Case study / Selected prior client work
A clearer next move for 354,000 contacts
For a productivity SaaS company, our lead consultant designed and refined a Clay and HubSpot qualification system that combined fit, engagement and intent across four client-defined customer segments. The aim was simple: help sales see which accounts deserved attention, why they were prioritised and what to do next.
The business problem
A large database is not a decision system
The commercial team had substantial contact coverage but needed a dependable way to separate good-fit accounts from activity that only looked promising. The model had to account for four different ICP definitions, changing research and website signals, and the difference between an interested company and an engaged person.
The architecture / One connected flow
From account signal to sales action
Research intent, website activity and Clay visitor signals fed account-level qualification. Clay helped find relevant people at interested companies. HubSpot kept company and contact scoring distinct, then surfaced priorities through sales views, Slack and email digests.
Research intent, website activity and Clay visitor intent.
Bring signals into a company view and compare with four ICPs.
Clay searches contacts at the company, without identifying an anonymous visitor.
Company and contact fit and engagement remain distinct in HubSpot.
A1–C3 grades inform sales action or nurture.
HubSpot views, Slack and email digests carry the reason; sales feedback refines the model.
Interest arrived in three different ways
Research intent, website activity and Clay visitor intent each offered a different view of account interest. The system combined those observations with fit rather than treating every signal as an equally urgent lead.
Business meaning: a relevant signal shows which company to examine, not which person visited.
Fit came before urgency
The client defined four ICP segments. Account context and incoming intent were assessed against those definitions, so activity from an unsuitable company did not automatically become a sales priority. This gave the commercial team a more consistent explanation for why an account was elevated.
Decision principle: intent is useful only in the context of the right customer.
Clay found people at the interested company
Once a company warranted attention, Clay helped find relevant contacts there. That expanded the sales team’s view of the buying committee and connected account interest to people a rep could evaluate. A company-matched visit remained an account signal; it was never treated as proof that a newly found person made the visit.
Identity boundary: interested company ≠ identified website visitor.
Fit and engagement stayed separate
HubSpot scoring considered company fit, company engagement, contact fit and contact engagement as different questions. Fit mapped to A–C and engagement to 1–3, forming the A1–C3 priority grid. A strong account signal could raise the account’s priority without inventing personal activity for a contact Clay found later.
Decision principle: a priority grade should be explainable at both account and person level.
The score became a reasoned next action
Priority records moved into HubSpot lists and dashboards used by sales. Routing and lifecycle workflows helped distinguish prospects ready for attention from contacts better suited to nurture. Slack alerts and daily or weekly email digests kept the relevant changes visible without forcing sellers to inspect the entire database.
Business meaning: the output was a focused workflow, not merely another score field.
Sales feedback kept the model honest
Our lead consultant refined the scoring approach with feedback from sales and adjusted signal and qualification logic during implementation. The point was to check whether the model produced a useful distribution of records and a better daily decision for the team, rather than optimising a number in isolation.
Feedback loop: observe → qualify → act → review → refine.
What the rollout showed
A more calibrated definition of qualified
During implementation, reporting showed around 10% more contacts meeting the agreed qualification criteria. The result reflects the classification produced by the refined model and the data available to it. It gave the team a stronger basis for prioritisation and continued sales review.
This is a qualification-classification result. We are not presenting it as a 10% increase in conversions, pipeline or revenue; those downstream outcomes were not verified for this case.
More contacts met the agreed qualification criteria during rollout
Contribution and scope
Designed for the way sales actually works
This is selected prior client work. Our lead consultant designed the fit and engagement criteria and the feedback process, worked with an engineer on the initial HubSpot and Clay implementation, and refined the signal logic, Clay contact search, return automation and sales delivery during rollout.
Qualification design
Four ICPs, fit and engagement logic, and the distinction between account interest and contact activity.
Clay + HubSpot flow
Intent context, relevant contact discovery and the path back into prioritised CRM workflows.
Sales feedback
HubSpot views, alerts, digests and ongoing refinement with the commercial team.
Apply the model to your CRM
Prioritise accounts with clear evidence
If your team cannot identify which CRM accounts deserve attention, we can define the signals, scoring and handoffs for a focused first build.