Data dashboard for a Hair and Beauty salon

We designed and developed a custom data dashboard for a hair and beauty salon, providing real-time insights into key business metrics. The dashboard streamlined appointment tracking, revenue analysis, and customer retention trends, enabling the salon owner to make data-driven decisions with ease.

Key features included:

• Data imported from the salon’s Fresha based system.
• Daily and monthly revenue tracking to monitor business performance.
• Appointment analysis to identify peak booking times and optimize staffing.
• Customer retention insights to track returning clients and implement loyalty strategies.
• Product sales reporting to highlight best-selling items and stock trends.

By leveraging data visualisation and automation, this dashboard transformed the salon’s operations, saving time and improving profitability.

Lead generation for a London-based last mile delivery service

We built a high-quality lead generation system for a last-mile delivery service in London, leveraging Companies House data to identify and target the most relevant businesses.

Our approach included:

• Extracting business data from Companies House, focusing on active companies in relevant industries.
• Filtering by location, ensuring only London-based businesses were included.
• Data enrichment, combining Companies House data with additional sources to assess delivery needs and business size.
• Lead scoring, ranking businesses based on their likelihood to require last-mile delivery services.

The final result was a structured, highly targeted lead list, enabling our client to run effective outreach campaigns and secure new business opportunities.

Data cleansing and consolidation for a CRM system

We helped a client streamline their CRM data by combining and cleansing multiple spreadsheets, ensuring accuracy, consistency, and usability.

Our process included:

• Data merging – Consolidating customer records from various sources into a unified dataset.
• Deduplication – Identifying and removing duplicate entries to prevent redundancy.
• Standardisation – Formatting data consistently (e.g., addresses, phone numbers, company names).
• Error correction – Fixing inconsistencies, missing values, and outdated information.

The result was a clean, structured, and reliable CRM database, allowing the client to enhance customer engagement, improve sales efficiency, and run targeted marketing campaigns with confidence.

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