Commercial Property Business Boosts Qualified Calls by 83% and Adds £900K in Revenue

Industry: Real Estate

Client

A commercial property business

Goal

Providing consistent customer experience across multiple locations and improving market presence.

Challenges

  • The business was generating only 30 qualified sales calls per week.
  • The company operated 38 buildings but struggled with variable response performance across locations, creating an inconsistent customer experience.
  • There was no systematic way to capture and share best practices across the organisation.
  • Despite a strong £85 million revenue base, the business experienced client churn of 2.45% annually

Solution

Rather than fixing each location individually, the business implemented standardised response protocols applied uniformly across all 38 buildings, ensuring every customer received the same level of service regardless of which property they enquired about.

The business also created cross-location best-practice sharing mechanisms, allowing high-performing teams to mentor struggling ones and ensuring continuous improvement across the organisation.

The business established performance measurement and feedback loops that provided real-time visibility into response times and conversion rates at each location, enabling managers to identify underperforming areas quickly.

The business deployed automated lead-routing and management systems that intelligently distributed enquiries based on capacity, expertise and urgency, removing the human bottlenecks that had previously caused delays.

Impact:

Within 120 days, the systematic approach increased weekly qualified sales calls from 30 to 55 (an 83% improvement).

The initiative reduced client churn from 2.45% to 1.41%.

The initiative generated an additional £900,000 in annual revenue through the combined effects of improved retention and acquisition.

Context

A commercial property business operating in the Real Estate sector sought to provide a consistent customer experience across multiple locations while strengthening market presence. With a portfolio of thirty-eight buildings and an established £85 million revenue base, the organisation recognised that its growth trajectory depended on reliably converting enquiries into qualified sales conversations and retaining existing clients. The leadership team prioritised improving response performance and standardising service delivery so every prospective tenant or buyer received the same high-quality engagement regardless of which property they contacted.

Challenges

The company generated only thirty qualified sales calls per week and faced wide variability in response performance across its thirty-eight buildings. Some sites were consistently responsive and converted enquiries effectively; others suffered delays and inconsistent follow-up, producing a fragmented customer journey. There was no systematic way to capture and spread best practices across the organisation, leaving high-performing teams isolated and underperforming teams without clear guidance. Despite a strong revenue base, client churn stood at 2.45% annually, eroding lifetime value and limiting market momentum. Manual routing of leads and localised processes created human bottlenecks that exacerbated delays and made it difficult for managers to see real-time performance differences by location.

Implementation

Rather than attempting to improve each building individually, the company implemented a suite of coordinated, organisation-wide measures to standardise and scale response excellence. The Fractional Head of AI and operational leaders introduced standardised response protocols that applied uniformly across all thirty-eight buildings, ensuring every customer received the same professional, timely service regardless of property. Automated lead routing and management systems were deployed to intelligently distribute enquiries based on capacity, expertise, and urgency, removing the human bottlenecks that had previously caused delays and missed opportunities.

To ensure consistent adoption, the organisation established performance measurement and feedback loops that provided real-time visibility into response times and conversion rates at each location. Dashboards and alerting enabled managers to identify underperforming areas quickly and intervene with targeted coaching. Crucially, the business created cross-location best practice sharing mechanisms: high-performing teams were paired with struggling locations in mentoring relationships, documented scripts and workflows were made available centrally, and regular forums surfaced tactics that reliably improved conversion. These mechanisms turned isolated successes into replicable processes and embedded continuous improvement across the portfolio.

The combined approach balanced technology, process, and people. Automation handled routing and prioritisation while standard protocols removed ambiguity for front-line staff. Measurement and mentoring closed the loop, ensuring that insights led to action and that improvements were sustained.

Results

Within 120 days the systematic approach delivered measurable commercial gains. Weekly qualified sales calls increased from thirty to fifty-five, an 83% improvement in inbound, qualified engagement. Client churn declined from 2.45% to 1.41%, reflecting improved retention driven by faster, more consistent responses and higher perceived service quality. The combined effects of improved acquisition and retention generated an additional £900,000 in annual revenue, a material uplift on top of the £85 million revenue base.

Beyond the headline metrics, the business benefited from faster identification of underperforming locations, reduced variability in customer experience, and an organisational culture oriented toward shared success. Standardised protocols and automated routing removed friction that had previously limited growth, while best-practice sharing and real-time feedback ensured gains were scalable and durable across all thirty-eight buildings.

*Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.