I love data. I really do. The more data you have, the better decisions you can make.
Unless…
Unless you read the data without context and understanding.
Consider this example: Your e-commerce vendor is reporting to you that your Google Adwords (the ads that show during a Google search) campaign is doing extremely well and shows you the data to back it up. You are buying clicks for an average of $1 per click and generating revenue of $20 per click. Seems like a great deal, so you sign off on continued spending. You continue to watch the metrics and, sure enough, the money keeps rolling in. You are spending $1 to make $20. You are happy.
What you lack is the context or additional information to help you make a good decision. In the example above, the e-commerce vendor did not separate the branded versus non-branded advertising. A branded advertisement is when someone Googles your company name or domain name (without .com) and an advertisement shows up. The cost to run this ad (in this example) is 25 cents, because you are the only buying your name. Obviously, people searching for your name are looking for your company and intend to do business with you. And, whether you ran the ad or not, it’s highly likely you would have received the order.
Digging into your data, you find that 80 percent of the sales are coming from branded advertisements. The cost of those branded advertisements is next to nothing. So, you ask your e-commerce expert to break out the non-branded advertising and learn that you are paying $20 per click for non-branded terms (think terms like promotional products) and generating $5 in revenue average for each click. The context makes what was an easy decision before look totally different.
It seems obvious you would not pay $20 to generate $5. Not so fast. If you analyze your cost of offline customer acquisition and find that the cost to acquire a new customer offline typically is $25 to generate $5 in revenue, the online acquisition costs are less expensive than offline and should be continued.
A quick recap of this short story:
- Executive thought the cost was $1 per click generating $20 per click. Easy to keep spending!
- Reality was cost was $20 per click generating $5 per click for the majority of the spend. Easy to cut online spending!
- Other acquisition costs were $25 to generate $5. Not so easy to cut online spending.
Being data driven without information would have continued spending. By adding context, you are able to be data informed and make your decision with all the information you need. The decision might be to improve your overall acquisition costs or look at the lifetime value of each customer type (offline acquired vs online acquired).
Consider this second example:
Let’s say your first quarter starts off with a 25 percent increase in sales. Woohoo! You are excited because your dashboard is showing a 25 percent increase, but, upon investigation, you notice that a customer who usually orders a very large order in the second quarter placed that order in the first quarter. That single order caused your sales to be up 20 percent, which means your second quarter will be behind by 20 percent.
If you were data driven and looked at the dashboard showing the 25 percent growth without the context, you might have hired staff to support growth that wasn’t really there. By being data informed, you avoided the costly mistake. (Of course, this could be a new order from that same customer too but you’ll have to do research to be sure).
Data and context are required to make good decisions. Be data informed, not data driven.
