Marketing teams have access to an unprecedented amount of data and customer insights, but too many aren’t actionable or useful. It may be fascinating that 40% of your customers come from Kansas, but how does that help your business?
Marketing teams need higher standards for what is considered an insight. AI is now deployed in analytics tools to surface insights faster than you can read them. Take a look at how Google Analytics does it.
You can’t let analytics software tell you what an insight is. Only your team can determine that. Of course, the software can help, but the final decision is yours. If you don’t maintain standards, your team will eat the equivalent of “fast food” insights.
The rise of fast food insights
Fast food tastes great but has few nutrients. I love Popeyes and will go out of my way to get it every once in a while. However, I don’t pretend to make healthy choices when eating there.
I work with marketing teams, and I see “fast food insights” all over the place. They report metrics they don’t care about, like pageviews, bounce rates, etc. They celebrate if their likes increase to an arbitrary target without considering the metric.
Insights need to drive behaviors. Do you change anything in your strategy if a metric goes up or down? If not, then why are you tracking it? It would be like checking the weather every day but deciding to wear whatever you want regardless of the forecast.
Like fast food, these kinds of insights can feel great.
I once worked with a marketing team that measured their agencies’ performance by pageviews. Their paid spend was directed at the channels that drove the most visits. There wasn’t enough discussion on what the users were doing once they landed on the website.
Your team needs to have a balanced diet. Fast food insights are fine every once in a while but not as your daily bread.
Fast food insights are also popular because they give the impression that someone is data-driven. Simply working with numbers can provide confidence to anyone. However, don’t let the means justify the ends. Data-driven is not about working with numbers but about driving meaningful results for the business through the help of data.
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What are your standards?
Take a second to think about what standards are enforced within your team. Many companies default to standards set externally. Their customers expected them to reply within a specific time frame or expect a certain price from their products. Investors expect specific revenue targets and goals.
You need your own standards. I once worked with a consumer fitness company with 30 pages of stringent branding standards on the proper sizing of their logo and specific fonts that should be used.
As a result, all media that represented the brand was always consistent. Perhaps their standards were too rigid, but at least they knew what they wanted and weren’t willing to settle for less.
Great companies impose high standards on themselves. Think about Gucci for a second. Do you think they care about why people don’t buy their products? Unlikely.
There are countless reasons why people don’t purchase their products. Instead, Gucci focuses on why people buy and how to get more of those customers. They don’t lower their standards, i.e., price. Instead, they raise them even further.
Raising your standards on insights
The data world is going through a fascinating change. For a long time, the issue was too much data. Then software and AI got better, and now the issue is too many insights. Creating standards for insights is the long-term solution.
When it comes to insights, the most important element is being able to explain its importance. In my first book, “The Data Mirage,” I discuss the WDIM or “What Does It Mean” question.
WDIM is a simple reminder that every insight needs to have a believable explanation. For example, if 40% of your customers come from Kansas, what does that mean? Should you change your marketing to focus on that region? Is that good or bad? Are these the customers you want to be attracting?
WDIM starts to get to the heart of the issue. Raising the standard means that you won’t consider an insight until there is a clear WDIM attached to it. If someone is sharing an insight, ask for the WDIM. In slide decks and reports, WDIM should be the focus.
Discussing insights without WDIM is a waste of time. Over time, your definition of a good WDIM can increase. It might not be enough to raise a couple of good questions. You might be looking for strategic connections to the business or relevance to current campaigns.
You can also think about imposing technical criteria on your insights. For example, I have helped companies impose minimum requirements such as:
- Statistically valid
- The pattern is seen over multiple days or weeks
- Insight verified by two or more data sources
- Builds on a new previous successful insight
If your team is just getting started with data insights, it still makes sense to enforce standards early. You don’t want to build a culture that believes in weak insights. Over the long term, it can hurt trust in the data. Why would anyone trust insights that haven’t proven helpful to the business?
For many teams, enforcing standards starts with your technical data people. They know the data in and out and are the first line of defense against vanity insights. For non-technical folks, you need to go through coaching on how to spot “fast food” insights. Basic training in probabilities and statistics helps work through the hype.
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