How to compensate and when to trust your gut
Anyone who’s watched “Mad Men” knows the parallels to modern marketing range from comical to cringeworthy.
One memorable scene features the lead character, Don Draper, who disagrees with his colleague who is part of a strange, new wing of their advertising agency called “Market Research.”
Instead of a fresh concept that pushed women to see using Pond’s Cold Cream as a form of self-indulgence, a focus group only validated the concept they’d been running with for decades: women use beauty products in the hopes of finding a man to marry. ::Slaps forehead::
Photo Credit: AMC
We all know how this story ends, if not in the show, then in real life. The beauty industry, which will be worth over $805 billion in the U.S. alone, has thrived on many concepts like self-care, individuality, and women’s empowerment.
It’s not the 1960s. Market research and data analytics has come a long way. It’s more methodical than a handful of chatty ladies haphazardly gathered in a conference room, and the data is more abundant, backed by AI, algorithms, data visualization, and more.
That doesn’t mean we shouldn’t still be asking ourselves: where does the power of data start and stop?
Most of the data out there is at best incomplete, at worst inaccurate
According to Demand Gen Report, over 62% of companies use prospect data that is incomplete or invalid. Additionally, when Dun & Bradstreet analyzed 223M they found 66% were missing revenue and industry data.
Most of us have had first-hand experience with the painstaking process of correcting customer databases. We grin and bear it because we know that our marketing campaigns can’t function on bad information. With some foresight, many of these problems can be avoided.
Before you end up with an unruly database of information, consider:
- Are you validating your data?
- Can you spot the difference between good and bad data?
- Are you baking in some advanced planning? For example, what data can you start to gather now that will later foster segmentation and personalization?
- What parts of your data strategy can be automated?
It’s not just about the effectiveness of your marketing campaigns. Bad data can get your digital assets blocked or blacklisted. Take our word on this, recovering a blacklisted domain can be an even bigger problem to fix.
The example from our favorite TV show above is a great example of bad qualitative data. Focus groups are problematic because of inherent social dynamics and groupthink. A better alternative is one-on-one interviews that truly reveal the voice of the customer.
Correlation is not causation
Photo Credit: AMC
This point is obvious, but it begs to be repeated. In fact, a recent study by Wharton showed that “57% of marketers are incorrectly crunching the data and potentially getting the wrong answer — and perhaps costing companies a lot of money.”
The abundance of data we have at our fingertips makes it easy to draw conclusions. The key is striking the right balance of using data to inform decisions without allowing it to steer the ship.
While it seems counterintuitive, always take the data with a grain of salt. Take baby steps when using data to inform decisions and always consider what is perhaps missing from the data.
A collaborative approach to data analysis is crucial
For many companies, one data specialist digs through the raw data and decides what to present to the rest of the team. And while it’s not possible for everyone on the team to get elbow deep in the actual numbers, it’s important to collaborate from the ground up.
There are several ways to do this:
- Work in teams instead of individually
- Rotate roles when it comes to analyzing data, making a point to revalidate previous insights along the way
- As a team, discuss possible ways to look at the raw numbers ahead of time
Strive for a balance between collaboration and efficiency. After all, coming to the wrong conclusions could be much more damaging than a few extra hours spent on getting quality insights.
If you don’t have the internal resources to be confident in your data insights, consider outsourcing this to an experienced marketing partner.
Data and its application changes dramatically with technology
Photo Credit: AMC
Technology is constantly advancing. Algorithms change and technologies get phased out. Marketers get frustrated because just as we get the hang of things, something changes. Technology changes can make strategies obsolete and make it impossible to benchmark against previous performance.
Here’s how to keep with the times, and avoid a data-kerfuffle:
- Don’t put all your eggs in one basket; diversify your data sources between internal and 3rd party sources.
- Make sure you, or your marketing partner, stay ahead of trends in marketing data and technology.
- Adopt new technology early, especially if it means old technology is getting phased out. (Hint: if you haven’t installed Google Analytics 4 on your website yet, do it now!).
Supported by data… with a grain of salt
In a world of shrinking marketing budgets and increased emphasis on ROI, we can’t be afraid to try new things. Yes, it’s obviously important to use data-driven insights to fuel ideas and strategies, but if the above points out holes in your own data strategy, let’s chat.
Our team of experts can help you make the best of best practices and data insights while also adding a dash of bold, new ideas. In this world of formulaic marketing strategies, oftentimes simply doing something different will make your brand stand apart.