10 Dec What Happens Without A Measurement Strategy?
Creating and running a new ad campaign means that your team works with many different moving parts. Your team builds creative, decides which audiences to target, and more, all within weeks or months of work by many different people at your company. After rigorous preparation, your team launches your campaign and wait for the sales to roll in.
Sound familiar? That’s probably because your business follows this process when creating a new campaign. But it’s important to note how your business moves through this process, and why.
Think about the order of steps you follow when building a campaign. Like many businesses, you may think about measurement only after you’ve solidified all the other parts of the campaign.
The key to the most successful marketing campaign is measurement, right from the start. If you want your digital marketing campaign to provide the most accurate results, you need to start with an honest understanding of your current data, even if that data shows areas of weakness.
However, evaluating your current data can seem time-consuming and unnecessary. Many businesses choose a more straightforward route simply in the interest of time and convenience. A quote from a recent AdExchanger news update is a perfect example of the reason many businesses don’t initially emphasize measurement:
“One startup manufacturer decided to reduce Facebook advertising “for the sake of their business and their own sanity,” instead of testing a 15-second TV spot. Returns were harder to prove without the data feedback, says one executive, but at least “you can push the button and get on with your life.”
This example demonstrates something true for many businesses: Measurement is ignored or never included in discussion until the team has already created the campaign. And this somewhat backward way of thinking is not only present in the marketing space. In fact, many organizations think this way in other areas of their business as well- especially when hiring new staff.
In 2005, a group of researchers at Stanford conducted a research study about hiring practices in which they asked participants to read the resumes of two qualified candidates for the job of Police Chief. Both resumes highlighted a different set of skills.
Applicant A was street-wise and agreeable with fellow officers, but only had a basic education and lacked administrative skills. Applicant B was highly educated and well-experienced in the administrative side of the job but lacked street experience and good rapport with other officers. Another factor: Candidate A’s name was Michael and Candidate B’s name was Michelle.
Participants then were asked to rank the most important skills needed for the role of Police Chief. Participants overwhelmingly agreed that the Police Chief should be “tough and take risks.” They also agreed that the right person for the job must be “physically fit, and agreeable with fellow officers”.
Participants also overwhelmingly agreed that it was less important that the Police Chief was “well educated, family-oriented, and able to communicate with the media.”
However, when the researchers reversed the names on the resumes, presenting Michelle as the “street-wise officer” and Michael as the “educated administrator,” the participants also reversed their opinion on which set of traits were more important to them.
Without consciously realizing it, the participants used the candidate’s names to justify their internal beliefs. This study is an example of hiring bias, but it’s an even better example of the importance of honest data.
Many marketers treat their campaign analytics similar to how the participants treated their job applicants. Instead of referencing past data, (or in the hiring example, looking at the careers of successful Police Chiefs to see what skills they had in common), many marketers use their own data to confirm the results they want to see from their campaign.
What is the best way to remove bias from your campaign? Start asking questions about your current data and allow it to show you where your real weaknesses are.
Which channel provides you the most ROAS? What is your most popular product? Which online interaction is the most critical for closing an offline sale?
Without building measurement into your media campaigns right from the start, you miss out on vital performance data, and your own bias can influence the results of the campaign.
CMO and marketing leaders must commit to transparent and honest data if they want to see the best results from their digital marketing campaigns. So how can your business put it all into practice?
Insist on honest data; gather and analyze it for what it is, not what you want it to be.
Abandon any preconceived notions that you already know the results of what you want to measure, and make the data prove itself instead. From there, you’ll know that you are making decisions for your marketing strategy based on information that reflects your real needs and strengths.
Unlike many other digital marketing consultancies, our team at DELVE takes a data-first approach to digital marketing. Learn more about our data-driven mindset, powered by the Google Marketing Platform.