Martech and AI are increasingly becoming essential tools in every marketer’s arsenal, helping them reach prospects in new ways and more efficiently harness the power of data. Higher ed marketers can use martech to improve their campaigns and reach prospects with the right messages throughout the student lifecycle, from application to graduation.
Doug Olsen, vice president of analytics and product strategy at Collegis Education, has 15 years of experience bridging marketing, technology and analytics in the higher ed space. Throughout his career, he has leveraged over 20 years of software engineering and digital marketing experience to create technology platforms that drive consumer engagement and revenue growth. Prior to joining Collegis, Olsen was vice president of data strategy and analytics at Capella University.
We caught up with Olsen to discuss how martech will transform the industry, how higher ed marketers should adapt to these new technologies and the opportunities that martech and AI can help higher ed marketers uncover.
Q: Martech can help higher ed marketers better target students and potential students with more personalized messages. How does the martech stack provide insight for marketers throughout the student lifecycle, and create data points for better communication at each phase?
A: Absolutely. All the tools exist today to make personalized message testing and delivery a reality. Google and Facebook have tools for targeting, testing and delivering messages through advertising media. Content management and CRO tools can deliver personalized content and message testing on websites, and marketing automation tools like Salesforce Marketing Cloud and Marketo can create and test user-specific email journeys, all of which can create insights for marketers in those areas. The problem for higher ed, though, is that all of those tools operate on their own silos of data. Going back to school is a considered decision that takes time. A student going through the decision-making process interacts with a school at multiple points over the course of multiple months throughout their research, making those silos of data less effective. To truly target students with personalized and relevant messages in higher ed, you need to connect those disparate systems and data silos and create a holistic view of your student across the lifecycle.
Q: And how do you do that?
A: Creating a holistic view is probably one of the most complicated things to do, because you’re essentially stitching data together across a number of systems. Here at Collegis, we have something called the Connected Core that connects the disparate systems across the student lifecycle. Essentially, you want to take touchpoint interactions from the upper funnel and map them to the lead and student information and behaviors in the lower funnel so you have all the information together in one place, which gives you the whole picture for each student.
Q: Compared to other industries, higher ed is typically a laggard when it comes to adopting new technology. What’s your advice for higher ed marketers in overcoming this?
A: Lagging adoption isn’t due to a lack of interest on the marketers’ part. I think when they bring ideas to their IT teams they come back feeling like large initiatives. To accelerate things, my advice would be to find an external partner that has martech experience in the education industry. Martech is a specialized skill set that hasn’t typically resided in higher ed IT. It requires knowledge and experience with advertising and marketing platforms that are designed to make adoption easier for far less effort than many internal IT teams would have thought. Finding someone that works in higher ed is important, too. Given that it is a highly regulated industry with a more common set of student systems, having a partner that has worked through a variety of those regulation and system challenges can help you efficiently navigate issues you may encounter along the way.
Q: Martech can help higher ed marketers maximize their resources and save time and money, but working with limited budgets and small staffs can make actually implementing the new technologies a challenge. How do you find the right balance?
A: Create focus and start small. I always keep in the forefront of my mind that it’s not about the technology itself, but about the outcomes we seek to drive with our marketing. As such, I believe in starting with the data. Whether you’re responsible for new enrollments or retention or something else, get the data in place to understand your performance and the drivers behind your key metrics. Doing that creates visibility to your opportunity areas. Once you know where you need to focus, start small. Test out your ideas to get a sense for the size of impact they may have to find out if they’re worth a larger investment.
Q: What are some of the best ways you’ve seen martech being put into practice in higher ed, and what can marketers learn from these scenarios?
A: Look-a-like audience targeting is one of my favorites. There are a number of platforms that support look-a-like audience buying. By feeding enrollment data back to platforms like Google and Facebook, you can have them target prospective students. It’s simple to implement and very effective.
Paid search and display optimization is one of the most common ways I’ve seen martech put into practice. It’s standard practice to place a pixel on an inquiry form ‘thank you’ page to indicate a conversion that advertising systems can optimize on. However, we have also leveraged more valuable milestone points further down the funnel, like application, to help the advertising platforms optimize to something more valuable.
Display targeting optimization is one of the best ways I’ve seen martech being put into practice. We fed likelihood to enroll information back to the advertising platform in real time when prospective students drove an inquiry. This helped to create an optimization feedback loop so the platform was not only able to optimize to inquiry generation but also to the quality of the inquiry.
Website optimization is another. Through our website analytics, we observed that there were three pages that generated the majority of our inquiries. In addition, we saw that if someone visited one of three specific pages, we’d have an average conversion rate of four percent. For people who visited two of the three pages, the rate went to 12%, and for those who visited all three, the rate jumped to 25%. Through website testing and CMS personalization, we were able to dynamically add a secondary call to action to drive more views of those additional pages, increasing the number of people in the two- and three-page groups and driving up overall site conversion.
Q: What advice do you have for higher ed marketers about not getting too swamped with all of the data opportunities that martech can provide? How can they use this data in the most effective, relevant and profitable ways?
A: This answer is going to be similar to an early answer I gave, but it’s incredibly important to marketing success: focus. It’s critical to establish a strong data foundation and to have visibility to key metrics across the student lifecycle. With this visibility, you can get an understanding of where your next best opportunities are, then leverage the data and solutions that can positively impact those areas. There are always cool new data opportunities coming to market, so you should maintain awareness of those as they may solve a future problem, but don’t feel like you have to implement everything. This is also a great place to lean on your martech partner. They have likely seen many of these things implemented and can help you understand if it’s right for your particular situation.
Q: How is martech transforming higher ed, overall, and how can higher ed marketers prepare themselves for the future and stay ahead of the curve as these technologies evolve?
A: With the democratization and accessibility of machine learning, martech is on the cusp of transforming higher ed marketing in a very significant way. Machine learning is beginning to permeate many aspects of marketing, as it can leverage large amounts of data to make more accurate decisions and make them more quickly than a human marketer.
We’re already seeing a steep change in results being shared outside of the education industry with Orangetheory and Harley-Davidson NYC. After launching an AI platform, Orangetheory decreased its cost per lead by 60% while quadrupling media spend. Harley-Davidson NYC used an AI platform company, Albert, in its customer targeting efforts, and saw a whopping 2,900% increase in leads per month. The company is now attributing 40% of its sales to AI. And both companies found new groups of people they were resonating with. Given these results, it’s not difficult to see that companies and institutions that don’t embrace the coming martech AI will struggle to deliver the same results and will ultimately lose out to their competitors.
To be prepared for the future, it’s important for marketers to understand that the key to marketing AI success is data. Data is the fuel that powers the machine. Machine learning requires large amounts of clean and accurate data to work. The more you have, the better your results are likely to be. The challenge for marketers right now, in partnership with their IT departments, is to develop a data strategy that is able to create that robust data asset that connects the data elements of a student from the first marketing touchpoint through to graduation. Having a holistic and connected dataset that can be deployed in machine learning driven martech AI environments will bring big advantages. Those with the highest volume of quality data will be able to drive the machines to the most efficient and effective marketing they’ve ever seen, and are likely uncover new opportunities they didn’t even know existed.