Ido Wiesenberg is the CEO of voyantisa UA platform that helps growth teams activate signals based on LTV data to optimize UA campaigns.
To say that the subscription industry has changed dramatically several times since the course of the pandemic is a huge understatement. Because of all this, many facets of the subscription economy showed resilience time and again.
That’s not to say the subscription industry didn’t face its own roadblocks along the way. I’ve written before about how companies that did exceptionally well during the pandemic, which previously showed two or three digit growth, were beginning to experience slowdowns. Peloton is an example of this.
More broadly, however, the subscription industry is thriving. It all comes down to metrics. Amid all the changes happening between consumer behavior, privacy restrictions and changes within ad networks, subscription brands in the post-pandemic world became more data-driven than ever before.
1. Being data-driven
There is one saying that I hear a lot in my professional circles, which mainly consist of growth marketers and data scientists: Data is the new oil. And it’s not for nothing. Data helps create value for consumers and growth for the subscription businesses themselves.
This realization has led to a host of new partnerships with digital infrastructure providers to drive long-term profitability growth efforts. This also explains why investors became increasingly enamored with subscription brands. As mentioned in a report by Robeco, subscription companies generally have more certainty about their long-term revenue due to the nature of their business model. The report goes on to say that “these companies tend to generate a constant stream of data that can be used to improve service, increase customer satisfaction, and identify additional business opportunities.” Of course, this generally leads to relatively stable growth over time.
So, what are the performance metrics that subscription brands have looked at? There are several. Some of the more obvious ones are data on different cohorts and average order value. The more advanced brands that have more big data to work with have taken it a step further by analyzing lifetime value (LTV) data. As the name implies, LTV data refers to the average amount of money each individual customer brings in to the brand over their lifetime, from acquisition to churn.
2. Investing in the Most Profitable Subscribers
Subscription companies were able to maintain their unprecedented 2020 LTV by building on their metrics and investing in the most profitable subscribers. As a result, a significant portion of customers who first purchased a subscription in 2020 experienced lasting behavioral changes in 2021.
According to a Recharge report, brands within the beauty and personal care industry have “huge” 120% increase in subscribers and a 30% increase in LTV in 2020.” The fact that these companies have been at the top of the charts for so long demonstrates their long-term resilience with consumers.
So what exactly were the most successful subscription brands doing with their LTV data? They used that data to see into the future. Futurespecting is proving to be a way for subscription brands to stay ahead of the user acquisition and growth marketing curve.
3. Future vision to capture scalability
Futurespection stems from my first point above about being data-driven. It is absolutely crucial that all important decisions are made based on thorough data analysis. In theory, however, that is looking back. Thanks to AI technology, it is now possible to make informed decisions based on what is very likely to happen in the future. You can think of it as taking business growth through the lens of a chess master. Full disclosure, I founded a company that falls under the growth marketing industry, and my team of growth experts and I firmly believe that online brands, especially subscription brands, need to get on board with vision for the future; we think it will become an industry standard within the next five years.
Futurespecting refers to the use of data to predict future events or even future campaign results. Of course, not all companies have the resources or time like larger companies to build solutions in-house to help them take advantage of LTV data for forward-looking research. Fortunately, there are plenty of solutions that fall under the umbrella of predictive marketing that leverage AI and ML technologies to help the growth teams behind subscription brands and other businesses that rely on recurring revenue.
In the early 2000s, companies of all sizes talked a lot about conducting pre-mortem meetings/analysis where teams would imagine a project or organization had failed and work backwards to determine the causes that could lead to the failure of a project. the project or organization . It’s the opposite when subscription brands look to the future with LTV data – because it’s more about visualizing the best realistic outcome backed by data than determining exactly how to get there in the most efficient way.
Now is the time for growth leaders in the subscription industry to make good use of the tools and technology available to meet their unique needs and ensure they can build on their growth and momentum for years to come. The teams that are naturally the most data-driven will find the next phase of growth and scalability seamless, and it will be a great relief to both internal marketing and data science teams.