Enhancing your business relationships with NLP

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As consultants and service providers being able to build effective business relationships with a variety of people, e.g. buyers, supplier relationship managers, users, client staff, is crucial for the success of assignments or contracts.

How many times do business relationships break down due to repeated misunderstandings or so called ‘cultural’ differences? How many times do proposals not turn into sales because the service provider did not hit the customer’s key values and decision criteria? How many times did a relationship turn sour because the customer or client staff felt they were not listened to or taken seriously by the service provider?

Understanding the other party’s or person’s core values or criteria, motivations and decision making preferences can help to not only build effective business relationships but also improve existing relationships.

NLP (Neuro-linguistic Programming) recognises a number of preference filters[1] that can help us to respond more effectively to others and make it easier for our customers to do business with us. Matching someone’s filters makes people feel understood and listened to, and thus creates a better chance for a good relationship and a sale. Conversely, using our own, and potentially opposite, filters may lead to a mismatch, conflict or misunderstandings and therefore a failed sale or a difficult and/or short relationship.

Out of the ca. 60 identified filters, I have selected three, which I found very useful in sales, negotiation and consulting contexts:

Towards vs away from: People who are ‘towards’ focus on what they can gain or achieve, i.e. the positive benefits like growth, increased profits, engaged staff; people who have an ‘away from’ focus are looking to avoid costs or risks, save money, fix or solve problems. It is no good to list of the away from benefits of a proposed solution if the customer has a ‘toward’ preference or vice versa.

Options vs procedures: Options people like to keep things flexible and are looking for different ways of doing things. They want choices. Procedures people prefer tried and tested solutions, rules and guidelines, and often tend to look for the right (meaning one) solution rather than a number of options to choose from.

Convincer pattern: This filter is about what it takes to convince people that something is right or not right for them. In sales, it would be how many times someone needs to have an interaction before they are ready to buy, or how many options the client needs in a proposal to be able to make a decision. In service delivery, it might be how long a time it takes before the client is convinced the provider is doing good work or whether the client assesses each interaction on its own merits.

Most of these filters are quite easy to detect by listening to the client’s or provider’s words or reading their documentation; and a lot of us subconsciously pick on these filters but do not make use of that subconscious knowledge in all cases. If the filters are not apparent asking a few simple questions (see book recommendations) quickly yields the answer. Be aware that these filters are context dependent, i.e. if the client or provider has one filter in one context, they could have the opposite filter in another context, so it is always worthwhile to check before making assumptions.

Communicating with the other party through their preference filters is not manipulation as some people tend to think. It is the ability to see the world from another person’s perspective, i.e. ‘walk in their moccasins’, and communicate with them in language that immediately makes sense to them without them having to translate your preference filters into theirs. Knowing one’s client’s filters makes proposals or ITT responses much more focussed and effective, and helps to build stronger and more open relationships.

For further reading, I would recommend Shelle Rose Charvet’s book Words That Change Minds or Jeremy Lazarus’ book Successful NLP.


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[1] also sometimes called deep filters, meta programs or language and behaviour patterns. Although there are ca. 60 identified preferences filters, ca. 15-20 are generally used.

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