When Metrics Fail - Deepstash

When Metrics Fail

  • Adding new features makes the metrics go up, but it fails when we keep adding newer features, making the application bloated.
  • The brand power, of big brands like Apple or Nike, is hard to track on mere numbers, and the goodwill or trust they enjoy due to their past work is hard to put down in metric numbers.
  • Current behaviour cannot accurately predict future behaviour due to the inherent complexity and unpredictability of where technology and consumer preference goes.

STASHED IN:

90

STASHED IN:

0 Comments

MORE IDEAS FROM Metrics Versus Experience

Just like statistics, anything with numbers can be selective honesty.

  1. If the click-through-rate or the percentage of people clicking on your ad is increased, does it mean better earnings? It won’t work if the ad is just a false click-bait.
  2. If people spend less time on your app, does it mean it is a failure? That can also mean it gets the job done fast, and depends on what your app is supposed to do.
  3. Certain metrics provide information that is irrelevant or disposable, wasting our time.

1

STASHED IN:

104

Certain things cannot be measured just by the number of likes and shares.

The way a product is designed, how simple and intuitive it is, the consumers trust in the product, their love and hate towards it, how they interact with other products, and how they use it as time passes.

1

STASHED IN:

94

Value In Numbers
  • Doing something people find valuable should be able to push your metric scores up, as a by-product. This is the real-world proof of quality in this age.
  • Similarly, if we do something, and the metrics go down, it’s a clear indication the action was wrong, no matter how right it seemed.
  • Numbers speak and provide a clear and tangible ‘score’ to rally a team around.

1

STASHED IN:

125

  1. Use retention as a way to assess your market-product fit, as it tells you how valuable the customers find your product after they stop using it.
  2. Understand the steps your customers have to take to get to your product, and if you can eliminate extra steps.
  3. Focus on key data, and do not waste time on unimportant metrics.
  4. Ask yourself what information you want from the customers to increase sales.
  5. Understand the metric goals clearly, not just on face value.
  6. Use counter-metrics to stress-test your figures.
  7. Pair your hard data with qualitative research like usability testing, focus groups and surveys.

1

STASHED IN:

122

Deepstash helps you become inspired, wiser and productive, through bite-sized ideas from the best articles, books and videos out there.

GET THE APP:

RELATED IDEA

At Netflix, running A/B tests, where possible, allows us to substantiate causality and confidently make changes to the product knowing that our members have voted for them with their actions.

An A/B test starts with an idea — some change we can make to the UI, the personalization systems that help members find content, the signup flow for new members, or any other part of the Netflix experience that we believe will produce a positive result for our members.

STASHED IN:

2

STASHED IN:

0 Comments

Retention measures how long your customer stays actively engaged with your product or business.

The two key retention metrics are:

  • Core retention: The total number of active users after a specific time period.
  • Proxy retention: These are action-based metrics. They are the core actions users need to take to support your model. It is not pure retention but an action that should lead to retention at some time.

1

STASHED IN:

7

STASHED IN:

0 Comments

What are productivity metrics?

Productivity metrics are a means of tracking and measuring how quickly and efficiently employees are completing assignments.

These metrics are also helpful insights to track, manage, and improve employee performance.

As you would expect, there are various types of employee productivity metrics, including quantitative and qualitative measurements.

7

STASHED IN:

86