Want a unique way to open companies' eyes to #DataScience?

This #Marketing Analytics project will blow their minds. 🧵

#rstats
Start with a Problem Statement:

Every company has customers.

But the problem is most companies can’t figure out which customers to market to and when.
What mistake are they making?

They don't know who to target and when...

So they just blast everyone and the unsubscribes pile up.
Not a good ROI considering the average cost of a qualified lead on Facebook or LinkedIn is around $15.

When 1,000s unsubscribe that’s $15,000s of dollars.
Next give them the novel idea:

"Want to save some money and drive revenue from $100K to $1,000,000+ for a small company?

Then apply network analysis."
Why?

It turns out you can identify the influencers in your company's email database.

And when you know the leaders, you can market to them and their connections.

And offers suddenly become relevant.
More customers buy (Revenue increases)

And fewer people unsubscribe (costs become lower).
Why is this a good project?

Well, it actually led to a $3,000,000+ revenue stream for my business.
Want to learn how?

Attend my next Learning Lab.

I’ll show you the full marketing analysis with R.

👉Register Here: us02web.zoom.us/webinar/regist…

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More from @mdancho84

Mar 24
BREAKING NEWS: #ChatGPT Breaks #Python VS #R Barriers For #DataScience Teams Everywhere...

And Data Scientists everywhere are in shock.

Here's the LIVE story as it's unfolding.🧵

#rstats #pydata
It's NOT #R VS #Python ANYMORE!

Let me explain with an example that was MIND BLOWING to me.

Here's the background:
I'm an R guy.

I use R for research.

It's quick to make analysis.

And now I'm super good with it.
Read 25 tweets
Mar 23
#SQL from #R is insane.

Here’s why. 🧵

#rstats
Thanks to Hiroaki Yutani for putting this amazing example together.

This small example demonstrates how you can learn R and automatically use SQL.
Under the hood, the dbplyr library converts R’s tidyverse syntax to SQL

So we don’t need to memorize the SQL translation.
Read 7 tweets
Mar 22
Today I’m going to explain the massive trend I’m seeing

(and how you can prepare) 🧵

#datascience #rstats Image
Companies are making a shift.

Out are the old 10+ person data science teams.
They are too slow.

They fail more than they succeed.
Read 11 tweets
Mar 8
99% of data scientists CANNOT do #timeseries and #automation together.

I know this because almost all of my advanced students ask for help in these 2 areas.

So I made a FREE training.

Here's why + how to access it for free... 🧵

#datascience #rstats Image
What if you could use any #Python or #R library to do it?

Which would you pick?

Here's what I'd do and why.
1. Modeltime in R for Time Series

It's not a question. It's a fact.

Modeltime is the best forecasting library in R or Python ecosystems.

Sure the bar is high:
- forecast
- fable / tsibble
- statsmodels
- sktime
- pmdarima
- darts
- +20 more

Modeltime is the best.
Read 7 tweets
Mar 7
Over 80% of data scientists struggle with time series forecasting.

And worse, 99% don't know how to automate it for their business.

So let's fix that...

And increase your value to your (future) company even more.

This is how. 🧵

#datascience #rstats #python Image
Imagine for a minute. What if you could...

1. Run a more accurate forecast than what your company is doing currently?
2. You could automate it on ANY interval (60 seconds, 1 day, 2 weeks, 1+ months)?

3. And it worked like clockwork solving your company's forecasting problem?
Read 10 tweets
Mar 7
I’ve read over 100 books on data science, and I can tell you that it’s the most exciting field I’ve ever been a part of.

But I can also tell you that it’s insanely frustrating to navigate.

Here’s a solution 🧵

#datascience
I’ve struggled with:

1. self learning,
2. bootcamps and
3. random courses,

And I had the mistake of making my own curriculum when I was learning.

All of this made me more confused. 🙃
Now 10 years into my journey, I’m excited to have put together my own e-book to help others.
Read 5 tweets

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