Strategy & Planning

How to set quarterly okrs as Small Customer Success Teams

Strategy & PlanningFor Small Customer Success Teams3 apps12 steps~24 min to set up

Every quarter your three-person team tries to set OKRs that actually reflect what's happening in your book of business — but the data lives in five different places. HubSpot has deal stages and renewal dates. Intercom has ticket volume and response times. Your usage dashboard (if it updates this week) has activation rates and feature adoption. The QBR notes from last quarter are in someone's Google Docs. You spend two days pulling this together in a spreadsheet, arguing about what 'improve retention' actually means in measurable terms, and then the OKRs live in a Notion page nobody looks at until next quarter's retro. You never know mid-quarter whether you're on track until it's too late to course-correct.

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Strategy & PlanningFor Small Customer Success Teams3 apps12 steps~24 min to set up

Outcome

What you'll set up

A live CS OKR dashboard that pulls renewal pipeline from HubSpot, ticket trends from Intercom, and usage signals from your product analytics tool — so your key results have a single source of truth you can check on Tuesday, not just at quarter-end

A repeatable quarterly planning process: Starch drafts your OKR candidates from last quarter's performance data, your team refines them in a 60-minute working session instead of a half-day spreadsheet fight

Automated mid-quarter check-ins that surface which key results are on track, which are at risk, and which accounts are driving the variance — sent to your Slack channel every two weeks without anyone pulling a report

The Starch recipe

Apps, data, and prompts

The combination of Starch apps, the data sources they pull from, and the prompts you use to drive them.

Apps used

CRM Knowledge Management Task Manager

Data sources & config

Starch syncs your HubSpot data on a schedule — contacts, companies, deals, and owners — so renewal dates and deal stages are always current. Connect Intercom from Starch's integration catalog; the agent queries it live when your OKR check-in automation runs. Starch also connects directly to Slack so the biweekly summary posts automatically. For usage data from a tool like PostHog, connect it from Starch's integration catalog and the agent queries it live alongside your other sources.

Prompts to copy

Pull last quarter's closed-lost renewals, expansion ARR, and average time-to-first-value from HubSpot. Show me which three metrics moved the most compared to the prior quarter and flag any accounts that renewed late.

Build me a CS OKR tracker for Q3 2026. Objectives should be: reduce churn risk, improve time-to-value for new accounts, and grow expansion ARR. For each objective, suggest three measurable key results based on the HubSpot data I just pulled, with current baseline values and target values.

Every two weeks on Monday morning, check our HubSpot deal pipeline for renewals due in the next 60 days, count the open Intercom tickets per account tier, and post a summary to our #cs-team Slack channel showing which key results are green, yellow, or red.

Run these in Starch → or paste them into your favorite agent

Walkthrough

Step-by-step

1 Connect HubSpot — Starch syncs your contacts, companies, deals, and deal owners on a schedule. This is your renewal pipeline, expansion opportunities, and account health baseline all in one place.

2 Connect Intercom from Starch's integration catalog. The agent will query ticket volume, open issues, and response times live when your OKR review runs — no manual export needed.

3 Tell Starch: 'Pull last quarter's performance data from HubSpot and Intercom — renewal rate, average ticket resolution time, number of accounts that expanded, and number that churned. Organize it by account tier.' This is your OKR baseline.

4 Open the Knowledge Management app and create a page called 'Q3 2026 OKR Planning.' Paste in the baseline data Starch generated and any context from last quarter's QBRs or retro notes. This becomes the single doc your team works from.

5 Tell Starch: 'Based on this performance data, suggest three CS objectives for Q3 2026 with two to three key results each. Each key result should have a current value, a target value, and a data source I can check automatically.' Starch drafts the OKR set; your team edits it in a 60-minute working session instead of building from scratch.

6 Finalize your OKRs as a team and write them into the Knowledge Management page. Include the owner (which of your three team members is accountable), the data source for each key result, and the check-in cadence.

7 Set up the biweekly check-in automation: 'Every other Monday at 9am, pull our HubSpot renewal pipeline for deals closing in the next 60 days, query Intercom for tickets opened per account in the past two weeks, and post a CS OKR status update to #cs-team in Slack. Flag any key result that's more than 10% below target as red.'

8 Use the Task Manager to capture any follow-up actions that come out of the OKR-setting session — assign owners, set P1/P2 priorities, and due dates. Tell Starch: 'Add a task for me: schedule 1:1 OKR alignment with each of our three team members by Friday, P2.'

9 At the six-week mark (mid-quarter), run a manual OKR review: 'Show me current values for each of our Q3 key results versus target. Which accounts are dragging down our churn-risk objective? Which expansion plays are on track?' Starch queries HubSpot and Intercom live and gives you a direct answer.

10 If a key result is off track, tell Starch: 'Which accounts with renewals in the next 45 days have open Intercom tickets older than seven days? Draft a short account health summary for each one.' Use these summaries to prioritize your team's intervention work for the rest of the quarter.

11 At quarter end, tell Starch: 'Compare our Q3 OKR targets to actuals using HubSpot and Intercom data. Write a two-paragraph summary I can paste into our board update and a detailed breakdown for our internal retro.' Your QBR prep and OKR retro become the same motion.

12 Update the Knowledge Management page with the final Q3 results and any lessons for Q4 planning. Next quarter, Starch pulls from this same page as context when you ask it to draft OKR candidates — your planning process compounds over time.

See this running on Starch

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Worked example

Q3 2026 OKR Set — 3-person CS team, 250 B2B accounts

Sample numbers from a real run

Objective 1: Reduce churn risk	4
KR1: Renewal rate ≥ 91% (baseline: 87%)	91
KR2: Accounts with 0 open tickets at renewal ≥ 75% (baseline: 61%)	75
Objective 2: Improve time-to-value for new accounts	3
KR1: Median days to first meaningful usage ≤ 14 (baseline: 22)	14
KR2: Onboarding ticket rate (tickets in first 30 days) < 40% of new accounts (baseline: 54%)	40
Objective 3: Grow expansion ARR	3
KR1: Expansion ARR from existing accounts ≥ $85,000 (baseline: $61,000)	85,000

Going into Q3 planning, the team asked Starch to pull last quarter's performance data from HubSpot and Intercom. In about four minutes they had a table showing Q2 renewal rate (87%), median onboarding ticket resolution time (6.2 days), and expansion ARR closed ($61,000 against a $75,000 target). Starch flagged that 54% of new accounts opened a support ticket in their first 30 days — a signal the team knew was bad but had never quantified. From there Starch drafted nine key result candidates with baseline values already populated. The team's 60-minute planning session was spent arguing about the right targets, not copying numbers out of HubSpot. They set a 14-day time-to-first-value target (down from 22), a 91% renewal rate goal (up from 87%), and an $85,000 expansion ARR target. The biweekly Slack check-in went live that afternoon. At week six, the check-in flagged three accounts — TerraLogic, Bridgepoint Analytics, and Novus Health — as at-risk based on open tickets older than seven days and renewals inside 45 days. The team ran targeted outreach that week. Two of the three renewed on time.

Measurement

How you'll know it's working

Quarterly renewal rate (% of ARR renewed on time)

Expansion ARR from existing accounts (dollars, not just count)

Median days to first meaningful product usage for new accounts

Ticket-to-renewal rate: % of accounts with open tickets at renewal date

OKR completion rate: % of key results hitting target by quarter-end

Comparison

What this replaces

The other ways teams handle this today, and how the Starch version compares.

Gainsight or ChurnZero

Built specifically for CS health scoring and OKR tracking at scale, but costs $40k–$100k/year and requires a CS-ops person to configure — not built for a three-person team doing this themselves.

Manual HubSpot + Google Sheets + Notion

Free and flexible, but someone spends two days every quarter pulling the data, and your key results go stale the moment the export is out of date — no automated mid-quarter check-ins.

Lattice or Leapsome (OKR module)

Good structured OKR tracking and check-in workflows, but the key result data has to be entered manually — there's no connection to HubSpot or Intercom, so you still own the data-pulling work.

Salesforce + Tableau

Powerful reporting if you have a RevOps or data analyst to build and maintain the dashboards; a three-person CS team without that function will spend more time maintaining the stack than using it.

On Starch RECOMMENDED

One platform — crm, knowledge management, task manager all running on connected data. Setup in plain English; numbers stay current via scheduled syncs and live agent queries.

Try it on Starch →

FAQ

Frequently asked questions

Does Starch actually connect to HubSpot, or does it just let me manually import a CSV?

Starch syncs your HubSpot data on a schedule — contacts, companies, deals, and deal owners are pulled automatically and kept current. Your OKR check-ins and mid-quarter reviews pull from that live data, not a stale export. No manual imports.

We use Intercom for customer support tickets. Can Starch pull from that?

Yes. Connect Intercom from Starch's integration catalog and the agent queries it live when your automations run. You can use ticket volume, open issue counts, and per-account ticket history as inputs to your key result tracking.

What if our product usage data lives in a tool like PostHog or Amplitude?

PostHog connects from Starch's integration catalog and the agent queries it live. For other analytics tools, check Starch's integration catalog — it covers 3,000+ apps. If your tool isn't in the catalog but has a web interface you can log into, Starch can automate it through your browser with no API needed.

Is Starch going to replace HubSpot or Intercom for us?

No. Starch connects to HubSpot and Intercom and builds surfaces on top of them — the health-score dashboard, the OKR tracker, the automated Slack check-in — that those tools don't ship out of the box. Your team keeps working in HubSpot and Intercom; Starch just makes the data useful for planning.

We're not SOC 2 certified ourselves, but our customers sometimes ask about the tools we use. Is Starch SOC 2 certified?

Not yet. Starch is not SOC 2 Type II certified today. If that's a hard requirement for your team given your customer contracts, it's worth knowing upfront.

Can Starch actually write our OKRs for us, or does it just pull data?

Both. You can ask Starch to draft OKR candidates based on your HubSpot and Intercom performance data — with baseline values, suggested targets, and the data source for each key result. Your team then edits and owns the final OKRs. Think of it as Starch doing the 'blank page' work so your planning session is about judgment, not data gathering.

What happens if a key result's data source changes mid-quarter — like we switch CRMs?

You'd update the connection in Starch and tell it where the data now lives. Because you described your OKR tracker in natural language, you can also tell Starch 'update the renewal pipeline key result to pull from Salesforce instead of HubSpot' and it rebuilds that piece. Nothing is hard-coded.