Apply machine learning models to your data
Ecommerce Machine Learning platform that boost customer retention, increase products sales and help you grow sustainably
How does Catwing help you grow?
We combine all of your data sources to give you insights so you can boost your business by:
- selecting right products and bundles
connecting the products to the right audience
retain your existing customers
- early warnings for possible churn of your customers
enabling you to convert your new and existing customers into loyal and increase their LTV
combine audience with products for higher ROAS on campaigns creation
assessing your channels
Normally integration takes a couple of days without developer support, and within 3 months you are able to see your first quality results.
There are several steps that we normally follow. Identify top-performing products among tens of thousands of them then suggest the right bundles and the last creating relevant product catalogs which are customer-driven.
For identifying top-performing products we use ABC analysis it follows the Pareto Principle, where 20% of items bring 80% of the value to the business.
Something else we believe is crucial if we can classify products based on their variability of demand, so we introduce and XYZ analysis, they capture seasonalities and variations of demand for all products.
Market basket analysis (MBA) is widely used to analyze retail basket or transaction data and is intended to identify strong rules discovered in transaction data using measures of interestingness, based on the concept of strong rules.
Defining product catalogs based on customer patterns and interests outside of category restriction is a powerful model to rely on data and provide personalized customer experience over your channels – site, facebook, email and SMS campaigns, etc…
Customer persona and what is your audience is the main questions to which each marketer is willing to know the answer.
Here in Catwing we are able to identify your audience, split it into segments based on their product, item interests, patterns, sales funnel progress, site behavior and suggest relevant actions for each segment or customers. We rely on several models.
For identifying your key accounts we use ABC analysis it follows the Pareto Principle, where 20% of your customers brings 80% of the value to the business.
Introducing XYZ analysis on the customer level gives information about the variability of demand over a period for each customer.
Customer behavior segmentation – RFM allows marketers to identify specific clusters of customers, up to 14, and redesign their marketing strategy toward loyalty, having the instrument to measure and convert their customers to become loyal, with the right communications that are relevant for their particular behavior. As a result, it generates much higher rates of response, plus increased loyalty and customer lifetime value.
Building a predictive churn model helps you make proactive changes to your retention efforts and be in control to reduce leaving customers rate, by reacting on early warning with the right customer communication.
In contrast, Customer profitability analysis is a method of looking at the various activities and expenses incurred in servicing a particular customer. In other words, it focuses on analyzing profit per customer rather than profit per product.
The key is to position your high conversion products or bundles to the right audience and to focus on increasing your repeat purchase rate and incentivizing long-term customer loyalty. It is not going to happen overnight and need to include some of these tactics in your customer outreach.
We suggest to start with selecting the right products or bundels with the right audience at the right time in order to increase your ROAS and achieve higher profit.
Also there are several other campaigns that can incorporate everything that matters about CLTV into smart copy, design, messaging, and targeting.
Repeat purchase campaigns – campaigns that aim to get customers to make a second purchase are perfect for increasing CLTV.
Replenishment or repurchase rate campaigns – offering replaceable or consumable products over a period defined by a model.
Cross-selling campaigns – to offer related products that acknowledge their needs, the more likely they are to make additional purchases.
Loyalty campaigns – offering rewards in exchange for purchases is a powerful way to encourage higher-value customers to buy more.
Each marketing team is allocating resources on various channels and the constrain they have is where to focus on, how to measure their effectiveness in order to be more profitable in their efforts.
Introducing multichannel attribution models can help to measure channel effectiveness, as well as channel synergies, optimal budget allocation, and to assess which factors influence multichannel effectiveness.
How to launch
Great services. Applied models.
We need at least 3 months to gather data and fine-tune the models
If you have any questions related to the size of your store, pricing plans, models, data sources – please contact us directly. We are here to help and share our expertise in Data Science and Machine Learning and guide you through the process 🙂
Subscribe to our monthly newsletter, we share information about various models applied from our customers, organizing webinars and presenting customer cases and good practices.