Guessing isn’t strategic, but experimenting is.
Many times in marketing, you need to make outbound projections with little to no confidence in your inbound techniques. The lack of confidence is not a reflection of subpar skills or poor practices. Rather, it comes from watching numbers remain static, or worse, decrease despite generous, well-informed efforts.
Marketing, now more than ever, requires agile adjustments and nimble techniques to keep up with the turbulence of our times. In our technology-ruled world, the conversation and its protagonists are changing hour by hour, minute by minute.
Audiences from all pools–nonprofit, public affairs, fashion, e-commerce, governmental, education–are being oversaturated with information, opinion, and persuasion from peers and companies.
Sifting Through the White Noise
Anyone can say what you say. But not everyone can say it how you do.
Do you remember that one professor you had in college that stood out from the rest? They taught in a way that made you, a 19-year-old with no idea what they were doing in that room, feel like you belonged. They made you feel like they were explicitly speaking to you like you would change the world?
Months ago, I encountered this feeling when I attended Simon Sinek’s TedX. His message was plastered on all of his social channels and was repeated throughout the thousands of his prior speaking engagements. And, yet, it felt as if I heard it for the first time sitting 8 rows back in a dark theatre.
Delivery is key.
Not all of us can have storytelling prowess and an ability to synthesize the complex world in an elementary fashion like Simon Sinek or Professor “X.” The good news is that you don’t have to.
Experimentation Does Not Equate To Entropy
While marketing experimentation offers more flexibility in delivering to your audience, it does not equal entropy. Experimentation is a calculated, fixed process of steps: making an observation, ask a question, form a hypothesis (testable explanation), make a prediction based on your hypothesis, test the prediction, and finally, analyze results.
For marketers, this is where you ditch your pen in exchange for a pipette.
The most important part of any experiment is developing a hypothesis. A hypothesis gives you a plan. Identifying a hypothesis will give your research direction, and will ultimately help you understand why your consistent, high-quality content is failing to see the engagement you had hoped for.
Using human behavior to drive insight into building marketing roadmaps will allow you to customize content that is tailored to your audience. This technique allows you to isolate trends and outliers, and identify the different confounding variables that might attribute to your post’s success.
Each marketing experiment should always revolve around the data that shows how your audience or users think and act. (This data shouldn’t scare anyone reading this–it helps show consumers things online that fit their wants, needs, and attention.) In doing so, you will give your readers what they want to read, and more importantly, what they expect to read. This tactic should be integrated throughout all brand channels and platforms to create a cohesive, well-aligned marketing effort that ties back into your overall content strategy.
Don’t be afraid to revisit your audience persona board and make changes in the way you are communicating with your audience and potential core clients. Experimenting is necessary for an organization to evolve with the changing social ecosystem and needs of online users.
Capturing behavioral data is easier than ever and critically important to tinkering with your marketing strategy. Once you have data and start to build an altered plan around it, you’ll find that your strategy’s performance will repeat and stay consistent, because the human behavior it is derivative of is consistent.
At the core of any science experiment’s validity is repetition. If a scientist can’t replicate their results, it was very likely a fluke. But if you’re able to repeat an experiment over and over and get the same results, then it’s trustworthy. Try to replicate your solutions as much as possible, so you can get a sense of the cause behind the data trends you’re seeing. A new marketing strategy that works well once is nice, but one that consistently performs well is a game-changer.
Taking all this together, how many marketing strategies are experimental? When standard marketing approaches aren’t working for your business, you have no choice but to try something new. Slightly modifying your SEO approach, shifting your social media budget around, and using your users’ data differently are slight modifications to the existing best practices. But when does an altered best practice become experimental? Are the “best practices” we’re familiar with really just best guesses?