Marketing Analytics & Sales Growthwith Dr. Denise Gosnell
There are so many buzz words, trending about data science, machine learning, artificial intelligence. Those people on your team who are capable of analyzing large digests of data and telling you of a specific behavior in your site. It’s those types of individuals you need to have employed to look at your data.
If you will tell Dr. Gosnell about your conversion rates, she would ask you historically what type of customers you have who were successful?
As a data person, what she is asking you about in that question is whether you have been labeling or tracking an event you care about historically because that tells her a lot when she’s conversing with people whose conversions aren’t running well.
Let’s look at your historical conversions, and maybe historically, you never even had that event set up. Dr. Gosnell pointed that it’s a chicken and egg problem because if that’s kind of where we go.
It’s the same as making a decision and put something out there that you think your audience is going to resonate with and ensure that you also have the systems up and running to measure it to the event you care about.
For the people trying to dabble into machine learning, we would call this a labeled event or supervised learning. It’s giving you your training data.
It’s that line in the sand where you wonder if your people even get there and cross over it or not. Without having that line that you’re measuring and tracking, it’d be tough to talk you through and look at your data and say where it’s not working.
Make sure that you can start to model and understand what the data is going to tell you about your best guess. If you already have it up, look at it historically. And find the groups of your customers who successfully get over that line and inspect what they did and why they were successful getting through that conversion funnel.
Many people want to overapply the world of machine learning, and working with all of these data points to throw everything out their data.
When the super simple techniques of defining and measuring goals, and looking at a percentage of people who meet that goal or not are some of the most empowering ways that you can get started with using data to inform your business decisions. So absolutely keep it simple.
When it comes down to the connected data components of how people keep it simple—this one is also hard because we’re out of phase of trying to figure out what crawling, walking and running means for the community. We already interact all day with very powerful ways that people are using connected data.
Your whole world’s probably using Netflix or your favorite streaming device these days. And they’re also using all the connections of who watched what movies to recommend more content to you.
We’re already used to the power of what it feels like to be running with connected data. If you want to apply this to your business, it’s really hard to recognize that you’ve got to crawl and walk before you can get to recommendations with connections and data.
Teaching people to be patient and do the simple items is where we need to be no matter where you are on your data journey with connected or with just regular non-connected data.
It’s going to be an exciting tug of war because data essentially is our new oil, it’s our new economy of how people are exchanging value on the internet. It’s your information.
And let’s think about this entire conversation. We’ve been talking about the power of what you can do when you capture your customer’s data. You can now use that to drive more business, but that’s what our business hat on.
When you put your consumer hat on, that feels different because it feels like you’re being forced into this world that you don’t know if you want to opt-in or opt-out.
Over the next 10 to 15 years, Dr. Gosnell sees this as a very interesting struggle between those of us who want to help inform our businesses with data and are consumers of these services. Those two worlds are kind of at an impasse on how we’re going to be moving together because one world wants to use your data to increase business.
And the other is wanting to is essentially start to bring more of your personal details back inside because you don’t want to be involved.