Programmatic Inventory Explorer - Use Cases

Dive into some ideas on how to get the most out of Kayzen's Programmatic Inventory Explorer

Tomás Yacachury avatar
Written by Tomás Yacachury
Updated over a week ago

About Kayzen's Programmatic Inventory Explorer

Programmatic is the most transparent method for buying in-app inventory outside walled gardens (Meta, Google, TikTok, Twitter). A good evidence of this is the vast array of signals available on the bidstream, allowing buyers to understand better what the in-app market looks like beyond their current purchasing behavior.

Leveraging the full transparency of programmatic, Kayzen has developed the first-ever Programmatic Inventory Explorer to help you navigate the in-app space and make more data-driven decisions when planning your campaigns.

The following guide will help you understand how to translate the information available on the tool into actionable insights.

We suggest the following links to expand your understanding of the Programmatic Inventory Explorer:

Use Case #1 - CPM Benchmarking

The Market Price section on the Programmatic Inventory Explorer helps understand how your current buying strategy fares against the market.

How many impressions am I able to reach my current CPM? How many additional impressions should I get if I increase my CPMs by $X?

You can now answer these questions by following these steps:

  • Position your avg. CPM on the price distribution curve

  • Compare against the upper and lower percentiles

  • The slope of the curve on your avg. CPM position will determine the impact of price changes on your impression reach.

Use Case #2 - Reach as a means to determine campaign duration

For how long should I run my campaigns? How many incremental users can I impact if I extend my campaign beyond one week?

To determine this, you may want to look at the jump in unique devices between the WAU and MAU values.

Based on the above image, the left example shows an increase of, on average, 4MM unique devices by extending the campaign from a week to a month, i.e., roughly a 20% increase. As such, in this case, you should keep your campaigns shorter, 1-2 weeks, as there is no significant added value, in terms of reach, to extend the campaign beyond that.

On the other hand, looking at the right-side example, we also see an increment of about 4MM unique devices, but in this case, it would mean doubling the number of users potentially impacted in a single week. Hence, running longer campaigns of about 3-4 weeks might make more sense to maximize your campaign's reach.

Use Case #3 - Reach as a means to determine daily impression capping

The Programmatic Reach section can also be leveraged to determine how many times a day, at most, I want to impact a specific device.

To do so, we will look at DAUs and WAUs in two extreme, hypothetical cases:

  • DAU = WAU

    • Everyday I am seeing the same users. 100% overlap between days.

    • Multiple opportunities to target the same user across the week

    • Proposed strategy: Strict daily impression capping. 1-2 daily impressions per device.

  • 7x DAU = WAU

    • Everyday I am seeing different users. 0% overlap between days.

    • Devices impacted one day cannot be reached for the rest of the week.

    • Proposed strategy: Flexible daily impression capping. +7 daily impressions per device.

When looking at your DAUs and WAUs, understand how close you are to these extremes. That will determine how flexible or strict your daily impression-capping strategy should be.

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