How to handle differing digital marketing audiences

If you didn’t hear about it, Twitter recently released its own version of Audience Insights. I wrote up a lengthy review of it here that you might find helpful for understanding what’s in the box.

What’s not in the box is the last paragraph, which is about differing audiences. What do you do when your Twitter audience looks radically different from your Facebook audience? What about when your Facebook audience looks different than your Google Analytics-assessed audience. How do you interpret that data?

For example, here are the interests Twitter says my followers have:

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And for comparison, here are the interests Google Analytics says my website visitors have:

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How do you reconcile these? The only thing they obviously have in common is the technology/technophile interest and general business interest. The answer is to think about them like Venn diagrams:

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Let’s start with the most important audience. Audience 3 is the vital one, the topics that both have in common. I’d play to those topics more because I know that both audiences will find them valuable. These topics would be the anchors, the hero or hub content that would garner more views and more engagement.

What about the unique, exclusive audiences, audiences 1 and 2? How do we reconcile these different groups of people and the topics they care about? I already know, for example, that entrepreneurship will resonate with Twitter or that photography stuff will resonate with my website audience. What would be a first test would be to cross the streams, as it were. I’d try posting photography content to Twitter and entrepreneurship stuff on my blog to see if the topics resonate. If so, that would open up doors to reaching new audiences in either channel.

Finally, I’d want to assess the value of each audience in terms of revenue and ROI. Which audience provides greater business impact? For example, if Twitter’s audience was more valuable than my website audience, then I’d want to lean more heavily on entrepreneurship content in both locations than I would photography content in both locations.

When you have different audiences, see it not as a marketing operations problem, but an opportunity to broaden your reach and impact!


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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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