Algospark designs and supports projects that span a wide range of opportunities and challenges. We are specialists that design and deliver analytics and artificial intelligence solutions. Our services span:
Our solutions are designed with leading data science applications, prototyping platforms and cloud based web frameworks to ensure easy transition from prototype to full scale solutions.
We are a consultancy and delivery partner with skills that span data science, customer experience, service design, finance and technology. Algospark is a network of associates that is led by Darren Wilkinson (CFA). He has over 15 years experience leading and managing service innovation and analytics projects across numerous industries.
Organisations we have worked with:
A sales forecasting tool that combines proprietary and third party data sets with machine learning. Delivers an efficient sales planning and feedback framework that targets 15-30% sales forecast error reduction.
Location analytics solutions to evaluate potential new sales locations. Our solutions combine operational metrics, location specific data and the use of location cluster analysis. Algospark Location Analytics help optimise site selection, store forecasting and projected trading patterns. This helps reduce analysis time (20-40%), ensure robust and repeatable processes, minimise the probability of poor investment decisions and increase forecasting accuracy.
A product portfolio dashboard to align product investment decisions across multiple projects, businesses and geographies. Targets 25% reduction in analyst time and faster project approval processes.
Cluster analysis tool to determine store clusters and new store sales patterns using information from across an existing network of stores. Targets management and analytics efficiencies for store portfolio management, and 20-30% reduction in sales forecast error for new stores.
Interactive product portfolio analytics tool that uses market basket analysis and a sales inference engine to determine product opportunities and their impact on the product portfolio. Targets 1-2% sales increase and 1-2% gross margin uplift from portfolio pricing efficiencies.
Machine learning framework to predict opportunities and challenges across business operations. Uses event classification and outcome rules to target increases in process efficiency.
A customer experience profiling engine for designing customer experiences based on user preferences and personality types. Expected sales conversion rate increase of 5-10%.
A word prediction tool trained on tweets, blogs and news articles. Built as a foundation for Natural Language Processing (NLP) projects such as document classification and automated user interaction responses.
A simplistic blog impact assessment tool to forecast the impact of blog posts on web traffic. Built as a foundation for web strategy and analytics projects that link site scrapes and Google Analytics.
Use of artificial intelligence to recommend actions to customer service specialists. Targets 20% increase in customer response productivity.
A classification and feedback tool to streamline adult social care needs assessments. Ensures consistent needs classification, ongoing wellbeing feedback and predictions of future needs. Targets 40% process time savings, and cost savings from reducing future hospital visits.
A prototype care supplier selection algorithm for care commissioners. Ensures suppliers are prioritized and selected faster to reduce care brokerage requirements. Expected 25% brokerage processing time savings.
A scheduling and team resource optimisation tool for private tutoring, home care delivery and other time slot based services delivered to homes. Targets 10% cost efficiency savings.