by Freddy J. Nager, Founder + Director of Marketing Forensics…
Most marketing forensicists focus on the data, but the numbers can tell you only what happened. For example, website analytics reports can reveal that a particular blog post is not receiving much traffic, and those who do visit spend less than a minute on it. What the data won’t tell you is why the visitors didn’t care for that post, or how to revise it so you get the results you want.
The Story Behind The Stats
The why and how call for a qualitative analysis, usually by experts. In the case of a blog post, that would be a professional content strategist/writer (obviously, other than the one who originally wrote the post). While another writer’s assessment might appear subjective, it has credibility if she is a professional with extensive education and experience, particularly in that market.
The content strategist/writer can evaluate the post’s tone and flow, and, yes, determine how “interesting” it is objectively. Is the post telling a story with concrete details and facts, or is it mostly abstract with no narrative structure? Is the post providing information of value to the reader, or is it just self-promotional for the company?
Continued Quantitative Input
The qualitative analyst, however, should not work in a bubble. She should receive further input from the data analyst, such as the source of the visitors. For example, the data may show visitors coming from a foreign market where the company does not do business, in which case rewriting the post for them would be a waste of resources. Or perhaps the visitors are primarily using phones, and the article is too long or not device responsive, which calls for both site redesign and copy editing.
If the strategist/writer determines that the post is fine, just incorrectly targeted, she can then request that it be made more mobile friendly then promoted to audiences who would care about its content.
Finally, If she determines that the audience isn’t the issue, but that the post does need rewriting, she can then provide multiple options that can be tested. (In a typical A/B test, two versions of a post are uploaded, and each is served to different visitors randomly. Their responses are then recorded.) The quantitative analyst can then note which version of the post is performing better. (Note: A/B testing requires hundreds of visits to be statistically valid. If the site generally receives little traffic, testing will have to take place over a much longer period.)
Not All Results Are Equal
Once the test results are in, both the qualitative and quantitative analyst must determine the business implications of the numbers.
For example, version A of the post might generate more traffic and social sharing (“going viral”) than version B. That has branding and publicity value, which advertising and social media agencies tend to emphasize.
However, while version B is less popular, it might generate more actual sales for the company — which the quantitative analyst can determine by tracking user paths and actions through the site.
The strategist/writer might then try to write a version C of the article combining successful elements of both A and B — but only if the numbers justify this investment of her time. Both analysts might agree that she should develop new blog posts instead.
- Evaluate marketing content both quantitatively and qualitatively.
- Employ professionals who have extensive education and experience.
- Make sure the professionals work collaboratively, not simply one after the other.
- Test conclusions and content further, but only if the tests can be statistically valid.
- Make decisions based on value to your company, not necessarily what matters to your ad and social agencies — including whether that particular kind of marketing warrants any further investment.
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