We built a custom AI sales tool for B2B marketers in 6 weeks
March 2018 In response to recent reports in the media concerning Cambridge Analytica, we wish to clarify that ASI’s only relationship was with its parent company SCL, which was one of over 110 companies and organisations that have recruited from an internship programme which ASI organises.
For over a decade, Faculty’s Fellowship programme has been developing technical talent and helping organisations build AI capacity. We screen, recruit, and train an elite cohort of data science, AI, and machine learning specialists (fellows), who, during a short-term placement, execute impactful, bespoke AI projects selected by their host organisations.
In our most recent programme, our Fellowship Marketing team tasked a fellow with streamlining our own sales and marketing processes.
We were paired with fellow Theo Rashid, Epidemiology and Biostatistics PhD from Imperial College London. His academic journey saw him pioneering scalable Bayesian models to unravel the complexities of life expectancy in England. Leveraging his rich background in data modelling, Theo’s Fellowship project addressed a pressing need within the Marketing & Sales divisions of the Fellowship team: Improving the personalisation of sales enablement materials for potential clients, a task previously mired in manual, time-consuming processes.
Over six weeks, Theo developed a Large Language Model (LLM) driven application, transforming the way the Fellowship Marketing & Sales teams interact with an unstructured database of previous fellowship projects.
Personalising outreach for prospects
The challenge of personalising outreach is not unique to the Fellowship Marketing team but rather a pervasive issue experienced by marketing and sales departments across industries.
In an era where personalised communication is crucial, the manual and time-consuming process of sifting through historical data, testimonials, case studies, and project examples to find the perfect match for each prospect significantly impedes efficiency.
To solve this common problem, Theo developed the “Project Explorer”: a scalable, full-stack LLM application aimed at streamlining this workflow, automating the search and selection of relevant content. This tool uses augmented generation techniques and natural language processing to succinctly extract useful information from a comprehensive database, enabling the marketing team to craft deeply personalised and impactful sales enablement materials with ease.
“Depending on the material, it would sometimes take a couple of hours to sift through the database to find the perfect project example, testimonial or case study. Now with the Project Explorer, it takes just minutes.”
Madeleine Butler, Fellowship Marketing Manager
Improving operational efficiency
The Fellowship Marketing and Sales teams have significantly reduced time spent manually sifting through data. Now, they can quickly identify a relevant project and extract the necessary insights to use in various materials. It has accelerated the content personalisation process, saving valuable time but also enhancing the precision of the Fellowship’s marketing efforts, ensuring the communications are highly targeted.
By simply asking the Project Explorer a question, for example:
“What is the best project example to send to a legal services scale up focussed on automating document reviews?” In just seconds, the perfect project is displayed.
For more on the project watch Theo’s final presentation as part of the Fellowship.
Join the Faculty Fellowship
Our Fellowship programme serves as a bridge between businesses’ aspirations and technical talent’s expertise. Over a short-term placement, your business can undertake a bespoke AI project and get matched with Europe’s top AI talent.
If your organisation is looking to overcome its greatest challenges with AI or would like to discuss more about Theo’s project, please get in touch.
