Analyze assists data

Using data from the Assists dashboard you can get a broad perspective on how each of your marketing channels impact one another.

If you are running CTV to mobile campaigns, understanding the role of assists is particularly important because CTV impressions tend to be higher up the funnel and drive users to down-funnel channels via which they convert.

Widget breakdown

All of the widgets on the Assists dashboard can be used to draw important insights and inform your decision making. Below you can find recommendations on how to act on the data you see reported in some of the more complex widgets.

Average assisting engagements per assisted install

An install can benefit from more than one assisting engagement. This means that a network can provide multiple engagements for each install they assist. Filter this widget to see the difference between average clicks and impressions per assisted install.

What to look out for:

  • If you see a low average number of impressions per install, this is a good sign of campaign performance. Using a minimal number of ads, you're converting users. We'd recommend increasing your budget for this channel.

  • If you see a very high average number of clicks per install this could indicate click spamming. Take a closer look to see whether you are receiving fraudulent data.

  • If you see a medium-to-high number of assisting clicks per install, you may want to investigate why users are bouncing and not converting. For example, is there a disconnect between the creative copy and app store listing, and is the targeting correct?

  • If you see a high average number of impressions per install, you may want to speak with the network about the number of impressions served. Ask them to improve your targeting or implement a lower daily impression cap to avoid wasting ad spend or degrading the user experience.

Level breakdown for assisted installs

This widget gives you precise insights by offering a complete breakdown of your data to all campaign levels. Use this data granularity to assess key budget and creative changes.

For even more flexibility with your reporting data, you can open this widget as a Datascape report. This allows you to break the data down to the assisting engagement type, and modify the filter settings as you require. To open the widget as a report, select (Open as report).

What to look out for:

  • If you see that Network A is assisting Network B, you can drill-down to see exactly which campaigns and creatives are proving to be the most effective.
  • If you see that a specific creative plays an important role in driving conversions (even for another network), consider increasing the budget for that ad. You can also replicate successful ad formats or campaign targeting across other campaigns or networks.
  • If you see that a creative is heavily assisting itself, this could indicate a high bounce rate and you may want to invest in creatives that convert better.

To see how efficiently Network A is assisting Network B, try opening a report and looking at the average number of assisting engagements between those two networks. With this, you can further see how scaling an assisting network would impact other specific networks' performance.

Assisting engagement trends by assisting network

You can use this widget as a monitoring tool to see how many assisting engagements are provided by different networks over time. For example, compare how different assisting networks perform against one another. What's more, if you launch a new network you can measure its impact earlier - as it may begin assisting other networks before it drives attributions itself.

What to look out for:

  • If a network shows assisting engagements trending upwards, look up what networks it is assisting. The scenario to look for is that growth in assisting engagements drives install growth for the assisted networks.
    • If this is not the case, you may want to reduce the budget of the assisting network, particularly if the network is assisting itself.
  • Create a report to see in one view the assisting engagement trends in comparison to overall install trends. This can show you whether assisting engagements are leading to more installs, in which case scaling assisting networks makes sense.

See how the line trends: do the number of assisting engagements change incrementally or in sudden jumps? Compare changes with the dates of campaigns you've run, and see if there is any overlap with the numbers of assisting installs.

Assisted install engagement metrics

Use this widget for insight into how users engage with ads prior to install. Judge the impact different networks have by comparing the average number of clicks or impressions they serve to converting users.

What to look out for:

  • A high performing network will show a low number of assisting impressions. This means that they are reaching converting users faster and spending less.
  • Compare the average total assisting engagements, average assisting clicks and average assisting impressions in one view. With this data, you can determine whether to work on lowering your bounce rate, improve targeting, cap impressions further, or scale or downsize budgets.

User paths

This widget provides a visualization of the most common paths in your customer journey. It includes both the assisting engagements and the attributed engagement, grouped by the name of the network generating the engagements. For every path the number of installs is displayed, along with the percentage of the share of the total number of installs.

What to look out for:

  • The order in which the name of the networks are displayed is defined by their timestamp: the closer in time to the moment of the install, the further to the right the name will appear. This means that a network can appear multiple times within the same path, provided assisting engagements of another network were generated in between.
    • No more than four names of assisting networks are displayed. Additional assisting engagements in a specific path are grouped as ‘other’.
  • Hover over an attributed network to see detailed information about that path. The total number of engagements (impressions and clicks) is always equal to the number of installs for that specific path, because installs are only attributed to one unique engagement.

How to use the filters:

Filter for specific assisting networks to ensure you only see paths where your specified network is included. Further filter for a specific position of the assisting network (last assist, second-last assist, etc.), or add multiple filter conditions for multiple assisting networks.

You can also filter for a specific attributed network and display only those paths where the network generated the attributed engagement.

The role of self-assists

A self-assist is when a network provides an assisting engagement for an install they are attributed to. For example, a user who engages with multiple ads on ironSource before installing the app may be attributed to ironSource for both the install and assisting engagements. These engagements are self-assists.

CTV networks rarely self-assist. This is because TV ads appear at the top of the conversion funnel and are rarely the converting engagement for an install. You will also not see self-assists from SANs.

Why are you seeing a lot of self-assists?

It's normal to see that a large number of assisting engagements are self-assisting. If you consider how users are targeted online, it is not uncommon to see the same ad displayed on the same channel to a user multiple times.

Self-assists can be a positive sign. Users who have seen multiple ads before they install an app will:

  • Have greater brand awareness
  • Be better informed about what the app actually does

However, if you see a particularly large number of self-assists, you may need to consider:

  • Over-exposure and brand fatigue

How to recognize and act on self-assists

To see the extent to which a network is self-assisting, use the Assisting engagements by assisting network and Assisted install engagement metrics widgets.

These can help you to define whether a network is creating brand awareness or merely spamming audiences, particularly by looking at the average number of 'engagements per assisted install'.

Be conscious of the attribution window you have set. If you have a 24 hour window set for installs, and you see an average of more than 50 assisting impressions per assisted install, this is a sign that users are being served too many ads.

You can also use the Campaign breakdown for assisted installs widget to check whether there is a mix of campaigns, ad groups and creatives being used. If this is not the case, it's a sign users are being served the same ad over and over again.

Using this analysis, you can decide whether to reduce or increase the budget for a network. Any time you make a change, monitor how this affects the overall performance of that channel. For example, it may go up or down, or you may see that just the level of self-assisting goes down.