Retina AI Persona Predictive Customer Lifetime Value CLV

The environment is changing rapidly for marketers. With the new privacy-focused iOS updates from Apple and Chrome eliminating third-party cookies in 2023 – among other changes – marketers are having to adapt their game to fit with new regulations. One of the big changes is the increasing value found in first-party data. Brands must now rely on opt-in and first-party data to help drive campaigns.

What is Customer Lifetime Value (CLV)?

Customer Lifetime Value (CLV) is a metric that estimates how much value (usually revenue or profit margin) any given customer will bring to a business over the course of the total time they interact with your brand—past, present, and future.

These shifts make it a strategic imperative for businesses to understand and predict customer lifetime value, which helps them identify key segments of consumers for their brand before the point of purchase and optimize their marketing strategies to compete and thrive.

Not all CLV models are created equal, however – most generate it at the aggregate rather than the individual level, so, therefore, are unable to accurately predict future CLV. With the individual-level CLV that Retina generates, customers are able to tease apart what it is that makes their best customers different from everyone else and incorporate that information to supercharge the profitability of their next customer acquisition campaign. Additionally, Retina is able to provide a dynamic CLV prediction based on the customer’s past interactions with the brand, allowing customers to know which customers they should target with special offers, discounts, and promotions.  

What is Retina AI?

Retina AI uses artificial intelligence to predict customer lifetime value before the first transaction.

Retina AI is the only product that predicts the long-term CLV of new customers enabling growth marketers to make a campaign or channel budget optimization decisions in near-real-time. An example of the Retina platform in use is our work with Madison Reed who was looking for a real-time solution to measure and optimize campaigns on Facebook. The team there opted to run an A/B test centered on the CLV:CAC (customer acquisition costs) ratio. 

Madison Reed Case Study

With a test campaign on Facebook, Madison Reed aimed to achieve the following goals: Measure campaign ROAS and CLV in near real-time, reallocate budgets toward more profitable campaigns and understand which ad creative resulted in the highest CLV:CAC ratios.

Madison Reed set up an A/B test using the same target audience for both segments: women 25 years of age or older in the United States who had never been a Madison Reed customer.

  • Campaign A was the business as usual campaign.
  • Campaign B was modified as the test segment.

Using customer lifetime value, the test segment was optimized positively for purchases and negatively against unsubscribers. Both segments used the same ad creative.

Madison Reed ran the test on Facebook with a 50/50 split for 4 weeks without any mid-campaign changes. The CLV:CAC ratio increased by 5% immediately, as a direct result of optimizing the campaign using customer lifetime value within the Facebook ads manager. Along with a better CLV:CAC ratio, the test campaign earned more impressions, more website purchases, and more subscriptions, ultimately leading to increased revenue. Madison Reed saved on cost per impression and cost per purchase while also acquiring more valuable long-term customers.

These kinds of results are typical when using Retina. On average, Retina increases marketing efficiency by 30%, boosts incremental CLV by 44% with lookalike audiences, and earns 8x Return on Ad Spend (ROAS) on acquisition campaigns when compared to typical marketing methods. Personalization based on predicted customer value at scale in real-time is ultimately a game-changer in marketing technology. Its focus on customer behavior rather than demographics makes it a unique and intuitive use of data to turn marketing campaigns into effective, consistent wins.

Retina AI offers the following capabilities

  • CLV Lead Scores – Retina provides businesses with the means to score all customers to identify quality leads. Many businesses are unsure of which customers will yield the highest value over their lifetime. By using Retina to measure baseline average return on advertising spend (ROAS) across all campaigns and continuously scoring leads and updating CPAs accordingly, Retina’s predictions generate a much higher ROAS on the campaign that was optimized using eCLV. This strategic use of artificial intelligence gives businesses the means to identify and access customers that are indicative of residual value. Beyond customer scoring, Retina can integrate and segment data through a customer data platform for reporting across systems.
  • Campaign Budget Optimization – Strategic marketers are always looking for ways to optimize their ad spend. The issue is that most marketers have to wait up to 90 days before they can measure previous campaign performance and adjust future budgets accordingly. Retina Early CLV empowers marketers to make smart choices about where to focus their ad spend in real time, by reserving their highest CPAs for high-value customers and prospects. This quickly optimizes target CPAs of higher value campaigns to yield higher ROAS and higher conversion rates. 
  • Lookalike Audiences – Retina we’ve noticed that many companies have very low ROAS—usually around 1 or even less than 1. This often happens when a company’s ad spend isn’t proportional to their prospects’ or existing customers’ lifetime value. One way to dramatically increase ROAS is to create value-based lookalike audiences and set corresponding bid caps. In this way, businesses can optimize ad spend based on the value their customers will bring them in the long run. Businesses can triple their return on ad spend with Retina’s customer lifetime value-based lookalike audiences.
  • Value-Based Bidding – Value-based bidding is predicated on the idea that even lower-value customers are worth acquiring一as long as you don’t spend too much acquiring them. With that assumption, Retina helps customers implement value-based bidding (VBB) in their Google and Facebook campaigns. Setting bid caps can help ensure high LTV:CAC ratios and gives clients more flexibility to modify campaign parameters to fit business goals. With dynamic bid caps from Retina, clients significantly improved their LTV:CAC ratios by keeping acquisition costs below 60% of their bid caps.
  • Financial & Customer Health – Report on the health and value of your customer base. Quality of Customers Report™ (QoC) provides a detailed analysis of a company’s customer base. The QoC focuses on forward-looking customer metrics and accounts for customer equity built with repeat purchase behavior.

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