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 44.2, difficulty 36.2.
Tracked keywords
123
0 ranked • 123 not ranking yet
Top 10 coverage
—
Best rank — • Latest leader —
Avg opportunity
44.2
Top keyword: easy
Avg difficulty
36.2
Lower scores indicate easier wins
Opportunity leaders
- 85.2
easy
Opportunity: 59.0 • Difficulty: 59.0 • Rank —
Competitors: 1,246
- 88.7
time
Opportunity: 59.0 • Difficulty: 62.9 • Rank —
Competitors: 1,805
- 85.2
help
Opportunity: 59.0 • Difficulty: 61.1 • Rank —
Competitors: 1,236
- 78.1
top
Opportunity: 58.0 • Difficulty: 58.9 • Rank —
Competitors: 706
- 80.9
right
Opportunity: 58.0 • Difficulty: 62.5 • Rank —
Competitors: 912
Unranked opportunities
easy
Opportunity: 59.0 • Difficulty: 59.0 • Competitors: 1,246
time
Opportunity: 59.0 • Difficulty: 62.9 • Competitors: 1,805
help
Opportunity: 59.0 • Difficulty: 61.1 • Competitors: 1,236
top
Opportunity: 58.0 • Difficulty: 58.9 • Competitors: 706
right
Opportunity: 58.0 • Difficulty: 62.5 • Competitors: 912
High competition keywords
time
Total apps: 8,391 • Major competitors: 1,805
Latest rank: — • Difficulty: 62.9
help
Total apps: 5,873 • Major competitors: 1,236
Latest rank: — • Difficulty: 61.1
easy
Total apps: 5,849 • Major competitors: 1,246
Latest rank: — • Difficulty: 59.0
using
Total apps: 4,473 • Major competitors: 924
Latest rank: — • Difficulty: 61.4
want
Total apps: 4,034 • Major competitors: 840
Latest rank: — • Difficulty: 57.9
All tracked keywords
Includes opportunity, difficulty, rankings and competitor benchmarks
| Major Competitors | |||||||
|---|---|---|---|---|---|---|---|
| top | 58 | 100 | 59 | 78 2,843 competing apps Median installs: 305,500 Avg rating: 4.6 | — | — | 706 major competitor apps |
| artificial intelligence | 57 | 100 | 31 | 45 99 competing apps Median installs: 179,050 Avg rating: 4.6 | — | — | 15 major competitor apps |
| right | 58 | 100 | 63 | 81 3,793 competing apps Median installs: 282,075 Avg rating: 4.6 | — | — | 912 major competitor apps |
| easy | 59 | 100 | 59 | 85 5,849 competing apps Median installs: 250,625 Avg rating: 4.6 | — | — | 1,246 major competitor apps |
| easy steps | 20 | 100 | 56 | 31 22 competing apps Median installs: 281,912 Avg rating: 4.6 | — | — | 8 major competitor apps |
| support | 58 | 100 | 56 | 78 2,741 competing apps Median installs: 233,950 Avg rating: 4.6 | — | — | 515 major competitor apps |
| learn | 58 | 100 | 57 | 77 2,669 competing apps Median installs: 250,600 Avg rating: 4.6 | — | — | 552 major competitor apps |
| scientist | 56 | 100 | 22 | 30 21 competing apps Median installs: 182,975 Avg rating: 4.6 | — | — | 2 major competitor apps |
| scientists | 56 | 100 | 23 | 34 32 competing apps Median installs: 241,375 Avg rating: 4.6 | — | — | 5 major competitor apps |
| using | 58 | 100 | 61 | 83 4,473 competing apps Median installs: 247,200 Avg rating: 4.6 | — | — | 924 major competitor apps |
| time | 59 | 100 | 63 | 89 8,391 competing apps Median installs: 259,600 Avg rating: 4.6 | — | — | 1,805 major competitor apps |
| help | 59 | 100 | 61 | 85 5,873 competing apps Median installs: 257,100 Avg rating: 4.6 | — | — | 1,236 major competitor apps |
| video | 58 | 100 | 56 | 76 2,262 competing apps Median installs: 268,550 Avg rating: 4.6 | — | — | 467 major competitor apps |
| tree | 57 | 100 | 33 | 46 112 competing apps Median installs: 295,300 Avg rating: 4.6 | — | — | 24 major competitor apps |
| path | 58 | 100 | 42 | 60 440 competing apps Median installs: 256,650 Avg rating: 4.7 | — | — | 82 major competitor apps |
| understanding | 57 | 100 | 37 | 55 266 competing apps Median installs: 199,150 Avg rating: 4.6 | — | — | 39 major competitor apps |
| test | 58 | 100 | 50 | 73 1,727 competing apps Median installs: 258,500 Avg rating: 4.6 | — | — | 389 major competitor apps |
| students | 57 | 100 | 38 | 54 253 competing apps Median installs: 213,650 Avg rating: 4.6 | — | — | 38 major competitor apps |
| complete | 58 | 100 | 52 | 78 2,946 competing apps Median installs: 253,475 Avg rating: 4.6 | — | — | 625 major competitor apps |
| comprehensive | 58 | 100 | 46 | 66 795 competing apps Median installs: 206,650 Avg rating: 4.6 | — | — | 126 major competitor apps |
| provides | 58 | 100 | 49 | 74 1,846 competing apps Median installs: 221,075 Avg rating: 4.6 | — | — | 308 major competitor apps |
| quality | 58 | 100 | 53 | 74 1,906 competing apps Median installs: 248,725 Avg rating: 4.6 | — | — | 383 major competitor apps |
| analytics | 57 | 100 | 32 | 48 127 competing apps Median installs: 249,950 Avg rating: 4.6 | — | — | 24 major competitor apps |
| simple | 58 | 100 | 54 | 80 3,416 competing apps Median installs: 254,625 Avg rating: 4.6 | — | — | 695 major competitor apps |
| want | 58 | 100 | 58 | 82 4,034 competing apps Median installs: 255,375 Avg rating: 4.6 | — | — | 840 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