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How to Quantify the Value of your Facebook Fans

Facebook_Fan_Value
Are your Facebook fans really buying your products? This question has plagued Facebook, brands and marketers for the last few years but now there is an easy way to find out. This post will show you how to calculate the percentage of your fans who have bought your products, and how much more or less likely they are to purchase than the average Facebook user.

What percentage of your fans have bought your products, and how much more or less likely they are to purchase than the average Facebook user.

Before diving in, please note that Nanigans is not in the business of buying fans. We focus on building best in class technology that helps marketers achieve ROI goals; however it’s very useful to measure the quality of a fan base as it can be leveraged in performance marketing campaigns.

We start with your CRM database. Slice and dice this as you like to pull together a list of email addresses, telephone numbers or Facebook IDs–if you have them–which represent a list of your customers. This list can be as simple as all customers who’ve purchased in the last six months. Or it can be more advanced by breaking out customers based on criteria such as time, value, quantity, type of product and/or geography.

  • Time: When did these users buy or register?
  • Value: How much money did they spend?
  • Quantity: How many purchases did they make?
  • Product Category: What type of product did they buy?
  • Geography: Where do they live?

Once you have your customer list together, you can use Nanigans’ Ad Engine or Facebook’s Power Editor to upload the list and create what’s called a custom audience. This is a secure and anonymous matching process that finds your list of customers on Facebook in order to make them available for targeting when running Facebook ad campaigns. Expect a match rate between 40% and 85% depending on the quality of your list.

Custom Audiences
Now for the interesting part. Because your list of customers is available for targeting as a custom audience, Facebook will tell us the reach of these users. We can then layer in targeting to your fans to see the reach within your fan base, and thus the approximate customer penetration among your fans, as well as how this compares to the population at large.

Let’s assume the reach of your custom audience is 100K and it has a 50% match rate (i.e. your initial list had 200K users). When we layer on fan targeting, this reach drops to 5K, or an assumed 10K given our 50% match rate. If your fan base is 500K strong we can simply divide 10K/500K to identify the penetration of purchasing users among your fans is 2%.

So how does this compare to the average user? In other words, what is the likelihood of a fan being a purchasing user compared to the average person on Facebook? To do this, we need to find the reach of additional groups of users:

          A. Reach of the total Facebook population in your target demo (e.g.15M)

          B. Reach of all fans in your target demo (e.g. 500K)

          C. Reach of your custom audience within your fans in your target demo (e.g. 10K)

          D. Reach of your custom audience within the total Facebook population in your target demo (e.g. 200K)

As noted before, we can see the penetration of purchasing users among fans by using C/B. We can now also find the penetration of purchasing users among all FB users by using D/A.

To calculate the probability of a fan being a purchasing user compared to the average Facebook user, we can use (C/B) / (D/A). Using the examples above this gives us (10K/500K) / (200K/15M) = 1.5. In other words, based on the example reach data above a fan is 50% more likely to be a purchasing user than the average person.

To be clear, this doesn’t answer the question of whether fans convert to purchasers, or whether purchasers are simply more likely to be fans. Instead what we get is a measure of the quality of a fan base. For one large eCommerce client, for example, we saw almost no correlation between young males being fans and buyers, however we saw a very strong correlation for older females. In this case the client likely purchased a number of young male fans who never converted to purchasers.

To be clear, this doesn’t answer the question of whether fans convert to purchasers, or whether purchasers are simply more likely to be fans. Instead what we get is a measure of the quality of a fan base.

So how can you leverage what you’ve learned about your fans? I’ll be following up with a post on leveraging these insights in your marketing campaigns, as well as how to use custom audiences for performance focused remarketing and acquisition campaigns, including on mobile.

As always, if you are revenue focused and interested in working with us please reach out to websales@nanigans.com.

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