Product Maturity and Quality

Technology adoption is a term that refers to the acceptance, integration and the use of new technology in society. The process follows several stages, usually categorised by the groups of people who use that technology;

• Innovators
• Early Adapters
• Early Majority
• Late Majority
• Laggard

In the early 2000’s social media started with a younger audience. The people who used social media initially were Innovators and Early Adopters. But as time passed, more people adopted to this as the demographic increased.

Older generation of parents and grandparents started to use social media. They are Late majority and Laggards. This meant social media companies must develop the product and view on quality to support these kinds of users. Hence, the way these companies looked at testing changed.

A product goes through 3 broad categories;

1. Validation phase- the phase where the company is validating the product market fit.

2. Predictability phase- the company is creating a stable infrastructure for scale

3. Scaling phase- the company is aiming to limit the negative impact to unlock growth.

Validation Phase — Product Market Fit

Innovators, Early Adapters are the users in this phase. Characteristics of these users are:

• Tech savvy
• Enthusiastic about new product.
• Forgiving if the product rapidly iterates through versions

In this phase things change rapidly as the team is trying to build something new. In this phase, product development is based on MVP. It is focused on getting feedback and iterating.

The company QA strategy is ad-hoc and flexible. Good communication, unit testing and code reviews are conducted. Automation is not a focus as it’s not worth to do automation till the product is out of the initial proof of concept phase.

Users of this phase are Early Adopters who are quite forgiving of issues. Quality is however heavily dependent on customer expectations. The more mature the industry the higher the expectations.

E.g. Early days of online dating, the idea was very novel. People didn’t know what to expect in terms of quality. They were highly taken up with the new concept it was providing. Hence, this kind of audience didn’t have any preconceived expectations on quality. Today those same users are not so forgiving with a newly launched dating service. From login time they are expecting to have a good experience like any other established services like Tinder or match.com. They have a mental benchmark.

The bar is even higher in industries like banking and insurance. Developing an app in environments like these, it is necessary to move slower and keep quality higher before release despite being in the validation phase.

During this phase features can be easily abandoned as you iterate around what you should be building. Constant change and uncertainty make it prone to bugs and issues. Because of how new the product is, manual testing is more flexible and higher ROI than automation. Your testing focus is on core user flows, new functionality, unblocking critical user flows.

Predictability Phase: Creating Stable Infrastructure for Scale

This is when the user base grows to Early Majority. The team needs more reliability and they value stability more in this phase than in the Validation Phase. The QA strategy changes as the application gets more complicated; the focus is on the team to move fast with the correct infrastructure. Testing revolves around exploratory testing and automating stable features.

After the product is validated, the company would put more resources behind the app in this phase. They can invest more on,

· Testing

· Optimising code for testing

· Creating or expanding automation suite.

· Tools for monitoring testing.

Scaling Phase- Minimising Negative Impact to Unlock Growth

Finally, product matures in the primary market and now the stakeholders are looking at additional market and opportunities. The application user base now includes Late Majority and Laggard.

This phase is about accelerating growth with new user adoption and increasing engagement for existing users. In this phase even a small problem effects a large number of users. In the validation phase an issue that impacts 1% of the users won’t even be on the quality teams’ radar. In the predictability stage that smaller percentage is a low priority edge case. But in the scaling phase, 1% (of users) may comprise of more people than in the first two phases.

E.g. A tiny bug effecting Google Map users amounts to affecting approximately around 10 million people. That’s roughly equivalent to Portugal or Sweden not being able to use Google Maps.

In this phase you will need a QA strategy that empowers scalable growth. A wide range of testing takes place in this phase (e.g: performance testing such as battery, network, CPU consumption to make sure it meets expectations). When things start to fail in this phase it doesn’t mean that your QA is failing; it means that your needs have changed, and you need to change your strategy.

Conclusion

There are common testing challenges in each phase which need to be addressed as it grows in complexity and user adoption. There is no one method to test in each phase. You always need to have a good blend of testing types, and that blend should evolve to match your product maturity.