Sales and Marketing often argue about lead quality, wasting time and opportunities. At Keboola, we solved this by building a shared data stack that gives both teams one trusted view of the customer—leading to more trust, faster decisions, and true alignment.
When Sales and Marketing Don’t Speak the Same Language
Every B2B leader has seen it: Marketing insists they generated 200 qualified leads, while Sales argues none of them were worth a call.
Campaigns optimize for clicks and traffic, but sales reps care only about active pipeline. The result is finger-pointing, frustration, and missed opportunities.
At Keboola, we wanted to break this cycle. We set out to build a shared data stack that gives both Sales and Marketing a single, trusted view of the customer. The outcome? More trust, faster decisions, and real alignment.
The Challenge We Needed to Solve
Sales and Marketing weren’t wrong — they were simply working from incomplete pictures. Marketing relied on engagement signals like campaign clicks and page views. Sales, on the other hand, looked to CRM data in Salesforce.
When we tried to stitch the two perspectives together manually, the process was so slow it often became irrelevant.
What we needed was more than dashboards. We needed a system that could bring together all the signals, reliably match leads to accounts, apply a scoring model both teams believed in, and deliver results fast enough to act on. In short, it was about building trust in the data itself.
The Shared Stack We Built
Keboola became the hub where our Sales and Marketing data flows through. Here, information is collected, cleaned, enriched, and then pushed back into the tools where teams work every day.
Instead of scattered numbers, we had a foundation that consolidated engagement, intent, and CRM data, removed duplicates, and applied scoring models designed with both sides in mind.
This meant that a lead arriving from a campaign was no longer just a name with a few clicks attached. By the time it reached Sales, it had been enriched with firmographic data, matched to the correct account, and scored in context. For Marketing, that same enriched data flowed back into automation platforms, fuelling campaigns that were finally aligned with what Sales actually cared about.
What Changed When We Got It Right
Once the shared stack was in place, the atmosphere shifted. Sales began to trust the leads coming their way because they could see the full context. Marketing could finally prove contribution to the pipeline instead of stopping at MQL reports. The endless cycle of manual exports and spreadsheet chaos simply disappeared.
And because the system was modular, we could test and integrate new signals quickly. Suddenly, iterating on our approach took days rather than months.
Tangible Wins That Made the Difference
The impact was very real. Lead enrichment time dropped from three hours to just fifteen minutes. Sales reps stopped wasting time on poor-fit accounts thanks to scoring that mirrored their own qualification criteria.
Dormant accounts that suddenly re-engaged with our website were flagged to the right salesperson on the same day. Even our reporting transformed: weekly updates came from the exact same source as our campaigns, which meant no more mismatched numbers.
Lessons We Learned Along the Way
Of course, we didn’t get everything right the first time. Matching leads to accounts turned out to be harder than expected — generic email domains or misspelled company names forced us to build fallback rules.
Engagement signals also proved meaningless without context; ten visits from the wrong person were worth far less than a single visit from the right decision-maker.
And perhaps the most important lesson was that naming conventions matter. At first, we had three different scoring systems. It was only once we unified them under one framework that the system really started to deliver.
The Biggest Shift: A Shared Language
The real victory wasn’t just better data pipelines. It was alignment.
Now, when someone says “top ICP account” or “hot lead,” both Sales and Marketing mean the same thing. Conversations stopped being arguments and started being collaboration. That shared language was what turned our data stack from a technical project into a cultural shift.
For Teams Facing the Same Struggle
If your Sales and Marketing teams are stuck debating lead quality, a shared data stack can change everything. It’s not about adding dashboards — it’s about creating a system both sides trust.
And once that trust exists, alignment, speed, and growth follow naturally.
This article was prepared by Keboola, a data platform that helps companies unify, automate, and activate their data for real business impact.
FAQ: Building a Shared Data Stack with Keboola
Why use Keboola instead of building everything manually?
Because manual integrations are slow, error-prone, and hard to scale. Keboola automates the flow of data between tools, cleans and enriches it, and makes sure both Sales and Marketing work from the same trusted source.
Can Keboola connect to the tools we already use?
Yes. Keboola has ready-made connectors to CRMs like Salesforce, marketing automation tools, intent data providers, and BI platforms. You don’t have to rip out your stack — Keboola integrates with it.
How fast can teams see results?
Most organizations start seeing impact in weeks, not months. For us, lead enrichment went from hours to minutes almost immediately.
Is this just for large enterprises?
Not at all. Even mid-sized B2B companies can benefit. The complexity isn’t in company size — it’s in the number of tools and signals teams have to reconcile.
How do we measure success?
Look for reduced lead qualification time, higher Sales acceptance of Marketing leads, and consistency in reporting. With Keboola, both pipeline growth and internal trust become measurable outcomes.