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Facebook Targeting Suggested Strategies and Examples
Facebook Targeting Suggested Strategies and Examples

Learn more about some of Bluecore's recommended strategies to use our audiences within Facebook to retarget your users.

Updated over a week ago

After you’ve completed your Facebook integration and started syncing audiences from Bluecore to Facebook, the next step is to take the information that’s now available in Facebook and target your users, or users that are similar to your best users within Facebook.

To create Audiences similar to yours for prospecting, use Facebook’s Lookalike Audiences.

Facebook Lookalike audiences enable marketers to generate a list of net new customers to target and acquire with prospecting campaigns.

Target one audience per ad set. Facebook’s most granular reporting is at the ad set-level, so if you target more than one audience against one ad set, you will have no way to know how well each audience is performing.

Use multiple ads/creatives for each ad set. We’ve seen wide ranging results depending on the creative, so it’s worth including more options when possible.


The following use cases are by not comprehensive of all the campaigns Bluecore can power on Facebook. The below examples focus on Bluecore’s Predictive Audience capabilities, but you can experiment with our Customer Behavior filter too. These use cases are meant to highlight some of the more interesting options and also to point out some suggested strategies, so you can get the most out of Bluecore Audiences on Facebook.

  • NOTE: Category Preference and Predicted Customer Lifetime Value (PCLV) are Predictive Audiences. Predictive Audiences is an advanced feature. Please contact your CSM if you do not see this enabled in your account. 


Good Facebook campaigns are built around Category Preference. It’s great for campaigns targeting a specific product, brand, category, or breadcrumb. For example, a new product launch, a promotion on a specific brand, or an event around a category. It’s a much better option than using past purchasers or past viewers to decide how to target. See Category Preference in the Predictive Audiences Overview for more information.

Suggested Strategies:

  • Do not use this same audience as a source for a Facebook Lookalike audience. Be sure to read the Lookalikes section below for best practices on this audience type.

  • The creative of your Facebook campaign should match the attribute value you chose to create the audience (e.g., the specific brand, category, etc.).

  • Depending on the type of category, consider whether to include or exclude past purchasers. Past purchasers will be included in the Category Preference audience by default, as they will likely have very high preferences for the attribute you used as an input. However, if you are looking for existing contacts that have an preference for a product or category that is rarely purchased more than once, like a refrigerator or a mattress, you should consider excluding past purchasers from the audience to avoid targeting them with your Facebook campaign. Exclude past purchasers by using the Customer Behaviors filter within the Audience Builder.

  • If you find your campaign is performing very well, consider lowering the level of preference to broaden the audience and increase the reach of the campaign. If your campaign is not performing as well as you would like, you should raise the level of preference and/or consider layering in the Predictive CLV filter to remove low CLV contacts from the audience. See CLV suggested strategies below for more detail.


PCLV can be used to divide Facebook targeting across your entire customer list. For example, events, sales, or promoting products and categories you know will appeal to your entire customer list. By splitting up your customer list, budget and bidding can be optimized to improve ROI on your campaigns. For example, a discovery on a low ROI on Low Predicted CLV audience may allow you to boost overall campaign ROI by over 50% by shifting budget into higher Predicted CLV audiences.

See Predicted Customer Lifetime Value in the Predictive Audiences Overview for more information.

Suggested Strategies: 

  • Try dividing Predicted CLV into thirds – high (top 33%), medium (between 33% and 67%), and low (bottom 33%), plus a fourth audience for unknown PCLV contracts. These four groups encompass your entire customer list.

  • For a campaign targeting your entire customer list, create four identical ad sets for the campaign, and target each ad set against one of the four CLV audiences.

  • Be sure to include unknown PCLV in your campaigns, as we’ve found the performance to be higher on this group than the Low PCLV folks in many instances.


Facebook Lookalike Audiences take a source audience to find similar customers on their network, based on interests, demographics, and many other data points. Use a Bluecore audience as a source for an especially powerful Facebook Lookalike Audience.

The Bluecore audience you use as a source for the lookalike audience depends on the purpose of the campaign. If it’s a general branding campaign, you should focus on creating a source audience from your most valuable customers - your top 20% of PCLV. If it’s a prospecting campaign around a specific product, brand, or category you carry, you should still use PCLV, but also use category preference and set the preference level to high or very high to get a small but focused group of customers.

Suggested Strategies:

  • Facebook doesn’t provide guidance on the optimal size of a source audience, other than to say it must be at least 100 people from a single country, and that a larger audience provides more opportunities to find similarities amongst the group. We’ve found good success with source audiences between 1,000-5,000 customers - there’s not much reason to go much larger than that.

  • Do not target this audience for any Facebook campaigns as it will be too small - only use this to source a Lookalike audience. If you want to target your actual customer list, see the category preference section above.


Automatically target recent purchasers with products they are likely to buy in addition to what they already bought. To create this audience, choose a preference to a specific category you think will be a good cross-sell option in general (e.g., speakers).

Create an Audience of customers who have made a purchase in the last seven days who have NOT bought speakers in the last seven days but who have a high or very high preference to speakers. This is a group of customers that bought something other than Speakers, but have demonstrated a strong interest in speakers. Create a campaign with speakers creative to target against this audience.


Target a winback or reactivation offer to customers that have become at-risk in the last seven days. Reactivate them before they become Lost customers.

Suggested strategies here would be to include some reason for the customer to reactivate, such as a special discount just for them or free shipping. You can make a few adjustments to improve performance here as well, such as layering in the PCLV filter to remove low value customers, as well as layering in category affinity to show creative based on a customer’s personal product preferences.

Separate your discount buyers from your full price buyers. There are different options of how to use this segmentation. For example, offer different discounts to the two groups using promo codes within the ad creative or copy. Alternatively, if you’re doing a site-wide promotion, you could do a pre-sale event for full price buyers, and then exclude any recent purchasers when you promote the sale event to the whole customer base.

See Discount Preference in the Predictive Audiences Overview for more information.

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