For those of you that didn't get a chance to read my blog post recap , I had the pleasure of attending the Adobe Summit out in Salt Lake City. At the conference, I saw Adobe validate something for Stratigent that we had seen coming in the industry for awhile. Adobe announced that they were releasing "Predictive Marketing" into their Digital Marketing Suite of products over the course of the next year.
What is "Predictive Marketing?"
I've always called this predictive modeling, as you probably have too. At the highest level, it's about taking a dataset and being able to build models and draw correlations that not only allow you to better understand your business but to also give you the opportunity to predict what is going to happen in the future. From a statistical standpoint, you're basically removing the outliers and coming up with a model that takes several inputs and gives you an expected output.
Let me give you an example that Adobe used at the Summit, as I thought it was a great way to apply this concept in the real world. Let's say you're an online retailer and you have an expectation for how well Black Friday is going to be for your business. Now, imagine that you could build a model to predict your results ahead of time based upon several inputs (marketing activities, distribution of spend, etc.). If you happened to notice, based on the model, that your results were going to miss the mark you were shooting for you could make appropriate changes to correct the issue before it was too late. The beautiful thing about this is that the model will allow you to calculate which changes in marketing mix and spend would most likely give you the result you want.
Another example, one that we've done recently for a client, involved identifying the best possible pages/processes to optimize on a site while garnering the most quick wins for the business. We built a model that allowed us to fully understand the relationship between key actions on the site and the goals that this particular client wanted their visitors to complete. In doing so, we were able to justify which actions held the most weight in a successful goal completion and built the business case on where to test. Not only did this focus the resources on the highest value area, but it also allowed our client to publicize some really great returns to the executives.
What is Stratigent doing?
As I mentioned before, we made the efforts to add this skill set to our team about 1.5 years ago. Having a multi-channel focus over the last couple of years has allowed us to change with the times. As we began to integrate the offline and online data for our clients, an inherent need for modeling and prediction developed. With that being said, it's definitely time to grow that team significantly to support our client's needs. So, we have started recruiting more Data Scientists to add to our analysis and optimization teams. If you know of anyone, or if you'd like to apply, please reach out to us directly at firstname.lastname@example.org.
We pride ourselves on being a pioneer in the space, and will continue to lead the charge on the innovation front. Predictive analytics is a lot of fun, and is very rewarding for those that are trying to take advantage of it today in combination with their analysis initiatives. Personally, I'm really excited to see what Adobe comes out with over the next year in their products. It's also really cool to see SAS have such a prominent placement at the recent industry trade shows I have attended.
As an industry, we are finally bringing data science into analytics. Clients will now be able to do modeling, identify trends, and ultimately make predictions about their goals based upon all of the data that has been previously collected. This is a really exciting time to be in the analytics field, and an even better time to be a client of Stratigent's.
Bill Bruno is the CEO - North America, Ebiquity.