S1E7 – DNA, Data & Dollar Signs: 23andMe

Key takeaways

• A compelling first purchase does not always create lasting customer value.
• Subscription pricing is difficult to defend when customers have little reason to return.
• A low entry price only works when there is a clear path to repeat revenue or expansion.
• Personal data may be valuable, but customers need to understand how it is used.
• Go-to-market and pricing strategies must be built together, not managed as separate decisions.

The problem with a one-time customer

The basic appeal of a DNA testing kit is easy to understand. Customers want to learn about their ancestry, find potential relatives, or gain insight into certain health risks. It is an interesting purchase, and for many people, the results are meaningful.

But the business model has a natural challenge: how many times does one customer need the same test? Once the results arrive, the main transaction is complete. There may be new features or additional insights, but the reason to buy again is not always obvious.

That makes customer lifetime value difficult to build. If the company spends heavily to acquire a customer and only receives one payment, the first transaction has to carry much of the economic burden. A $99 or $200 purchase may feel attractive to the customer, but it leaves little room for acquisition costs, testing, technology, support, and ongoing research.

This is a common pricing issue across industries. A low price can drive adoption, but adoption alone is not a business model. Revenue Management Labs helps companies look beyond the initial sale and identify the specific margin levers that can support sustainable growth.

Why the subscription model looked shaky

23andMe has tried to move customers toward subscriptions, offering access to additional reports and features over time. On paper, this can make sense. Subscriptions create recurring revenue and may improve the value of each acquired customer.

The problem is stickiness. Customers need a strong, ongoing reason to keep paying. If the service does not regularly provide new and useful information, churn can become very high.

A subscription should answer a simple question: What will I receive next month or next year that is worth paying for? For a DNA testing service, that answer is not always clear. The customer may be interested in the first set of results but less interested in paying indefinitely for incremental updates.

A discounted first year can make the offer even more complicated. A customer might see a low introductory price, but not understand the longer-term cost or the difference between a one-time test and ongoing access. When the value trade-offs are unclear, customers may subscribe briefly, cancel quickly, and leave with a poor impression of the brand.

The pricing gap in health-related services

The company also moved into health-related testing, but that placed it beside a much more established healthcare system. Doctors, laboratories, insurance providers, and medical testing centers already have processes for diagnosis and follow-up care.

A consumer DNA kit priced around $99 is not directly comparable to a physician-led service that costs $1,000 or more. The higher-priced service may include administration by a medical professional, interpretation of the results, and a plan for what the customer should do next.

That difference matters. Customers are not just paying for information. They may be paying for confidence, guidance, and action. A pricing strategy that focuses only on the test itself can miss the larger value created around it.

This is where customized pricing work becomes important. The right price depends on the customer segment, the level of support, the risk involved, the competitive alternatives, and the outcome being promised. A generic price comparison will not capture those differences.

Could personal data have been part of the value strategy?

23andMe also held a major asset: a large collection of genetic and health-related data. That data could potentially support research, insurance modeling, pharmaceutical development, or other commercial uses.

However, data monetization creates a difficult value exchange. Customers may ask:

1. Who can access my information?
2. Will it be shared or sold?
3. How will it be protected?
4. What benefit do I receive if it creates value for someone else?

These concerns became more serious after data security incidents and the company’s financial problems. If a business enters bankruptcy, customers may worry about what happens to the data included among its assets. Even the process of deleting an account or changing sharing settings can become frustrating, especially when customers have already lost trust.

Privacy could have been treated as a clearer pricing attribute. For example, different packages might have made the data-sharing options more visible, with a premium attached to stronger privacy protections. That would not remove the ethical and legal questions, but it would make the trade-offs easier for customers to understand.

The lesson for pricing leaders

The larger lesson is not simply that 23andMe chose the wrong price. The issue was the connection between customer value, revenue design, and market strategy.

Companies often focus on growth first. Customer numbers rise, investors respond positively, and pricing receives less attention. But if the offering does not create repeat value, or if customers cannot understand what they are paying for, the weaknesses eventually become visible.

A stronger approach is to connect pricing decisions to the full customer journey:

• Define the core problem the product solves.
• Identify what customers value beyond the initial purchase.
• Test whether repeat usage is real or assumed.
• Make package differences and trade-offs easy to understand.
• Build privacy, service, and support into the value proposition where relevant.
• Measure retention, willingness to pay, margin, and adoption together.

AI can help identify patterns in customer behavior, churn, and willingness to pay, but it is not a substitute for pricing judgment. The analysis still needs to reflect the company’s data, industry, customer expectations, and operating reality.

There is also a practical lesson in simplicity. Customers are busy. They rarely study every detail of a product page or pricing structure. If the value is complicated, the package needs to make the decision easier—not harder.

For pricing leaders, 23andMe is a cautionary example: a strong growth story can hide a weak revenue model. Pricing and go-to-market need to stay in lockstep, because eventually the customer will decide whether the value is real.