How to make Twitter objective-based advertising work

Twitter recently announced that it was making objective-based advertising available to everyone. These new campaigns ensure that you pay only for the specific result you’re aiming for:

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On the surface, this seems like an excellent deal for advertisers. You pay only for what you want to buy. The question is, are these things you want to buy?

The answer depends on understanding what your objective is. If you haven’t already mapped out your social media funnel then it’s unlikely you’ve got a solid handle on what to buy:

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Before you spend a dollar on any kind of social media advertising, understand what you’re buying.

You’ll need to invest serious time digging around your analytics to find what’s working least well so you understand what to buy. For example, inside Twitter’s analytics, people following you and the reach of your tweets would be metrics that fall in audience. Favorites and replies would be engagement, as would media engagements. URL clicks might be actions. What’s most broken for you?

Which of these areas is your greatest problem in?

If you try to skip the entire top of the funnel by buying leads, you might find yourself disappointed with the outcome. Likewise, if you don’t engage or drive people towards the bottom of the social funnel in any way, you might spend a lot on growing your following but not produce a business outcome.

Buy first what’s broken most!


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Inferred impressions

Newgate Lane

“You never get a second chance to make a first impression” is a time-honored cliche. Yet we also hear not to judge a book by its cover, that beauty is more than skin deep, and a variety of other cliches advising against snap judgement. What’s a marketer to do?

Impactful first impressions are inferred impressions; what you take away from an interaction creates an inference for subsequent interactions.

For example, if you’re a hotel and your lobby is unclean, the inferred impression is the rest of the hotel is unclean.

If your sales staff is surly before the sale, imagine what customer service will be like after the sale.

First impressions containing non-relevant data won’t create much of an inference. A restaurant’s poor graphic design on its menu doesn’t create an inference about the quality of its food or the service. After all, graphic designers are not cooking your food.

A business that delivers freight and cargo won’t be affected much by a driver’s wrinkled uniform. In fact, a slightly shabby looking driver might create a mild positive inference that the person is working so hard, he’s not had time to do laundry.

Wells Fargo bank made a huge splash in the bank marketing world years ago when they eschewed the expansive lobbies and giant buildings in favor of normal, average offices. Why did they make such a bold leap? The quality of the decor had little to do with the services they provided.

When contemplating what first impressions you’re creating, consider whether they create an inference about the product or service you deliver. Worry about it only if it creates an inference which runs contrary to the promise of what you serve your customers.


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Use Big Data Remarketing in Google AdWords and Analytics

Here’s a tip about a powerful, under-rated Google Analytics feature, “You’re bad at Big Data”, aka Smart Remarketing lists. Google rolled out this feature to all Google Analytics accounts last year. Smart Remarketing Lists attempts to process massive amounts of conversion data and identify those visitors to your website who are most likely to convert if you were to remarket to them.

This option, relatively unpublicized, is an interesting twist, especially for smaller businesses who don’t have dedicated PPC and Google Analytics analysts to crunch big data for them about massive conversions. That said, I wouldn’t leave this solely in Google’s hands, since there’s limited flexibility to the tool. Instead, what you’ll likely want to do is A/B test your ad spend for a little while.

Here’s where to find it, in the Admin section of the application:

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When you go to create a new audience, it’s one of the options:

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Simply pick how long of an observation window you want. This should be mapped to your sales cycle, ideally.

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Once you’ve got your lists set up, head over to AdWords and start building out your ad campaigns. I recommend you run 2 parallel campaigns with equal budgets, ads, and keywords for both campaigns so that you have a completely fair A/B test and see which performs better, a hand-built list or Smart Remarketing List. Remember that in order for the best outcome, you’ll need to link your AdWords account to your Google Analytics account and have goals and goal values already defined.

Try this feature out and see if it works for your business!


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