
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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This new video explains natural language processing: what it is, how it works, and what can it do for your organisation. Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that focuses on giving computers the ability to understand human language, combining disciplines like linguistics, computer science, and engineering.

This free A/B test calculator will help you compare two variants of your website, A and B, and tell you the probability that B is better. You can read more about A/B testing in our earlier blog post on the subject. You may also be interested in our Chi-Squared sample size calculator which will help you calculate the minimum sample size needed to run a Chi-Squared test, given an expected standardised effect size.

See also: Fast Data Science A/B test Calculator (Bayesian) A/B testing is a way you can test two things, Thing A, and Thing B, to see which is better. You most commonly hear about A/B testing in the context of commercial websites, but A/B testing can be done in a number of different contexts, including offline marketing, and testing prices.
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