# Why have my sales dropped?

If you spend as much time as I do hanging around forums for independent developers, you will often see questions of the form “I only made X sales today/this week/this month, has something gone wrong?”. There are two distinct possibilities:

1. Something has changed (e.g. your website is broken); or
2. It’s a statistical fluctuation.

Rather than guessing, we can use some stats to work out the probability that a drop in sales is just a random fluctuation.

The Poisson distribution gives us the probability of a given number of discrete events occurring in a fixed interval of time (or space), if these events occur with a known average rate and independently of each other. It can be used to investigate the accuracy of v1 flying bombs, the number of 19th century Prussian soldiers kicked to death by horses and the number of South Africans attacked by sharks. It can also be used to calculate the probability of getting <= n sales per day/week/month, if we average N sales per day/week/month.

A comparison between the number of PerfectTablePlan sales per day over 90 days (blue histogram) vs predicted by the Poisson distribution (red histogram). We would expect the prediction to become more accurate with more data, assuming nothing else changes. Obviously things do change over the lifetime of a software product, hence the relatively short time span chosen.

Using this online Poisson distribution calculator we can work out some example probabilities:

 expected number of sales over period Probability of drop in sales of: 5 10 50 100 >= 20% 44% 33.3% 8.6% 2.3% >= 40% 26.5% 13% 0.2% 0% >= 60% 12.5% 2.9% 0% 0% = 100% 0.7% 0% 0% 0%

(0% = too small for the calculator to display)

For example:

• If we average 5 sales per week, the chance of a 40% or more drop in sales (i.e. a week with 3 or less sales) is 26.5%.
• If we average 50 sales per week, the chance of a 40% or more drop in sales (i.e. a week with 30 or less sales) is 0.2%.

So the less sales we make (or the shorter the period we look at), the bigger the random fluctuations we can expect. If I was averaging 5 sales per week, I wouldn’t be too worried about a drop of 40% in sales for one week. In fact, I would expect it to happen approximately one week in every 4 (running a business that averages 5 big B2B sales a year, must be very stressful!). But if I was making 50 sales per week, a 40% drop in sales should only happen by chance approximately once every 10 years. I would definitely check for other causes.

Assuming it isn’t just a statistical blip, the most likely cause of non-random change is an issue with your website. Rather than waiting for a problem, I suggest you set up continuous monitoring that emails or SMSs you if a problem occurs. There are various services for this. I use free pingdom.com and siteuptime.com accounts. Using 2 different services protects you against one of them silently failing.

Don’t assume that random strangers on the Internet will email you to tell you that something is broken. Perhaps 1 in a hundred or a thousand will. The rest will just click the back button. You can improve your odds by having loyal and engaged customers and a clearly displayed email address and/or phone number. But still don’t depend on it. When is the last time you noticed an issue on a website and took the time to report it?

Also some seasonal variation in sales is likely. The pattern depends on your market. Many businesses see a drop in sales in the northern hemisphere summer. But my wedding table plan software sells better in the summer. Hopefully you will know the pattern for your product after a year or two.

Random fluctuations and the lack of visitors to report issues means that it is hardest to tell whether a drop in sales is real when you start out. This is  when you need the sales most, both financially and emotionally. It gets easier as your traffic and sales improves. No one said that life was fair.

# I’m a millionaire!

Well, not in pounds or dollars.  But, according to WordPress.com and to my considerable surprise, this blog has now had over a million impressions since I started it, 3 and a bit years ago.

OK, I know Joel Spolsky or Jeff Atwood probably wouldn’t get out of  bed for a meagre million impressions, but I still couldn’t resist crowing about it.

As you can see in the graph below the traffic is very uneven, dominated by a few posts that made it on to the front page of social news sites.

In fact over 40% of the total impressions come from just 5 (2%) of the posts:

 Post Impressions The software awards scam 234,909 10 things non-technical users don’t understand about your software 55,291 Lessons learned from 13 failed software products 51,676 Your harddrive *will* fail – it’s just a question of when 47,505 Where I program 47,075

Here are a few things I have learnt along the way:

• As with many things in life, persistence is the key.
• Choose your audience and write for that audience.
• Pick a realistic posting schedule and try to stick to it.