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Feb 05, 2019 - 12:00 PM
One of the best pieces of writing on the subject is from CRE (Conversion Rate Experts) book "Making Websites Win". I have learned a lot from them over the years and recommend you get a copy:
https://www.amazon.com/Making-Websites-Win-Customer-Centric-Methodology-ebook/d
p/B076XSCTB2/
First, before you even consider "money back guarantees" figure out what your site visitors most common objections are. As they say:
Conversion solutions are highly targeted; the problems are like locks—the solutions like keys Here’s an example to illustrate why DiPS is so effective.And why the alternative—blindly applying best practices—is so ineffective. Imagine that a company, ABC Corps, had just launched a new product, the ABCmatic. Would you buy one? Probably not, for one of the following reasons: 1. You don’t know what it does. 2. You know what it does, but you don’t know why you’d need one. 3. You aren’t convinced that it will do what it claims to do. 4. You don’t know whether it’s compatible with your existing technology. 5. You think it’s too expensive. 6. You don’t trust the company. You’ve never heard of them before. 7. You are going to think about it. If you don’t know what the ABCmatic does, ABC Corps would have to explain what it does. Would a guarantee help instead? No. Would a lower price help instead? Not at all. Would testimonials help? No. None of those things would help one iota. The only thing that could advance your decision is an explanation of what the ABCmatic does—such as “ABCmatic allows you to manage your computer’s memory.” In fact, all those other solutions would merely reduce the chance that you’d ever find the paragraph that explains what the product does. The problem is like a lock, and the solution is like a key.
Having applied the the "D" in their DiPS (Diagnose Problem Solution) you may find that a guarantee will work. Now use the following guidelines and their 9 point checklist for guarantees:
When (and why) do guarantees work?
Guarantees don’t always increase sales. To understand when a guarantee would help, consider the two major functions of a guarantee: Function 1: A guarantee reduces the risk for the customer. If the company doesn’t fulfill the guarantee’s promise, the customer is compensated. Function 2: A good guarantee self-evidently promises that your business will be harmed if you don’t honor your claims. It effectively says, “Our promise must be true. Otherwise we wouldn’t be in business.” It thus acts as a kind of proof.
Many people underestimate the importance of Function 2. So guarantees are effective when… • the visitors want what the company is promising, • but they are nervous about the risk, or are skeptical about the claims, • and your service lives up to its claims. A 9 Step Process for Implementing Guarantees Safely
A guarantee can do harm if it’s implemented badly. Also, with guarantees the feedback loop is long, because you can’t calculate the costs of invoked guarantees until after the guarantee period has expired. The following workflow provides a low-risk way to implement a bold guarantee: 1. Create the guarantee, based on the principles described previously. 2. Carry out scenario modeling, as follows: Create a table in which the columns represent different values of “uplift in conversion,” and the rows represent different values of “percentage of customers who invoke the guarantee.” Then work out the net change in profit for each combination. Also consider how guarantee claims would be handled operationally (accepting returns, restocking shelves, issuing refunds, etc.). If you are satisfied that the guarantee will generate additional profits, then proceed to the next step. 3. Run the guarantee as an A/B test for a short time—for just a few days, if that’s all the risk you can bear. 4. Wait for the guarantee period to expire. 5. Calculate the increase in profits, based on the measured uplift in sales. 6. Calculate the cost of people invoking the guarantee. In our experience, the invocation rate tends to be lower than companies expect, sometimes by an order of magnitude. 7. If you need more data (which you probably will), return to Step 3 and run the guarantee for longer. By doing this in small increments, you remove the risk caused by the long feedback loop. 8. If you do have enough data, and the increase in profit more than offsets the cost of returns, make the guarantee permanent. 9. Return to Step 1, creating a bolder guarantee.
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