4 Ways to Increase ROI During Economic Uncertainty, Part 2: Using AI
This is part two of the series, 4 Ways to Increase ROI During Economic Uncertainty, Using AI. Chief Growth Officer, Josh Francia, writes from the perspective of a business leader who’s achieved success throughout myriad economic struggles, including 2008’s recession, 2010’s volcanic eruption which halted air travel, and 2016’s Zika virus outbreak. For more on Josh’s experience, read part one, here.
When the global economy shifts as drastically and as quickly as it has over the last few weeks, it can seem as though no one has the answer to how we’re all going to get through this. While the past 10 years have seen a growing economy and positive outlook, they’ve still been riddled with challenges that we can take valuable insight from. In my own experience as a business leader for the last 15 years, I’ve noticed 4 key strategies that can help you see immediate ROI in times of economic uncertainty. In part one we talked about unifying data, and here in part two we’ll take a closer look at how AI can quickly increase ROI.
Utilize the power of your existing customer data and AI
As we discussed in part one, the basis of seeing real ROI and impact for your business relies on the fullness of your customer data. AI isn’t nearly as impactful without the data to fuel it. So, unifying and storing your data is a prerequisite for any other ROI boosting measure you may take — but it isn’t the full answer.
In marketing, AI has proven time and again that it’s extremely great at sifting through the noise to find the most valuable data points for your business. In fact, 98% of marketers using AI report seeing massive improvements to their marketing initiatives. Within the Blueshift platform, there are 4 different types of AI that can help your business reach their goals and improve ROI:
1. Predictive Segmentation
This form of AI answers the “who?” of your customer base and predicts the best customers to target. This “who” can be based on a number of goals predetermined by your team, such as conversion, engagement, or other desired actions. In the Blueshift platform, customers are given scores and ranked by their scores, so it’s easy to build segments later on based on these scores to filter out low-likelihood or high-likelihood to purchase customers. Skillshare, a leading online-learning service has used Blueshift’s Predictive Segmentation to see an 89% increase in enrollment by messaging the right customers.
In challenging times, predictive modeling is a great way to reduce spend on sending messages to those customers who probably won’t purchase any time soon — reserve your ad dollars and email sends for those who are actively engaged and ready to convert.
2. Predictive Recommendations
Recommendations are the “what” of your tech stack. Now that you’ve identified who you should be messaging, Predictive Recommendations can build out the content blocks of these messages. This content can be in the form of videos and articles, or products and new offerings. Zumper, an online apartment search, and rental service saw a 128% increase in CTR using predictive recommendations to serve up the best rental listings for each customer.
By including predictive recommendations within messages, you’re ensuring each message counts, as it’s packed with valuable information for customers and ample chances to get them back into your site or mobile app and converting.
3. Predictive Engage Time
Now that you have your segments and messages built out and ready to fire off, AI can help predict the best possible time to message a customer based on previous behaviors. This “when” factor will predict when any given customer is most likely to interact and ultimately convert with your brand.
Even though our lives may be changed significantly at the moment, we still tend to keep a routine. Marketers can essentially throw away a message if they’re reaching customers at in-opportune times. If a customer always cooks dinner at 5:45, that’s probably a bad time to reach them as their inbox will pile up and your message will be one of many deleted post-meal. Predictive Engage Time AI essentially determines when consumers enter their own shopping mode and will message during this time to increase the likelihood of a message open turning into a browsing session.
4. Predictive Channel Engagement
Finally, with all the other components in place, this AI determines which channel will be the most effective for each customer. The “where” is determined by historic and real-time behavioral data that indicates a channel preference or affinity. This feature in the Blueshift platform ranks different channels by the likelihood of conversion on each one. LendingTree, a leading consumer finance platform, used Engage Time Optimization to see a 35% increase in revenue by messaging customers at the best time possible for their unique schedule.
The end result of using these various AI models is marketing flows that hone in on high-intent valuable users that are most likely to bring in revenue for your business when you need it most. 81% of marketers that use AI have exceeded revenue goals by over 30%.
Ready to see how AI can create an immediate impact on your business? Watch my full webinar and download the complete Marketer vs. Martech report for insights into how top brands are exceeding their goals. Then, reach out to our team to see how the Blueshift platform can help you succeed in these uncertain times.
Also, stay tuned for the third installment of this four-part series coming next week to learn about how your business can increase ROI and thrive during uncertain times.
