UX Report:
Revenue & NPS Drivers in DTC Genetic Testing

A strategic conflict between short-term financial targets and long-term user trust. Because one-time kit sales are unprofitable due to high customer acquisition costs and market saturation, the business is forced to prioritize Annual Recurring Revenue (ARR) to satisfy investors.

This creates an urgent, short-term priority: maximize subscription revenue at all costs. Consequently, a poor user experience – like a confusing cancellation process or a misleading paywall – is not an accident.

Conflicting departmental goals (product, marketing, customer service) lead to a poor user experience. Product teams prioritize KPIs like subscription rates, potentially at odds with user-friendly features like clear billing.

This lack of a unified customer-centric vision harms the overall user experience. Each department optimizes for their own metrics without considering the holistic customer journey.

The company justifies subscriptions by offering continuous value through research, DNA matches, and updates, while customers perceive the product as a one-time purchase.

This fundamental misalignment creates friction when customers encounter subscription requirements for features they expected to be included with their initial purchase.

Billing and subscription systems, initially designed for one-time purchases, are inflexible and buggy. These legacy architectures struggle to handle the complexity of modern subscription models.

A complete architectural overhaul is needed, but it's too costly. Companies are trapped between maintaining poor user experiences and investing significant resources in system modernization.

Managing subscriptions, taxes (VAT), currencies, and different regional promotions is immensely complex. The technical infrastructure required to handle global billing creates multiple points of failure.

Sometimes, a poor user experience is an unfortunate byproduct of a backend system stretched to its limits. The complexity of global compliance often forces compromises in user-facing functionality.

Many consumer genomics companies, founded by scientists and bioinformaticians, developed science-led cultures that prioritize algorithms and raw data over user experience. This contrasts with product-led organizations that integrate user-centered design as a core competency.

With platforms like GEDmatch and Dante Labs, technical language is used in a way that alienates rather than educates. The interfaces are saturated with essential, discipline-specific terminology – such as cM, SNP, Autosomal, and Haplogroup – without any in-context definitions, tooltips, or integrated glossaries.

This failure forces users into a frustrating cycle of leaving the platform to conduct external research simply to understand its basic functions.

DTC genetic testing platforms often disappoint users due to vague or changing ethnicity estimates. This stems from marketing promoting definitive answers, while the science is probabilistic and evolving. Users perceive broad results as product failures rather than scientific limitations.

The root cause is a demographic imbalance in genomic reference databases. For example, 23andMe's European dataset is significantly larger than its Asian and Sub-Saharan African sets (800% and 2800% respectively). This Eurocentric bias makes the product less accurate for a large portion of its global customer base.

The disparity leads to more "variants of uncertain significance" (VUS) for non-white patients, causing distress and confusion while eroding trust in the platform.

DTC genetic testing tools often fail by delivering complex genetic analysis in static formats like PDFs, hindering user interaction and exploration. Companies like 3X4 don't allow users to download their raw data, while AncestryDNA and MyHeritage create "stopping point" experiences.

Users want to interact with genomic data – explore, filter, compare, question, and seek outside perspectives – not just view it. They expect data ownership and portability as fundamental rights.

Non-interactive platforms or those lacking manipulation tools limit exploration and fall short of user expectations, creating frustration and reducing the perceived value of genetic testing services.