October 13, 2020– As you know, I’ve been continuing my education with a few new courses that I found really intriguing. I’ve completed Consumer Neuroscience and Neuromarketing at the Copenhagen School of Business. I’m almost done my course at Wharton Business School on Viral Marketing and How to Craft Contagious Content. I’ve learned many things, but today I’m going to focus on what I really enjoy, and that’s data.
I can hear a couple of you sighing from behind your screen right now, but trust me, this kind of data tracking, analysis, and integration will help you meet your goals for your business. Companies mine data all the time but what does that mean?
Data mining in the most simplistic forms is gathering data, analyzing it, and using it to know your consumers better. When we know who are consumers are and have a firm grasp on what they do, how they behave, the things they buy, and how they find our products, the better we can serve them and fill their needs. This is also called Customer Analytics.
Let’s do a case study so that you understand what I mean:
We have an email list of 5,000 subscribers. 500 of those subscribers are men, 4,000 are women, and 500 are teens. If we are going to spend our money on a children’s book marketing campaign, we need more information and we need to further break down our list.
500 teens are immediately disqualified because they aren’t in our target market. Yes, there is some variable data that suggests that some teens are already parents, but lack the median income or disposable income needed to purchase books for their children. This is a sweeping statement and used as a general example and is not intened to offend or exclude anyone. That leaves us with the women and men. We know from previous data that most women are the primary purchasers in their homes. Out of the 4,000 subscribers, 3500 of the women are between the ages of 30-39. Women between the ages of 30-39 (based on the data we have from our webstore analysis) are the primary purchasers of children’s titles on our site. If we break that number down further, we see that 500 women are from Oakville, 500 from Toronto, 1,000 from Hamilton, 1,000 from Niagara, and 500 from other places in Southern Ontario. Again, we retrieved this data from analytics on our site. We decide to use data from previous sponsored ads on Instagram and Facebook to see how much of a response we’re getting and from who. We see that out of 500 views, we have 100 clicks on our site. Out of those 100 clicks, we see that 40 of them were for a specific title and were clicked on by women from Hamilton and those women used Instagram to find us (as the program segments it).
What does this mean? Well, the data tells us that they were interested in a specific children’s book, it tells us that they are from Hamilton, and it tells us that they’re active on social media (Instagram specifically). This also let’s us know that they’re on the younger end of the age spectrum from ages 30-35 if they prefer Instagram over Facebook as their main source of social media, plus the data collected confirms it.
How does this help us? It helps us in a number of ways; the data shows that we should be marketing a specific book, to a specific region, to a specific age group, at a certain time. We’re combining knowledge that was filtered from our ad, and what we know about the best times to post on Instagram. Now we can tailor our marketing plans to have the most effective reach and impact for our consumers so that they can find our products with ease and efficiency.
There’s so much more to know about how analytics and data can help your small business and entrepreneurs that I couldn’t possibly fit it all in one post. If you’d like more information about how the experts at Pandamonium Publishing House can help you collect and filter your data, send us an email at firstname.lastname@example.org.