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Hey team,
Hope everyone had a lovely 4th! 🇺🇸 🎇 🇺🇸
And welcome to this week’s Yem Jam.
I’ve been searching for the right one-liner to describe Yem. One of my friends called us a "customer data platform, owned by creators". And one of our customers called Yem a "growth team in your pocket".
I like both these taglines. The first hits on how hard it's been in the past for creators to access and use important data (let alone "own" the data). The latter hits on building products that have a tangible impact on helping creators grow their audience and make more money.
This week, we cover a few stories on bringing different data sources together, and growth products that could emerge from that data.
One of our customers had a Substack post that, within the first 12 hours, had a few more shares and likes than normal. They knew this intuitively — the numbers were small, and there were no alerts or easy comparisons.
They took the Substack post and turned it into a tweet thread. The tweet caught fire, receiving over 130k likes and 35k retweets. The thread ended with a call-to-action to subscribe to the newsletter. The viral tweet led to a huge influx of new subscribers: +5,000 subscribers, a large portion of subs at the time.
A few important realizations. First, the importance of a multi-platform view when looking at performance. The Twitter engagement and wave of new subs came in over a few days. The newsletter is daily and had two new posts during that time. Only looking at Substack data, the two new posts looked amazing, while the post that went viral on Twitter underperformed. Having Substack and Twitter data together reduces the likelihood of being misled.
Next up, trying to productize aspects of the scenario above. To start, helping identify posts that are a bit more shareable than normal. For new posts, we could create velocity checks that trigger an alert if something is being viewed or shared more than average. We could also automatically transform the post (text, links, images) into a tweet thread. Whereas it may have taken 10 minutes to turn a post into a tweet thread before, maybe we can reduce the time to 1 minute.
We've been running surveys to help creators understand their audience, and how it's changing over time. Here’s an example survey in Typeform with the questions below. (We mark all questions as optional and the results are anonymous.)
The responses help prioritize ways to make the product better and expand audience. Guest posts from a more diverse set of voices or perspectives to bring in new readers. Or better allocating time across platforms, and maybe even launching on new platforms or creating new types of content.
We've just started tracking survey responses over time. This helps us measure efforts aimed to improving the product and expanding audience. Here’s an example with dummy data.
More than a few creators have launched communities, to engage with their audience, but also for the audience to connect with each other. Some offer it as a benefit for paid-subs-only, which seems to be working in at least a few cases.
I wrote about Sidechannel, the new Discord server I’m launching with some of my favorite people in media. It’s for anyone who pays for any of our publications. And we have some big plans. platformer.news/p/announcing-s…
There's more tools than ever to create and manage these communities. But online communities are super hard to cultivate. Even if there's value with early members, it's tricky to maintain as the community grows.
We’re exploring whether there’s a way to take a more data-driven approach to building community.
We helped a newsletter launch a Telegram chat group in a very directed way. We aimed for 300 people to start: enough to support vibrant conversation and live events. But not too many where it becomes hard to manage or we lose the intimacy.
We made assumptions on email open rate & open-to-join rate. We used this to back into the number of emails we needed to send. We then reached out to the most engaged, longest-tenure subs. We felt this group would give us the best shot at setting the tone with the community. And from that foundation, perhaps we could add more folks in gradually over time.
To help launch the chat, we ran a live AMA with the creator. We even took a bit of a data-driven approach to evaluating how it went:
16% of the chat was online during the event
31 total questions (10 before it started, 21 during the hour)
signs of power users: ~5 people asked half the questions (potential moderators?)
12 responses → 40% response rate (opportunity to improve)
The chat launch and AMA were awesome learning experiences. It's fun to test out a data-driven approach in an area where it's mostly intuition.
Along with the above — expanding the reporting, running user surveys, and helping launch communities — we’re in more of a rhythm running growth tests. These ideas and tests have emerged through our experience working with creators. But also from building the growth function at Hulu, Crunchyroll, and HBO Max.
In my head, I can see all the teams that helped grow those businesses. And the millions of things we did right to nudge us in the right direction. All that stuff took a ton of effort, investment, and hiring the right team to execute.
I'm hoping Yem can make this growth function much more accessible to creators.
Let me know what you think! And please share with anyone you think would enjoy it. As always, we appreciate your support.
Hey team,
Hope everyone had a lovely 4th! 🇺🇸 🎇 🇺🇸
And welcome to this week’s Yem Jam.
I’ve been searching for the right one-liner to describe Yem. One of my friends called us a "customer data platform, owned by creators". And one of our customers called Yem a "growth team in your pocket".
I like both these taglines. The first hits on how hard it's been in the past for creators to access and use important data (let alone "own" the data). The latter hits on building products that have a tangible impact on helping creators grow their audience and make more money.
This week, we cover a few stories on bringing different data sources together, and growth products that could emerge from that data.
One of our customers had a Substack post that, within the first 12 hours, had a few more shares and likes than normal. They knew this intuitively — the numbers were small, and there were no alerts or easy comparisons.
They took the Substack post and turned it into a tweet thread. The tweet caught fire, receiving over 130k likes and 35k retweets. The thread ended with a call-to-action to subscribe to the newsletter. The viral tweet led to a huge influx of new subscribers: +5,000 subscribers, a large portion of subs at the time.
A few important realizations. First, the importance of a multi-platform view when looking at performance. The Twitter engagement and wave of new subs came in over a few days. The newsletter is daily and had two new posts during that time. Only looking at Substack data, the two new posts looked amazing, while the post that went viral on Twitter underperformed. Having Substack and Twitter data together reduces the likelihood of being misled.
Next up, trying to productize aspects of the scenario above. To start, helping identify posts that are a bit more shareable than normal. For new posts, we could create velocity checks that trigger an alert if something is being viewed or shared more than average. We could also automatically transform the post (text, links, images) into a tweet thread. Whereas it may have taken 10 minutes to turn a post into a tweet thread before, maybe we can reduce the time to 1 minute.
We've been running surveys to help creators understand their audience, and how it's changing over time. Here’s an example survey in Typeform with the questions below. (We mark all questions as optional and the results are anonymous.)
The responses help prioritize ways to make the product better and expand audience. Guest posts from a more diverse set of voices or perspectives to bring in new readers. Or better allocating time across platforms, and maybe even launching on new platforms or creating new types of content.
We've just started tracking survey responses over time. This helps us measure efforts aimed to improving the product and expanding audience. Here’s an example with dummy data.
More than a few creators have launched communities, to engage with their audience, but also for the audience to connect with each other. Some offer it as a benefit for paid-subs-only, which seems to be working in at least a few cases.
I wrote about Sidechannel, the new Discord server I’m launching with some of my favorite people in media. It’s for anyone who pays for any of our publications. And we have some big plans. platformer.news/p/announcing-s…
There's more tools than ever to create and manage these communities. But online communities are super hard to cultivate. Even if there's value with early members, it's tricky to maintain as the community grows.
We’re exploring whether there’s a way to take a more data-driven approach to building community.
We helped a newsletter launch a Telegram chat group in a very directed way. We aimed for 300 people to start: enough to support vibrant conversation and live events. But not too many where it becomes hard to manage or we lose the intimacy.
We made assumptions on email open rate & open-to-join rate. We used this to back into the number of emails we needed to send. We then reached out to the most engaged, longest-tenure subs. We felt this group would give us the best shot at setting the tone with the community. And from that foundation, perhaps we could add more folks in gradually over time.
To help launch the chat, we ran a live AMA with the creator. We even took a bit of a data-driven approach to evaluating how it went:
16% of the chat was online during the event
31 total questions (10 before it started, 21 during the hour)
signs of power users: ~5 people asked half the questions (potential moderators?)
12 responses → 40% response rate (opportunity to improve)
The chat launch and AMA were awesome learning experiences. It's fun to test out a data-driven approach in an area where it's mostly intuition.
Along with the above — expanding the reporting, running user surveys, and helping launch communities — we’re in more of a rhythm running growth tests. These ideas and tests have emerged through our experience working with creators. But also from building the growth function at Hulu, Crunchyroll, and HBO Max.
In my head, I can see all the teams that helped grow those businesses. And the millions of things we did right to nudge us in the right direction. All that stuff took a ton of effort, investment, and hiring the right team to execute.
I'm hoping Yem can make this growth function much more accessible to creators.
Let me know what you think! And please share with anyone you think would enjoy it. As always, we appreciate your support.
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