Waggfluence Boosts Shopper Engagement and AOV using Predictive Recommendations

Introduction

Waggfluence is a D2C brand that offers a wide array of pet supply products to support animal lovers and their furry companions. 

Silas Lepcha sits as their General Manager of Product Management and Marketing. He is in charge of taking products to market and scaling-up several brands under the Nimble Wireless portfolio.

We sat down with Silas to learn about his challenges and goals with Waggfluence, and how predictive personalization has helped him out. 

Happily for both Silas’s team and ours, predictive personalization has been a valuable tool in their toolbelt. (Results below!)

Broader eCommerce Challenges

During our conversation, Silas explained the priorities and challenges of a mid-sized D2C business looking to scale. 

After his team instituted a strong setup – established their products, built their brand, and found the channels and go-to-market plan that reliably generated repeat customers – their focus shifted to efficiency and scalability.

The challenge and directive he posed may resonate with you: 

How could their brand balance margin with marketing spend so as to generate sales at a healthy and sustainable customer acquisition cost (CAC)? 

In other words, the Waggfluence team must continuously optimize for more efficient conversions. More sales; lower costs.

He says, “You just simply can’t surpass a certain CAC.” The economics don’t work.

Silas keeps a close pulse on the CAC and LTV of his shoppers to ensure their products, marketing channels, and tools stay ROI-positive. 

So what are the levers that his team pulls to get more out of the website traffic they earn? 

Addressing Challenges

The Waggfluence team regularly tests their marketing strategy, advertising channels, and optimization tools to drive growth while maintaining healthy business metrics.

They have an especially acute focus on conversion rate optimization (CRO).

CRO nowadays is often tied to personalization. So, we talked briefly about how major social media platforms are effectively enormous predictive personalization engines.

 “Personalization tools help to create more relevance. For example, TikTok and Facebook are based on that.” 

Silas wanted to test how this “big-tech” type of machine learning (ML) personalization would work when applied to Waggfluence’s e-com site. 

A CRO approach driven by hyper-relevance.

So, he used Jarvis ML to test predictive personalization across key touchpoints for shoppers on his website. 

Predictive Personalization

Silas and his team have experimented with personalization on their storefront before.

However, he says it’s been mostly fairly lightweight and not actually backed by ML.

He was excited to put ML-powered predictive personalization to the test to see if he could drive more of his hard-earned traffic towards more sales – making their spend more efficient. 

The goal: “We want to personalize experiences to users through artificial intelligence to show them products more related to what they’re looking for.”

The Waggfluence team believes that most of the people that come to their site don’t want to waste time. So they want their shoppers – even a first-time cold customer – to get something they’re looking for. And quickly.

Results from Predictive Recommendations

Silas deployed predictive recommendations across the Waggfluence website and within a couple of days he was already seeing impact on customer engagement.

The individualized product recommendations served to each user drove more engagement, more clicks, more purchases, and higher AOV. 

After an evaluation period against a control, the results were awesome:

  • In just the first week, Waggfluence saw a 49% increase in Conversion Rate and 52% growth in Revenue per Shopper
  • Product page predictive recommendations have a 250% higher Click-through Rate.
  • Shoppers clicking homepage recommendations increased Average Order Value by 33%. (From $30 to $40!)

The predictive recommendations that Jarvis calculated with Waggfluence’s eCommerce data created more sales, and did so more efficiently. 

“The Jarvis team is really good. They were very clear on how to get started, and within 24 hours we were live. They’re open to feedback on our calls – it’s a good experience.”

Would you Recommend Predictive Personalization? 

When we asked Silas if he would recommend Jarvis, he told us “If it was our competitor I would not inform them.” 

We laughed and he went on, “But if it was a friend, I’d tell them that it’s been working for us and you should test it out to see if it works for your business.” 

Predictive personalization wins out against legacy personalization methods for a few reasons. At the core: it is automated, doesn’t rely on manual rules-based logic, uses more 1st party data, and fully utilizes the power of machine learning. 

Silas has been observing larger D2C brands hiring teams of machine learning engineers – he believes this is because eCommerce companies are eager to start applying ML across more places in their shopping experience. 

“However, for small and mid-sized companies,” he says, “software that does this work for you has a big business impact. We can take advantage of ML and our data to influence buyer behavior.” 

Big tech companies trap SMB brands to rely on their platforms – but Jarvis ML wants to democratize “ML” so any business can be a machine learning company. 

Interested to hear how we can help you drive more efficient sales using predictive recommendations? Let’s talk!

And if you have a pet, check out Waggfluence’s innovative flagship product that monitors your pets body temperature! The Waggfluence store also has playful accessories to help make life a bit more fun. (One of my favorites is the Harry Potter house color robes for Hogwarts. My cat would be Hufflepuff.)

 

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Nick Budincich
Nick's objective in life is to create good, happy, fulfilling experiences and memories for himself and everyone he interacts with.

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