Case Study: [Client] — +45% Qualified Meetings Driven by Signals

Context: +45% Qualified Meetings Thanks to Commercial Signals

In this client case, the Sales team was facing a large volume of accounts, but had limited capacity for active prospecting. SDRs were spending too much time on low-responsive accounts, while hot opportunities were slipping under the radar. Traditional indicators (company size, sector, CRM history) were no longer sufficient to prioritise effectively.

The introduction of actionable commercial signals made it possible to reorganise prospecting around accounts that were truly “in motion”. In less than six months, the client increased the number of qualified meetings by 45%, with the same sales capacity, simply by changing the way accounts were detected, scored, and handled.

This case study shows how intent, engagement and context signals were integrated into the prospecting process, how account prioritisation was rethought, and which operational adjustments were required to turn these signals into real pipeline.

What Is Meant by “Commercial Signals” in This Client Case?

Commercial signals are observable indicators that an account is potentially in an active phase of research, comparison or decision-making regarding a given solution category. They complement firmographic and CRM data with a dynamic view of the market.

In this client case, three main families of signals were used to increase qualified meetings:

• Intent signals: thematic searches, consultation of specialised content, participation in events related to the problem addressed by the client.
• Engagement signals: repeated visits to the website, opening and clicks on email sequences, partial responses or requests for information.
• Context signals: fundraising, key recruitments, tool changes, project or restructuring announcements.

The objective was not to multiply data, but to transform these commercial signals into a clear prioritisation system for SDRs and Account Executives. Each signal was normalised, scored, and linked to concrete actions in the prospecting playbook.

Why Commercial Signals Are a Game Changer for B2B Teams

B2B Sales teams often operate in environments where the volume of addressable accounts far exceeds processing capacity. Without commercial signals, prospecting relies on static criteria (size, sector, country) and on salespeople’s intuition. The result: a lot of effort on accounts that are not in a buying phase, and a strong dependence on a few inbound opportunities.

Commercial signals change the game because they introduce a temporal and behavioural dimension into prioritisation. An account that matches your ICP but shows no sign of interest does not have the same immediate value as an account that has just hired a new CMO, downloads a white paper on your topic and compares competing solutions.

In this client case, the integration of signals made it possible to:

• Focus efforts on “hot” accounts: those that combined several recent signals.
• Adapt the messaging: an SDR no longer contacted an account “cold”, but with a clear understanding of the situation (ongoing project, tool change, new team, etc.).
• Reduce the prospecting cycle: fewer back-and-forths to qualify the need, as part of the context was already known.

Beyond commercial performance, the signals also improved collaboration between Marketing and Sales. Campaigns were no longer evaluated solely on lead volume, but on their ability to generate actionable signals for field teams.

Step 1: Map Available Signals and Define Priorities

The first step of the project consisted in mapping all signals potentially accessible to the client. The objective was not to collect everything, but to identify the signals that were truly correlated with meeting booking and opportunity creation.

Three main sources were analysed:

1. Internal data: CRM history, on-site behaviour, responses to email campaigns, webinar participation.
2. Partner / existing tool data: marketing automation platform, anonymous visit tracking tool, sector-specific intent data solution.
3. Public data: fundraising announcements, job offers, press news, management changes.

In parallel, workshops were conducted with SDRs and Account Executives to identify “empirical” signals which, in their view, often preceded an opportunity: change of sponsor, contract renewal, team restructuring, etc. This qualitative phase helped prioritise the signals to be integrated into the model.

At the end of this step, a short list of priority signals was defined, each associated with:

• a source (tool, feed, database),
• an update frequency,
• a reliability level,
• and an operational translation (play to trigger).

Step 2: Build a Priority Score Aligned With the Field

Once the signals had been identified, the client implemented an account priority score combining intent, engagement and context. The objective was not to create a “perfect” score, but one that was simple enough to be understood and used daily by the teams.

The chosen model was based on three components:

• Intent score: based on research and content consumption signals related to the problem.
• Engagement score: based on direct interactions with the client’s assets (website, emails, events).
• Context score: based on major business events (fundraising, recruitment, tool change).

Each component was rated out of 100, then weighted according to its observed impact on meeting booking. For example, a tool change signal at a target account carried more weight than a simple page visit.

To ensure adoption, the score was tested on a sample of accounts for four weeks. SDRs were invited to compare their “field” perception with the proposed score. The discrepancies made it possible to adjust weightings and exclude certain signals considered too noisy.

Ultimately, the score was integrated directly into the CRM, with a daily prioritisation view: each SDR had a list of accounts sorted by score, with the associated signals visible in one click.

Step 3: Adapt the Prospecting Playbook to the Signals

One of the key success factors was the adaptation of the prospecting playbook. The signals were not only used to decide “who to contact”, but also “how” and “with which message”.

For each combination of signals, a specific play was defined:

• Strong intent + medium engagement: sequence of personalised emails around the identified problem, followed by a discovery call.
• Strong context (fundraising, recruitment) + low engagement: advisory-oriented approach on project structuring, with benchmark sharing.
• High engagement but few context signals: rapid follow-up with a proposal for a free diagnostic or audit.

Call scripts and email templates were rewritten to explicitly incorporate the signals. For example, instead of a generic pitch, the SDR could start with: “I saw that you are recruiting a Head of Revenue Operations and that you recently attended a webinar on Sales/Marketing alignment. How are you currently organised on this topic?”

This personalisation, made possible by the signals, had two immediate effects:

• Higher response rates: prospects perceived a contextualised approach, far from mass prospecting sequences.
• Faster qualification: the conversation went straight to the heart of the matter, which made it possible to identify priority projects more quickly.

Results: +45% Qualified Meetings With Constant Capacity

After six months of using commercial signals, the results observed at the client were significant:

• +45% qualified meetings generated by the SDR team, without increasing the number of accounts handled.
• +30% conversion rate from meeting to opportunity, thanks to better upstream qualification.
• Reduction in average prospecting time per meeting: SDRs spent less time “searching” for the right accounts and more time engaging in relevant conversations.

Beyond the figures, several qualitative benefits were reported by the teams:

• Better visibility of the active market: the signals provided a more accurate picture of accounts that were truly in motion.
• Stronger alignment between Marketing and Sales: campaigns were designed to generate signals, not just leads.
• Increased motivation among SDRs: the feeling of “shooting in the dark” was replaced by a structured, data-driven approach.

Key Takeaways for B2B Teams

This client case highlights several lessons that can be applied to other B2B organisations:

1. Start simple: it is not necessary to collect every possible signal. It is better to start with a core set of reliable signals, correlated with opportunity creation, then enrich progressively.
2. Involve the field from the outset: the best signals are often already intuitively known by salespeople. Including them in the model design fosters adoption.
3. Link each signal to an action: a signal without an associated play remains just data. The value comes from the ability to quickly trigger the right scenario.
4. Measure and adjust continuously: score weightings and playbooks must evolve based on field feedback and observed results.

By structuring prospecting around commercial signals, this client demonstrated that it is possible to generate significantly more qualified meetings without increasing headcount or the volume of addressed accounts. The key lies in the ability to detect the right moments, understand the context, and adapt the messaging accordingly.