When testing new platforms, messaging, visuals, and whatever else, we generally pursue one thing nowadays: data. Whatever we do, we must gather enough data to learn how to improve. That is crucial to an efficient marketing ecosystem. Another essential thing is that the collected data must be valid to have any hope of being used for the aforementioned purpose.
Related: Do You Measure Your Marketing Enough?
Reality vs. expectations
But there’s always the possibility that what you expect is entirely different from reality. There are at least four scenarios that can play out:
- the data is like you expected (lucky you)
- the data shows better results than you expected (still lucky you)
- the data shows worse results than you expected (oh well, but workable)
- the data is a complete mess and unusable (bad)
Some of these situations require more analysis than others, but it is generally good practice to also critically review the positive outcomes. All of these scenarios do have their place in learning more about your marketing.
Let’s break down the above scenarios.
When the data is like you expected or better
So, what should we think about a successful marketing campaign? First impressions may range from “quite satisfactory” to “hell yeah,” but generally, this is a positive outcome. As I mentioned, there are still opportunities to learn and improve, even if the campaign results are above expectations.
What to do: reflect on the results critically on business goals and analyze what exactly it was that worked so well.
When the data shows worse results than expected
The good news is that you at least have some valid data to analyze. When the results are wrong, it might be easier to examine it. You may notice some significant problems instantly, even after a quick glance. So, in this regard, it’s not that bad of a situation. The real question is, however, whether you have the resources to make the needed adjustments and improvements.
What to do: analyze all the aspects of the results that you can, and try to really understand what went wrong. Remember to allocate enough resources for improvements.
If the data is a complete mess
It can happen that the data you collected is clearly wrong or lacking. You may have way more clicks, opens, or impressions than you actually got. Perhaps you noticed only at the end of the campaign that the targeting was way off.
Well, the situation may not be completely hopeless. These kinds of things happen, and often, the cause is errors in measuring and setup processes. They offer valuable lessons if you are open to critical analysis and tangible changes.
What to do: Take a break, breathe in, and analyze what went wrong. Double-check measuring and campaign setup processes.
Related: From Marketing Jumble to a Sustainable Ecosystem
Takeaways
Things can go unexpected in several ways, but the correct course of action is always more or less the same: analyze past performance and actions critically. What led to the results you got?
Debriefing can be a powerful tool for future campaign designs. By taking into account what has worked and what hasn’t, designing new marketing campaigns should become more straightforward in the future. If a particular way of doing things proves challenging, it should be easy to either leave it out or improve it.
In all cases it is essential to understand how you got into this situation, and even more important to figure out how to make it work (even) better.
Do you need help with problems with data accuracy or reliability? Aboad has a long history of helping its customers with exactly this. If you want to learn more about that, I would suggest to get in touch without hesitation.
Also read:
B2B Marketing Measurement – Creating a Meaningful Measurement System
Digital Marketing Data Analytics – Tools and Tips