We've all been there, haven't we? As Customer Success or Product-Led Growth professionals in a lean B2B SaaS team, you're juggling a hundred things. The promise of data-driven decisions is always there, lurking behind an endless stream of dashboards.
You connect your data, you set up your reports, and then... you're still left wondering: what now?
"I dunno about you guys and gals but I am utterly burned out. ... Just to clarify that this goes past the CSM role and just being utterly burned out with the corporate life/culture/games/politics/drama" shared one professional on r/CustomerSuccess recently. It’s a feeling many of us can relate to, especially when a significant chunk of our day is spent trying to piece together disparate usage data to figure out who needs attention and why.
Traditional product analytics tools like Amplitude or Mixpanel are fantastic for understanding what users are doing in your product at a high level. They show you usage trends, feature adoption rates, and conversion funnels. But if you're asking "what do enterprise companies use instead of Amplitude for customer insights?" or, more accurately, "how can my growth-stage B2B SaaS get deeper, actionable insights without enterprise-level complexity and cost?", you're hitting on a crucial point. Standard dashboards often show the 'what,' but rarely explain the 'why' or which specific customers need attention most.
The core challenge isn't usually a lack of data. Many of us have robust product usage data flowing into a data warehouse like Snowflake or BigQuery. The real hurdle is translating that raw data into something that genuinely helps you:
This is where many B2B SaaS teams, especially those in the early to growth stages (think $1M-$5M ARR with 10-50 employees), find themselves in a bind. You might look at enterprise CS platforms, but then you read things like, "Gainsight is only a great tool if you can get it implemented and supported correctly and most companies aren't willing to pay for that, so they over pay for a tool... that isn't being used to its full potential and leads to massive amounts of frustration because of it". Sometimes, a full enterprise CSP is overkill, or requires dedicated admin resources you simply don't have.
So, how do you bridge this gap without breaking the bank or hiring an army of data scientists? The good news is, you can start with low-hanging fruit.
If you're feeling overwhelmed, try this for a week: Identify the single most important positive usage behavior (e.g., a key feature adopted by multiple users in an account) and the single most critical negative signal (e.g., a sharp, sustained drop in weekly active users for an account) for your product.
For just one hour each day, focus only on trying to spot these two signals across a handful of your accounts. This isn't about perfect data, but about training your eye to see what truly matters and building a prioritization muscle.
Customers churn for one reason - they're not getting results. But what constitutes "results" in your product?
Take 3-5 recently churned accounts and 3-5 seemingly similar, but retained, accounts. Manually compare their usage patterns for your product's core value-driving feature(s) in the 30-60 days before the churn date versus the same period for your retained accounts.
You might uncover subtle behavioral shifts that act as early warning signs for your specific product. This exercise, though manual, can reveal patterns that generic health scores miss, as one user pointed out, "My company uses Gainsight and has a health score that's tracked automatically... but it's often inaccurate... when there's a drop in usage the health score drops, even though the clients always drop in usage every summer".
For identifying expansion opportunities, move beyond just hitting usage limits. Define one clear, simple "Product Qualified Account" (PQA) trigger based on usage. For example: "Account invited 3+ teammates AND used Feature X more than 10 times." Manually identify accounts that hit this trigger this month. These are your warmest leads for a value-based expansion conversation, allowing you to "make expansion feel natural".
These manual exercises are valuable, but they quickly hit a wall when you're managing a growing customer base. Imagine if, instead of manually digging, the most impactful signals – both risks and opportunities – were automatically surfaced and explained for you, daily.
This is where specialized tools come into play. If you're leveraging a product-led growth motion and already have your product usage data in a data warehouse like BigQuery or Snowflake, you're sitting on a goldmine. GrowthCues is designed for exactly this scenario:
It’s about turning your existing product usage data into a clear path for proactive customer success and product growth, without the overhead of a full enterprise CS platform or the need for a dedicated data science team.
If you're ready to stop firefighting and start leading with proactive insights, why not take a small step and see what your data can tell you? GrowthCues offers a 7-day free trial. No credit card required, and you can get your first insights in about 30 minutes after connecting your data.
Take care 👋,
-Toni / Builder of GrowthCues
