Most support leaders at B2B software companies have a tough relationship with their data tools.
I've seen this pattern repeat itself across countless startups: as the company grows, the support team's ability to quickly understand and resolve customer issues diminishes. It's not that the team is getting worse; it's that the complexity of the data they need to wrangle is outpacing their tools and processes.
The root of the problem is simple, yet insidious. In the early days, a support rep could keep most of the relevant customer information in their head. They knew the handful of customers, understood the product intimately, and could quickly piece together what was going on when an issue arose.
But scale changes everything.
As the customer base grows, the product evolves, and the company adds integrations and features, the amount of data a support rep needs to access to do their job effectively explodes. Suddenly, they're juggling information from multiple sources:
The core product database + application data
Billing systems like Stripe
CRM data
Transactional messaging touchpoints
Bugs and errors that live in systems like Sentry or Datadog
Support ticketing history
.. you get the point, the list goes on and on.
And that's just the tip of the iceberg.
The knee-jerk reaction is often to throw more tools at the problem, or increase headcount to cope with poor tools. So, dashboards proliferate. BI tools like Looker or Tableau get deployed. For a while, it seems like progress. But then the cracks start to show.
These dashboards, initially helpful, become rigid and stale. They're not flexible enough to keep up with the rapid pace of change in a growing B2B SaaS company. Support reps find themselves opening five, ten, sometimes even more tabs just to get a complete picture of a customer's situation. It's slow, it's frustrating for both the rep and the customer, and it's ultimately unsustainable.
The irony is that most support teams are far more capable and technically inclined than their companies give them credit for. They want to dig deeper, to proactively solve issues, to see patterns across customers. But they're hamstrung by tools that weren't designed for their workflow.
Here’s a common scenario: a support rep is troubleshooting a delayed shipment due to an address issue. In an ideal world, they should be able to quickly identify all other orders going to the same problematic address. But in most companies, that kind of proactive analysis is painfully difficult, if not impossible, for a front-line support rep to do – often because the dashboard just isn’t built for that use case in mind.
So what's the solution? It's not just throwing money at the problem (or rather, begging your CEO to throw money at the problem) by hiring a dedicated data resource. The real answer lies in fundamentally rethinking how we approach data in the context of B2B support.
Here's what needs to happen:
1) Build a solid data foundation through denormalized tables.
What are denormalized tables? Simply put, this means bringing all relevant attributes about a customer, transaction, event, etc. into one table. In other words - producing a “360-degree” view.
For example - it can be as basic as adding human-readable labels to datasets (instead of “product_id”, join in “product_name”) so reps can add filters based on human terms. Or, it can be as powerful as joining on a “contract_renewal_date” column pulled in from Salesforce so that reps can appropriately prioritize a customer issue.
Denormalizing tables (and the upfront data integration work) is often the most difficult step because it requires a technical resource. Most support teams don’t have a dedicated technical resource. The data team that is already backlogged with requests from other “higher-priority” departments at the company.
Your responsibility as a support leader is to make the case to your CEO / CFO – how better data tooling ultimately translates to higher revenue goals and retention for B2B customers.
2) Choose data tools built for investigation, not just reporting
Most BI tools are great for creating static reports, but terrible for the kind of dynamic, exploratory work that defines great B2B support. Look for tools like Dataland that offer powerful full-text search capabilities across all data fields, easy filtering and sorting, see related data, and the ability to quickly drill down from high-level metrics to individual data points. With generative AI, it’s now easier than ever for a rep to use AI assistants to get the data they need.
The key here is flexibility. Your support team should be able to start with a high-level view – say, all customers who've experienced a particular error in the last week – and then drill down to individual user sessions or transactions without switching tools or waiting for new queries to run, all without requiring SQL knowledge.
The best support reps are naturally curious problem-solvers. Give them tools that let them follow that curiosity, rather than constantly hitting walls or waiting for someone from the data team to run a custom query for them.
Ultimately, the impact is worth the investment
We at Dataland worked with a fast-growing Series C company that had a support staff of a dozen agents, each handling a few dozen cases a day. Within a week of deploying the tool, the support staff was able to handle four times - yes, 4x - the number of cases per day, and run novel analyses that had never been accomplished before, such as uncovering a fraudster ring.
The support leader estimated that the efficiency gains alone from Dataland were worth 10x compared to the initial time spent on constructing new datasets.
In the B2B world, support isn't just about reducing ticket volume; it's about delivering an experience so good that customers can't imagine leaving. And that kind of experience is only possible when your support team has the data and tools they need to be true customer advocates.
The path forward isn't easy. It requires rethinking ingrained processes, investing in new tools, and trusting your support team with more responsibility. But the payoff – in terms of customer satisfaction, retention, and ultimately, growth – is enormous.
The best B2B companies of the next decade won't just have better products; they'll have support teams that are true strategic assets, armed with data and empowered to use it. The only question is: will your company be one of them?
