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How we reduced our cancellation rate by 87.5%

331 点作者 kareemm将近 13 年前

14 条评论

patio11将近 13 年前
Seriously, one of the best and most actionable articles you'll read this week. (n.b. This sort of thing <i>prints money</i> for companies at pretty much all sizes. Well, after you've got enough customers to worry about cancellations.)<p>I'll probably write something about this eventually. There are a lot of generalizable tactics which repeatably work well. (Email engagement is probably the highest bang for the buck, considering that you can implement it in about an afternoon and, coming from the starting point "We send no email", it will virtually immediately produce visible results.)
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ThomPete将近 13 年前
Great analysis and I really want to believe in this but I am a sceptic and this:<p><i>Interested in learning how a cohort analysis can help your business grow? Get in touch – I work with select clients to help identify growth and retention opportunities, and build features to realize those opportunities.</i><p>Kind of killed it for me. Now I am not sure whether I should trust the results.
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ehsanu1将近 13 年前
If the average time to cancel is 61 days, and they waited only 2 months since the changes to calculate the new cancellation rates, it stands to reason that the cancellation rate will rise over the next few months, right?<p>Assuming a normal distribution (probably not that accurate, but it's just a guess), the final cancellation rate would be about double that measured until now.<p>Am I missing something here?
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jamiequint将近 13 年前
I'm interested in why you found Mixpanel hard to use. It satisfies every requirement you have described out of the box and only takes minutes to set up. Unless you wanted to process a ton of past data it probably would have been easier for you to skip all the manual data entry excel requires.
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bdunn将近 13 年前
These are the sort of posts that keep me coming back to HN. Great analysis, and as a former Crossfitter - awesome product idea!
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edhallen将近 13 年前
Great post on the usefulness of cohort analysis (or of experimentation more broadly, which if you think about it, is exactly what cohort analysis is - it just uses the past as a control).<p>One thought on ways to analyze the follow-on problem of customers canceling after 61 days (a problem similar to what I've seen at every web company I've ever worked at).<p>First, perform the same cohort analysis you’ve already done, but look at the cancelling customers vs retained customers at day 1, day 15, day 30 and day 45, then use this analysis to figure out your triggers (things like # of Facebook posts needed by day 15, % of profiles claimed by day 30, etc).<p>Once you have your triggers, you can make proactively calling / emailing problematic customers a key part of your daily routine. While discounts might still be the way to go, this trigger based approach is one I've seen work well. Additionally, because you are in touch with problematic customers it often gives you insight into what do next.
DanielRibeiro将近 13 年前
Related great post written by Shopify guys a while ago: <a href="http://www.shopify.com/technology/4018382-defining-churn-rate-no-really-this-actually-requires-an-entire-blog-post" rel="nofollow">http://www.shopify.com/technology/4018382-defining-churn-rat...</a>
Smerity将近 13 年前
Congratulations on the impressive result. It seems you have a good product but the real change appears to be encouraging those who wouldn't use your system properly to improve their habits.<p>I wish you could work out more concretely why the situation improved but with three substantial improvements (that likely impact different customers in different ways) that's difficult. I could imagine "drop[ping] prices by 15-60%" would help those not using your product fully for example as even if they don't use all the features they don't feel like they're overpaying.
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Angostura将近 13 年前
Interesting article, two issues.<p>First, you changed two variables simultaneously, so its tricky to tell how much either contributed. The cynic in me, suggests that the article <i>could</i> actually be summarised as 'we cut our prices'.<p>Second, you right:<p>&#62; So we improved our onboarding to help a gym owner export a CSV of their members’ email addresses to send to us.<p>Certainly in Europe, that could fall foul of data protection legislation, you'll need to make sure that the customer has given permission for their data to be past to 3rd parties.
janesvilleseo将近 13 年前
Great article. I went to check out your site socialwod.com and was unable to scroll on my iPhone. You may want to check your analytics to see if this effecting a large percentage of your visitors. Keep up the great work!
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1123581321将近 13 年前
Which items from your analysis made a the most difference?
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philip1209将近 13 年前
Cool. I've read about JBara, which provides a CRM plugin that aims to predict when people are going to cancel and give you a chance to retain them.
RobPfeifer将近 13 年前
I think the real takeaway here is: "Email is a better marketing channel then Facebook"
mredbord将近 13 年前
This is a good article. I have a few issues with price-reduction for existing customers, though, that I want to highlight. I think it's fantastic that OP got the desired results on customer churn, which was his goal - but I'd categorize pricing changes as "gray hat" retention improvement with regard to the overall health of his business and future revenue. Here's why:<p>On price specifically: In a subscription business like this one, you have to meet a minimum utility requirement in each month that a customer is able to cancel if you want to retain customers. Each customer's minimum utility is different and could even be comprised of different factors/features depending on the breadth of the product offering. But there is one factor that cuts across all of them: price. A significant element of churn is price because the initial purchase thrill may decrease over time and result in customer cancellation requests at a certain point in their lifecycle. So, cutting price is kind of an easy way to reduce churn in a subscription model...particularly because people bought in at X and are now paying fractional X. Boom - happy customers. Also, price-cutting is habit-forming, and the customers who received a reduced price will come back asking for more reductions in time.<p>On features: Multiple times, I've seen the "get more people using our product" as a good way to reduce churn. I won't comment on permission customer marketing and whether or not what OP did was legal, but the results of a feature like this are great, and seems like he added more than just this one. He added improved functionality and invested in his product at reduced prices - great deal!<p>On onboarding &#38; cohort analysis: OP was right to focus on onboarding features and adoption to improve stickiness among new cohorts. He would have also been smart to raise the price for new customers if he materially improved the product (which it sounds like he did). Over the same time period, he could have had newer cohorts of higher paying customers, making the older ones less important to the financials of the business. By "hiring" higher priced customers to increasingly recent cohorts and continually "firing" older-lower-priced customers, the balance of his revenue would have shifted to these newer, more valuable customers over time, making the older-less-happy customers less important to his business. That's how you really turn the crank on a subscription business, and if your onboarding is good enough to continually improve retention in new cohorts, you've really nailed it.<p>Overall, I don't mean to be overly critical of OP's choices. I aim to highlight where optimizing for customer churn alone can harm the financials of the business, particularly around price-cutting for existing customers. He's doing lots and lots right with his cohort analyses, onboarding improvements, and assumptions about churn impact of new features. However, we're in business to make money, so these have to be balanced with the health of the business itself.