Have you ever had an injury? Chronic pain? Something that really gets in the way of being able to live life the way you want to? You do everything within your power to get rid of it. You receive a diagnosis—sometimes from multiple medical professionals—and determine a treatment plan. You fork over lots of money and time at physical therapists’ offices and chiropractors’ offices and acupuncturists’ and… well, you get my drift. If you’ve been caught in this frustrating situation, you know exactly how irritating it is to go from one PT to another, only to discover that the reason the pain keeps recurring is because the first group you saw treated only your symptoms.
It’s not that treating symptoms doesn’t help. You get temporary relief, and may even be able to do things that you enjoy. Until the lingering pain returns with a vengeance, more stubborn than ever, and you’re back at square one, thousands of dollars short.
This is the current state of marketing and experience data today.
If you’ve been looking for a solution to solve your attribution and measurement pain, you’ve likely come across a lot of blog posts, infographics, and slick web pages that tell you similar variations about your marketing and experience data:
- Step one: Collect
- Step two: Standardize
- Step three: Transform
- Step four: Integrate
- Step five: Magic/jazz hands/unicorns 🦄
I’m so sorry to tell you this, but they’re treating your symptoms, and what they’re giving you is a literal impossibility. You will never trust that this data will get to numbers that make your CMO, CFO, or CEO happy, because it’s done in the wrong order. And it will never make magic happen.
Because they’re doing it wrong. Nearly everyone does. The industry as a whole is limited by their approach to the data life cycle because they’re merely treating symptoms.
The harsh reality is you cannot standardize data after you’ve collected it and expect it to be complete, accurate, and trustworthy.
And yet that’s what the entire industry expects you to accept.
It’s why every time you look at reporting that’s two weeks later than you needed it, you question what it tells you, and you just go with your gut.
It’s time to stop treating the symptoms and to start treating the underlying problem: the insight gap.
Let’s be like WebMD for a minute here and see if you’re experiencing signs of insight gap.
- Your team has either multiple standard taxonomies, or no standard taxonomy at all.
- You rely on UTM parameters for campaign tracking.
- Your tracking code infrastructure is done through multiple spreadsheets, and isn’t centralized.
- You’re only tracking by campaign or channel, with little to no content tracking.
- You have only partial coverage for tracking codes.
- Your data infrastructure comes through web and native ad/martech analytics or 3rd party marketing analytics.
- Your data sets are either siloed or colocated.
- You have little to no identity resolution in place.
- You’re using single touch or rules-based multi-touch-attribution.
- Your ROI is calculated based on campaign or channel.
If you’re using a solution that only treats each of these symptoms, and doesn’t solve for the underlying issue (the data completeness, consistency, and accuracy), we can help. To learn more about how Strala by ObservePoint closes the insight gap and helps companies trust their ROI, schedule a demo now.