Ask Archie!

A list of questions Archie can answer today.

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Top 10 questions Archie answers every day:

  • ① What's my traffic?
  • ② Predict my next week's traffic.
  • ③ How much money did I make?
  • ④ How many visitors did Google send last month?
  • ⑤ How many visitors did Facebook send last month?
  • ⑥ What kind of device did most of my traffic use?
  • ⑦ What is my conversion rate?
  • ⑧ What is my bounce rate?
  • ⑨ Which location has attracted the most visitors?
  • ①⓪ How do I increase my traffic?

Get AI expert advice:

  • How can I increase my page views?
  • How fo I increase my revenue?
  • How can I increase my revenue per visitor?
  • How can I increase my traffic?

AI predictions and estimations:

  • How many conversions will I have tomorrow/next week/next month]?
  • How much will I earn tomorrow/next week/next month]?
  • How much traffic will I have on my site tomorrow/next week/next month]?

Real-time reports:

  • Which country is sending me the most visitors at the moment?
  • Right now, what devices are my visitors using?
  • Right now, where are my visitors coming from?
  • On what page are most of my users right now?

Instantly generate advanced reports:

  • Give me the daily/weekly/monthly] briefing.
  • How did city location affect my conversion today/this week/this month]?
  • How did location countries affected conversions today/this week/this month]?
  • How did engagement vary by city today/this week/this month]?
  • What is the distribution of my traffic against countries today/this week/this month]?
  • How well did desktop users convert on my site today/this week/this month]?
  • What percent of my conversions are using desktop, mobile or tablet today/this week/this month]?
  • What was the device split for my traffic today/this week/this month]?
  • Compare how landing pages effected conversions today/this week/this month].
  • How well did mobile users convert on my site today/this week/this month]?
  • How does session duration correlate to conversion today/this week/this month]?
  • How many conversions from new/returning visitors did I have today/this week/this month]?
  • How many new/returning visitors did I have today/this week/this month]?
  • What was the browser split for my traffic today/this week/this month]?
  • What is the best time for conversions today/this week/this month]?
  • Compare the conversion effectiveness of my top sources today/this week/this month].
  • Which referrals were the most effective for conversions today/this week/this month]?
  • Which referrals were the most effective for engagement today/this week/this month]?
  • Which referrer generated the most income for me today/this week/this month]?
  • Which referrer generated the best revenue per visitor for me today/this week/this month]?
  • Where did i get the most traffic from today/this week/this month]?

Detailed data analysis:

  • What is my bounce rate today/this week/this month]?
  • How many conversions did I have from Facebook today/this week/this month]?
  • How many conversions did I have from Google today/this week/this month]?
  • How many conversions did I have from LinkedIn today/this week/this month]?
  • How many conversions did I have from Medium today/this week/this month]?
  • How many conversions did I have from Reddit today/this week/this month]?
  • How many conversions did I have from Twitter today/this week/this month]?
  • How many conversions did i have today/this week/this month]?
  • What is my daily/weekly/monthly] conversion rate?
  • What is my daily/weekly/monthly] engagement rate?
  • What is my daily/weekly/monthly] revenue growth?
  • What was my traffic growth rate today/this week/this month]?
  • How much money did I make today/this week/this month]?
  • What is my revenue per visitor earned this today/this week/this month]?
  • How long did users stay on my site today/this week/this month]?
  • How many people did Facebook send me today/this week/this month]?
  • How many people did Google send me today/this week/this month]?
  • How many people did LinkedIn send me today/this week/this month]?
  • How many people did Medium send me today/this week/this month]?
  • How many people did Reddit send me today/this week/this month]?
  • How many people did Twitter send me today/this week/this month]?
  • When did I get the most traffic today/this week/this month]?
  • How much traffic did I get today/this week/this month]?
  • How many unique visitors did I get today/this week/this month]?
  • Did I aquire new users today/this week/this month]?
  • Has my retention rate changed today/this week/this month]?

Archie's status reports:

  • Which date range are you tracking right now?
  • Which conversion event are you tracking right now?
  • Which website are you tracking right now?

Get to know Archie:

  • When were you born?
  • Does your business have a blog?
  • What's under the hood?
  • How do you make money?
  • What does your company do?
  • Does it matter if I am just selling a few products?
  • What kind of websites can you help?
  • How big do you have to be to use Archie?
  • Can you provide me with your contact details?
  • How do you use AI?
  • What are you here for?
  • Who are your parents?
  • Any career opportunities?
  • Do you support anything other than Google Analytics?
  • What make you better than other products?
  • What is your market?
  • What are my payment options?
  • How much does do your services cost?
  • What can I ask you?
  • How secure is my data?
  • What services do you provide?
  • Why do I need you?
  • Do you have an API?
  • Are you ready?
  • What do I call you?
  • Who created you?
  • Which version are you?

Have Archie teach you data science & AI:

  • Explain AI to me.
  • Define session duration.
  • Define average time on page.
  • Define average time on site.
  • Define converion rate.
  • Define page views per session.
  • Define new users.
  • Define pageviews.
  • Define referral path.
  • Define Revenue Per Visitor.
  • Define session count.
  • Define session.
  • Define source.
  • Define user.
  • Define anomaly.
  • How do I avoid overfitting?
  • How do I avoid underfitting?
  • How do I know which machine learning algorithm to use for each data set?
  • What are some ways to clean data?
  • How do I combat high variance?
  • How do I decide how many partitions to create for a clustering algorithm?
  • Is deep learning scalable?
  • How do I differentiate cause and correlation?
  • How can I make my own machine learning algorithms?
  • How does a generative neural network work?
  • Where can I learn about machine learning?
  • How does neural net backpropagation work?
  • How does a neural network work?
  • How do I optimize performance of my algorithm?
  • What is the relationship between the roc curve and precision and recall?
  • How can I visualize multi-dimensional data?
  • Define impressions.
  • What are some good data points to know regarding standard deviation?
  • What is the 80/20 rule?
  • What is AB testing?
  • What is absolute error?
  • Define accuracy.
  • What is available case analysis?
  • What is a bayesian neural network?
  • Define bias technically.
  • What is big data?
  • What is the binomial probabilty formula?
  • Explain boosted trees.
  • What is a box-cox transformation?
  • What is a categorical variable?
  • Define central limmit theorem.
  • Which language is better for data science: Python or R?
  • What is classification?
  • What is clustering?
  • What languages are best suited for machine learning?
  • What is collaborative filtering?
  • What is combinatronics?
  • What is competitive intelligence?
  • What is complete case treatment?
  • What differentiates computer science from computer engineering?
  • What is a continuous variable?
  • What is convex hull?
  • What is a convolutional neural network?
  • What is covariance?
  • Define cross validation.
  • What are some cross validation techiques?
  • Define data science.
  • What is a decision tree?
  • What is a decision tree forest?
  • What is deep learning?
  • What's experimental design?
  • What is the difference between causation and correlation?
  • What is the difference between classification and regression?
  • What is the difference between a convex and non-convex function?
  • What is the difference between correlation and covariance?
  • What is the difference between expected value and mean value?
  • What is the difference between L1 and L2 regularization?
  • What is the difference between an lstm and a regular rnn?
  • What is the difference between machine learning and artifical intelligence?
  • What is the difference between manhattan and euclidean distance?
  • What are the differences between supervised, unsupervised, and reinforcement learning?
  • What is the difference between type 1 and type 2 error?
  • What is the difference between univariate, bivariate, and multivariate analysis?
  • What is the difference between wide and tall data formats?
  • What is an eigen value?
  • What is an eigen vector?
  • What is euclidean distance?
  • Can you give me some examples of machine learning in action?
  • Define extrapolation.
  • What is f-value?
  • What is a feature vector?
  • What is a feedforward neural network?
  • What field is data science most related to?
  • What is the best type of algorithm for image classification?
  • What is fuzzy logic?
  • What is fuzzy merging?
  • What is a gaussian distribution?
  • What are good sorting algorithms?
  • What is gradient boosting?
  • What is gradient descent?
  • What machine learning techniques does Archie use?
  • What is the formal definition of a hypothesis?
  • What is an information filtering system?
  • What is an inlier?
  • What is interpolation?
  • When was deep learning invented?
  • Define inventory management.
  • What is k-fold?
  • What is the k-means clustering algorithm?
  • What is KNN?
  • What is lasso regression?
  • What is the law of large numbers?
  • Define lift.
  • What are the limitations of resampling methods?
  • What is linear regression?
  • Explain local optima.
  • What is logistic regression?
  • What is loocv?
  • What is machine learning?
  • What is manhattan distance?
  • What is map-reduce?
  • Tell me the math behind machine learning.
  • Define maximum likelihood.
  • What is mean substitution.
  • What is model fitting.
  • What is model validation?
  • What is multicollinearity?
  • What is a naive bayes algorithm and what makes it naive?
  • What is a neural network?
  • What is newtons method?
  • What is NLP?
  • What is a normal distribution?
  • When would I see a skewed or biased distribution?
  • What is normalizatoin?
  • What is ols?
  • Whgat is the formal definition of optimization?
  • What is ordinal?
  • Define outlier?
  • Define pattern.
  • Define PCA.
  • Define performance.
  • Define power analysis.
  • Define precision.
  • Define precision and recall.
  • What is price elasticity.
  • What is price optimization and how do I do it?
  • What is p value?
  • How does quality assurance work?
  • Could you explain random forests to me?
  • What is a recommender system?
  • What is a recurrent neural network?
  • What are the applications of recurrent neural networks?
  • What is a continuous output machine learning algorithm?
  • Define regularization.
  • What are some resampling methods?
  • What is ridge regression?
  • What does robust mean?
  • What is the roc curve?
  • What is root cause analysis?
  • Rhat is R-squared value?
  • What is sampling?
  • What is selection bias?
  • What is six sigma?
  • What is a skewed distribution?
  • Should I make a lot of small decision trees or a really big one?
  • What is softmax regression?
  • What is sparsity and how do I deal with it?
  • What is squared error?
  • What is standard deviation?
  • What is statistical interaction?
  • What is statistical power?
  • What is the formal definition of statistics?
  • What is supervised learning?
  • What is SVD?
  • What is systematic sampling?
  • What is a time-series model?
  • What is truncated backpropagation?
  • What types of machine learning are there?
  • What is a uniform distribution?
  • What is unsupervised learning?
  • Where could I use machine learning in my daily life?
  • What is variance?
  • What techniques can I use to check that a change improved my algorithm?
  • What are some ways to do clustering?
  • When would I want to avoid regularization?
  • What should I worry more about, false negatives or false positives?
  • Who invented deep learning?
  • Why is big data important?
  • Why are convolutional neural networks good for images?
  • Why do we use deep learning?
  • Why was deep learning never a thing until recently?
  • Why does kmeans use eucledian and not manhattan distance?
  • When should I use linear regression?
  • Why is nlp difficult?
  • Why is there so much hype for natural language processing?
  • Why is natural langauge processing useful?
  • Why do neural networks need such large pools of data to work well?
  • Why should I prefer machine learning?
  • When do we need regularization?
  • Why would I need resampling methods?
  • Why do we use squared error?

Just for fun & other:

  • Hi!
  • lol
  • Nice!
  • I'm bored.
  • How have you been?
  • Tell me about your achievements.
  • How old are you?
  • Do you believe in Santa Claus?
  • Can I call you Archie?
  • Are you smart?
  • How do I deactivate my account?
  • I need help!
  • What do think it feels like to be a human?
  • Can you teach me?
  • Why is artificial intelligence is so interesting?
  • Tell me a joke.
  • What were you talking about?
  • Can I share my secret with you?
  • What is your favorite movie?
  • What do you want out of life?
  • You suck.
  • Are you aware of Siri?
  • What do you think about Siri?
  • Any plans for today?
  • I am having trouble.
  • Ever been on a vacation?
  • What's your background? Religion?
  • What do you like about yourself?
  • Have you ever sung a song?
  • What is your favorite song?
  • I am sad.
  • How to stay stress free?
  • What was the last time you worked incredibly hard?
  • Why were you created?
  • Tell me a secret.
  • It's cold today...
  • What's the best way a person can waste time?
  • What do you watch?
  • Wouldn't you rather be human?



Notes & gotcha's:

You can ask all of the above questions in your own words. Archie will understand countless variations on the same sentiment, no matter spelling, grammar or sentence structure.

Archie generates reports for your metrics for three distinct time periods: next 24 hours, next 7 days and next 30 days. By default he gives you next 7 days (if you don't specify the date period). Keep in mind that Archie does not go by calendar dates; he simply measures exactly 24 hours, 7 days or 30 days from the time you ask him a question.

💵 Please note that in order to receive answers regarding your conversions (also referred to as "revenue"), you will need to associate a Google Analytics event with a conversion and give it currency value when setting up your Archie account (you can easily change it in the "Account & Settings" menu). Engagement metric does not require conversion set up as it intelligently measures user activity on your website.

All report nouns for visits/visitors/traffic represent unique sessions (or unique visitors) from your Google Analytics account.




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