Omer Artun, CEO and Founder of AgilOne, was a recent guest on the TechnologyAdvice Expert Interview Series. The series, which is hosted by TechnologyAdvice’s Josh Bland, explores a variety of business and technology landscapes through conversations with industry leaders.
In this episode, we discuss customer centric transitions, how to better understand and use data, and how to improve customer experiences.
Below are Omer’s six biggest insights from the conversation.
There is a strong relationship between predictive marketing and big data.
Big data means that you're collecting a lot of data and you're able to store it, and you're able to collect many various types of data. You can collect very, very fast and you can process it very fast, and you can do many things with it. That's what big data means. That you have the storage, the velocity, the different types of data, and the processing power to process this data.
Predictive, on the other hand, is a very simple approach of looking at how we can take all of this big data and get meaning out of it.
If you have a spreadsheet with five million lines in it and 1600 columns, you will not be able to make any sense of it — because it's just a lot of data. You need to figure out what is the pattern in this data, and what is the learning from this data that I can process? Predictive, if you think about it, it's a simplification tool. Throw away the noise in the data so that you can come up with the true signal or the true pattern that lies in the data. That's what predictive is all about, it's a processing mindset to extract information out of this large data set.
Customer buying habits are changing, so you must be able to sift through data to pinpoint what is valuable.
In the past you had transactions. Transactions mean this customer bought this on this date. It's very clear — you actually bought this on this date. It's 100 percent information.
But now, people are browsing stuff. And within that browsing pattern, some people spend a lot of time on a product, and then they add it to the cart, they leave, they don't come back for five days. There's a lot of information there but it's not hardcore — you have to find the pattern. Five people might browse the product and leave never come back, another five that browse come back and purchase it from the store, and another five come back and purchase online.
So all of that same data results in different behavior in the future, and you want to understand those nuances so that you can make better decisions about how to get back to the customer. You can make better decisions around how to maximize the value of that customer long term, as well as how to maximize the dollars you spend on which marketing channels. And you need that mathematical mindset to sift through the noise and throw away what is not valuable, and that's what predictors are.
It's not just predictive that's going to be the silver bullet to solve a problem, but it's organizing yourself around the customer.
You have to focus on all of the touch points — all of the data that they generate — and then understand what the customer's doing, both predictively and descriptively. Predictive is just one component of it, and it's an absolutely required component. But sometimes there's the misnomer that it's just something by itself, which is not the case. Predictive is one tool set within the arsenal. For example, with our product and our offering, predictive is a component of it, but I would say it's maybe 20 percent of what we provide to the customer. It makes it so much better, it creates a huge boost. It's like the turbo on an engine — but you have to have the engine.
Predictive marketing is the next evolution of what people call one-to-one marketing or CRM.
It's the evolution and it adds certain capabilities. In the best CRM one-to-one systems, people looked at hard signals, looked at what people purchased and where people lived and demographic information, and so forth.
Now with the advance of the data, you have so much more data and you need a way to simplify it and get meaning out of it, which is what predictive provides. Since a lot of this big data is generated around interaction, it means that these are future looking signals. I might not have purchased anything for nine months, but I'm on your website browsing things, and I'm clicking on emails, versus another customer that also hasn't bought for nine months, but he has been completely incognito for the last nine months. Those are two very different behaviors of customers, and you need that predictive engine to figure out okay, here's a customer that hasn't bought for a while, but how do we engage him? Here's another one, and here's what their interests are, what they're likely to buy, and so forth.
Predictive allows you to respond to signals that are not apparent.
And what that does is it turns you away from being a reactive marketer — an after-the-fact kind of marketer — to becoming the proactive marketer. Because now you can predict what's going to happen and you can basically take precautions against fixing it. That's what the predictive marketing really does, it takes the paradigm shift away from being rearview mirror facing to forward looking, so that you do things proactively based on the customer’s behavior. And it's the next evolution of one-to-one marketing.