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Integrating with Fairing (formerly EnquireLabs)
Integrating with Fairing (formerly EnquireLabs)

How to connect to Fairing (formerly EnquireLabs) and structure your questions within.

Maggie avatar
Written by Maggie
Updated over a week ago


Fairing is a post-purchase survey app that helps stores gather feedback from their customers immediately following purchase. For our purposes, the primary question asked in this survey is about what led them to puchase.

Because are some cases where not all customer journeys will be tracked, it is beneficial to supplement first-party tracking data with zero-party customer feedback data. Here are some examples where the additional customer feedback can be helpful in assigning attribution:

  1. If you have not added Triple Whale's UTM Tracking Parameters to the specific ad the customer clicked;

  2. If the customer in question never clicked on an ad at all (but merely viewed one);

  3. If a customer saw an ad on a friend's device before purchasing on their own device.

In these cases and more, our integration with Fairing will help shed attribution light on what led these customers to purchase. Let's dive in!

Integrating with Fairing

On your dashboard, go to the Gear button at the bottom lefthand side of your dashboard and then to Integrations, from here click: Connect to Fairing

Generate a token, copy it, and click Save:

Next, connect to Triple Whale from within Fairing:

Paste the token from Triple Whale into Fairing:

Next, in Fairing, navigate to "Account", then scroll down to the API Credentials section.

Click the eyeball icon to unhide your "Secret Token" and copy that token.

Navigate back to Triple Whale and paste your Token in the "API Key" field.

Click Save, and then you're good to go!

Structuring Your Questions in Fairing

When a customer doesn't click on your ad but makes a purchase, you're left questioning where that customer came from. By creating a survey in Fairing, you will hear from the customer and how they came about making their purchase decision.

Here's an example:

One more thing... How did you hear about us?

You can then choose the answers based on the marketing channels you run ads through... Facebook, TikTok, Snapchat, Pinterest, Instagram, Google, etc.

We know that you can ask many questions via Fairing, but we're specifically looking for the question that includes the following text(s):

  • hear about

  • heard about

  • find out about

  • led you to purchase

  • platform brought you to

Supported Languages

We currently support this question in the following languages:

  1. English

  2. Spanish (examples below)

    1. Dónde escuchaste por primera vez de nosotros?

    2. Dónde escuchaste por primera vez de nosotras?

    3. Como te enteraste de nosotros?

    4. Como te enteraste de nosotras?

    5. Every question that contains the verb 'escucha' or 'enteraste' + de nosotr(*)

  3. German (examples below)

    1. Woher haben Sie von uns gehört?

    2. Wo haben sie zum ersten mal von uns gehört?

    3. Woher hast du von uns erfahren?

    4. Wo haben Sie zum ersten Mal von uns hören?

    5. Every question that contains 'von uns' + verb 'gehört/hören/erfahren' (and alike)

  4. French

    1. Où avez-vous entendu parler de nous pour la première fois?

    2. Où avez vous entendu parler de nous?

    3. Comment avez-vous entendu parler de nous?

    4. Comment avez-vous entendu parler de nous pour la première fois?

    5. Every question that contains the verb 'entend(*)' + 'parler de nous'

Where You Will See Fairing in Triple Whale

Once you get everything set up within Fairing, you will see it pulled into your Triple Whale dashboard on your Summary Page and it will tell you the percentage of customers coming from each marketing platform

How Triple Whale calculates % per response and % of responses:

To demonstrate how we calculate the percent per response type, let's use the following example:

Let's say your store had 20 orders today and your survey had 7 responses that were represented as follows:

  • Facebook: 2 = 28.5%

  • Google: 1 = 14.29%

  • Instagram: 2 = 25.57%

  • Other: 2 = Not Represented in summary page (*Important: In Triple Whale's summary page, any survey response that isn't Facebook, Instagram, Google, Snapchat, TikTok, Pinterest are considered as "Other")

To calculate the % response from Fairing, we divide the number of survey responses you received (7) divided by your stores total number of orders (20), which is 35%.


Fairing responses will also be used to improve your channel attribution. If a customer's response differs from what our pixel captured from clicks, we will attribute their order to the channel represented in their survey response.

Currently, Triple Whale supports the following response types for reporting on the summary page and Pixel.


Mapped Channel (in Triple Whale)















Customer Journey Examples

Here are some customer journey examples to help you interpret the Fairing data you will see in your Pixel table:

  1. Triple Pixel has attributed an order to Facebook via a link click from your Facebook ad AND the customer’s survey response = Facebook

    1. Triple Pixel will display the single order and its corresponding conversion value in the pixel table, under the Facebook channel

  2. Triple Pixel has attributed an order to Facebook via a link click from your Facebook ad AND the customer’s survey response = TikTok

    1. Using attribution model = Triple Attribution, this single order, and its corresponding conversion value will be displayed under the Facebook channel AND the TikTok channel within the Fairing Survey row in your Pixel table

  3. Triple Pixel does not have any click data on the customer who placed the order, BUT the customer’s survey response = Facebook.

    1. We will display the order count and conversion value within the Facebook channel of your pixel dashboard under the “Fairing Survey” row

*NOTE: Make sure the selected Attribution Model is Triple Attribution or Total Impact.

Questions? Reach out to our Customer Success team and they will be happy to assist you!

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