I ran recently into the latest Gallop survey rating honesty and ethical standards of selected US professions. Not surprisingly, car sales people are at the very bottom of the list (just above members of congress) and  business executives are right above.

That’s clearly the perception.

Let’s separate honesty into two:

  1. Honesty to prospects and customers
  2. Honesty to yourself and to your team – self honesty


Honesty to prospects

I assume that you will agree that honesty to your customers is the foundation of building trust required to start selling and then building long term relationships that drive more sales. Honesty pays off. But the focus here is self honesty.

Self honesty – the challenges

This topic is underrated.

There are few reasons that hinder sales people from being honest to themselves and their team:

  1. Natural optimism, which is shared across most people in sales
  2. Ability to sell – They can convince themselves and others that a bad situation may actually be good
  3. Organization reasons – examples include: the need to show healthy pipeline, hide some unpleasant facts hoping that things will get better (optimism)

Why is self-honesty important?

Sales people, by definition, are spending most of their time on lost opportunities. In B2B sales, win rate is about 25%. Which means that  sales people spend more than 3.5 days a week on lost opportunities and just a little more than one day on won opportunities.

Being able to identify likely to lose opportunities in an early stage can help sales people to spend more time on prospecting and opportunities  that have higher potential.

How can you become self-honest sales organization?

The manual way

In the early stages of each opportunity, you can ask your team to rank them as likely to win/lose and reward them for accuracy. Obviously when they rank an opportunity as likely to lose they’d need to propose an action plan, either to rescue it or to stop investing time (closed lost or disqualified).

This method is better than not having anything. But the major challenge is that it is sometime emotionally and organizationally biased. The sales person is too close and may not see the big picture and they may have other organization reasons to rank win or lose.

The machine way

If a machine could provide highly accurate predictions it would probably be optimal. You could still ask your team to rank opportunities manually, but you’ll have a second opinion.

The machine will not stop at scoring opportunities it’ll also identify the main reasons that made it predict win over loss. Focusing on these most significant metrics could also help you boost your win rate.

The main challenge is that there are not that many companies that offer opportunity win/loss prediction. There are even less that can identify the most significant metrics. And most of them require long and costly implementation projects.

Clearly these machine predictions are based on correlation to past opportunities that won/lost and cannot identify the causality.

Komiko – Predicting won/lose after a couple of weeks

Komiko can accurately predict win/loss in the very early stages of an opportunity sales cycle. It can also identify the most significant metrics that drive winning. Komiko measures conversations and meetings that you had with your prospects as well as other parameters from your CRM system to determine the probability to win/loss. We’ll be happy to share much more, click here.


Categories: AI-CRM

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