How to leverage reverse psychology in negotiations

Peter Thomson


by Peter Thomson


Leveraging reverse psychology in negotiations with the aid of contract management software

There is a part of our human nature that makes us resist what we feel we are being forced to do.  A young child may resist going to sleep after being told to do so.  She may stay up late defiantly even though she is extremely tired to assert independence. Likewise, a teenager may be more inclined to experiment with an illegal substance if she receives strong messages from her parents that it is forbidden.

This aspect of our humanity can be applied to the sphere of negotiations. For example, an adult and a salesperson may negotiate on the price of a car.  A sales person may ask a question such as, ‘If you could pick a number between 1 to 10 about how convinced you feel about making this purchase  what would it be?’ The prospective buyer may pick a number such as 7. Traditionally, a salesperson would be taught to ask the prospective buyer what’s required to get it up to 10. However, some negotiation experts suggest that an alternative approach is more effective.

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Mike Michalowicz, an American business author, suggests that a more effective response is “Oh, I thought you were less convinced.  I thought your number would be more like a 3… Why did you pick a number so high?”  This question leverages reverse psychology to obtain a positive result for the sales person.  Michalowicz argues that by asking this question, the purchaser is more likely to consider all the positives of the sale and more inclined to buy.  A video of Mike Michalowicz explaining this technique can be found here:

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Some modern negotiation and contract management software provide tools for leveraging reverse psychology in simple but effective ways.  It allows you to highlight the contractual clauses upon which you would like your counterparty to focus.  By making contentious clauses visually prominent the counterparty may be less likely to contest these terms.  They also may be more likely to trust the party with whom they are negotiating.

Similarly, some modern contracting software promotes trust in the multi-party negotiation process.  Older contract management software creates a more contentious, friction-oriented engagement by requiring such things as a document comparison to be run over documents returned from a counterparty to make sure no unrecorded changes were made (that is, someone slyly turned off the “track changes” feature in MS Word).  A more symbiotic approach would be for the solution to perform this review automatically without the need to “call people out”.

Another way a more progressive contract lifecycle management solution could promote transparency is through its data analytics functions and predictive analytics. In this way, it could capture data during the term negotiation and clause review process (the “agreement-building” phase) and analyse it to determine, among other things, what particular clauses are most effective, least negotiated and provide insight into why this is so. It would do this using machine learning techniques. This information could be shared between negotiating parties so they could have a more informed and perhaps more open discussion on how to reach the “yes” or “no” in a faster and happier manner.  This is because they could consider and discuss what other negotiating parties in similar situations have agreed upon in the past.

Modern contract management solutions should allow for more transparency which leads to more trust and more seamless negotiations - and less need to employ reverse psychology tactics.  Negotiating parties who use this contract lifecycle management software feel less controlled and for reasons similar to those for reverse psychology are less defensive and more willing to collaborate.  These parties effectively are able to “negotiate less and agree more!”

How have you used reverse psychology while negotiating?  Do you think it’s effective? How do feel about a system that provides insights into your negotiations based on machine learning?

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About the author

Peter Thomson

Peter Thomson

Peter has been involved in technology since he developed his 1st product for the legal industry in 1987 - a case management system called CaseTrack. But didn't stop there, and has continued to push for innovation and disruption to make processes more efficient and just plain happier!

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