You may have had the experience of filling out a long form on a website. For example, creating an account to make a purchase, or applying for a job, or renewing your car insurance.
A long form can lead to customers losing interest and taking their business elsewhere. Each additional field can result in up to 10% more customers dropping out instead of completing the form.
If you have a business with a form like this, one reason why you’re not able to simplify your form is because the data you are requesting is valuable.
Fast Data Science - London
There are lots of ways to address the problem, such as improving the design of the form, or splitting it across multiple pages, removing the “confirm password” field, and so on. But it appears that most fields can’t be removed without inherently degrading the data you collect on these new customers.
However with machine learning it’s possible to predict the values of some of these fields, and completely remove them from the form without sacrificing too much information. This way you gain more customers. You would need to have a history of what information customers have provided in the past, in order to remove the fields for new customers.
If you are interested and would like to know more please send us a message.
For an example of how data can be inferred from an unstructured text field please check out our forensic stylometry demo.
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You are probably familiar with traditional databases. For example, a teacher at a school will need to enter students’ grades into a system where they get stored, and at the end of the year the grades would need to be retrieved to create the report card for each student. Or an employee database might store employees’ home addresses, pay grades, start dates, and other crucial information. Traditionally, organisations use a structure called a relational database, where different types of data are stored in different tables, with links between them, and they can be queried using a special language called SQL.
A problem we’ve come across repeatedly is how AI can be used to estimate how much a project will cost, based on information known before the project begins, or soon after it starts. By “project” I mean a large project in any industry, including construction, pharmaceuticals, healthcare, IT, or transport, but this could equally apply to something like a kitchen renovation.
Senior lawyers should stop using generative AI to prepare their legal arguments! Or should they? A High Court judge in the UK has told senior lawyers off for their use of ChatGPT, because it invents citations to cases and laws that don’t exist!
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