Analytics and big data are such hot topics that there's a tendency to think of them like they're a panacea—solving problems you didn't know you had and effortlessly providing a clear picture of your company's future. Don't misunderstand me: Big data and customer marketing analytics are amazing, but it's not a foolproof process. It's not always a smooth road. Sometimes your analytics are going to get it wrong, and you might make decisions based on marketing insights that are flawed. So what should you do?
How Can Customer Marketing Analytics Fail?
As you might imagine, that's not always a simple answer. But there are a few common problems that can screw up your attempts to use customer marketing analytics to guide your business decisions.
First, your analytics can only be as good as the data you feed into the process. If the data's wrong—and it can be seriously wrong—then you're unlikely to draw sound conclusions based on that incorrect data.
How do you end up with bad data? It can be easier than you think. Just take one tiny example: tracking visits to one of your website's pages.
If the code that tracks visits isn't just right, your numbers will be off. That means if you're relying on that visit count to decide whether to make changes, you're on shaky ground. Something as simple as an incorrect count can produce bad data.
But there are also human factors that can hinder your ability to collect accurate data. If you're relying on your salespeople, for example, to provide you with information in order to assess how well you're serving clients, you may not get the most accurate information. Inter-department miscommunication can cause problems, as can minor turf battles among members of your staff.
Sometimes it's a lack of expertise that accounts for customer marketing analytics failures. It's more than just plugging numbers into a computer and waiting for it to spit out brilliant insight. Analytics is a relatively new field, and it's not always an intuitive one.
And finally, customer marketing analytics can fail to produce stellar results when the stakeholders aren't fully invested in its potential to yield valuable insight. For analytics to work, you need to get buy-in from the people in key positions in your business. And yes … sometimes that means you!
How Can You Prevent Customer Marketing Analytics Problems?
I recommend that you first sell the concept. Get that buy-in from the people you know can make or break your initiative's success.
Try finding real-world examples of the sort of insight that's been gained by other organizations who have used customer marketing analytics, whether inside or outside your industry. When people begin to see the potential of using all the vast amounts of information you have at your fingertips, they may start to see the value for themselves and their role in your company.
And it's smart to start small. Just like many other aspects of your business, it's not an all-or-nothing decision. Try running a small trial. See if studying how prospective customers arrive at your website can guide your efforts to bring more visitors to your site. Carefully track the results of a direct mail campaign to see if it justifies the cost.
When you start small, you can determine if it's worth going big.
What Can You Do If Something Goes Wrong?
So let's say despite having run some successful small trials with using customer marketing analytics in your company, you end up with a mess.
You've collected bad data or you don't know exactly what to do with the data you have.
Or perhaps you've made a decision that turned out to be a flop.
Do you quit?
Of course not. But customer marketing analytics isn't magic. When it goes wrong, you can't just give up on the potential benefits you can reap.
You may need to ask for help. There are companies that specialize in helping businesses learn how to gain valuable insight from data. And there are even free resources. Google Analytics provides information and tools to help you use your company's data, and there is a wealth of information available if you're willing to track it down.
Whether you reach out to a mentor, colleague or analytics expert, learning what went wrong can help you put together a plan to make it go right the next time.
Though you may believe you can always trust your gut instinct, the data may say otherwise. Instincts can be valuable, but you now have the ability to check, refine and adjust your insight and decisions based on real data.
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