Exciting New Product Updates: Extended Permissions, User GeneratedContent Categories, Entrant Demographics, and New Likes and Followers!

Many of our customers already use Wildfire’s analytics features to better understand their audience, but with our updates to our Promotion Builder, we have made it easier than ever to run compelling contests, gather demographic information and track new engagement!

We’ve added three new, exciting features to Promotion Builder: Entry Form Likes and Followers, Entrant Demographics, and User Generated Content Categories.

User Generated Content Categories
With the updates to Promotion Builder, you can now create multiple categories within your user-generated contests, allowing you to run several sub-contests within a larger single contest. For example, if you were running a user-generated photo contest that asked your Fans to submit the cutest picture of their pet, you could create groupings of the photos based on the type of pet. From there, you can apply Promotion Builder’s existing features to your categories; you can apply one of our four winner selection formats and control when and how the users vote for each one.

What does this mean for you and your users? First and foremost, the feature gives you increased flexibility and control over your contest. For example, you can create a gallery featuring the pictures in each category for easy separation and a specified voting process. It also provides your users with additional chances to win the contest, and gives you the chance to further specialize the prizes to increase relevance and value for your consumers.

Check out the Intrepid Sea, Air and Space Museum promotion below for a great example of how a brand used UGC categories to allow more tailored entries to their contest.



Warning! The next two awesome features are only available on our white label product!

Entry Form Likes and Followers

Our platform now allows you to track how many new Likes and Followers your Fanpage and Twitter receive from the Like and Follow buttons in the campaign itself. This means that, in addition to seeing how many Likes you have received since your promotion began (using our Monitor product), you can also see how many of those new Likes came directly from the campaign user interface. (In other words, you’re able to see return on investment in action.) The same works for new Twitter followers and the Twitter integration feature in a campaign. Whenever you run a White Label campaign that includes a Like button on the entry form or Twitter integration, the advanced Like and Follower analytics, respectively, will automatically be included in your campaign analytics. If your campaign includes both an entry form Like button and Twitter integration, both the Like and Follower analytics will be available to you.

This screenshot shows how these data appear within your campaign analytics:



Entrant Demographics

This new feature allows you to gather the age, gender, education, and location data for entrants throughout the lifetime of your campaign. You can have access to our advanced Entrant Demographic analytics simply by running a campaign which asks users for extended Facebook permissions. Unlike Facebook insights for a given application, these demographics show you who has actually entered the promotion; Facebook insights demographics relate to any user who has interacted with the application, which could include users who dropped off and did not enter.

Demographic data will be visible in a given category once your campaign has at least 25 entrants with Facebook profile details in that category. For example, once your campaign has 25 entrants who have defined their location in Facebook, the location demographic data will appear.

This screenshot shows how these data appear within your campaign analytics:



Standard vs. Extended Permissions

Worried that extended permissions will hurt your entries? We have conducted tests on the rate at which users grant permissions when presented with the requests for permission box shown below. In our tests, the grant rate dropped between 1 to 3% when using extended instead of standard permissions, depending on the type of contest format used. As the campaign administrator, you always have the option to use standard permissions if you prefer the more streamlined user experience over the demographic data that extended permissions provide.

These two screenshots show the difference between standard and extended Facebook permissions from a user’s perspective:






Given the very slight drop off in grant rate, we highly recommend that our customers use this extended permissioning to get to know their entrants better.

We’re excited about all the new features that will make your promotions even more effective! If you’ve already used any of these features, tell us what you think.

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How to Use A/B Testing to Maximize your Facebook Advertising ROI

Running Facebook ads can be a great strategy to increase the reach of your brand, and drive traffic to your pages. However, unless you know which ads work well for your demographic, and which ads fall flat, you may be tossing money into the wind. By A/B testing your ads throughout the campaign process, you can determine what works for your users, and what doesn't. In this post, we will explain in an easy way how you can effectively test, measure and optimize your ads (what many call ‘A/B testing’) to ensure that you get maximum results. *This post has been updated from its original publication on the Wildfire blog. 


What is A/B testing and how can it help your Facebook ad performance?A/B testing is the process of comparing two ads against each other, one slightly different than the other, and seeing which one gets the best results then testing the ‘winning’ ad against a new variation and so on until you’ve optimized your ad. So, for example, you might run two ads that have identical copy and targeting but one has a photo of a cupcake and the other has a photo of a burger. You measure which has the best results and find that the burger is the most successful image. Then you test the ad with the burger image against a new variation - perhaps you test another image to see if it beats the burger image or you keep the burger constant in both variations of your ad and you instead try adding different copy to your ad to see what works best. You keep testing ads against each other in this way until you find the optimal combination of images, text and audience targeting for your ad. Anyone can do this—you don’t need to be an expert to optimize your ad.

[caption id="attachment_1190" align="aligncenter" width="351" caption="Which ad will perform better? A/B Testing is one way to find out, accurately."][/caption]

How do you use A/B testing to increase the performance of your Facebook ads?

Step # 1: First decide what you are going to measure to determine success

Before running two variations of an ad to determine which is more successful, you first have to decide how you’ll measure success. Below are a few possible success questions:Is the winning ad the one that:

• gets the most clicks?


• leads to the most fans?


• produces most signups?


• yields the most coupon redemptions?

Common practice is to measure and optimize for click-thru rate but you should be aware that this isn't necessarily the best metric for your business. For example, you may have created an advertisement that is great at getting people to click, but terrible at getting people to complete your sign-up form, become a fan or browse your website. In other words, your click-through rate is high but your conversion rate is low.  Cost Per Acquisition (CPA) takes both the click through rate and conversion rate into account, so it's generally the strongest indicator of advertising success.

CPA Example 1: If your goal is to generate fans, you could measure the effectiveness of each of your ads in terms of generating fans.

CPA Example 2: If your goal is to generate email address, measure the cost per email address acquired by each version of your ad.

CPA Example 3: Of course the most powerful measurement would be the number of sales that each ad generates for your business, but realize that for most businesses there may be a delay of many weeks or months between when someone clicks on your ad and when they buy your product so you’d need to wait too long to test which of your ad variations is most successful in terms of sales.

The idea of A/B testing is that you test, measure and learn quickly, and not wait months to get results.

Hot Tip! Sometimes it may actually make sense to optimize your ad so that people do NOT click on it. This might seem odd, but you can actually remind users about your brand and pay very little in return because ultimately you only pay if someone clicks on your Facebook ad. So, for example, you may want to run ads for your existing fans to wish them a ‘Happy Holiday’. This will generate very different results from an ad that contains an explicit call-to-action (e.g. click here to get a free Holiday coupon) but if your goal is branding discouraging clicks can be highly cost effective.

Hot Tip! Wildfire recently launched conversion tracking in our new analytics dashboard (see “NEW PRODUCT: Real-Time Campaign Analytics” for more details) which enables you to run different ads to your Wildfire promotion and track how well they are converting in terms of the leads they generate.

Step # 2: Choose a control for your experiment

The next step in your process is to create your ‘control’ ad. This is the starting ad against which you will test new variations of this ad in order to see if you can improve its performance. So start out with whatever you think will be the most effective image, copy and targeting for your ad - this will be your ‘control’ ad. Don’t worry if you’re not sure - the great thing about A/B testing is that you start with your best guess and then you use measurement and testing to turn your best ‘guess’ into an ad that’s proven through measurement.

Hot tip! For inspiration for your ‘control’ ad try looking at the ads of other companies that are known to successfully use Facebook ads (e.g. Groupon, Zynga, Living Social). You should also read our post about successful ads,  “18 Super Easy, Highly Effective Tips to Grow your Fans via Facebook Ads.”

Step # 3: Now create your ‘test’ ad by changing a single element.

Now that you have your control ad, its time to create ads to test against. When creating new ads for testing change only one element in each new ad. If you change more than one element (e.g. the image and the text) when you measure the results you won’t know if the change in performance is due to the new image or the new text.

Example for test ad #1: You might work on optimizing your ad image first by creating several new ads in which you try a new image for your ad but keep the description and title the same.

Example for text ad #2: For the next set, keep the image and description the same but change the title in each ad.

Example for test ad #3: Finally test different descriptions, each with the same title and image.

You may also test the target audience for the ad by keeping the ad exactly the same but targeting different kinds of viewers e.g. 20-30 year old women versus 30-40 year old women (the Facebook ads tool provides you with this targeting feature). Altogether it’s not unusual to run through approximately 20-30 variations of your ad for one ad campaign.

Hot tip! Unlike A/B testing for Google ads, where titles and descriptions are extremely important, on Facebook graphics trump both of these characteristics. Spend more time testing different image variations, followed by title, and then, if time and budget permit, test your ad description.

Step # 4: Test a large number of images

When doing your image tests, focus on quantity - we’d recommend testing 5 images at a minimum, but testing 20 images is preferred. If you test many images you may find that several of them work well - which will provide you with a great base of images for your future ad campaigns. For some very effective tips and tricks about exactly what types of images to try, check out our previous blog post with “18 Super Easy, Highly Effective Tips to Grow your Fans via Facebook Ads.”

Hot tip! When testing images try to form a hypothesis about which ones will ‘win’ rather than simply waiting for the data to find the winner. This will help you to learn why one image is better than another, thus enabling you to become more and more adept at choosing appropriate images in the future.

Step # 5: Use A/B testing to identify the appropriate target audience

Facebook ads have very powerful targeting features. You can control which users see your ads based on very specific guidelines, such as age, gender, geographic location and even interests. Use A/B testing to identify what kind of audience is most receptive to your ads by displaying identical ads to users with different demographics or interests.

Example for targeting: You might try displaying your ad to American women aged 25-35 years who indicate they are married and then to American women aged 25-35 years who indicate they are unmarried. This will help you to determine if your ads resonate best with married or unmarried women. You might then wish to further refine your audience by running the ads for American married women aged 25-35 years who indicate ‘cooking’ as an interest versus those who don’t.

Step # 6: Run all the versions of your ad simultaneously

When you are testing different variations of an ad be sure to run them at the same time. If you run them at different times you won’t know if the reason for the different performance of the ads is the changes you made to the ad itself or differences relating to the timing of the ads. For example, if you’re testing two images and you run one on Friday and the other on Sunday, the Sunday ad might perform better because of the image or perhaps just because people have more time to click on ads on Sundays because they are not at work. Unless you run the ads simultaneously you won’t be able to isolate the true cause of performance differences.

Step # 7: Run your ads long enough to reach statistical significance

Be sure to run your ads so that they get enough clicks for your results to be statistically significant. You may find, for example, that in the early stages of your test one ad gets twice as many clicks as the other but if the number of clicks is very low (e.g. 10 clicks for ad A versus 5 clicks for ad B) you simply don’t have enough data to be sure that Ad A is performing better than Ad B. As a general rule of thumb, make sure you have at least 100 clicks for each ad.  Once you’ve run your ads long enough then pause the less effective ads and push your budget towards the successful ads, versus running the “losers” for longer and wasting your budget.

Step # 8: How to use Facebook’s ad tool for A/B testing

To run your A/B tests using the suggestions provided in this blog post, the following steps are necessary:

Part 1: Use the "Create a Similar Ad" feature in Facebook’s ad set-up wizard. This will enable you to quickly duplicate your ad in order to test small changes to it.

Part 2: In order to ensure your ads get displayed by Facebook an equal number of times (which is critical if you are to run an accurate test), you have to create a separate ‘campaign’ for each ad variation. This is because when multiple ads are running within a single campaign, Facebook's system will allocate more of your daily budget to higher performing ads, and often ads that are added after the first two or three do not get run at all, which makes them useless from the point of view of A/B testing.

Step # 9: Don’t always assume that Facebook’s ‘suggested bid’ is the best

When setting up an ad Facebook will ask how much you are willing to pay per click for each ad.  You’ll notice Facebook offers a suggested bid but you should take this suggestion with a grain of salt.  You’ll notice in the image above, which is a real campaign, the suggested bid is between $1.06-2.03, yet we bid $0.65 and get a good amount of traffic. In other words, we pay almost half of what Facebook suggests and get good results. The point is - start low and then move your bids up until you start to get traffic. You might have to increase your bids as high as the suggested range, or even above. But it depends on many factors, so don’t be afraid to play around with bids until you get traffic at a decent price.  Be aware, however, that the more granular you get with your targeting, the more expensive your ads tend to be, i.e. you’ll pay more if your ad targets a very specific demographic (e.g. 30 year old women from California who are married) versus a broad demograhic (e.g. women from the United States).

Step # 10: Evaluate and improve upon your results

For each round of tests you run going forward, make the winner the new “control.” This way, your control ads will keep evolving with each ad campaign effort you undertake, and your ad strategies can continue to be refined over time.When you’re evaluating the results for the campaigns you run, remember to pause all ad variations that are producing a high Cost Per Acquisition or Cost Per Entry (i.e. if you are running a promotion). These campaigns are clearly not cost effective so you’ll want to save your precious ad budget for those that are and switch of your expensive ads as soon as you can.

Hot tip! Be aware that certain times of the year will be more competitive when it comes to running ads and thus more expensive. For example, around the holidays lots of companies are wanting to advertise their products so you may find that the cost of your ads increases. You should take this into account when you evaluate your campaign success during the holidays.

Step # 11: The most important lesson of all!

Lather, rinse, and repeat! There is no such thing as a perfect ad (at least, a perfect ad that you can run over and over, for any campaign or any purpose.) In our experience, by the time you’ve narrowed down a successful ad from your tester group of 30, you can run it for a few days or weeks (depending on how narrow your audience is) until it falls out of vogue. Call the Facebook audience fickle, picky, or quickly disinterested, but successful brand ad campaigns are those that evolve continuously. Logically, this makes sense. Once you have found the winning image, title, copy, and targeting info that’s generating you all the attention (with clicks and entries), you won’t be able to keep running it successfully because you’re basically showing it to the same people over and over again and once someone has clicked on your ad once they are unlikely to do it again unless you show them a new ad. So for better or for worse, you’ll need to keep developing new ads (and using our A/B testing techniques to enhance them) if you want to continue running successful ads on Facebook.

We hope the advice is helpful to make your ads perform better. Use the comments box below to provide us with your own advice and feedback!

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