 9,766 competing apps Median installs: 75 Avg rating: 4.3 | — | — | 83 major competitor apps |
| understanding | 72 | 100 | 42 | 69 14,118 competing apps Median installs: 25 Avg rating: 4.3 | — | — | 40 major competitor apps |
| test | 69 | 100 | 46 | 77 38,346 competing apps Median installs: 50 Avg rating: 4.1 | — | — | 408 major competitor apps |
| students | 71 | 100 | 43 | 72 19,118 competing apps Median installs: 25 Avg rating: 4.0 | — | — | 33 major competitor apps |
| complete | 68 | 100 | 49 | 81 65,048 competing apps Median installs: 50 Avg rating: 4.2 | — | — | 667 major competitor apps |
| comprehensive | 70 | 100 | 46 | 76 35,148 competing apps Median installs: 25 Avg rating: 4.2 | — | — | 126 major competitor apps |
| provides | 67 | 100 | 49 | 81 73,091 competing apps Median installs: 25 Avg rating: 4.1 | — | — | 272 major competitor apps |
| quality | 68 | 100 | 48 | 79 52,779 competing apps Median installs: 50 Avg rating: 4.2 | — | — | 394 major competitor apps |
| analytics | 72 | 100 | 37 | 62 5,158 competing apps Median installs: 25 Avg rating: 4.2 | — | — | 19 major competitor apps |
| simple | 67 | 100 | 50 | 84 97,962 competing apps Median installs: 50 Avg rating: 4.1 | — | — | 754 major competitor apps |
| want | 67 | 100 | 50 | 82 84,186 competing apps Median installs: 75 Avg rating: 4.1 | — | — | 753 major competitor apps |
App Description
We aim to help you learn concepts of data science, machine learning, deep learning, big data & artificial intelligence (AI) in the most interactive manner from the basics right up to very advanced levels.
Analytics Vidhya app provides high quality learning resources for data science professionals, data engineers and students who want to study data science and machine learning algorithms, along with codes.
Some of the popular posts on the app
• A Comprehensive Learning Path for Deep Learning in 2019
• The Ultimate Learning Path to Become a Data Scientist and Master Machine Learning in 2019
• A Complete Tutorial to Learn Data Science with Python from Scratch
• Essentials of Machine Learning Algorithms (with Python and R Codes)
• An Introduction to Implementing Neural Networks using TensorFlow
• A Complete Guide on Getting Started with Deep Learning in Python
• Tips and Tricks to Ace Data Science Interviews
• 7 Types of Regression Techniques you should know!
• A Complete Tutorial on Ridge and Lasso Regression in Python
• Deep Learning Tutorial to Calculate the Screen Time of Actors in any Video (with Python codes)
• Comprehensive Introduction to Apache Spark, RDDs & Dataframes (using PySpark)
• A Simple Introduction to Facial Recognition (with Python codes)
• 30 Questions to test your understanding of Logistic Regression
• A Complete Tutorial on Tree Based Modeling from Scratch in R & Python
• The most comprehensive Data Science learning plan
• 6 Easy Steps to Learn Naive Bayes Algorithm (with codes in Python and R)
• Top 28 Cheat Sheets for Machine Learning, Data Science, Probability, SQL & Big Data
• Solving Multi-Label Classification problems (Case studies included)
• Understanding Support Vector Machine algorithm from examples (along with code)
• Architecture of Convolutional Neural Networks (CNNs) demystified
• Complete Guide to Parameter Tuning in XGBoost (with codes in Python)
• Practicing Machine Learning Techniques in R with MLR Package
• Heroes of Deep Learning: Top Takeaways for Aspiring Data Scientists from Andrew Ng’s Interview Series
Machine Learning and Deep Learning Algorithms:
• Linear and Logistic Regressions
• NaiveBayes
• Neural Networks
• Decision Trees
• Convolutio