Predictive Lifetime ROI at Scale
Nanigans offers the only performance marketing platform that measures, predicts and optimizes ad spend for lifetime ROI on both desktop and mobile. By harnessing the power of predictive lifetime value (LTV) to inform more intelligent and efficient media buying, the company is moving the industry away from buying on a cost-per-click and cost-per-action basis to a true ROI basis.
What is LTV?
LTV describes the amount of revenue or profit a customer generates over time. While many digital advertisers try to minimize how much they spend to acquire a customer (cost per acquisition or CPA), by understanding the lifetime value of various customers, they can improve their ROI in the long run. As marketers we can agree, that it’s worth spending a little more to find and acquire a customer that is 20x more valuable than another.
Find out how to:
Identify high value customers with maturity curves
Once a customer has been acquired, it’s imperative to instantly start tracking her purchase behavior via maturity curve analysis.
By utilizing maturity curves, advertisers can immediately start to determine whether or not the customer they acquired was of high value. In addition, early profitability recognition positively influences predicative modeling algorithms, so that similar customers can be targeted in real time using affinity models.
Target similar customers with affinity models
Profitability recognition influences predictive modeling algorithms so similar customers can be targeted using affinity models. Also known as look-a-like models, affinity models will bid to potential customers who have similar profiles to those of your most profitable customers.
Identify high performing cohorts with Cohort Analysis
It’s important to track revenue and identify high performing cohorts so that you can continue to spend with confidence. By examining high performing cohorts, advertisers are able to understand historical performance so that similar learnings can be applied to current campaigns at scale.
By building affinity models, new correlative demographic targeting opportunities (that produce similar purchasing behaviors) become apparent and allow advertisers to both quantitatively and qualitatively scale with confidence.
Scale with Expected Revenue Tracking
While revenue to date allows advertisers to continue spending with confidence, predictive revenue allows them to scale, and scale with certainty. High-level metrics like spend, CTR and revenue to date are of interest, but by understanding expected revenue over time today, capitalizing on future growth happens in real time.
As you assess your advertising budget, consider the opportunity loss that CPA-based optimization represents and the incremental revenue and value that can be achieved with revenue-based optimization. By strategizing, bidding and optimizing to predictive lifetime value, you can be sure that you’re protecting yourself against low future values, and maximizing all of the investments that you can be making today, that will pay off the biggest in compounding future lifetime value.