{"id":1665,"date":"2016-08-15T14:11:39","date_gmt":"2016-08-15T14:11:39","guid":{"rendered":"https:\/\/www.searchenginewatch.com\/2016\/08\/15\/facebooks-lookalike-audiences-for-ecommerce-segment-before-you-build\/"},"modified":"2020-01-14T03:04:56","modified_gmt":"2020-01-14T03:04:56","slug":"facebooks-lookalike-audiences-for-ecommerce-segment-before-you-build","status":"publish","type":"post","link":"https:\/\/searchenginewatch.com\/2016\/08\/15\/facebooks-lookalike-audiences-for-ecommerce-segment-before-you-build\/","title":{"rendered":"Facebook\u2019s Lookalike Audiences for ecommerce: segment before you build"},"content":{"rendered":"

One of the most efficient types of targeting in Facebook<\/a> (second to retargeting, of course) is lookalike audience targeting. <\/strong><\/p>\n

Lookalike targeting is basically a targeting type that allows you to use first\u00a0party data (e.g. customer lists, remarketing lists, etc.) as a seed audience to find new users<\/a> with very similar characteristics, behaviors, and traits.<\/p>\n

It\u2019s applicable for all business models (B2B, B2C, EDU, etc.), but in this post, we\u2019ll lock in on best practices for ecommerce<\/a>.<\/p>\n

When using lookalike targeting, the audience you select as your seed audience is extremely important. Essentially, you want to make sure you are developing audience lists from\u00a0your best-performing audience.<\/p>\n

For example, if you had an option to choose between people who signed up for a free trial of your product or people who actually purchased your product, you should start off with the audience that has actually purchased the product; these are the users driving revenue to your business, and you need to find more users like those.<\/p>\n

Okay so now that we know we want to target our customers, are we ready to get started and build lookalike audiences? Nope! Hang tight, especially if you have a large customer base.<\/p>\n

\"lookalike<\/p>\n

Step 1: Create smart segments<\/h2>\n

If you\u2019ve got a ton of user data to pull from, use it to segment your base into groups with definable characteristics. This helps you tailor creative, messaging, and bidding with far more precision.<\/p>\n

When it comes to ecommerce<\/a>, there are three fundamentals ways you should look to segment your users:<\/p>\n

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  1. Average Order Value (AOV):<\/strong> Say you sell a variety of different products, from high-end\/expensive items to affordable accessories. Segmenting out your 1st<\/sup>-party data by AOV allows you to better understand the audiences who can afford to go after your more expensive product vs. those who are looking for a bargain.<\/li>\n
  2. Product Category:<\/strong> If you sell multiple different types of products, you\u2019ll want to split out your customers by the product categories they have purchased (e.g. women\u2019s handbags, women\u2019s apparel, etc.). This allows us to better tailor content when running our ads.<\/li>\n
  3. Lifetime Value (LTV):<\/strong> Segmenting audiences by LTV helps you create audiences of users who will most likely be repeat purchasers\/loyal customers vs. those who will tend to just buy a few items for their more immediate Separating the two groups will allow you to bid accordingly as you see performance kick in.<\/li>\n<\/ol>\n

    Step 2: Build your lookalikes<\/h2>\n

    So now it’s time to build out your lookalike audiences, which range from 1% – 10%. What this means is that the 1% are audiences closest in similarities, traits, and behaviors as your seed audience, and it contains only those users, which restricts scale. The 10% audience is the least similar \u2013 but it\u2019s also the biggest pool.<\/p>\n

    The way you\u2019ll want to set up your campaign is by building ad sets for each segment. So let\u2019s say you chose to segment your first\u00a0party data by AOV; your setup would look like this:<\/p>\n