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discussion Making AI accessible for everyone

Our mission here at ReSci is to make artificial intelligence accessible and usable for brands. We believe that everyone should have access to the predictive capabilities that have made companies like Amazon and Netflix into the powerhouses they are today. So how did we seek to do this? We had proven data science models that worked, and we ran constant validation tests to prove it. But it was difficult for marketers to do something with this information, never mind attempting to apply it to marketing [...] [more]
retentionscience.com    Intelligence

tactics Is RFM still king? A data science evaluation

Predicting and preventing customer churn has a strong impact on the success of e-commerce businesses. Many businesses understand the importance of churn and engineer a predictive model to analyse and identify churning users. There are various flavours to define user churn in e-commerce. One commonly used definition is “the probability that a user will cease buying from an e-commerce business in the future.” However, not all businesses have the resources to build, tune, and run a churn prediction mode [...] [more]
retentionscience.com    Intelligence, Segmentation

tactics Using predictions to get your customers to buy again

If you sell a consumable product, you want your customers to buy again and again. When a product gets used up or wears out, it makes sense to send a reminder to customers to refill, replace, or repurchase that product or a similar product. [...] [more]
retentionscience.com    Automation, Intelligence

strategy 2017 Holiday Season: 4 Data-Backed Tips for Retail Marketers

In 2016, Cyber Monday was the biggest day in US ecommerce history. Consumers spent $3.45 billion. Black Friday was close behind at $3.34 billion with a year-over-year growth rate of 21.6%. Black Friday was the first day ever to generate over a billion dollars in sales from mobile devices: $1.2 billion to be exact. [...] [more]
retentionscience.com    Automation, Event, Conversionrate, Marketing

tactics Female, Male, or Neutral? Filtering Based on Gender

Our gender-match filter requires that we first tag users, with our best guess at their gender preference, and items, with our best guess at their gender-specificity. [more]
retentionscience.com    Intelligence, Segmentation

discussion Are You Sending Price Drop, New Arrivals, and Back in Stock Emails to The Wrong Customers?

If you’re sending out a discount email, you want to find the most efficient way to group users who all have a high affinity to a specific item. Here at ReSci, we call it predictive product segments. What this means is that our proprietary AI models are baked into our lifecycle stages. Predictive product segments are an inherent function of our Price Drop, New Arrivals, and Items Back in Stock. Target excess inventory to interested buyers. Retailers may run into an issue with excess inventory due to [...] [more]
retentionscience.com    Intelligence, Segmentation

tactics Behind the Data Science: Sending Item Alerts to the Right Users

Recommendation algorithms usually try to optimize the best set of items (products) to show a specific user. In certain situations it is necessary to obtain the best set of users that might be interested in a specific item. Many digital marketers face the hard problem of targeting the right users not only for their promotional emails, but also for specific item triggers. [...] [more]
retentionscience.com    Intelligence, Recommendation

tactics Machine Learning Predictions for Subscription Businesses

Machine learning can be a marketer’s proactive assistant in increasing their understanding about their subscribers. Intelligent segmentation combined with strategies can be useful to mitigate churn and increasing life time value of your users. This blog posts covers some aspects of our new product exclusively made for marketers at subscription businesses. So let’s stop guessing, start leveraging machine learning and take Subscription Cortex for a spin! [...] [more]
retentionscience.com    Intelligence, Segmentation

tactics When to Use Multi-Armed Bandit A/B Testing

What if as a marketer you could run 10 A/B tests within a week without lifting a finger instead of the standard monthly testing? You could be getting a significant increase in productivity and performance, if you do it right. A/B testing is a standard step in the marketing process. Without A/B testing, marketers wouldn’t have the necessary data points to maximize their marketing efforts and drive an effective campaign. The A/B test is mainly used when you want to see what treatment is causal to [...] [more]
retentionscience.com    Test

tactics 3 Major Recommendation Algorithm Mistakes Fortune 500 Companies Make

Several recommendation algorithms power email-marketing campaigns as well as on-site product recommendations. With Amazon’s success in driving revenue and engagement from product recommendations, several companies leverage these algorithms to cross-sell/up-sell products to users. [...] [more]
retentionscience.com    Intelligence, Recommendation

strategy Customer Segmentation Strategy: How To Scale Up, Save Time, and Convert

Historically, it’s been going into an email service provider (ESP) and manually building segments that make some intuitive sense: High spenders who live in LA; or females who bought in the sports category in the last 30 days. Then target these segments with some specific messaging: “Damn it feels good to be a VIP in LA!” Then customize this message in any number of ways with variables such as {username} and {user location} and {sale date} and {rewards balance} and {product interest}. And perhaps [...] [more]
retentionscience.com    Intelligence, Segmentation

tactics The Right Users For Incentive Emails [PDF]

We’ve illustrated the effectiveness of incentives for sales and analyzed which users are good candidates for incentive emails. By identifying the right candidates and sending incentive emails to them, our client is able to improve customer loyalty and brand image while boosting sales. [...] [more] 
retentionscience.com    Customization, Intelligence

tactics Scaling Recommendation Engine from 15,000 to 130M Users

Delivering users with precise product recommendations (recs) is the creative force that drives Retention Science to continue to iterate, improve and innovate. In this post, our team unveils our iteration from a minimum viable product to a production-ready solution. Here’s the chronology of events: [...] [more]
retentionscience.com    Intelligence, Recommendation

discussion Learn how scientific email marketing can generate 70% of your company revenue

When it comes to choosing an effective digital marketing tool, email just doesn’t seem as sexy anymore. In a space inundated with viral video campaigns, hashtag wars, and the flash-bang tactics of mobile marketing, connecting with customers through email appears outdated and old-fashioned, and not nearly trendy enough to compete. [...] [more]
retentionscience.com    Customization, Intelligence

strategy 3 Essential Components of Email You need to Personalize

While email is still one of the most effective ways to market to your customers, most people have learned to tune out messages that aren’t relevant to them. That’s why it’s essential for brands to take on a more personal approach to email marketing. Ditch the old “batch and blast” strategy and treat your subscribers like the unique individuals they are. [...] [more]
retentionscience.com    Customization, Segmentation, Sendtime
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