Why Growth Strategy for Your Brand Needs to Revolve Around High-Value User AcquisitionQuick wins are great in UA, but it's better to think long-term and focus on people that demonstrate greater lifetime value.
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获取用户的努力根本不是他们used to be for brands, largely due to a long list of recent changes. On the customer's side, there have been lifestyle pivots, including an end to quarantines and shelter-in-place orders. From the business side, changes between ad networks and operating systems led to lower return on ad spend (ROAS) and decreases in scalability.
The question is, what are growth teams supposed to do going forward, as it's obvious that previous efforts are no longer fitting the bill? Brands that were living it up during the course of the pandemic need to figure out how to build up the momentum and scale fast, before entering the danger zone. So, what's left?
The future-proofed solution for sustainable growth
If you ask me, I'd say that what growth teams need is a future-proofed solution to all these challenges. After all, it simply isn't feasible for user acquisition (UA) managers to keep changing strategies in panic mode due to surprise changes. To me, the best approach is to reignite the focus on growth, and sustain profitability by focusing on high-value UA through predictive modeling — a statistical technique used to predict future behavior. This modeling can overcome obstacles by using a single signal to embody a user's lifetime value (LTV) based on a set of actions and behaviors, in addition to campaign performance. This allows marketers to send predictive signals to users who are most likely to make high-value purchases over time.
This is important, because there are difficulties associated with the limitations imposed by short-term optimization, which places focus on upper-funnel events like registration, trial completions, tutorial engagements and lots of one-time purchases. Those are great, but fail to provide visibility into whether users will make a second purchase.
Related:Why Industry Leaders Are Turning Towards Predictive Analytics
Conversely, long-term LTV based optimization, especially with predictive-based UA, enables growth teams to target loyal subscribers, pay less for one-time buyers and tap into an untapped audience (in this context, people who would be more inclined to make purchases outside of the attribution window). There's less competition there, which means lower CPA and higher profit margins for brands.
Top companies that saw success after applying LTV optimization
Facebook uniquely understands and acknowledges the importance of LTV optimization. A series of discussions in the 2021 Facebook LTV Summit covered how top companies were met with success by incorporating LTV data into predictive modeling to amplify growth efforts. One example discussed was the ever-popular subscription goods brand BoxyCharm (owned by Ipsy), which wanted to target high-value customers in order to lift ROI and reduce churn. The company had been optimizing its UA on subscriptions within the standard seven-day conversion window. That approach worked, but only to an extent, considering that while it yielded high conversion-to-subscription rates, churn was still a concern. What was needed was to target its long-term LTV audience to reduce churn and increase both LTV and profitability at scale, and BoxyCharm wound up turning to a marketing tool to help build a prediction model, then running campaigns optimizing on that signal. The A/B testing proved to be successful: the acquisition of high-value customers that yielded a higher ROI.
The Facebook summit also included a presentation on how a major casual gaming brand also benefited from predictive modeling. It wanted to increase ROAS and expand its audience beyond the CPI ceiling, and this was only possible by creating a single predictive metric to target its long-term LTV audience, lower customer acquisition cost and increase LTV and profitability at scale.
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An LTV prediction model (based on an internal data lake) was created, and activated by sending a custom conversion signal to Facebook, allowing the company to run the campaign by optimizing on the signal. The results were outstanding across the board, and included a ROAS uplift of 150% and a 75% reduction in UA costs.
These solutions are for companies either in growth mode or already large and well established, but even the biggest of growth teams with the deepest of pockets can benefit from an added boost to amplify their UA campaigns on Facebook.
How LTV data can be used to maximize results for user acquisition campaigns
If your brand is facing difficulties in building up from or even sustaining the growth from 2020, you should consider focusing on LTV to achieve growth and scale. By matching demographic data with affinities, interests and other factors, you can create whole new audiences with the same background as current cream-of-the-crop customers. Doing so essentially opens up campaign diversification opportunities by covering a larger portion of the customer journey and, therefore, acquiring new audience groups that previously might have been missed. Scalability will be increased, without suffering from diminishing returns on ad spend. You can also use this data to optimize retention campaigns after promotional periods, or optimize paid search campaigns by focusing on keywords. The use cases are plentiful!
