When you're setting the price for physical goods, particularly commodity goods, you may not have a great deal of flexibility.
However, if you are selling something less tangible—like a service, a subscription, a seminar or downloadable report or book—the range of prices you can charge is very broad, and often surprising.
One management consultant might charge $200 an hour, while another might charge $100 an hour. Is the first one twice as good as the second? Not necessarily. But he or she is probably a lot better at setting prices.
Is a 68-page e-book worth five times as much a 200-page book by a more established author on the same subject? Probably not. But we have all seen e-books flying off their virtual shelves at prices that seem astonishing compared with those of printed books.
And how about online subscription services? Is the value you offer behind your subscription wall worth $9.95 a month? $34.95 a month? Or maybe even over $100 a month?
The only way to determine your best price is to test
When you test by offering a variety of different price points, you will get objective data to work with. You'll be able to see what people actually do, as opposed to what you think they will do.
In other words, testing takes a lot of subjectivity out of the equation.
There is one fundamental guideline to testing prices: Keep charging more and more until you reach the point at which people walk away.
That highest price may not be the best price for you to choose. But you should at least know what the highest acceptable price for your service may be. Here is an example of a price test conducted by MarketingExperiments.com for a leading psychiatrist and author to determine how to maximize the online sales of his newly published book. These were the three price points tested:
A large volume of traffic was driven to three sales pages using just five search terms on Google AdWords. Using an A/B/C split test, the traffic was evenly distributed to these three pages—each of them identical except for the price.
Here are the results of this three-day micro-test:
The highest price was the "torture" price, to see how high the price could be pushed. As it turned out, it was the highest price that generated the most revenue, by a significant margin.
The first lesson learned here is that if the highest price had not been tested, nobody would know that so many people would still buy the book at $24.95.
However, after you have tested, it's time for some analysis...
In the case of this book, it would have been tempting to declare the highest price the "winner" and look forward to high monthly revenues from that time on.
For some services or products, that could have been the right decision. In this case, it was the number of orders that caught everyone's attention.
While the $14 price point didn't generate the highest revenue, it did attract the highest number of orders, by a very large margin.
This raises an important question: "Which is more important, to achieve the highest, immediate revenue? Or to secure the largest number of new customers?"
If a key priority is to get new customers, then you might want to choose the $14 price point. This is particularly relevant if your service generates recurring revenues, or if you have a track record of being able to successfully upsell or cross-sell to your customer base.
Start with testing, then follow with analysis
It's impossible to be sure about the best price point for a product or service without first testing a variety of options. And, as mentioned, it makes sense to find out how high you can push that price.
Then, as with all testing, it's important to study the results in detail before jumping to conclusions too quickly.
Consider your business model carefully, and choose the price point that best supports your long-term goals.
You may like these other MarketingProfs articles related to Customer Behavior:
- The Factors That Most Influence Buyers of B2B Services
- How to Build Marketing Automation Campaigns That Prompt Desired Behaviors From Your Leads
- How to Use the Awareness Stages to Nurture Leads From MQL to SQL
- Do People Trust Brands to Protect Their Personal Data?
- How to Adapt to Changing B2B Tech Buyer Behavior [Infographic]
- Meh on the Metaverse: How Americans Feel About Virtual Worlds