How do you come up with time-frames for when growth strategies should be executed?

Is it always “move fastest,” or do you plan around certain timely events? I can imagine how much this decision-making changes per project. So maybe tell us of a project you can explain in detail, of how you chose a special time ‘when to execute’ and why :)

I’m talking about the specifics of a growth strategy too, as most have a bunch of moving parts. How do you pin-point the best times for each part to go into motion? @DesignerDarius



I’m going to focus on tech-enabled Startups with my response. A lot gets written about how to execute specific growth tactics. Generally they are in the form of paid and unpaid campaigns or on-page or in-app optimization of an activity. What I don’t think gets enough attention is how to consider bigger picture implications before defining time-frames for what, when, how, to execute and why. Forgetting the bigger picture can have you ‘moving fast’ in a direction (aka busy) or worse, ‘moving slow’ or not at all in the right direction at the right time. If you want to just look at time-frames, skip to ‘Agile Growth Hacking’ below.

I start with a general mental model when thinking about growth that has three characteristics, then adapt from there:

1) Balancing financial and human resources available to do Growth experiments with founders even investors desires to achieve milestones, metrics, and validating hypothesis key to growing the business.

  • I recommend a Lean Startup filter to chart 90-day planning cycles.


  • Investors, if you have them, like metrics.


2) Aligning Growth strategies with your Product Development team

  • The Right Way To Ship Software


  • It’s a ‘Marketing Problem”, The product is actually good — The Engineer’s Myth


3) Agile Growth Hacking

  • Weekly Sprints: 1–2 stand-ups and a rhythm of getting things done.

For example: Thursday planning for following week; Friday reporting; Monday standup for the week.

  • Weekly reporting of new experiments that includes leading indicators like bounce rates and funnel metrics*
  • Paid Experiments: between 2 days — 2 weeks
  • Non-paid Experiments: between 2 weeks — 8 weeks
  • On-page or in-App: between 1 week and up to 12 months if you’re doing cohort analysis.


  • When an experiment is validated it gets moved into an ongoing activity until its usefulness has expired (ex. milestone achieved) or is trumped by a better tactic.

* search ‘marketing funnel metrics’ on Google

Any comments and suggestions welcome.


as first seen on

follow me at @mposada and likely see some of the experiments in action

One clap, two clap, three clap, forty?

By clapping more or less, you can signal to us which stories really stand out.