MARKETING
3 recession-defeating marketing strategies

At least thrice a week, somebody asks me if our agency business has declined because of economic uncertainty. My answer: No. Enterprise companies have not slowed down or pulled back. If anything, they are accelerating.
Consider this: 17% of companies are planning RFPs this year, according to the 2023 State of the ESP RFP. You might not think that sounds like a large number, but it is if you scale that number to industries. So, that doesn’t sound like a pullback to me.
Among the clients for whom we manage RFPs, we see more requests for technology platforms that help marketers execute and innovate faster. They ask, “What can I do to insulate myself from the coming economic apocalypse if it happens by being innovative and agile?”
Below are smart decisions to improve your business, whether the economy goes sour or not.
1. Rethink that RFP
Before you replace or add technology, ask yourself whether you maxed out your current functionality. Whenever anybody asks me to start an RFP, my first question is, “Are you using everything the platform gives you right now?”
Dig deeper: Economic uncertainty means marketers will re-evaluate ad buys more frequently in 2023
A rule of thumb holds that marketers use only about 20% to 30% of what a tech platform offers. Maybe they didn’t have time to learn how to use the really cool stuff. Or the vendor didn’t offer training. Or they couldn’t get the platform to integrate with external data sources. Sometimes it doesn’t matter how innovative the platform is. It has so many other deficits that you still need to switch.
Today’s vendor marketplace makes the RFP process much more challenging if you don’t have someone to do the work. Look at what you’re paying for now but not using before beginning the time-consuming and potentially disruptive process of finding something new.
2. Develop a plan to shift your marketing priorities
Remember when, at the height of COVID, email saved ecommerce? That’s not an exaggeration. Many companies rediscovered how well email drives sales and revenue and builds customer relationships, especially during a crisis.
Your CEO might remember that. If the CEO asks how the company could change its marketing approach, what would you say?
If your email program became your company’s hero this past few years, it’s even more likely that your CEO will seek your input now. But even if it just kept on keepin’ on, you should still have a plan for the next few months that lays out your options and how you could use them for marketing against a downturn.
What to put in your plan
It shouldn’t begin and end with “Send more email.” If your customers don’t have the money to buy more often or to fill larger carts, sending more offers won’t move the revenue needle.
Look at your targeting. Consider your segmentation program. Review your price structure on promotions. What should it look like to stimulate more sales?
Dig deeper: 5 tips to get more value from your tech stack
Identify segments that can be more lucrative to target, such as regular buyers, people who buy at full price instead of waiting for sales and shoppers who send you clear purchase or upgrade intent signals.
Look for propensity to purchase. Consider developing a next-logical-purchase plan that moves beyond cross-selling or upselling.
If your CEO asks for your advice, that’s as much of a blue-sky question as you’ll ever get. So be ready to jump. Don’t stop to think about the process. Be able to respond quickly with a plan.
It could go like this: “We need to structure campaigns around our best customers’ propensity to buy in these lines. Here’s what those email campaigns would look like.”
Develop your plan now, and have it ready to go when the CEO or another high-ranking executive comes calling. But even if that call never comes, if the recession doesn’t happen, or if your customers keep buying, why not execute your plan anyway instead of doing business as usual? This is an excellent opportunity to think strategically without getting bogged down or distracted by tactics.
If you’re unsure where to start, begin with an email audit. This can help you find gaps and other weaknesses in your messaging strategy. (Get background information and details in this earlier MarTech column: 10 questions to ask when auditing your email program.)
3. Educate yourself and reach out to your community
Think about all the advice — in columns like this on MarTech, during webinars, in white papers and guides — that poured out as the business world shifted gears during the pandemic. Expect the same if the economy stutters.
Besides these thought leadership sources, you can call on your email communities for advice and ideas. These communities thrive because the members feed off each other for support and advice.
Watch the news every day. Raise your sights and educate yourself about what’s happening in the broader economy beyond your vertical. Maybe you weren’t directly affected by the mass layoffs that have rolled through the tech industry, but the repercussions could affect your company or industry.
Spend at least an hour a week reading up on everything that’s happening in email, social media and mobile marketing, in privacy legislation and customer expectations. Add to this cauldron of content news about changes in consumer behavior, the unemployment rate and the economic impact they could have.
Be informed so that when your CEO asks for your advice, you can report what’s happening in your immediate market. CEOs can call on higher-level business forecasts, but you will be the expert on your market conditions.
Wrapping up
Use these suggestions to jumpstart your own thinking. If you want to tap into the added functionalities a new vendor can provide so you can increase your business, then go for it. Suppose implementing propensity is the right strategy to improve your marketing results; get it done.
The one thing that marks a potential recession is what we saw during COVID: fast-reaction pivots that scale to a new market condition. A recession doesn’t have to be scary. But now is not the time to rely on the adage that email is recession-proof.
Keep your eye on the future. Think back to November 2019. How would you have prepared if you had known that the world would shut down three months later? You have that time now. What’s your plan?
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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
MARKETING
The Secret to Grow Your Business

In today’s digital world where over 50% of the world’s population (Hootsuite) is on social media, leveraging social media for e-commerce marketing is a great idea if you want to grow your business.
Consider this:
According to a 2021 Sprout Social’s the State of Social Media Investment survey, 34% of online consumers say they use social media to learn about products, services, and brands.
In the same survey, 33% said they use social media to discover new products, services, and brands.
Besides, according to Hootsuite’s Global State of Digital 2022 report mentioned above, users spend 2 hours and 27 minutes on average daily on social media:
What’s more?
In 2022, global sales via social media were estimated at $992 billion. Besides, social commerce sales are forecasted to reach approximately $2.9 trillion by 2026.
Seeing all these statistics, it’s clear that using social media for e-commerce is a great idea for promoting your business online.
Still not convinced?
Here are 4 reasons why you should use social media for e-commerce.
1. Helps You Drive Website Traffic
Using social commerce is a great idea if you want to drive traffic to your website.
As mentioned in the statistics above, consumers are using social media to learn about brands and discover new products and services.
E-commerce brands can leverage this huge social audience to drive more traffic to their websites.
The good news is that social media for e-commerce is affordable. You can even drive traffic to your e-commerce website for free.
Here are handy social media tactics to drive traffic to your e-commerce website:
- Research your e-commerce target audience.
- Choose the right social media platforms that are relevant to your e-commerce business.
- Post user-generated content.
- Post valuable content consistently at the right time.
- Collaborate with influencers.
- Target your e-commerce audience with social media ads and PPC ads.
- Utilize your social media and e-commerce data.
- Follow the 80/20 rule.
2. Helps Create Brand Awareness
Social media is one of the most powerful channels for generating buzz around your brand, products, and services while managing business expenses, effectively track finances, and curtailing them thanks to a large number of users it commands.
Right social media strategy help you to increase the brand value and traffic on your ecommerce website.
According to a 2022 State of Inbound Marketing Trends report by HubSpot, 39% of marketers say their primary goal in using social media is to increase brand awareness:
By creating a robust social media marketing strategy, you can boost the visibility of your e-commerce business, thereby increasing brand recognition.
Here are practical tips to build brand awareness for your e-commerce store using social media:
- Ensure you’re using social media networks that your target customers are using.
- Create an advertising budget and stick to it to handle business finance better.
- Demonstrate your brand’s personality and values.
- Deliver valuable content consistently and engage with your audiences.
- Take advantage of trends and breaking news.
- Always track and measure progress.
3. Improves Conversions
The US retail social commerce sales are projected to reach $79.64 billion by 2025:
There’s no doubt that social media marketing can help e-commerce brands improve their conversion rates.
Thus, creating a powerful social media strategy can help you improve conversions for your e-commerce business. In fact, with features like smart links, you can easily drive B2B sales on platforms like LinkedIn too.
To help boost their conversions, Walmart partnered with a US singer Jason Derulo in a live shopping event for which the singer shared a link on Twitter.
Here is how to use social media to boost e-commerce conversions:
- Share user-generated content to empower your customers.
- Improve conversions with influencer marketing.
- Use trending and relevant hashtags.
- Drive authentic engagement.
- Build deeper trust and loyalty with your audience.
- Make it easier for customers to shop for products directly on social media.
- Leverage social media analytics.
4. Provide Customer Service
Take a look at how lululemon responded to a subscriber’s question on Twitter.
The e-commerce brand provided the subscriber with a means to reach out to customer support. And they did so quickly too.
These days, the most popular social media platforms allow customers to purchase products directly without leaving the platform. These platforms work as the most digital marketing tools for the marketers and business owners.
This makes social media an important platform for customer service for your e-commerce business.
Here are useful tips to use social media for e-commerce customer support:
- Reply to all questions, comments, concerns, and feedback.
- Know what to address in public or private.
- Address crucial matters as soon as possible.
- Respond positively to both negative and positive feedback.
Conclusion
There are many incredible benefits of using social media for e-commerce marketing.
So, if you’re not using social media to promote your brand, products, and services online then you’re missing out on a lot of huge business opportunities. In fact, you’re giving your competition the edge.
The key lies in leveraging the right social media marketing strategies and promoting your e-commerce store using them. The right combination can give your brand a lift. So, go ahead and start leveraging these strategies.
MARKETING
Mnemonic Content Strategy Framework Can Spark Conversations

I’m a sucker for mnemonics.
In fact, I remember how to spell it by “Me Nomics Except M nOt N In Case Spelling.”
OK, that’s a lie. But I daresay ChatGPT could never come up with that.
Anyway, one of my favorite idea-remembering devices comes from my hero Philip Kotler. He reduces his perfect definition of marketing to CCDVTP – Create and Communicate Value to a Target at a Profit.”
I lean on that mnemonic device when anyone asks about the best definition of marketing’s function in a business.
However, what makes a great mnemonic like CCDVTP is that each word the letter represents has something deeper behind it. So it’s not just six words – it’s six operating concepts with definitions made easier to remember by just remembering how the six words go together.
A mnemonic device for content strategy
I’ve written about the standard framework for developing or strengthening your content strategy. It’s one of the core modules of a CMI University course. It can be a lot to take in because the framework’s concepts and definitions need to be explained in varying levels of detail.
So, recently, I created a mnemonic device to use in my explanation – the 5 Cs: Coordination and Collaboration produce Content before Containers and make Channels measurable.
5Cs of #ContentStrategy: Coordination and Collaboration produce Content before Containers and make Channels measurable via @Robert_Rose @CMIContent. Click To Tweet
It works as a core or high-level definition of a content marketing strategy. But, like Kotler’s CCDVTP, it also lets me drill into the framework’s five concepts or pressure points. Let me explain:
Coordination
The primary purpose of a content strategy is to develop and manage core responsibilities and processes. In addition, they allow marketing to build and continually assess resource allocation, skill sets, and charters the marketing team needs to make content a business strength.
Most businesses that lack this C struggle with content as a repeatable or measurable approach. As I’ve said, content is everyone’s job in many businesses and no one’s strategy. A key element of a content strategy is a focus on building coordination into how ideas become content and ultimately generate business value.
Most businesses that lack coordination struggle with making #content a repeatable and measurable approach, says @Robert_Rose. Click To Tweet
Collaboration
In many businesses, content is developed in silos, especially with sales and marketing. Sometimes, it may be divided by channel – web, email, and sales teams don’t work together. In other cases, it may be by function – PR, sales, marketing, brand, and demand generation have different approaches.
Content is a team sport. The practitioners’ job is not to be good at content but to enable the business to be good at content. Scalability only happens through an effective, collaborative approach to transforming ideas into content and content into experiences.
Content before containers
As marketers, you are trained to think container first and content second. You start with “I need a web page,” “I need an email,” or “I need a blog post.” Then, your next step is to create content specific to that container.
If you start with “I need a blog post” and then create the #content idea, you’re doing it wrong, says @Robert_Rose via @CMIContent. Click To Tweet
I can’t tell you how many big ideas I’ve seen trapped in the context of a blog post simply because that was how it was conceived. I’ve also seen the reverse – small ideas spun into an e-book or white paper because someone wanted that digital asset.
This pressure point requires reverse thinking about your business’ process to create content. The first step must be to create fully formed ideas (big and small) and then (and only then) figure out which containers and how many might be appropriate.
My test to see whether marketing teams put content before containers is to look at their request or intake form. Does it say, “What kind of content do you need?” and list options, such as email, white paper, e-book, and brochure? Or does it say, “Please explain the idea or story you’d like to develop more fully?”
Channels
I purposely put channels last because they express the kind of content you create. Channels dictate how you ultimately reach the customers and how the customers will access your content. Which or how many of your content channels do you treat as a media company would?
Is your corporate blog truly centered on the audience, or is it centered on your product or brand? Is it a repository where you put everything from news about your product and how to use it to what to expect in the future and how other customers use your product?
What about your social media, website, newsletters, and thought leadership center? What is their purpose and editorial strategy? How do you evolve your content products as your audience changes as a media company does? Without a clear strategy for every channel, the measurement of content becomes guesswork at best.
When you examine your strategic approach to content, I hope the 5Cs mnemonic device helps you have those necessary conversations around coordination, collaboration, content before containers, and channels with the stakeholders in your business.
It’s your story. Tell it well.
HANDPICKED RELATED CONTENT:
Cover image by Joseph Kalinowski/Content Marketing Institute
MARKETING
The Moz Links API: An Introduction

What exactly IS an API? They’re those things that you copy and paste long strange codes into Screaming Frog for links data on a Site Crawl, right?
I’m here to tell you there’s so much more to them than that – if you’re willing to take just a few little steps. But first, some basics.
What’s an API?
API stands for “application programming interface”, and it’s just the way of… using a thing. Everything has an API. The web is a giant API that takes URLs as input and returns pages.
But special data services like the Moz Links API have their own set of rules. These rules vary from service to service and can be a major stumbling block for people taking the next step.
When Screaming Frog gives you the extra links columns in a crawl, it’s using the Moz Links API, but you can have this capability anywhere. For example, all that tedious manual stuff you do in spreadsheet environments can be automated from data-pull to formatting and emailing a report.
If you take this next step, you can be more efficient than your competitors, designing and delivering your own SEO services instead of relying upon, paying for, and being limited by the next proprietary product integration.
GET vs. POST
Most APIs you’ll encounter use the same data transport mechanism as the web. That means there’s a URL involved just like a website. Don’t get scared! It’s easier than you think. In many ways, using an API is just like using a website.
As with loading web pages, the request may be in one of two places: the URL itself, or in the body of the request. The URL is called the “endpoint” and the often invisibly submitted extra part of the request is called the “payload” or “data”. When the data is in the URL, it’s called a “query string” and indicates the “GET” method is used. You see this all the time when you search:
https://www.google.com/search?q=moz+links+api <-- GET method
When the data of the request is hidden, it’s called a “POST” request. You see this when you submit a form on the web and the submitted data does not show on the URL. When you hit the back button after such a POST, browsers usually warn you against double-submits. The reason the POST method is often used is that you can fit a lot more in the request using the POST method than the GET method. URLs would get very long otherwise. The Moz Links API uses the POST method.
Making requests
A web browser is what traditionally makes requests of websites for web pages. The browser is a type of software known as a client. Clients are what make requests of services. More than just browsers can make requests. The ability to make client web requests is often built into programming languages like Python, or can be broken out as a standalone tool. The most popular tools for making requests outside a browser are curl and wget.
We are discussing Python here. Python has a built-in library called URLLIB, but it’s designed to handle so many different types of requests that it’s a bit of a pain to use. There are other libraries that are more specialized for making requests of APIs. The most popular for Python is called requests. It’s so popular that it’s used for almost every Python API tutorial you’ll find on the web. So I will use it too. This is what “hitting” the Moz Links API looks like:
response = requests.post(endpoint, data=json_string, auth=auth_tuple)
Given that everything was set up correctly (more on that soon), this will produce the following output:
{'next_token': 'JYkQVg4s9ak8iRBWDiz1qTyguYswnj035nqrQ1oIbW96IGJsb2dZgGzDeAM7Rw==', 'results': [{'anchor_text': 'moz', 'external_pages': 7162, 'external_root_domains': 2026}]}
This is JSON data. It’s contained within the response object that was returned from the API. It’s not on the drive or in a file. It’s in memory. So long as it’s in memory, you can do stuff with it (often just saving it to a file).
If you wanted to grab a piece of data within such a response, you could refer to it like this:
response['results'][0]['external_pages']
This says: “Give me the first item in the results list, and then give me the external_pages value from that item.” The result would be 7162.
NOTE: If you’re actually following along executing code, the above line won’t work alone. There’s a certain amount of setup we’ll do shortly, including installing the requests library and setting up a few variables. But this is the basic idea.
JSON
JSON stands for JavaScript Object Notation. It’s a way of representing data in a way that’s easy for humans to read and write. It’s also easy for computers to read and write. It’s a very common data format for APIs that has somewhat taken over the world since the older ways were too difficult for most people to use. Some people might call this part of the “restful” API movement, but the much more difficult XML format is also considered “restful” and everyone seems to have their own interpretation. Consequently, I find it best to just focus on JSON and how it gets in and out of Python.
Python dictionaries
I lied to you. I said that the data structure you were looking at above was JSON. Technically it’s really a Python dictionary or dict datatype object. It’s a special kind of object in Python that’s designed to hold key/value pairs. The keys are strings and the values can be any type of object. The keys are like the column names in a spreadsheet. The values are like the cells in the spreadsheet. In this way, you can think of a Python dict as a JSON object. For example here’s creating a dict in Python:
my_dict = { "name": "Mike", "age": 52, "city": "New York" }
And here is the equivalent in JavaScript:
var my_json = { "name": "Mike", "age": 52, "city": "New York" }
Pretty much the same thing, right? Look closely. Key-names and string values get double-quotes. Numbers don’t. These rules apply consistently between JSON and Python dicts. So as you might imagine, it’s easy for JSON data to flow in and out of Python. This is a great gift that has made modern API-work highly accessible to the beginner through a tool that has revolutionized the field of data science and is making inroads into marketing, Jupyter Notebooks.
Flattening data
But beware! As data flows between systems, it’s not uncommon for the data to subtly change. For example, the JSON data above might be converted to a string. Strings might look exactly like JSON, but they’re not. They’re just a bunch of characters. Sometimes you’ll hear it called “serializing”, or “flattening”. It’s a subtle point, but worth understanding as it will help with one of the largest stumbling blocks with the Moz Links (and most JSON) APIs.
Objects have APIs
Actual JSON or dict objects have their own little APIs for accessing the data inside of them. The ability to use these JSON and dict APIs goes away when the data is flattened into a string, but it will travel between systems more easily, and when it arrives at the other end, it will be “deserialized” and the API will come back on the other system.
Data flowing between systems
This is the concept of portable, interoperable data. Back when it was called Electronic Data Interchange (or EDI), it was a very big deal. Then along came the web and then XML and then JSON and now it’s just a normal part of doing business.
If you’re in Python and you want to convert a dict to a flattened JSON string, you do the following:
import json my_dict = { "name": "Mike", "age": 52, "city": "New York" } json_string = json.dumps(my_dict)
…which would produce the following output:
'{"name": "Mike", "age": 52, "city": "New York"}'
This looks almost the same as the original dict, but if you look closely you can see that single-quotes are used around the entire thing. Another obvious difference is that you can line-wrap real structured data for readability without any ill effect. You can’t do it so easily with strings. That’s why it’s presented all on one line in the above snippet.
Such stringifying processes are done when passing data between different systems because they are not always compatible. Normal text strings on the other hand are compatible with almost everything and can be passed on web-requests with ease. Such flattened strings of JSON data are frequently referred to as the request.
Anatomy of a request
Again, here’s the example request we made above:
response = requests.post(endpoint, data=json_string, auth=auth_tuple)
Now that you understand what the variable name json_string is telling you about its contents, you shouldn’t be surprised to see this is how we populate that variable:
data_dict = { "target": "moz.com/blog", "scope": "page", "limit": 1 } json_string = json.dumps(data_dict)
…and the contents of json_string looks like this:
'{"target": "moz.com/blog", "scope": "page", "limit": 1}'
This is one of my key discoveries in learning the Moz Links API. This is in common with countless other APIs out there but trips me up every time because it’s so much more convenient to work with structured dicts than flattened strings. However, most APIs expect the data to be a string for portability between systems, so we have to convert it at the last moment before the actual API-call occurs.
Pythonic loads and dumps
Now you may be wondering in that above example, what a dump is doing in the middle of the code. The json.dumps() function is called a “dumper” because it takes a Python object and dumps it into a string. The json.loads() function is called a “loader” because it takes a string and loads it into a Python object.
The reason for what appear to be singular and plural options are actually binary and string options. If your data is binary, you use json.load() and json.dump(). If your data is a string, you use json.loads() and json.dumps(). The s stands for string. Leaving the s off means binary.
Don’t let anybody tell you Python is perfect. It’s just that its rough edges are not excessively objectionable.
Assignment vs. equality
For those of you completely new to Python or programming in general, what we’re doing when we hit the API is called an assignment. The result of requests.post() is being assigned to the variable named response.
response = requests.post(endpoint, data=json_string, auth=auth_tuple)
We are using the = sign to assign the value of the right side of the equation to the variable on the left side of the equation. The variable response is now a reference to the object that was returned from the API. Assignment is different from equality. The == sign is used for equality.
# This is assignment: a = 1 # a is now equal to 1 # This is equality: a == 1 # True, but relies that the above line has been executed
The POST method
response = requests.post(endpoint, data=json_string, auth=auth_tuple)
The requests library has a function called post() that takes 3 arguments. The first argument is the URL of the endpoint. The second argument is the data to send to the endpoint. The third argument is the authentication information to send to the endpoint.
Keyword parameters and their arguments
You may notice that some of the arguments to the post() function have names. Names are set equal to values using the = sign. Here’s how Python functions get defined. The first argument is positional both because it comes first and also because there’s no keyword. Keyworded arguments come after position-dependent arguments. Trust me, it all makes sense after a while. We all start to think like Guido van Rossum.
def arbitrary_function(argument1, name=argument2): # do stuff
The name in the above example is called a “keyword” and the values that come in on those locations are called “arguments”. Now arguments are assigned to variable names right in the function definition, so you can refer to either argument1 or argument2 anywhere inside this function. If you’d like to learn more about the rules of Python functions, you can read about them here.
Setting up the request
Okay, so let’s let you do everything necessary for that success assured moment. We’ve been showing the basic request:
response = requests.post(endpoint, data=json_string, auth=auth_tuple)
…but we haven’t shown everything that goes into it. Let’s do that now. If you’re following along and don’t have the requests library installed, you can do so with the following command from the same terminal environment from which you run Python:
pip install requests
Often times Jupyter will have the requests library installed already, but in case it doesn’t, you can install it with the following command from inside a Notebook cell:
!pip install requests
And now we can put it all together. There’s only a few things here that are new. The most important is how we’re taking 2 different variables and combining them into a single variable called AUTH_TUPLE. You will have to get your own ACCESSID and SECRETKEY from the Moz.com website.
The API expects these two values to be passed as a Python data structure called a tuple. A tuple is a list of values that don’t change. I find it interesting that requests.post() expects flattened strings for the data parameter, but expects a tuple for the auth parameter. I suppose it makes sense, but these are the subtle things to understand when working with APIs.
Here’s the full code:
import json import pprint import requests # Set Constants ACCESSID = "mozscape-1234567890" # Replace with your access ID SECRETKEY = "1234567890abcdef1234567890abcdef" # Replace with your secret key AUTH_TUPLE = (ACCESSID, SECRETKEY) # Set Variables endpoint = "https://lsapi.seomoz.com/v2/anchor_text" data_dict = {"target": "moz.com/blog", "scope": "page", "limit": 1} json_string = json.dumps(data_dict) # Make the Request response = requests.post(endpoint, data=json_string, auth=AUTH_TUPLE) # Print the Response pprint(response.json())
…which outputs:
{'next_token': 'JYkQVg4s9ak8iRBWDiz1qTyguYswnj035nqrQ1oIbW96IGJsb2dZgGzDeAM7Rw==', 'results': [{'anchor_text': 'moz', 'external_pages': 7162, 'external_root_domains': 2026}]}
Using all upper case for the AUTH_TUPLE variable is a convention many use in Python to indicate that the variable is a constant. It’s not a requirement, but it’s a good idea to follow conventions when you can.
You may notice that I didn’t use all uppercase for the endpoint variable. That’s because the anchor_text endpoint is not a constant. There are a number of different endpoints that can take its place depending on what sort of lookup we wanted to do. The choices are:
-
anchor_text
-
final_redirect
-
global_top_pages
-
global_top_root_domains
-
index_metadata
-
link_intersect
-
link_status
-
linking_root_domains
-
links
-
top_pages
-
url_metrics
-
usage_data
And that leads into the Jupyter Notebook that I prepared on this topic located here on Github. With this Notebook you can extend the example I gave here to any of the 12 available endpoints to create a variety of useful deliverables, which will be the subject of articles to follow.
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