Insight Lab

Data science, artificial intelligence and machine learning all buzzwords we are hearing more and more often. Their definitions have been bastardised by marketing departments the world over, however, due to the increase in the data available to organisations, the lower cost and higher availability of processing that data, and genuine advances in the field of artificial intelligence, there are great gains to be had for businesses of all sizes in investing in this area.

Rittman Mead's Insight Lab is a data science service that provides a lightweight starting point to gain insights and understanding of how your data can help you before embarking on large scale data science projects.

Introducing data science into your business will not only require an understanding of relevant tools, processes and technologies, but also an understanding of the underlying data, where it comes from and your business processes. For any analytics work, the first stumbling block is always obtaining, tidying and transforming the source data. With our experience in both data engineering and building machine learning models, we can offer an end-to-end advisory service.

We will advise which metrics and/or data would best impact your business, this is why our initial engagement is centred around understanding your business processes and available data.

How It Works


Our team will work with you to identify and validate possible machine learning avenues. This will include specific business processes you wish to improve, possible prediction or optimisation techniques, alternative use cases, success criteria, and measurable business improvement.


Next, using the types of data sources you have available to you as well as any public or external resources, our analysts will define the dataset required for your use case. We will determine what infrastructure and technology will be most applicable to your needs and outline our methodology and timeframes. Engagement will be carried out with your key stakeholders to confirm the above and define acceptance criteria.


Our team of expert data engineers prepares, cleans and standardises your data to make it ready for statistical modelling. This includes creating a data profile report including completeness, accessibility, and any identified data issues.


We use state-of-the-art machine learning algorithms to predict future events, segment customers, suggest next best actions and more.


Finally, we deliver a production-ready model via an API for maximum compatibility with any data architecture. Our model APIs can be hosted on-premises or in the cloud.

Typical Use Cases

Operational Efficiency

Identify key factors that can be used to support process improvement and be better prepared to respond to unforeseen challenges.

  • Identify assets at risk of failure and avoid expensive downtime.
  • Optimize manufacturing, production, and maintenance schedules.
  • Reduce costs.

User Experience

Understand user context to deliver impactful interactions at the right moment.

  • Deliver a custom experience to your users.
  • Adapt the target interactions based on user response.
  • Predict and extend the life of the relationship with a user.

Customer Retention

Evaluate your customer base, recognize your best customers, and predict future customer behavior.

  • Uncover strategies for introducing new products.
  • Identify key customer features that lead to late payments or cancellations.
  • Identify negative trends before they impact customer satisfaction.


Let your data handle simple decisions and eliminate labor-intensive, repetitive, and error prone processes.

  • Identify patterns of behaviors to automate decisions or detect fraud.
  • Filter results by likelihood of occurrence to focus attention for greater success.
  • Execute common administrative tasks.

Click below if you would like more information about Insight Lab or to discuss your next project.

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