One simple secret from an 1890 economist nearly doubles website profits . . .

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One simple secret from an 1890 economist nearly doubles website profits . . .Back in the early days of web marketing (2002 to be exact) we managed website conversion testing for a site called Wholesaler’s Handbook.

The product was aimed at EBAY sellers to provide access to wholesale product sources, and was priced at $49.95.

Around this time we’d begun experimenting with “Price Elasticity Testing”, which was originated by an economist in 1890.

By applying this methodology, we nearly doubled the site’s profit margin in about 2 weeks . . .

Price Elasticity Testing measures the impact of product pricing, on product demand.

For Wholesaler’s Handbook we picked new price points and split test them to see how sales would fluctuate vs. demand:

  • $49.95 – Variable A Control
  • $39.95 – Variable B
  • $19.95 – Variable C
  • $9.95 – Variable D

After ~ 3500 visitors saw each price point, here were the results:

One simple secret from an 1890 economist nearly doubles website profits . . .

From the above, you can see that there was clearly a lot more demand at the $9.95 price point than the other variables, and it won handily at conversion rate.

But – when you include the “gross profit” column, $19.95 was the clear winner in terms of total sales:

One simple secret from an 1890 economist nearly doubles website profits . . .

So out of those four price-points, $19.95 drove the highest overall gross profit rate.

Since they ran with primarily fixed CPC costs (oh for the 2002 days of $0.05 a click again!) this was a huge win and was incredibly simple to set up.

Stuff you should begin testing right away . . .

Although many of our clients require more complicated calculations to determine net gains – such as lifetime customer value, or variable product costs – here are a few tests that consistently produce interesting results:

  • Experiment with different pricing for different sources – for one of our clients, the sweet-spot for selling his product to Facebook users is $29.95, but for his Google Adwords traffic he generates the highest profits selling at $34.95. Think switching pricing on your users is is unfair or clumsy? The biggest ecommerce sites in the world have been doing it since the turn of the millennium!
  • Odd numbered pricing – ending your product pricing in odd numbers – particularly 79, 95, & 99 – outperform even numbers. This could mean $29.79, or $279, or even $79 alone. It’s worth testing all three of those iterations.
  • Set an outlier price double the price of your control price point – you know you want to! We’ve actually run tests where doubling the price has doubled conversion rate.
  • Try “two’fer” pricing – as in get 1 for $15, or 2 for $25. This works, sometimes even for eBooks (eg – buy one for a friend).

As always the crucial element is always-be-testing, drop us a line if you’d like to see why our clients call us their secret weapon – we’ll drive up your profits, guaranteed!  

We’re looking forward to hearing your feedback about this post – what’s working for you? What’s not?

4 Responses to One simple secret from an 1890 economist nearly doubles website profits . . .

  1. mike says:

    You need a lot of visitors to even start testing this kind of thing. A bare minimum test would need 3-4 candidates, and in your group you tested over 12000 visits! A lot of new sites don’t have nearly enough visitors.

  2. Zack says:

    “You need a lot of visitors to even start testing this kind of thing” – That is certainly true for 4 variant testing, and a fair comment.

    BUT you can run a meaningful A/B test as well – try a 30% increase or decrease of your current price point as a starting point, let it run for as long as it takes – the point being there’s not many more powerful tests that the price point in terms of your bottom line.

  3. Ed says:

    Mike is correct when he says you need x amount of visitors to get a statistically valid test, however for most businesses a simple adwords campaign can easily get you enough traffic to get the data you need.

  4. Yanan says:

    I do not see how this method handles the cross elasticities. Company often has more-than-one products, and most of the products also have their competitors; there are substitute/compliment/no effects amoung these products. Maximizing one product’s REV does NOT necessarily mean you can maximize the total REV.

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