Retina AI
Click to visit website
About
Retina AI is a customer lifetime value (CLV) prediction tool that uses machine learning to provide accurate, individual-level CLV scores. It helps businesses understand their customers' purchasing habits and predict future behavior, enabling better marketing strategies and more profitable decisions. Retina's models go beyond simple RFM analysis to incorporate various data points for a more comprehensive understanding of customer value. The platform integrates with data sources like Shopify and CDPs and delivers CLV scores, lapse probability, persona predictions, and other insights. The tool is particularly suited for businesses with repeat purchase behavior, offering features such as lookalike audience building and marketing campaign optimization.
Platform
Task
Features
• data imputation
• marketing campaign optimization
• lookalike audience building
• integrations with shopify, cdps
• individual-level clv
• predictive clv
FAQs
What is customer lifetime value?
Customer Lifetime Value (CLV) is a metric that estimates how much value (usually revenue or profit margin) any given customer will bring to your business over the course of the total time they interact with your brand—past, present, and future.
How do you calculate customer lifetime value?
There are many formulas available to calculate lifetime value. However, calculating predictive customer lifetime value at the individual level requires a complex model. The steps include: Locate the necessary data, Forecast every existing customer’s behavior, Split the data into two sets for training and testing, Add customer features and attributes to the model, Train and validate the model, Put the model into production
How do you know if your CLV metric is accurate?
Not all CLV models are created equal. If you’re reviewing CLV from your organization or a vendor, start by asking yourself a few questions to see if the metric is accurate and useful. 1. Is the CLV at the aggregate level or individual level? 2. Is CLV historic, predictive or some combination? 3. How much of CLV is already observed vs predicted future revenue/profit?
What is the difference between CLV and LTV?
Customer Lifetime Value is calculated at the individual level, while Lifetime Value is an aggregate metric.
Why is it important to calculate CLV at the individual level?
The most popular and commonly used customer lifetime value (CLV) models benchmark their strength on aggregate metrics. However, these models are incredibly inaccurate at the individual level. This becomes an issue because most business use cases require a strong CLV model at the individual level. Aggregate CLV simply does not allow you to adjust who you’re targeting with re-engagement or acquisition efforts to maximize the benefits of each campaign.
Can CLV change over time?
Yes, customer lifetime value is not a static metric. It changes over time as you observe new data about a customer. Knowing this, you can adjust your retention and product strategies to increase customer lifetime value.
How can CLV improve marketing strategies?
Customer lifetime value is an important tool for marketers: CLV can help you target, retain, and provide exceptional service to your best customers. Once you know what attributes and behaviors make up your high-CLV customer, you can use that information to build lookalike audiences.
Why is CLV important for segmentation?
It’s relatively simple to segment your current customers by attributes and/or past behavior. But if you want to predict the future behavior of your customers, it’s better to segment by features and attributes that impact customer lifetime value.
What makes a customer high value?
Customer lifetime value (CLV) is the metric leading companies use to understand their customers’ purchasing habits. Simply put, customers who purchase higher-value products, who purchase more frequently, and who continue to purchase on an ongoing basis are your high-CLV customers.
What should your CLV to CAC ratio be?
Once you’ve calculated CLV, you can use it to determine your target customer acquisition cost (CAC). Instead of simply targeting customers that bring in high initial revenue, focus your acquisition efforts on high CLV customers. Even if their first purchase is small, they will bring your business more value in the future. A customer acquisition is unprofitably only if CAC exceeds CLV. For most businesses, your CLV to CAC ratio should be 3:1 for each marketing segment.
How do you incorporate discounting when calculating the CLV?
You can take your annual discount rate and turn it into a daily discount rate, and apply a discount factor, which is: 1 / (1 + X)^Y where X is the discount rate and Y is the time variable.
How do you determine the right time frame for churn?
Typically, we compute the lifespan of every single customer using survival analysis. Once we’ve done that, you get a sense of what the longest life is of a customer. Based on that, you can choose the truncated time spans for computing customer lifetime value. We will typically calculate CLV for multiple year horizons, depending on the business. Sometimes, we will also compute full lifetime horizons as well.
Do Retina models go beyond RFM?
Recency, frequency, and monetary value (RFM) is a simple method to determine customer value. Retina models take into account data beyond RFM, including demographic and behavioral attributes, customer journeys, quiz and session data, and more. All of these data points make up a comprehensive data set that allows us to use machine learning to impute missing values from messy data and make customer lifetime value predictions early in the customer journey.
What types of companies does Retina work with, and what data do I need to work with Retina?
Retina works best with companies whose customers have repeat purchase behavior. This can include, but is not limited to: eCommerce, retail, CPG, financial services, healthcare, and even paid smartphone apps. In addition, customers ideally have 10,000 repeat purchases, 18-months or more worth of data, and customer identity resolution. Retina’s models use orders data and customer attributes, so we have integrations with Shopify as well as CDPs like mParticle or Segment to make data transfer a breeze.
In what format will I receive my eCLV scores?
Possible outputs of Retina’s models are: Customer ID, As Of Date, Retina CLV (up to 15-year predictions), Lapse Probability, Retina Persona, Likely Next Transaction , Typical Order Value , and Predicted Lapse Date. Each can be modified to fit a client’s needs, and will be sent through an established pipeline with your data warehouse.
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
Featured Tools
Songmeaning
Songmeaning uses AI to reveal the stories and meanings behind song lyrics. It offers lyric translation and AI music generation.
View Details
Whisper Notes
Offline AI speech-to-text transcription app using Whisper AI. Supports 80+ languages, audio file import, and offers lifetime access with a one-time purchase. Available for iOS and macOS.
View Details
GitGab
Connects Github repos and local files to AI models (ChatGPT, Claude, Gemini) for coding tasks like implementing features, finding bugs, writing docs, and optimization.
View Details
nuptials.ai
nuptials.ai is an AI wedding planning partner, offering timeline planning, budget optimization, vendor matching, and a 24/7 planning assistant to help plan your perfect day.
View Details
Make-A-Craft
Make-A-Craft helps you discover craft ideas tailored to your child's age and interests, using materials you already have at home.
View DetailsPixelfox AI
Free online AI photo editor with comprehensive tools for image, face/body, and text. Features include background/object removal, upscaling, face swap, and AI image generation. No sign-up needed, unlimited use for free, fast results.
View Details
Smart Cookie Trivia
Smart Cookie Trivia is a platform offering a wide variety of trivia questions across numerous categories to help users play trivia, explore different topics, and expand their knowledge.
View Details
Code2Docs
AI-powered code documentation generator. Integrates with GitHub. Automates creation of usage guides, API docs, and testing instructions.
View Details