How data visualisation and machine learning adds value for B2B digital services provider
Case Study
Background
A leading provider of B2B digital services, develops award-winning B2B mobile and desktop ordering solutions.
Specialising in the wholesale market, they aimed to transform digital into their clients’ most successful channel, thanks to supercharged omni-channels applications proven to increase sale and deliver a true return on investment.
The company has built more than 40 high-profile transactional apps, which process more than £150 million each year.
Established in 2014, the company has a deep understanding of the wholesale market, thanks to its initial forays into data visualisation and machine learning algorithms to further enhance its offering.
The Challenge
Over the last 10 years, there has been an increase to 98% in online ordering for wholesalers. This shift has resulted in many wholesalers understanding the need for website optimisation to ensure a better user experience. Some companies also release apps for an additional customer touchpoint.
These solutions, however, often lack the data maturity to identify trends or patterns in buying behaviour – meaning that they cannot provide the actionable insights businesses need to excel online.
Transactional apps collect a variety of data and the team understood the value that data visualisation and machine learning could offer services, such as the company’s ecommerce platform.
Management wished to explore means of visualising transactional data – thus demonstrating the value of analytics to their customers – as the first phase of work to secure further development support.
The team sought to deliver insights across the value chain by enabling its platform to help customers optimise their marketing, through better understanding of purchasing behaviours.
The Solution
Following an initial meeting, the client specified the need for a PowerBI demonstrator to showcase the business intelligence insights available to retail customers, to encourage retail engagement.
This gives wholesalers and suppliers easy access to data visualisations of key data, KPIs, and relationships across multiple data sources, while collecting market insights on the developments necessary for an analytical solution.
T-DAB restored the MongoDB in AWS, allowing the available data from the client to undergo review and assessment, and set up a PowerBI instance to visualise the data.
Powered by Microsoft, this business analytics service provides interactive visualizations with self-service business intelligence capabilities. PowerBI allows users to create reports and dashboards, without needing to rely on depend on information technology staff or database administrators.
With set-up completed, T-DAB created initial mock-ups from the data set with KPIs/metrics specified by client feedback, which was then fed into mock-ups of the demonstrator.
Customised to their needs, this enables a truly personalised experience for the company’s clients, while enhancing product recommendations through machine learning.
The Result
Equipped with the insights necessary to help its customers to grow, the project has enabled the business and their clients to manage their digital channels more effectively.
Offering a better user experience has increased conversions by 24 percent. By optimising the information provided to customers, their solution has reduced inbound enquiries by 40 percent, while increasing revenue.
Best of all, they are now capable of delivering the insights that retailers need to better manage their customers.
With the first phase of development complete, the company’s team are already looking ahead. By utilising machine-learning-driven, predictive analytics, the client intends to offer in-market execution, drive intelligent price optimisation and improve product demand forecasting in the months ahead.
About T-DAB.AI
T-DAB.AI is data science and data engineering innovation company. We develop innovative, bespoke machine learning-driven solutions to allow anyone to infuse technology with the spark of predictive intelligence.
