AI

What is Entity Resolution?

Whenever a customer interacts with a business, a unique record is logged in the business’s database. Sometimes, this results in two different data points such as “T. Cruise” and “Tom Cruise” referring to the same Tom Cruise. If you want to get a more accurate, comprehensive view of customer behavior to improve your customer service and marketing, you may need to resolve these two points into one distinct entity. This is one example of what is called entity resolution, the process of merging various records into a single entity.

Making Smarter Customer Retention Decisions

The problem we see with most brands is that they take an “everything to everyone” approach to retention marketing, which means they try to appeal to all their customers with the same generic campaigns and messages, rather than tailoring their marketing efforts to specific customer segments. We find that this approach leads to poor engagement and low retention rates, as folks aren’t likely to respond to messages that aren’t tailored to their interests. And thus, we see the importance of segmentation!

Perfecting Segmentation: Bolstering your ESP with AI

Email Service Providers (ESPs) are a great starting point when trying to segment your customers, but nowadays, you're going to need more than just an ESP to make your campaigns the best of the best. We can't live without ESPs — I mean, they’re absolutely critical for delivering messages to consumers across various platforms. And while ESP’s are great at delivery and compliance, we’ve found the key to amplifying their existing impact even further: a robust RFM (or AI) model that enables brands to have more granular and predictive user segmentation.

Cotera's Segmentation Model: A Case Study

Recently, we had a large food & beverage e-commerce company come to Cotera looking for a strong segmentation model. The Head of Marketing needed to bring down a high one-and-done and churn rate. She knew they were facing an abundance of customer churn but that her team wasn’t proactively identifying these at-risk customers until it was too late. With a company-wide focus on retention, she knew they needed a dedicated tool that specialized in customer segmentation.

Diving into Apps on the Modern Data Stack: Understanding the Essentials

There has been a lot of talk of building 'data apps' on the modern data stack. It's not clear who exactly is to be blame but it may be Martin Casado [1] and Benn Stancil [2]. But what does it even mean to build a data app? Are there any benefits or downsides? What are the technical challenges? I think the proposition is interesting... but these are tough questions we must answer if the concept is to be taken seriously.

Cotera's Lifecycle Model: A Case Study

A case study of Cotera's lifecycle segmentation model. Learn how we helped companies decrease churn and identify upsell opportunities.

The Power of Segmentation Analysis

In the dynamic landscape of business, understanding your audience is crucial. Picture this: you have the key to uncovering the complexities of consumer behavior and preferences. This key is none other than the transformative field of segmentation research!

Why Your Churn Mitigation Strategy Might Be Too Little, Too Late

99.9% of businesses are in the business of selling something, and the person on the other end of the transaction is a customer. Now, different businesses have different numbers of customers: Delta flies hundreds of millions of customers around the world each year (I’m writing this on a Delta flight right now), while a company that creates missile defense systems might do so for very few but usually very large countries over the course of a given decade. Most of these companies also experience what’s called “churn.” The term is most often attributed to companies that sell a subscription, but is also present in most other types of business, just with differing amounts of importance.

Why customer churn prediction is what your retention team needs.

If you listen to music often, I’m sure you know of the Apple Music vs. Spotify rivalry in the music streaming industry. And usually, you’re on one side or the other—but not both. In this multi-billion dollar industry, companies like Apple Music and Spotify are forced to regularly produce updates and keep their subscribers happy. Then, in 2016, some researchers looked into what makes each company successful, and they found that Apple Music had a churn rate that was three times higher than that of Spotify. But what exactly does that mean, and what made this information useful for the researchers at the time?

Cotera's Replenishment Model: A Case Study

When a leading supplement brand was in need of an easy way to send out emails right when a customer was most likely to have run out of a product, they came to Cotera. Their retention team had tried exploring different ways to optimize email schedules manually, but estimating the right timing on their own was near impossible. This meant that there was so much wasted potential for campaigns sent to their top customers — but they knew they couldn’t make the needed predictions on their own.

Snowflake Cortex

Snowflake have launched an LLM function feature, they call it Cortex. The idea is it lets you create a new column with a plain old SQL expression, which makes it super flexible. It's in public preview, so anyone can try it out.

How ERA brings last mile analytics to any data warehouse via DuckDB

Have you ever waited for a dashboard to load for so long that you forgot what you were even looking for? I think we all have. It can be incredibly frustrating (especially if your organization is using Redshift...).

Unlocking Hidden Revenue: Why Abandoned Cart Strategies Should Include Upselling

What’s shocking is that according to a recent study, chances are high that only 3 out of 10 individuals will end up pulling the trigger to make the final purchase. That’s 70% of customers who end up abandoning their carts — a very worrying statistic. But don’t let this discourage you — there are solutions you can implement to nudge customers further toward that final trigger. And why go the extra mile to do so? Imagine being able to turn that 70% into 0%. That gives you and your company the ability to more than double your existing revenue — something that would be *significantly* more difficult and expensive to accomplish through a customer acquisition or brand awareness campaign.

Why Coupons Alone Aren't Enough: Embracing Customer-Centric Strategies

Here’s a question for you - why would you offer a coupon to a customer who you *know* would buy from you even in the absence of a deal? I guess the hard part would be determining which customers you *actually* need to offer promotions to and which you don’t. But it’s wrong to think that it’s a waste of your time to figure this out. By handing out coupons left and right, you’re simply losing money - and this is a mistake many companies (like Blue Apron) have made and continue to make. BUT there’s a solution! Just like for many problems we’ve covered in the past, segmentation is the key here. Let’s use the company Everlane as an example.

Data Enablement: Fueling Marketing Success in the Digital Age

It’s pretty clear that in the dynamic world of marketing, success today is driven by data. When we look at trends in the consumer retail industry especially, companies are beginning to up their digital game to keep up with their competitors. In other words, many traditional methods simply don’t cut it anymore. This is where data enablement steps in. Let’s dive into what exactly data enablement is and how it’s changing the way companies go about marketing.

How to Stop Losing Sales: Taming the Cart Abandonment Beast

So, you've got an online store, and you're pumped about it. People are adding stuff to their carts, but after a little while...poof! They vanish without completing their purchases. What happened? This phenomenon is called Shopping Cart Abandonment, and this article will cover what this metric is, why it’s a big deal, and how you can prevent it.

What is content-based filtering?

Content-based filtering considers item features and characteristics to find similar items that you might like. In this article we take a deep dive into how they work and how to use them effectively!

Predicting The Next Customer Purchase Day To Improve Email Campaigns

Predicting the next time that a consumer is expected to buy a product allows you to make well timed offers that boost conversion. Here's how to do it.

Better Marketing With Data - Personalizing Post Purchase

You just purchased a pair of sneakers from Allbirds, and you immediately receive a post-purchase email in your inbox. There’s about a 45% chance you even open the email in the first place, but let’s say you do. Which one of these emails would you be more likely to look through? Which would leave a more lasting impression?

Cotera's Recommendation Model: A Case Study

Around a year ago, an apparel and accessories brand came to Cotera looking for a new, strong recommendation model to replace its current one. The Head of Retention knew they should be generating higher incremental revenue from moving customers across different products. Yet they found themselves stalled leveraging their ESPs’ recommendation engine, as it was unable to adjust for the nuances of their business. And any attempts at testing stand-alone recommendation engines lacked the turnkey integration with their ESP.

Retention Renaissance: Adapting to a Retention-Driven Marketplace

In addition to high consumer spending, the customer acquisition landscape was quite different from what it is today - platforms like Facebook, Twitter, and Instagram offered clever segmentation tactics to target customers effectively, which gave these companies comparatively lower customer acquisition cost (CAC) than they had seen in the past. If you’ve been operating a business, you’ve got a plethora of data that you can use to your advantage. Here are some ways that our customers have seen growth from their existing customer base.

Personalization: What's the definition?

From Data to Dollars: Harnessing LTV to Drive Revenue

LTV is one of those concepts that can easily be understood at surface level but often misunderstood at its core. But what exactly makes it so difficult to grasp? 1. LTV is hard to calculate, and nobody knows what to do with it. 2. There’s no way easy way to use it to measure growth. 3. Fixing (1) and (2) is much easier said than done.

Unveiling Buyer Personas: How "Calvin", "Dora", and "Sammy" Can Boost Your Sales

We were working with a +$40M e-commerce brand last year that sold coffee and tea online, and we found that their customer re-targeting strategy amounted to taking every person who hadn’t purchased in the last 6 months and sending them a coupon for 10% off the highest selling product that the brand had (or sometimes a product that was in overstock). This, while better than nothing, was leaving money on the table. We’ve also found this on the SaaS side. The retention strategy for surprisingly large companies can whittle down to effectively a poke/prod to anyone who hasn’t logged in in a few weeks. We’ve found that you can increase engagement by double digit percentages by making sure that you target the right customers at the right time.

RFM Made Easy: A Guide to Profiling Your Best Customers

RFM is a customer segmentation methodology for e-commerce businesses. The insight behind this framework is that customers who purchased recently are more likely to purchase again. Equally, big and frequent spenders are more likely to respond to promotions than small and infrequent spenders. Together, the three metrics give you a way to create lifecycle segments that let you answer questions like: Who are my best customers? Which customers am I at risk of losing? Which customers are best to target with promotions? Which customers can I entice to spend more?