About SalePredict

Let’s say you have a lead list of 200 prospective clients. You need to talk to each of them to try make a sale. It would be very useful if you had a tool which could sort them in order of how likely they were to commit to a sale.

Earlier this year, I realised that it was possible to predict with high accuracy what companies could be brought on board with my company, by simply analysing the language used on their website, and comparing that with the language used by people already signed up with us.

For example, let’s say you are in the Field Service Management Software (FSM) industry as I am, and someone gives you a list of 100 local company websites.

You can make an educated guess at what companies you should approach, based on the wording used on the websites.

For example, FSM clients tend to talk about specifications, certification, standards, and tend to not talk about prices for products, or music, or knitting.

But think for a moment: when you make that educated guess, exactly why would you choose one company over another, if their websites are the only information you have so far?

The answer is that successful sales generally are made to companies that are similar to those you’ve already sold to.

That’s exactly what the SalePredict engine does!

You give it a list of your successful sales, to teach it what a successful sale’s website looks like.

You then give it a list of unsuccessful sales (fails), so it knows what kind of language is used by companies that are not suitable for your work.

Then you give it that list of 200 websites.

It will go through them all and assign them scores based on how similar they are to your successes (and how dissimilar they are to your fails).

It then orders the prospects so that you know which ones to call first.

Let’s talk it out with actual numbers.

Let’s say you have a list of 200 companies, and your usual hit/miss rate is 50%, so you can say with high certainty that of those 200 companies, you will make 100 sales.

Let’s say it takes 2 hours of work per company before you know if it’s a sale or a fail. You need to research each of the companies, and then talk to them.

Well, with your usual method, you will need to slog your way through them all. It will take 10 weeks, and you will make 100 sales.

Now, let’s say you use the SalePredict engine. Based on my own tests, it is 66% accurate even with just 41 data points, and gets more accurate as you feed it more data.

This means that it will order those 200 prospects so that 66% of the actual sales will be in the top 100 of the list.

You can now spend half the time (5 weeks) ringing up 66 sales, and then get another 200 leads, run them through the engine, and do another 66 sales for the other 5 weeks.

So, using a straight-forward by the numbers method, you make 100 sales. But, by using SalePredict, you make 132 sales.

Which is better? 100 sales or 132 sales? Hmm…

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