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Facebook Ads | How to use the export function to find targeting info

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“Hey John can you send me a spreadsheet with all the facebook ads we’ve performed this year and the targeting for each of them?”

“Sure thing. You mean the targeting for each ad set, not for each ad, right?”

“No, I want the targeting for each ad.”

Most of those who have worked in agencies and handle multinational clients have at some point put down the phone in cold sweat at the sound of a similar request. The problem with it is that targeting on Facebook is set at an ad set level and not at the creative (ad) level. A campaign might have several ad sets, each one of which might contain tens of ads. Multiply this with tens of campaigns each one containing tens of ad sets over a long period of time and you should get the point why a request like that can leave you in terror.

Unless, that is, you happen to know the method that you can use to actually see the targeting at the advert level.  

Finding the targeting at the advert level is not the easiest thing in the world and requires a bit of Microsoft Excel skills (nothing dreadful) but it will help you keep your sanity at a time when that didn’t seem like the most probable scenario.

Let’s dive into how you can see the targeting which was applied for each ad without any third party Facebook ads programs or excel add-ins.


The first thing you need to do is to select the ads you want to examine

Let’s say that you need the targeting for each different ad in the current year. Go to the advert level of Facebook Ads Manager, select 2018 in the time range and under filters select “Had Delivery”. Select all the ads, choose the icon “Export & Import” and then select “Export Selected”. You might need to export more than one batch as you’ll see that there’s a limit of ads you can export each time. If you need to export ads more than once, add the ads of the second/third export in the same spreadsheet as the first one omitting the headers (and keeping the headers of the first export).

This spreadsheet includes every single piece of useful and useless information about each ad. The name of the associated campaign, the campaign id, ad set id, tags, product catalogue id, optimization goal, attribution spec, creative type, video id, image hash and tens of other -mainly useless- parameters. Among this useless information however, there are parameters which, if read correctly, will give you the coveted answers your client needs in no time at all.

The columns you should be looking for are:

  •        Custom Audiences
  •        Excluded Custom Audiences
  •        Flexible Inclusions
  •        Flexible Exclusions
  •        Targeting Optimization
  •        Product Audience Specs
  •        Excluded Product Audience Specs
  •        Targeted Business Locations
  •        Publisher Platforms
  •        Facebook Positions
  •        Instagram Positions
  •        Audience Network Positions
  •        Messenger Positions
  •        Device Platforms
  •        User Device
  •        Excluded User Device
  •        User Operating System
  •        User OS Version
  •        Wireless Carrier
  •        Excluded Publisher Categories

If you know where to look you’re halfway there already. It only takes some editing to make the information legible otherwise your client will need to decipher the information you’ll provide and -generally speaking- that’s not something you want a client doing.


Let’s start editing the spreadsheet to make it eligible

Let’s say that you have some ads in ad sets with custom audiences, other ads in ad sets with interest targeting and other ads in ad sets with connection targeting. 

Starting from the custom audience column you will need to make entries like “25842997132774299:Add to Cart (30)” to something like “Added Item to Cart in the Past 30 Days”. “Find and Replace” is your friend. Select the column, “Find”  “25842997132774299:Add to Cart (30)” and “Replace” with “Added Item to Cart in the Past 30 Days”. Repeat with all the values in this column. It shouldn’t take more than a couple of minutes.

Then let’s check the column for interest-based targeting. That one should be named “flexible inclusions”.

Here, you will see something like

[{“interests”:[{“id”:”6002839660079″,”name”:”Cosmetics”}….. }

for each interest. Again, presenting the client with Facebook ids is not something you should be aiming for. Fixing the names should be easy. As we did before, we select the column and turn to “Find and

Replace”. We “Find”

{“id”:”*”

and “Replace” it with nothing.

Repeat by replacing

name

behaviors

{

}

[

]

:

with nothing and by replacing

,,

with

,

and you should have a perfect column.

That leaves us with “connections” targeting. In this column all you have to do is replace the ID of your page with something like “fans” and you’re ready.

You’re almost set; you just need to combine the cells which pertain to targeting to get perfectly legible information. Do not merge and center. Use the formula

=A1&” “&B1&” “&C1&…

in the row of the first ad (usually doing this in the last column is a good idea) and then drag the formula to the rest of the ads. Then copy and paste the formula as values.

We’re almost there. The client needed a list of all ads with the respective targeting. We saw that by selecting and exporting the ads we can find information about the targeting parameters of each ad but we haven’t talked about getting the links of the ads. This kind of information is in the same spreadsheet.

You will see a column named “preview link” which will give you a demo of each ad. My recommendation though would be to use the “Permalink” column for Facebook and “Instagram Preview Link” for Instagram. Permalink requires having access to the Facebook page to open the link but in all likelihood, you are providing these data to your client so they should have access to their page.

Combining these two facets, links of the ads (no links for Instagram Stories I’m afraid) and targeting, you have a list of each ad (name and link) and its targeting.


Other Applications

Exporting the ads gives tremendous amount of information. There is however one crucial piece of information which we lack. The actual amount spent (either on ad set level or on ad level). The only thing close we have on the export is “Ad Set Lifetime (or Daily) Budget” which shows how much money was assigned to the ad set had and not how much the ad set actually spent. If you’re running conversion campaigns, you will see that the ad set often does not spend your entire budget with the parameters you have set. That applies of course to all campaign types but it is particularly evident in conversion campaigns.

What you can do in this case to find the budget that was actually spent for each ad set is to download from Ads Manager a report containing the ad set ID and the “Amount spent” metric. Using VLookup you can add the metric “Amount Spent” from the spreadsheet with the actual budget to the spreadsheet with the exported entries.

PPC hubbub - LightbulbNote: In all likelihood you will have to deal with duplicate Ad Set IDs so it might be best to check first how to use VLookup with duplicate values if that’s something that isn’t in your daily toolbox.

If you also have information on the actual investment all kind of analyses are possible. You can delve into how much you have invested per creative type, per visual (image/video), per custom audiences’ and interests’ clusters, buying type and anything else you can think off.


In conclusion, learning how to export and how to utilize the data you will get is a useful skill to have. Not only will it get you out of tough situations like providing targeting criteria on ad level but you can use when a broader and more strategic view is required if you manage multiple campaigns and are asked to provide analyses, insights and recommendations based on past performance frequently.  

Chris Palamidis

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