Tome’s early stage growth strategy
Tome is a new storytelling format that empowers anyone to build and share compelling narratives with any kind of content: text, images, video, 3D renderings, prototypes, live web content, embeds, and more.
We chatted with Kian Kolahdouzan, Tome’s Customer Success Lead and first customer-facing hire, about the pre-revenue company’s growth so far and plans for the future.
In 2022, the company transitioned from a waitlist model where Kian personally chose people to onboard one-on-one via Zoom to a fully self-serve Product-Led Sales (PLS) approach where new users can sign up for free and get started on their own.
Despite the glow up in their onboarding process, Kian explains that Tome is still refining how and where to engage with their growing base of user signups.
Part of Tome’s growth plan is to use their Product-Led Sales motion to create product evangelists — power users who create tons of Tomes and share them with others.
So, customer success spends most of its time sifting through the self-serve onboarding process to maximize user activation and identify power users. Unlocking all the features and flows that users need to level up is very much top of mind.
Who are these people?
VIPs: Sometimes, someone with a high level of influence onboards onto Tome. Ideally, the Tome team wants to spot these people early and give them hands-on support in learning the ropes and creating and sharing content via Tome.
ICPs: In addition to VIPs, Tome has several other ideal customer profiles (ICPs), which are mostly related to their work roles:
- Founders in fundraising mode
- Product managers
- Customer-facing roles in sales and customer success: account managers, account executives, etc.
The Problem? Recognizing VIPs and ICPs in a non-manual way
In addition to zeroing in on level of influence and work roles when prioritizing personalized outreach, there are a few signals that Tome also looks at to determine who to focus on:
- Number of days on the product + activity in the product
- Number of people they’ve added to their workspace
- Amount of feedback provided about new features they would love to see
The issue? Identifying these signals through all the noise.
Finally, something Kian thinks about a lot, as inbound signups grow, is automation. More specifically, how to use automation to scale customer support.
One of his main concerns is that as Tome grows and scales its CS efforts, they’ll lose that human touch that is so often needed alongside self-serve PLS motions for onboarding success.
The issue? Losing touch with the human touch.
Tome Uses Pocus to identify ICPs & Act on Signals 🪄
Ultimately, Tome’s go-to-market team uses Pocus to enrich user profiles with product usage data — providing insight into the most rewarding nurturing opportunities.
Try this playbook
What You'll Need ⚙️
- Self-serve product with a healthy user sign up volume (enough you can learn from)
- Defined ideal customer profiles
- Understanding of product usage signals that your team cares about
- Pocus’ Product-Led Sales platform for aggregating insights about customers
1. Create cohorts of customers with Pocus’ list views.
The whole marketing team at Tome, as well as Kian, use List views in Pocus — which he says have been “really, really helpful” to create user cohorts divided by different signals: number of Tomes created, overall time in the product, and so on.
“Pocus list view has been really, really helpful for us — especially given the fact that I'm not the only person using Pocus. Our whole marketing team uses Pocus and looks at our lists, too.”
2. Create Magic Playbooks to surface high priority opportunities.
Kian also uses Pocus to set up Magic Playbooks that drive different outreach motions. Each playbook is set up to look at users in their first 30 days on Tome. If they have created less than two Tomes they are surfaced as, “not delighted” , Kian will reach out to these users differently than his delighted segment.
3. Drive behavior based messaging.
Using Playbooks to segment users, Kian is then able to create personalized email campaigns that help drive more usage based on signals and behavior.
Kian and team use segments created in Pocus to drive personalized email sequences in Customer.io.
Other tools that help Kian and Tome with customer outreach:
- Intercom for on-site customer support messaging
- Customer.io to send out product announcements and usage based campaigns
- SendGrid for product email notifications (mainly used by engineering teams)
4. Experiment with new cohorts.
Since no signal is forever in this fast-paced world, Tome even uses Pocus to slice up experimental user cohorts, enrich their data in Clearbit, and come out with a better idea of which personas are more (or less) successful.
With Pocus, Tome’s team is no longer at risk of guessing where to engage or reaching out to users totally cold. That’s because Tome uses Pocus to monitor key signals (time on product, Tomes created, users added, feedback provided, etc.) and whether they’re growing or shrinking. Whichever way the signal is moving, knowing this info about users triggers more helpful, targeted conversations.
The Results (so far)
Kian sees Pocus’ ability to identify areas to introduce the human touch as one of its biggest differentiators. Instead of blanketing everyone with a whole lot of unpersonalized content, the Tome team uses Pocus to really hone in on those moments where the human touch will make all the difference.
For Kian, that’s a major unlock when it comes to scaling CS without losing that connection or personality.
In addition to increasing visibility into where and how to engage with users, Tome has observed another interesting success metric while working with Pocus: saved time.
Specifically — engineering time.
Before Pocus, Kian would have to submit a ticket to engineering requesting a manual download of users that met specific criteria from the product database, several times a week. With Pocus, Tome’s GTM team can now see most of the usage data they need to inform their next best action. No tickets and no engineering needed — which saves time as well as expense.