There are approximately 8,978,367 marketing analytics tools on the market. You can measure everything from call analytics and web analytics, to conversion rate optimization and social media success. You can measure macro-level campaign success and micro-level lead quality.
Marketers can measure anything they want. The data is more available, more ready, and more profound than at any time in history. And yet marketers are still making dumb decisions.
Why? Because these marketers don’t use the data they have.
Instead of using the data, analyzing the data and making decisions about the data, marketers fail to use the data. They do this in three ways.
1) Make assumptions and persist in those assumptions
Marketers do this all the time. They assume that a specific tactic either will or won’t work and then regardless of what the data shows, they persist in their original assumptions. They ignore the analytics. They ignore the web analytics or the call tracking data or whatever.
Example – Recently I was on the phone with the Director of Marketing at a tech company. They assumed that their PPC efforts would produce good leads. They assumed it would generate phone calls. They assumed it would generate revenue and business.
However, after spending TENS OF THOUSANDS of dollars on PPC campaigns over a period of 3 months, they hadn’t seen success. The campaigns had failed to generate many phone calls, or many form fill-outs.
In short: the PPC efforts had failed.
But, the marketer insisted on continuing these efforts. “They’ve just got to work,” he said. “We know they’ll work.”
Wrong.
You ‘ASSUME‘ they will work. And even though your assumption flies in the face of the data, you continue in your assumption. #epicfail
2) Doing something for the sake of doing something
Most marketers, at one time or another, have fallen into this trap. They persist in a tactic even though it isn’t working simply because it has always been done. They do it because they do it. That’s the only reason.
Example – Tradeshows often fall into this category. Companies exhibit, attend, and spend money on tradeshows even though the data clearly shows a lower CPL for other marketing channels.
I have talked to no marketer–none, zero, zilch–who says that tradeshows produce even a comparable CPL or CPA to other marketing channels (inbound, SEO, PPC, email, social media, traditional, affiliate). Generally companies spend north of $5K to exhibit at a show and come away with 50 – 75 leads. The numbers just don’t add up when compared to other channels. This fact isn’t disputed.
So why do we continue to go to tradeshows when the data demands that we stop? Why don’t we hold tradeshows accountable like we do other marketing efforts?
Because going to industry events is just something ‘you do.’ This, therefore, must exempt these events from accountability from the actual data. Or something.
3) Discarding campaigns with limited data
Sometimes getting accurate data takes time. Marketers shouldn’t make decisions about campaigns, ads, or channels too quickly.
Example – Buying cycles can sometimes be significant. Perhaps a campaign that appears to be a failure will yield fruit only after more time.
If you conduct an email campaign and generate a couple hundred leads, it would be foolish to label the campaign a failure after only a few weeks. These leads might end up becoming customers after 3 months, for example.
Don’t give up too quickly. You may not have all the data you need. BUT, when you do have all the data you need, you should make a decisions EXTREMELY quickly.
Marketers have the data at our fingertips. We should use the data to make better decisions.
