Let’s start from the bottom line - I’ve found a stupid-simple way to make my video calls 30-50% more productive.

Ready for it? Here’s the playbook:

I use this wallpaper as my virtual background.

How I came up with this

This isn’t specific to marketers per se, but it’s been so effective for me that it’s crazy not to share. So let’s break it down.

Live many others around the world, I take a lot of video calls. And since COVID, my number of daily/weekly video meetings has only increased.

But for all the convenience, there was a downside and I grew frustrated with how little I was able to accomplish during these meetings. More often than not, it seemed like there wasn’t enough time on these calls to get to the important stuff. So I’d end up scheduling a follow-up and hoping for the best.

About a year ago, it got to the point where I felt compelled to make an adjustment. So I spent some time analyzing my video-call productivity and developed a theory. I realized that the productivity and familiarity of the call participants were closely correlated. My most inefficient calls seemed to be with people I didn’t know well, or with people I was meeting for the first time.

Many of these “inefficient” calls followed a simple pattern. The first 5-10 minutes of the call were spent on formal introductions and pleasantries. The next 20-25 minutes were focused on the agenda at hand, but an underlying sense of formality remained throughout.

To be clear, I’m all for formalities and professionalism. I’m also a natural people-person who can make conversation pretty easily. But there are plenty of folks out there who don’t feel as comfortable in these settings. And this impacts their ability to quickly get into a conversational rhythm on an otherwise unnatural video call with a complete stranger staring at them through the screen.

When it comes to these short conversations, it’s clear to me that comfort = efficiency. If I wanted to get more out of these calls, I needed a (really quick) way to create a comfortable, natural setting for everyone involved.

And after a bit of trial end error, I found the magic solution I was looking for in the form of a panoramic shot of an empty Madison Square Garden.

Why (I think) it works so well

The wallpaper background acts as a built-in conversation starter. It’s a picture that catches people off guard (without being offensive) and give them something to comment on and ask about within the first 30 seconds of the call:

“What stadium is that?”

“I love basketball!”

“Are you a Knicks fan?” (I’m not BTW…)

“Are you based in New York”

“Wow. Great picture!”

I get some version of this comment ~80% of the time.

And it seems like this small, natural exchange is just enough to set a more comfortable, open tone for the rest of the conversation. They comment and smike. I crack a joke in response. Everyone wins. Now let’s get down to business.

Try it yourself with MSG or whatever other empty stadium you prefer, and let me know how it goes.

LinkedIn has become a can't-miss platform for publishing professional content.

There are a lot of folks out there offering advice on how to build a LinkedIn content strategy. They focus on content clusters, post frequency, strategic engagement with other accounts, and other people's content.

All great. All important.

But the one part of the equation that many people skip is giving proper consideration to what type of post each post will be.

Whether you know it or not, every time you post on LinkedIn, you choose to put your genius post into one of four buckets on the LinkedIn Post Matrix. Knowing these categories will help you to be more deliberate with how you craft your content, and how you track which types of posts are most effective for you.

Here's my breakdown of the four types of LinkedIn posts including:

• What it's called

• What it communicates to the reader

• What it asks the reader to do

• The relative content value (how much readers are likely to care)

• The relative CTA (call to action) value (how readers are likely to care about the action you're asking them to take in your post)

(1) 💪 Flex posts

• 👉 What it communicates: I won this award. I gave this speech. I am so productive. I am so successful.

• 👉 What it asks you to do: Look at me. Pat me on the back.

• Content value (for the reader)= low🔻

• CTA value (for the reader) = low🔻

(2) 👀 Promotional posts

• 👉 What it communicates: This is my product/service/event/company. It’s awesome.

• 👉 What it asks you to do: Buy it/try it/apply for it/call me.

• Content value = low🔻

• CTA value = high🔺

(3) 🤔 Thoughtful posts

• 👉 What it communicates: Here’s an (often high-level, general) insight, observation, or new perspective that you might find interesting.

• 👉 What it asks you to do: Think about it yourself. consider sharing your own perspectives and experiences.

• Content value = high🔺

• CTA value = low🔻

(4) 💡 Informative posts

• 👉 What it communicates: Here’s some information (tool, recommendation, playbook, etc.) that I have that you might find valuable + actionable.

• 👉 What it asks you to do: Learn this/use this/try this to move ahead in a tangible, quantifiable way.

• Content value = high🔺

• CTA value = high🔺

A couple of quick thoughts based on this premise:

• I'm not post-shaming. There’s a legitimate time and place for all four types.

• Some people try to mix and match within the same post. They'll write a 'thoughtful' post for example, and then quickly end it with a 'promotional' CTA to call them or hire them as a guru/consultant. Curious if this approach converts well.

• Buckets 3 and 4 are self-sufficient. You can probably get good engagement and reach by only posting this content. But 1 and 2 get old quickly if left to fend for themselves. So share as many insights and tactics as you want. Don’t talk only about yourself.

• This isn’t exclusive to LinkedIn content. You can apply these categories to most other content that is created on other platforms.

What do you do? And why should I care?

Sure, people can talk about their product in conversation. They know what they are building and why it’s important. But breaking it down into something that can be used on a landing page, in an ad campaign or as an elevator pitch is a different ball game.

I’ve create a simple shortcut framework for quickly approaching this in a more systematic way. This is not a comprehensive solution, but it is a good way to break through the chaos and creativity block of early-stage marketing efforts.

Hopefully this will help you in:

• Better defining your products value proposition(s)

• More clearly developing your early-stage marketing strategy as you try and understand what messaging should be used in your assets and campaigns

This framework has 3 parts:

1. How to define your value proposition

2. How to expand this to understant your “benefit ripple effect”

3. How to use your benefit ripple effect to create your early marketing assets

A simple formula for defining your value proposition

What does your company do?

Ask 10 people this question. I bet at least half will struggle to give you a clear, concise response.

Here’s a simple framework I use to define a “value proposition”:
𝙑𝙖𝙡𝙪𝙚 𝙥𝙧𝙤𝙥 = 𝙘𝙖𝙥𝙖𝙗𝙞𝙡𝙞𝙩𝙞𝙚𝙨 + 𝙩𝙖𝙧𝙜𝙚𝙩 𝙖𝙪𝙙𝙞𝙚𝙣𝙘𝙚 + 𝙗𝙚𝙣𝙚𝙛𝙞𝙩𝙨.

Where:
𝗖𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 = Functionality of your product (what it does).
𝗧𝗮𝗿𝗴𝗲𝘁 𝗮𝘂𝗱𝗶𝗲𝗻𝗰𝗲 = Who you are trying to talk to and attract.
𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 = How a user's life is different/better after using your product.

In other words, a solid response to my above question would be:
𝙈𝙮 𝙥𝙧𝙤𝙙𝙪𝙘𝙩 𝙙𝙤𝙚𝙨 [𝙘𝙖𝙥𝙖𝙗𝙞𝙡𝙞𝙩𝙮] 𝙨𝙤 𝙩𝙝𝙖𝙩 [𝙩𝙖𝙧𝙜𝙚𝙩 𝙖𝙪𝙙𝙞𝙚𝙣𝙘𝙚] 𝙘𝙖𝙣 𝙖𝙘𝙝𝙞𝙚𝙫𝙚 [𝙗𝙚𝙣𝙚𝙛𝙞𝙩].

Now, you’re probably thinking to yourself - this is a good start, but my product has multiple capabilities, several target personas, and many benefits.

And you’re right.

This framework is just a starting point.

The next step is to understand what I call your product's "benefit ripple effect".

The "benefit ripple effect" of your product

Instead of stopping with just one “benefit” on our list, we can identify multiple “layers” or “degrees” of benefits that our product offers. (there are often more than you realize).

A fun way to identify multiple degrees of benefits is by playing the good old “so that…” game.

Here’s how you do it:

Take the first benefit on your list (remember, “benefit” = one way that you make your user's life different/better than it was before they met you).

Say it out loud.

Then, say “so that…” and simply continue the train of thought.

Sounds silly. But I’m 100% serious.

So for example, let’s say we were selling a budgeting app. Our train of thought might look something like this:

“Our capability = Our app shows you all of your spending in one place…”

“The benefits of our app = …So that you can stay more organized → So that you can make better spending decisions → So that you can save money → So that you can get out of debt → So that you can lower your stress levels → So that you can save your marriage…”

Great! This is a healthy list that shows the “benefit ripple effect” of your app.

And why is any of this useful?

Because you'll need to draw on this list when creating your initial content and marketing assets.

See, not every benefit on your list is appropriate for every type of asset you'll create. You'll need to match them up strategically.

Using the "benefit ripple effect" in your marketing assets

With our list of benefits clearly in front of us, we can appreciate an important marketing reality:

𝗧𝗵𝗲 𝗰𝗹𝗼𝘀𝗲𝗿 𝗮 𝗯𝗲𝗻𝗲𝗳𝗶𝘁 𝗶𝘀 𝘁𝗼 𝘁𝗵𝗲 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘁𝘆 𝗼𝗳 𝘁𝗵𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁, 𝘁𝗵𝗲 𝗺𝗼𝗿𝗲 𝗶𝗻𝗵𝗲𝗿𝗲𝗻𝘁𝗹𝘆 𝗯𝗲𝗹𝗶𝗲𝘃𝗮𝗯𝗹𝗲 𝗶𝘁 𝗶𝘀.

To use the above example, we don't need to work that hard to convince someone that our budgeting app "shows all spending in one place".

After all... that's what the app is built to do.

But if you tell the same person that the budgeting app "saves marriages", he'll raise his eyebrows and laugh in your face. Because this benefit (saving marriages) is farther removed from the product itself and is, therefore, less inherently believable.

This correlation between product proximity and inherent believability helps us decide what benefits apply to which marketing assets.

For example, when drafting the copy for the hero section of a landing page, we generally want to base our messaging on the more inherently believable benefits. We want people who visit the landing page to immediately and unequivocally understand what the product does and how it helps. So it makes sense to use clear, inherently believable benefits for this purpose.

But for other assets, like social proof from current users, we can focus on the less-believable, farther-removed benefits of the product. The experiences of real users can be the missing "proof" that the product has superpowers extending way beyond the functionality itself - like lowering stress, saving marriages, and generally impacting the quality of users' lives.

There's no objectively right or wrong way to go about any of this. But hopefully, some of this can help some of you operate more clearly and experiment more deliberately in your GTM process.

GitHub is the world’s largest social network for technical people, which makes it a great source of information and targeted activities if you’re targeting a technical audience.

But unlike other social networks, GitHub isn’t built for direct communication or chat. It’s designed to get people to look at projects and contribute code. GitHub users can also leave a “star” on projects they’re interested in. It’s equivalent to an “upvote” or a “like” on other platforms.

Analyzing clusters of users based on the projects they star, or the contributions they make can be very helpful for dev-marketers. Check out this playbook, for example, to see how I’ve put this into action IRL.

The hard part is accessing and exporting this information from GitHub.

So I’m going to outline the steps and the tools I use to export this data from GitHub and get it into a usable CSV.

GitHub GraphQL API Explorer

The main tool I use for this is the GitHub GraphQL API Explorer. It allows me to export lists of Stargazers from specific GitHub projects, together with their GitHub profile information.

It’s not glamorous, but it’s the path of least resistance to extracting the info I need.

Here’s how I use it.

The initial query - first 100 results

Open the GitHub GraphQL API Explorer and login with your GitHub account.

Paste the following query into the left pane of the Explorer to extract the relevant data from your desired GitHub project:

{
  repository(owner: "[repo owner]", name: "[repo name]"){
    stargazers(first: 100){
      pageInfo{
        endCursor
        
        hasNextPage
      }
      nodes{
        company
        email
        login
        email
        twitterUsername
        websiteUrl
        followers{
          totalCount
        }
        organizations(first:10){
          nodes{
            name
          }
        }
      }
    }
  }
}

You’ll need to replace the “owner” and “ name” to match the specific repository you’re targeting to extract stargazer lists.

Press the "play” button to run the query. The output is a list of 100 stargazers with the relevant profile information displayed in JSON format on the right side of the Explorer.

100 is the maximum number of results that the API allows in one batch. You can extract additional batches of 100 stargazers from the list by simply running the command again, and telling it to extract the next set of 100 users. But we’ll get to that in a second. First, let’s understand what to do with this raw JSON.

Converting the JSON to CSV

Once you have the JSON staring you in the face, you need to convert it to something usable, like a CSV. I found a simple “JSON to CSV converter” that you can use for free.

Copy the JSON results from the GitHub API explorer, and paste it into the JSON converter. The output is a table with the results that can be copied/pasted into a spreadsheet.

There are ways to further automate this part of the process, but you need to know a little coding to do that. So for now, we’ll stick to the basics.

With the first 100 results in your spreadsheet, you’re ready to get some more. To do this, you need to ask the GitHub Explorer to show you the next set of 100 results in the list.

Asking GitHub for the next 100 users in the list

To do so, go back to the same GitHub Explorer window and modify the top of the query that you’re using in the left panel. The top few lines currently look like this:

{
  repository(owner: "[repo owner]", name: "[repo name]"){
    stargazers(first: 100){
      pageInfo{
        endCursor

You now want it to modify those lines with two simple changes:

• Add the “after” parameter

• Make it point to the “endCursor” string

So now, the query on the left side looks like this:

{
  repository(owner: "[repo owner]", name: "[repo name]"){
    stargazers(first: 100 after: "[the endCursor string]="){
      pageInfo{
        endCursor

Now, copy the long “endCursor” string that appears at the top of the right panel, above the first 100 results. Paste that string next to the “after” parameter in your query. (replacing “the endCursor string” placeholder text above).

This is basically asking the API to pull the next 100 results in the list.

Every page of 100 results that is displayed has a unique “endCursor” string that appears at the top of it. So to see the next 100 results in the list, simply copy the endCursor, paste it into the query, and run the query again with the “play” button.

Here’s what it looks like IRL:

Each time the new endCursor is applied to the query and the query is run again, the results on the right side will update to show the next 100 users in the list.

For each set of 100 users, simply use the JSON-to-CSV tool to convert it and append it to your growing spreadsheet of contacts.

Run this as many times as needed until you have a healthy number of contacts to work with.

• Pro tip: Before closing your API Explorer window and analyzing your spreadsheet of GitHub contacts, Copy the next query that you’ll want to run and paste it somewhere for safekeeping. This will let you pick up where you left off in the stargazers list (which can be pretty long for a popular project).

At least 2 things in life are certain:

1. Developers hate marketing in all its forms

2. Developers REALLY hate receiving cold emails

So when one of my cold email experiments performed consistently well with developers, I was thrilled.

It’s an approach that combines multiple steps and several assumptions. But the underlying keys to success really come down to doing two things well:

• Identifying relevant targets before sending out any emails.

• Communicating with email recipients in a normal, effective way.

Here’s the whole playbook broken down step by step.

The playbook

Use GitHub to find relevant targets

This playbook revolves around GitHub, which is the world’s largest social network for technical people. I first tried it as part of the go-to-market play for Preevy - an open-source tool that we built at Livecycle.

Unlike other social networks, GitHub isn’t built for direct communication or chat. It’s designed to get people to look at projects and contribute code. GitHub users can also leave a “star” on projects they’re interested in. It’s equivalent to an “upvote” or a “like” on other platforms. And from a marketing and outreach perspective, GitHub is a powerful source of information.

So, once Preevy had reached a hundred stars or so, I used GitHub to better focus my upcoming marketing efforts. I did this by analyzing our list of “stargazers”. By understanding who was interested in our tool, I could do a better job of targeting similar people going forward.

I started by looking at commonly-starred GitHub repositories. I used a tool called Clickhouse to identify the other GitHub projects our group of stargazers had starred most frequently. These commonly-starred repositories represented an expanded pool of potential stargazers (and users) of Preevy.

Focus on the people who want to be contacted

This expanded pool of targets was a focused list of qualified personas - people who (likely) possessed the technical skill, experience, and interest to be relevant for Preevy.

My next step was to try and see if I could further focus on the people in this pool who also showed qualified intent.

In general, when you only qualify the persona, you’re just assessing if the people are technically qualified to do what you ask of them. When you qualify intent, you’re making sure the people are willing and interested to do so. Qualifying both persona + intent = you’re in really good shape.

In my case, the “intent” I needed was the willingness to open an email. To qualify this intent, I reduced my list of targets to those who had exposed email addresses on their GitHub profile page. I assumed that by publically listing their email address, these users were announcing that they were open to being contacted, out of the blue.

Exporting lists of stargazers from GitHub

Once I had my list of qualified targets in mind, I needed to export the list and their email addresses. But this was easier said than done.

Going through GitHub profiles one by one would take far too long, so I used the GitHub GraphQL API Explorer to batch the process and speed things up.

The GitHub GraphQL API provides native support for exporting lists of stargazers, and the Explorer is a convenient way for actually executing it.

It wasn’t glamorous, but it was the path of least resistance to extract the info I needed.

To see exactly how I used the API to export the user data from GitHub, check out this technical playbook with the details.

Give before asking for something in return

With the help of the GitHub API, I was able to generate a long list of qualified names and email addresses kept neatly in a spreadsheet.

But before actually reaching out to these people, I did one more thing to increase my chances for success.

I found a way to “give” before asking for something in return.

The vast majority of cold outreach is just someone asking you for something - Try this. Buy this. Subscribe to this. It’s far more uncommon for someone to offer you something. This is why many of us are pleasantly surprised when someone offers us a compliment or positive feedback. We instinctively don’t expect it.

In my experience, when you first offer and give, the recipient is more willing to listen and reply. And even if you end up asking them for something later on, they are more likely to respond positively once they’ve connected with you in this positive way.

The easiest and quickest way for me to “give” to my list of target users was to follow them on GitHub.

Like other social networks, GitHub allows you to follow other users. Unlike other social networks though, GitHub users have far fewer followers on average. When you follow someone, it means that you are taking the time to acknowledge them and their work. And chances are, they’ll see the notification and appreciate the thought.

By first following these users, I created an opportunity to focus my cold email on what I’ve given them (“just followed you on GitHub!”) and not what I want in return (“check out my open source project!”).

But once again - easier said than done.

Following thousands of GitHub users one by one, by hand, would take forever. I sped things up by using a Python script to automate this process (I’ll be posting the details in a separate, technical playbook - stay tuned).

Before long, I had a spreadsheet with my targets and I had followed them all on GitHub. Now I was ready to reach out.

Send a human-sounding email

My first few rounds of emails were sent via HubSpot. But I was soon blocked from sending more. HubSpot picked up that this was cold outreach, and while there was nothing technically (or legally) wrong with what I was doing, they weren’t into it. They didn’t love the fact that I was marking these people as “marketing contacts” (a HubSpot prerequisite when sending emails such as these) when the recipients hadn’t yet opted in.

Not wanting to compromise our HubSpot account, I moved over to other email marketing platforms.

I am currently sending most of my emails via AdRoll. I’m not thrilled with their platform, but it does the job. For now. Maybe we’ll cover some of these solutions in another post.

But for now, let’s turn to the email itself. It looked something like this:

Subject: hi - just followed you on github!

Hey [first name] 👋

I just followed you on GitHub - Looks like you're a Docker/open-source fan, so we have that in common. I'm always on the lookout for smart people I can connect with and learn from, so I figured I'd reach out.

I also thought you’d be interested in some of the tools my team is working on:

• "Preevy" - We've built an open-source CLI that makes it easy for developers to provision shareable preview environments for any Docker-Compose application the the cloud.

• Docker Extension - We're launching a Docker Desktop extension that lets you share your local development environment with remote team members and Get instant feedback without the hassle of commits, deployments and CI builds. You can also create a preview environment in the cloud at any time if needed.

If it sounds interesting, we’d be thrilled to have you try it for yourself. Here are the relevant links:

• Preevy GitHub repository

• Docker Extension

• Docker Extension demo videos

Obviously, no pressure or strings attached. We're just looking for some smart people who can benefit from our tools.

And if there is anything we can do in return (star a repo, give feedback, send you free swag etc. etc.) let me know and we'll do our best to make it happen!!

Thanks for your time! 🤩 🙏

Cheers,

Zevi

A few notes regarding the email:

• It wasn’t stylized or decorated. I wanted it to look authentic and personal

• I intentionally used lower-case letters for the subject line so it would look more like a real person wrote it

• I started by emphasizing what we have in common, and then presented what we’re working on in a non-salesy way

• I ended the email by offering to help in any way possible, with a few specific examples

The results

This approach has been working pretty well for me:

• ~60% unique open rate

• ~30% unique click rate

• Hundreds of GitHub stars

• Dozens of nice replies and collaboration opportunities

Here are a few of the human responses that I’ve received. Note how some people even complimented me on my marketing!

Summary

To sum up my key suggestions for cold-email outreach:

• Try to double and triple qualify your targets (look for intent, not just persona)

• Give before you ask for something in return

• Communicate like a human

• Don’t try to sell anything, but clearly present your offering

• Automate and scale the process as much as you can, but not at the expense of the above steps.

The rule states that 3 hours is the smallest reasonable investment of time needed to assess your ability to set up a new system with which you have zero familiarity.

If, after 3 hours, you manage to research and get something working to 80% functionality or more, then it’s worth completing the job on your own.

If however, you can’t manage 80% of it in 3 hours, then its a sign that you should strongly consider buying this thing off the shelf (if possible) or just hire someone on Fiverr to build it for you.

I used the 3-hour build vs. buy assessment in this playbook when deciding to build an automated swag store.

• How (and why) I built an automated swag store for Livecycle

• How I used my “3-hour build vs. buy” assessment to decide to do it

The problem

Swag is part of startup life. But it can also be a pain - designing, creating, and shipping it to users, fans, and investors. It’s a process that can quickly take up precious time and focus resources that a small, early-stage company doesn’t have to spend.

So when I first joined Livecycle to lead their GTM team, I knew I needed to find a way to make life easier.

A creative alternative

I knew what I wanted to achieve:

• The ability to design new products easily, on my own (I am not a professional designer)

• Avoid any involvement in the time-consuming printing, fulfillment, and shipping processes

I was reminded of people on social media bragging about how easy it was to create a private, online apparel store, so I wondered - what if I could do the same thing for our company brand? Unlike the social media stars, I wasn’t looking to generate revenue from this, but perhaps this could be a creative option for addressing my design, fulfillment, and shipping needs.

Conceptually, it seemed simple enough. Create an online storefront, connect it to an apparel fulfillment service, create some designs, and have stuff shipped to the relevant folks around the world as needed (perhaps even automatically, with some defined sequences and triggers).

I was encouraged when I saw some of my forward-thinking developer tool friends (at daily.dev and Amplication for example) running similar experiments for their companies.

The 3-hour build vs. buy assessment

My main objective was to save time. So I needed to make sure that my idea for an automated swag store wouldn’t become an ongoing babysitting job for me or anyone else on my team.

To complicate matters - I had very little experience building e-commerce entities from the ground up on my own, so there would almost certainly be a learning curve.

Was it worth the risk? Maybe I should just hire someone on Fiverr to do it all for me.

Enter the 3-hour build vs. buy assessment.

It’s a simple guiding principle (that I made up) that states that it takes up to 3 hours to assess your ability to set up a new system with which you have zero prior familiarity.

If, after 3 hours you managed to research and set it up to at least 80% functionality - it’s worth completing the job on your own. If however, you can’t manage 80% of it in 3 hours on your own, then it’s worth buying it off the shelf or hiring someone to build it for you.

3 hours later, I had a basically functioning storefront with a few branded products.

Here’s how I set up:

The step-by-step playbook

1. Create a Shopify storefront - First, I created a Shopify account and set up a storefront where users can order their swag directly with a gift card (more on that in a minute). Shopify has a bunch of themes to choose from. I opted to stick with a free, basic theme because I wasn’t trying to optimize for the ultimate in-store experience. I just needed it to be functional.

2. Create a Printful account - The next step was to set up an account with a print-on-demand service. I chose Printful, but there are other similar options out there to choose from. Printful deals with the catalog of products, printing, fulfillment, and shipping.

3. Create products in Printful and Sync them to Shopify - Once Printful was set up, I chose a few products and designed them with the drag-and-drop design features (I suggest you pick one or two products to start so you don’t get carried away with their catalog). I then synced the products to my connected Shopify storefront

4. Create a subdomain to host it - We chose something simple: store.livecycle.io

5. Expose the store on our site - Once I had a few products, I exposed the storefront on our site

6. Issue coupons and let people do their thing - When I want to send someone swag, all I need to do is go to Shopify and create a gift card for them. I can give them a specific amount of money or gift them a specific product. I send the user the digital gift card code, and they order the merch to their preferred location.

7. Further automation - This can be automated further by issuing a series of gift cards and distributing them based on some user sequence.

A few caveats and notes:

• As mentioned above, we were not looking to make tons of revenue off of this. We just wanted a convenient way to ship cool swag to people around the world. If you are just looking to save (or make) money off of this, there might be better ways to go.

• I suggest you read reviews from the Printful/fulfillment catalog. I tried to get fancy with some of the t-shirts and was disappointed with the quality. For me, it was better to stick to the basic, highly-rated items on their list

Check out the final product for yourself: https://store.livecycle.io/

Subscribe now