Playbooks: Running customer engagement experiments against maximum conversion

Whether setting up workflows for freemium and trial signups to convert more, or for paying customers to be expanding towards a higher tier, or preventing to churn, being able to compare and optimise different workflows for maximum goal conversion is pretty much on every sales and CS leader’s list.

If you’re one of those sales leaders, and you consider running [hybrid sales-led-]product-led growth operations, you need to rely on your sales teams to execute:

• on the best possible engagement workflow for the prospect at hand,
• and receive actionable triggers on whom to target first, as acting on every single lead is simply not possible anymore due to too large quantities.

At this point, you will benefit from a platform that will:

• automatically provide those product qualified lead triggers,
• automatically start best possible sales workflow for each specific PQL,
• and check which of these workflows provide most goal conversions.  

And this is particularly true for Customer Success teams who, even in a traditional sales-led model, is —or at least, should be— already working with product usage triggers and workflows. Finding out which workflow works best in which particular situation helps saving loads of unnecessary hours calling the customer, when automated messages might be working better.

That’s what Playbooks is all about.

Why Playbooks when you have PLG Scores?

To better organize a go-to-market motion, be it pure product-led or hybrid, we imagined there had to be a better way than just crunching account and user data. Even with PLG scoring (and sorting) in place.

In creating Playbooks, we started with what customer told us they wanted to achieve, in reaching out to their customers. That is: next to surfacing product qualified leads, they were in general looking to increase free-to-paying conversion, to see more tier expansions, and to be able to prevent churn. And, the most successful customers were organising their teams towards these specific goals, with clear workflows for achieving those goals. All well documented and quantified.

So, we simply built Playbooks to meet those exact same requirements, so that reps and CS professionals could receive full context and best possible tasks for each individual lead, while their leaders could continue optimising workflows against best outcomes.

Anatomy of a Playbook.

To set up a Playbook in journy.io, follow these steps:

Provide Playbook context and -flow.

Give your Playbook a name, and group them together by goal or functionality.
Indicate whether the playbook has a goal to reach, and if accounts/users can re-enter the playbook, after a certain period of time (not being in it anymore).

You can also chose to have the Playbook execute Exit tasks, when the trigger conditions aren’t true anymore.

Define the audience that can enter the Playbook.  

Playbooks are made for certain types of leads and customers, not necessarily for all. Most typical criteria would include Stage, Health, and Segments, but we’ve made it flexible that any interaction can contribute to audience conditions.

Define the trigger that starts the Playbook.  

Here’s where you indicate when the playbook should start for defined audience. Most typical criteria is based on scores, properties and platform interactions.

Here’s also where you tell the playbook what to do in terms of actions. For each previously connected ecosystem app, you’ll receive a couple of actions to choose from.

Define the Playbook’s Goal and Goal sequence!

As we’ve built Playbooks to execute tasks against a certain goal, here’s where you indicate when you consider a goal to be reached. Most typical criteria are related to changes in Stage, Health, and Segments, but we’ve made it extremely flexible again.

Optionally, you can also indicate if there’s a time-out. If after the time-out, AND ONLY THEN, the goal is not reached, the Playbook will enter its Exit sequence.

Create the Playbook’s Exit sequence.

Either reaching Exit due to trigger conditions becoming false, or simply because of Goal time-out, here’s where you define which final actions should occur.

How to use Playbooks.

From how we’ve built Playbooks, there’s really a couple of use cases you can cover:

1. Playbooks as simple trigger action. The moment a trigger is set for a certain audience, do something. E.g. Write something on Slack when account gets bad health score.
2. Playbooks as on-off switch. The moment a trigger is set for a certain audience, do something. The moment that same trigger is cleared, do something else. E.g. Add a case in journy.io inbox when PQL signal is set; remove the case when signal is cleared.
3. Playbooks as goal-driven sequence. The moment a trigger is set for a certain user, do something and wait until either a goal, or a time-out for that goal, is reached. E.g. Add a contact to a Salesloft sequence, when PQL signal is set; wait for maximum 3 weeks to convert to another [Customer] Stage. If that happens within the 3 weeks, post win message on Slack; if not, add task to HubSpot to follow up by another team.

We’ll soon post another blog post, elaborating on the different Playbook use cases.

The importance of Playbooks in a PLG motion.

Product-led growth resolves around being able to identify qualified leads for acquisition, expansion and retention.... AND doing something with those leads! Only surfacing PQLs is simply not enough.

We’ve previously introduced Stages, Health, Scores, Segments, Computed properties and other customer intelligence features to enable PQL-surfacing capabilities in a best possible way.

Today marks a historical day in the development of our PLG/SaaS Growth platform, as with the release of Playbooks and Inbox, we’re now set out to providing best practices for manual and automated outreach. In a way, we’re helping you transition your sales and CS teams from ’doing this, no matter what’ to ‘doing this, because it’s historically the best thing to do in this specific case’.