Unlock Reports:
Industry-wide studies on consumer behavior from the Cohley Insights team.
That perfectly “on-brand” photo you generated in-house is going to crush your KPIs. Your gut is telling you it’s going to knock it out of the park.
Then it falls flat. What gives?
The truth of the matter is that in today’s over-saturated digital world, predicting how your content will perform is a crapshoot.
You may know what “on-brand” content is for your business. But, unfortunately, “on-brand” doesn’t always translate to performance. In reality, optimizing a content strategy takes an enormous amount of testing...and then some more testing.
At Cohley, we find that oftentimes the highest performing piece of content is the least expected. Oddly enough, it can be the piece of content that garners a reaction like, “that will never work for our brand.” But, this type of groupthink presents a risk to your business. Mainly because to be a high-performer, the key is to constantly test new creative to learn more about your audience. And the data agrees: “Facebook announced its top-performing direct-response accounts, and they all had one thing in common. They created and tested 11-x more creative than the majority of advertisers.”
Brands who are able to unshackle their creatives from a preconceived brand identity and allow data to guide the process will win in the long run. Now, more than ever, replacing gut-feel with data is the key to success.
That’s why Cohley developed the concept of Content Engineering. In this article, we’ll cover the basics of Content Engineering and why it’s the key to growing your business in a hyper-competitive landscape.
Put very simply, Content Engineering is using data-driven processes to generate and optimize content. It’s the opposite of using subjective measures like aesthetic and traditional creative judgements to determine what is “good” content. Good content, in today’s complex marketing world, is content that performs.
Content Engineering requires testing large amounts of content across multiple channels with different audiences. Next, collecting the relevant data and using it to guide future content production. Gone are the days of relying on “gut-feel” to make content decisions.
Managing multiple channels, datapoints, and pieces of content can prove to be extremely challenging. In fact, it’s flat out hard. That’s why Cohley built the technology and the processes to make Content Engineering attainable for any marketing organization.
Tight, data-driven feedback loops are a necessity for Content Engineering to fully flourish. At Cohley, we take a 4-stage approach to Content Engineering.
Generate diverse content types and assets
To test large amounts of content, you need to generate large amounts of content. The first step of Content Engineering is creating a diverse collection of visual content to begin testing. User-generated content is a great way to build up your visual library without breaking the bank. On the Cohley platform, brands and agencies will run Creator Campaigns to partner with several content creators at once to produce UGC at scale.
Activate, repurpose, and test content across marketing channels
Having a stockpile of content is great, but don’t let it collect dust in a Dropbox. Put it to work! Activate your content across your digital channels. Social media ads, email campaigns, and ecommerce websites are all viable testing grounds for your content strategy. Within the Cohley platform, you can easily push your newly-generated assets directly to your digital channels via our integrations with TikTok, Facebook Business Manager, Yotpo, Klaviyo and more.
Measure results and identify what types of assets are performing best with your audience
Track the performance of your content to better understand what types of assets are resonating with your audience and working toward your KPIs. As always, it’s important to look at the most relevant data points as they pertain to your goals. You’ll quickly realize that the high-performers are often not what you expected.
Leverage data to inform your creative strategy moving forward
Take what you learned from testing and apply it to your overarching content strategy. Perhaps video testimonials were the highest performing assets on your product pages. Or, maybe photos that feature nature resulted in the highest performance within Facebook Ads. The important part is to double down on what’s working and incorporate data back into the Generate stage. The data is informing you that stop-motion videos were the highest-performing assets?
Over time, this feedback loop gets tighter, predictability increases, and your strategy becomes more refined. Rather than generating assets you, as an individual, think will perform well and hoping for the best, go to battle with content backed by hard data. The analysis paralysis and guesswork will continue to shrink each time the feedback loop runs its course.