First, any polarizing question like this can be answered with a catch-all: "It depends on whom you ask." There are likely strong angles to support both arguments. For the sake of this post, and to encourage discerning readers, we'll explore both options, and present why one may be stronger than the other, from our perspective.
Starting with the Story
Compared to the alternative, this process may seem more natural. You know what you want to say, so you begin crafting your story. You are taking action, and you are being agile, writing your content and working through the kinks as they arise; you just need to start writing, and you can support your points with evidence later. But at some point, you realize in order to gain credibility, to assert authority, and to be treated by your reader or listener, you will need to back up what you are positing, so you look for a statistic that validates your argument.
This is the easier of the two, as it allows you to begin with the narrative. You can chart out your goal, your audience, and your key takeaways, then form content that checks all of your boxes.
In this case, the stat is an afterthought.
This is often how we write essays, or even how we talk - we have a point to make, so we begin to make it, and in order to get buy-in or in order for our point to resonate, we find a stat that justifies or validates our opinion.
This isn't necessarily wrong, but we do need to add caution tape around this thought process, because it can seem manipulative if...
...the stat isn't chosen appropriately or integrated properly.
If you have a point to make, but you find a stat that supports your point indirectly, your audience may pick up on the fact that this stat was meant to make you appear smart or validated and may backfire. You never want your audience to think, "Well, that's a stretch."
Example: Your story is about the importance of email marketing. You use a stat about the importance of interpersonal conversations in B2B marketing, or the importance of the chat function, or the importance of orchestrating smooth marketing and sales handoffs. These may all be valid stats, but they don't directly support the focus of your piece necessarily. Make sure the data you choose tells the story you intend for it to tell.
...the stat isn't telling the whole story.
If you choose a data point that supports your point but was meant to support a different story, you are presenting too narrow a view. After all, we often only find what we're looking for, even if it's not the whole truth.
Example: Your story is about the importance of email marketing. You may find a report illustrating that 65% of marketers respond to emails. But maybe you leave out (or don't even know) the part about it being 65% of 200 marketers interviewed, or perhaps the type of email specified by the data point isn't the same you are talking about. Using vague context around stats doesn't make them more applicable - it makes you seem more manipulative.
...other stats are left out.
It will be clear to a reader that you are cherry-picking your stats based on what supports your point, and that may disintegrate their trust in you if they find that you are being less than honest with them.
Example: Your story is about the importance of email marketing. You find a report from two years ago with stats about marketing job functions, marketing challenges, marketers' preferred communication methods, and, within those layers, how email newsletters and sales emails have helped fuel new business in a few industry-specific case studies. So much could go wrong here. Hopefully you are citing all of your data points appropriately, in which case your reader may find out the report is outdated, or the data applied to a different industry, or the survey respondents were not comparable to those in your or your reader's position.
Without telling the whole story and conveying a data point the way it was meant to be conveyed, a stat can fall flat, hurt your credibility, dissolve trust, and turn a reader off from your brand.
Starting with the Stat
The more honest way is to find a great statistic, find out what it means, and craft your story around that data. In other words, let the data do the talking. Let the information you have drive your narrative forward; uncover the truth behind the numbers. Convey the meaning and the application and impact rather than using the stat as a fact to support another fact - instead, start with a fact then dive into the meaning and impact of it. This will feel less forced both when you write it and when your reader digests it.
Generally, this has the potential to be more difficult, since you have to sift through data, understand the context, and/or know what you're looking for. But once you have your goals established and your processes set up, you should be able to comb through filtered data easily or set up workflows to send curated data reports to your fingertips automatically so that the vetting process is at least partially done before you have to decide what story the data is trying to tell. Then, it is simply up to you to be the vessel, the channel through which that story is told. This approach takes the onus off of the writer and puts the stat in the spotlight where it belongs.
Conclusion: Both can be Acceptable in Certain Situations
Or Try Something Else - Get Creative With Your Marketing!
Clearly you may not always be able to start with cold, hard data. You may receive an assignment with a specific lede or focus, leaving you unable to redirect the story based on what the data might suggest. Or your content may be part of a larger series, and if you found conflicting data, your content might even hurt the brand by confusing your readers or diminishing the trust they have in your messaging. Maybe a company has already invested in something and your content asset needs to support that overarching theme, or maybe you're fulfilling a partnership and you don't want to present data that paints your collaborator in an unfavorable light. Marketers do sometimes have to mask data, or remove stats that don't support the strategy, or cherry-pick which stats justify the point they're trying to get across. The hope is that these moves are always done with integrity, with honesty, and with the audience in mind.
For example, if a marketer knew that 90% of ad campaigns failed if you employed Strategy X, but their project was all about promoting Strategy X, it would be dishonest to fudge that stat or to extract a fake stat saying that 90% of ad campaigns succeed under Strategy X. Instead of using a statistic, they may consider an emotional appeal, or a clever slogan, or another situation in which Strategy X yields better results. The point here is that you may be faced with situations in which you can't use the stats you see because they don't work for you; when you consider your alternatives, we encourage you to do so with integrity and honesty. Don't make up a fake statistic or cite an irrelevant report or hide your sources. Don't ignore the bad data or pretend it's better than it is. Instead, understand what the data is saying, and decide whether that is a story you are able to tell or not. If not, go ahead and be creative, be clever, be on-brand, and be successful, but be honest. Your authenticity will hold more credibility than any shady statistic you may be tempted to use. Remember that.

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