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How Tenders Become Customer-Proof

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How Tenders Become Customer-Proof

How Tenders Become Customer-Proof

People who have occasionally had to deal with answering tenders know that this is a time-consuming process that involves a lot of manual and repetitive tasks under high time pressure. Huge amounts of text have to be read and analyzed before they can start answering questions.

Also, there is not always a clear picture of the contracting authority and ‘the question behind the question’, especially if you have hardly or not at all been in conversation with the client before the tender is published. How can the tender team cope with the large volume of information and the time pressure and also make the tender response more customer-oriented?

It is not always possible to have a conversation with the client before the tender is issued and published. One of the ways to ensure a more customer-oriented approach is to free up time. This time saving can be realized by using AI technologies to automate simple and repetitive tasks. Such as automatically receiving and analyzing tender documents. This leaves bid and tender managers more time to make full use of their expertise and experience. It ensures a more customer-oriented approach and increases the chances of winning the tender.

Another way to answer tenders in a more client-focused way is by gaining more insight and information. Many tenders are not only won on filling in the hard requirements correctly; soft weighting factors are also important. The tender documents contain a lot of information, but often do not give a complete picture. AI can help by automatically performing stakeholder, environment, competition and subject analyses to create a better customer view. It can also help to create a profile with information about the customer, relevant themes and topics in the related context based on data from various public sources. This provides more insight into the question behind the question and relevant insights about the stakeholders, competition and environment involved. This leads to a qualitatively better tender response.

Automatically enriching relevant information and gaining insights can ensure that the answer to the customer’s question is tailored as closely as possible to its needs, and is written in a way that appeals to the customer. In practice we see that by using AI, 50% less time is spent on analyzing tenders and performing desk research to learn more about the customer’.

This article was written for and published by CustomerFirst!. The original article can be found here (article in Dutch).

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