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Ancestry's pricing lacking monetary DNA

Patrick Campbell Apr 8 2021

This week, we're going back in time to study the subscription model of And before you think, "Oh, that's for my parents, that's for my grandpa, that's for my grandma. They can go study what happened in the olden days," keep in mind this is a company that has three million subscribers, and they're not paying just ten bucks a month. They're paying a pretty good premium on the product, and in addition to that, they have 26 million people who have taken DNA tests.

We're focusing on the monetization pieces of the strategy. We'll cover what they're doing well and talk about things they could fix based on the mass gifting model that happens with subscriptions.

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Pricing field notes

logo's embrace of technology, a widening pool of products, including DNA health data, military records, and news databases, combined with a subscription model to keep your family tree locked in, has pushed them to over $1 billion per year with the market cap around $1.3 billion. But are their technological achievements too advanced? Does Ancestry have the ability to embrace their technology for the next echelon of growth?

Below are some valuable takeaways you can implement in your own business.


  • Segment willingness to pay to understand which segments value the product most.
    Aligning your pricing with customer segments increases both revenue and profit, keeping customers happy and helping reduce churn.You need to know what kind of customer demographic or attribute is the leading indicator of higher willingness to pay versus lower.

    In’s case, we see an evident differentiation between under 40 and over 40. has a lot of opportunity to figure this out across these two categories.
    • Segment willingness-to-pay data and your customer base to expose different opportunities for growth.
    • Understand your segments in order to know where you should be priced to create better pricing tiers.

  • Understand why the purchase is happening to adjust packaging.

    Having the right feature mix is key to optimizing value for customers and ensuring future growth.  Tailor your packaging to specific kinds of users, so that customers can get the most value out of your product

    • Examine the difference in willingness to pay. 

    • Ensure there's an upgrade path to take advantage of higher willingness to pay.
  • Understand feature preference to determine upgrade paths and bridge the gift path.
    Targeting the features that are most valuable to particular customers is what drives potential customers to convert and current customers to upgrade to higher plans. Optimizing this path is where there's much to be gained, at least in the monetization growth lever.
    • Features that aren't really a proxy for the company size or maturity, should definitely be offered to everyone and allow them to build them onto the subscription that they're on.
    • Don’t give away too much value.
    • Features that you're selling, bundled in different tiers, are used or valued by less than 40% of the people within that tier.

The history of

Genealogy fills the need in our humanity to understand who we are through the lens of where we came from, so we can fix the sins, and build on the lessons of the past. 

This is the central mission took on all the way back in 1983.

Before Ancestry, genealogy was a laborious task of trudging through bureaucracies for physical birth and death certificates. Ancestry wanted to make this discovery easier, so their first products in the 1980s were physical books that outlined all the genealogical data they could get their hands on—mostly for large families. 

Their core thesis was to use technology to get as much genealogical data into the hands of family sleuths to automate the production of their family tree. With this in mind they embraced every technological revolution. Floppy Discs in 1990 brought more data and searchability. CD-roms in 1996 brought even more data and the ability to document your tree in a more automated fashion. In  2000 they went online with more census data added every month, and then in 2002 they launched the first DNA service, so you could discover that second cousin, twice removed, Ralph, even if no paper or digital records existed. 


Ancestry's success focused on the customer need for data, but also the need for building the tree in as automated a way as possible. Thus, they moved the experience from compiling to compiling and exploring, widening their market from just family sleuths to those who were also curious about if all those stories told around the holidays were true, or where those characters came from. 

Their embrace of technology, a widening pool of products including DNA health data, military records, and news databases combined with a subscription model to keep your family tree locked in, has pushed to $400M per year with a market cap well over $1BN. 

Not everything is amazing though. While their technological edge got them here, technology also allowed for the market leader to get challenged by niche and new-age solutions. 23andMe is making their play in the DNA health and ancestry space. My Heritage and FindMy Past are claiming to offer not as good of databases as Ancestry, but a much cheaper price. 

Critics also point out that the market for DNA testing is souring over privacy concerns and a loss of novelty. After all, it's pretty cool that DNA sleuths have solved numerous crimes using DNA databases, but does that give a company like Ancestry too much power? Ancestry’s calmed these concerns, but the amazing technological achievement Ancestry made mainstream may end up being just too advanced. 

The questions then become: Does ancestry have the ability to embrace their technology for their next echelon of growth? Is there another market they could enter to widen their target customer segments? Is there more revenue to squeeze out of optimizing their current base further? It seems this market is Ancestry’s to lose and they’re in a good position, but we’re going to answer these questions and more by collecting data from 10,542 current and prospective customers. We’ll reveal all the data and answers to these questions, so keep reading.


A data product

Unlike other data products, with Ancestry, you're looking up information, and you're getting the data around this little leaf. The next leaf might tell you who your next relative is. But where they get this right—and this is a big lesson for many people—they tap into the actual action and actual recording of a living document or a living app essentially. And it's evolving.

When you think about data products. This is going to be a hard left turn to B2B products. I think where many folks get things wrong with Mattermark, or some of these other products where you're looking up data, this is where can provide a big lesson to both consumer products and other B2B products.

Some level of engagement is super important. If you're not a workflow product—meaning customers aren't using it every single day—and you're not an anti-active usage product, meaning the customer only needs to turn it on. If you're in the middle here, you need a work product the customer wants to save and retain. If they want to retain it, they'll keep paying you, even if they're not necessarily engaged. And I think that's an enormous lesson for many people. 




Ancestry's pricing page

The Amex effect

One thing I love about their pricing page is the six-month membership—they're taking advantage of the Amex effect. They're pricing the product right at that $100, $150, $200 mark, that we've found people are just so willing to swipe their credit card for. 


Screen Shot 2021-04-07 at 8.48.54 PM

This is key because people aren't great with percentages in terms of decision-making. When I look at save $100, save $90, that's a physical amount of money. Customers think, "Oh, it costs me $150, and I'm saving $90? Oh, great! Let's make that conversion. I'm buying it for grandma. I'm buying it for grandpa."

The other key point here is how bifurcated their product in terms of the different tiers: US Discovery, World Explorer, All Access.

There are a bunch of other features we'll talk about in a second relating to data. But the thing you need to understand when you have a data product is they're looking at data is they're basically using location as the primary as the primary kind of segmentation on that data. And here in the US, we are all immigrants on some level. It depends on how many generations you've been here. But eventually, you'll need an upgrade path to World Explorer.

It's fascinating how they do this. I think it's super smart. And it creates a path inside the product. You might think you're starting with just US Discovery. Well, you're probably very quickly going to upgrade to World.

Another thing we're not going to get into too much, but it's important to note: If you scroll to the bottom here, you can see "visit other sites." They have different centric sites: A French site, Australian site, Australian site, Canada... and more. They have many other sites. 

Screen Shot 2021-04-07 at 8.59.01 PM

Now, someone in Canada might not care about the US data base at all. So you want to make sure you tailor that site to those different use cases. What Ancestry does really well, and others should mimick, is they're in a position where they are localizing their pricing. They've been able to localize not only the experience and the language, but the actual pricing. In some places, customers are less interested in these databases. So they're selling the DNA testing kit.

In other places, they might have enough databases, and people want to explore these memberships. Ancestry puts that price in Euros or British pounds, etc. That's a key point we need to make. It's a theme from this season, and it's one of those things that should keep in mind.



Where does our data come from? 

Here at ProfitWell, our Price Intelligently software combines proprietary algorithms and methodologies with a team of pricing experts who think about this stuff more than anyone else to help companies optimize their monetization strategy. We do this by going out into the market and collecting data from current and prospective customers, having the ability to collect data from everyone, from a soccer mom or dad in the middle of Kansas, all the way to a fortune 500 CIO in South Africa. We then take that data and run it through our algorithms and analyze it in every direction to determine a company's ideal customer profiles, as well as which segments value, which features and which segments are willing to pay more, all in the spirit of determining how a company can use monetization for growth.


Data and analysis

Segment willingness to pay

Segment willingness to pay by the cohorts of your customers that value the product most.This is crucial. And we got crazy results for You can see in the data here, the willingness to pay, once you jump over 40 years old, is astronomically higher than below 40. It's almost troubling. Here's this giant cliff between people under 40 in their willingness to pa, and people over 40. But is pricing pretty much for people under 40. (1)

I would want to look at the demographics. I would argue that most folks are probably older. When you're older, you get a fascination with where you come from. When you're young, you don't care because you're young and stupid.

What's interesting and want to explore more and have some data on this—is that the older people get gifted a lot. Like, "Hey, let's give grandma or grandpa something to do, exploring their history, the family, these types of things." Ancestry has chosen to price based on the people giving the gifts, hoping that it also includes the people who are over 40 because they're willing to pay more.

And that brings us to our second point.

Understand why the purchase is happening to adjust your packaging

This gets to the heart of the actual gift aspect. We tested the willingness to pay amongst prospective and current customers. We asked "Hey, is this for personal use or is this a gift?" And what you'll notice here in the data, interestingly enough, someone under 40, their willingness to pay for personal use was half of what they were willing to pay for it as a gift. They're priced for the gift.

When you look at the folks over 40, personal use is much higher in terms of the willingness to pay for six months. For the folks who are essentially on the gift side, is still pretty hot, about 30% higher in some cases. (1)

So, what I think should do, is average things out.That means average things down. It's essential for most businesses. If you have a gift purchasing motion or a champion purchasing, but not a decision-maker purchasing, you need to adjust the packaging for when the actual user who has a higher willingness to pay, ends up using the product. has a gift-type packaging. That gift should probably have some limits. Maybe it's time-based, and then the price jumps back up. Maybe it's, "Hey, you don't get all-access. You only get US based."

I would reconsider their gifting strategy to not just be all-inclusive. The giver of this gift doesn't care about all the idiosyncrasies of the gift because it's not for them. They just want to make sure it's good. So you can kind of take advantage of that in a couple of different places in a good way. Once the actual or power user who cares about the product and willingness to pay is higher—you need to have a trigger to push them into the upgraded plan.

Now, may be doing something like this already. We don't have any insider information. But based on their price points and even their gifts price points, I don't think this is happening. They're leaving a considerable amount of money on the table. We're talking probably at least 20 to 30% ARPU, depending on how they would tinker to put this.

These prices are too low. And it's insane that they're not doing anything about it. Maybe there's something that we're not seeing, but even the prices top out pretty high. And there's some work to be done to adjust this and get the pricing in order. Because with three million subscribers, you get a fraction of those to upgrade and we're all buying yachts.

So to close this out and make it applicable for everyone, I think it's crucial to understand that one: who's willing to pay more than you're currently selling to. If you have one group willing to spend less, and another group willing to pay more, but you don't have a way to differentiate them, you need to make a decision. The worst thing to do is put the price in the middle. The second worst thing to do is just go with the lower price. What you should be asking is, "How do I get the lower price and then get to an upgrade path?" Especially if you can't offer up two different packages up front.

Now, the other thing to keep in mind is understanding what the purchase path. If someone is gifting it, if someone is a champion buying the product to test it out, you must understand what that path looks like. Then, you can hop in and take advantage of that path to get that ARPU expansion.


Understand feature preference to determine upgrade paths to bridge the gift gap.

What Ancestry does so perfectly is they have a natural, organic expansion opportunity within the product. And what's beautiful about this is I'm sure there's a level of community with

We saw this with the Golden State killer. They uploaded DNA, and they found a familial match. I think it was a cousin or something, don't quote me on this. They went to the cousin and said "Hey, this is what's going on. And here's all the information we have." And I think they had an image, like a crude drawing, and they suspected he was a former law enforcement professional. And the cousin says "Oh yeah, that's my uncle." And they caught the guy! It's crazy! And I think he's on trial this year.

People are super passionate about this. I think that the limitations of data, or records, is probably the right thing to do. And I think we saw this in the value matrix.



Value Matrix

You're about to see something called a value matrix. We collected data from the group comparing feature preferences and plotted those on the horizontal axis, more valued features on the right, less valued on the left. We then collected willingness to pay for the overall product and plotted that based on their number-one feature preference on the y-axis. Analyzing data in this manner allows us to determine which features are differentiable add-ons, core, or commoditized for each segment.


So, for Ancestry, things like the US Records, those are table stakes. Showing up in the core, these were largely US respondents. And there's the world database and the differentiable feature, which is kind of like a slam dunk. And then you have the and military subscriptions. These are showing up more as add-ons to keep a consumer subscription easier. (1)

Sometimes you don't want to nickel and dime and charge for these. Just include them into an all-encompassing tier, which is precisely what did. And I think they need to reconsider their upgrade path, especially with those gifts, to unlock some ARPU and raise their overall prices. Let people get in on the US subscription and expand to World, or get into World and expand all of those add-ons from there. There are different levels. 


Recap Banner


  • Segment willingness to pay to understand which segments value the product most. In this case, we see an evident differentiation between under 40 and over 40. has a lot of opportunity to figure that out across these two categories.

    I think for any business, this is just table stakes, monetization strategy. You need to know what kind of demographic or attribute of your customers or prospects is the leading indicator of higher willingness to pay versus lower. If you're B2B, it's probably going to be something like company size, team size, these types of things.

    If you're D2C, it's probably going to be household income, maybe it's age for a product like this. But you want to see what are things that have the biggest swings, then you want to make sure you're pricing based on those different personas. 

  • Understand why the purchases happen to adjust packaging. If you're getting all these gift-givers, essentially you have to make sure that if you have such a high difference in the willingness to pay for people buying for personal use of the people getting the gift, yes you want to price for the person getting the gift, but you need to have an upgrade path to take advantage of higher willingness to pay of the person receiving the gift. Allow them to grow their usage of the product over time after they get the gift.

  • Understand feature preference to determine upgrade, pass, and bridge that gift gap. We talked about this at length earlier. There are so many opportunities with to continue diversifying their plans with different features. And we saw that huge breakdown in willingness to pay between US and World, and some of those add-ons. I'm sure there are some other options with the DNA testing kits as well.

    I'm sure they're already doing that. But I think going back to the core of the three million subscribers and optimizing this path is where there's much to be gained, at least in the monetization growth lever.

Who's up next?

Next week we have the best media company, I think, in the history of humankind. They challenged Disney, and Disney is fighting back. It's Netflix. I think they're the best because Disney has the DNA to create great media. And Disney is an admirable company. But Netflix has the technology and data DNA that may allow them to take on Disney. And we'll get into the implications of what happens with the competitive marketplace with Disney.

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If you want help with this type of pricing research for your company, feel free to email me  at or, and we'll make sure you get hooked up with the right people to make sure you're focused getting your monetization right. 


This is a ProfitWell Recur production—the first media network dedicated entirely to the SaaS and subscription space.

By Patrick Campbell

Founder & CEO of ProfitWell, the software for helping subscription companies with their monetization and retention strategies, as well as providing free turnkey subscription financial metrics for over 20,000 companies. Prior to ProfitWell Patrick led Strategic Initiatives for Boston-based Gemvara and was an Economist at Google and the US Intelligence community.

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