Being a part of the e-commerce community means that you’ve willingly signed up for continuous monitoring, testing, and adopting new technologies. As a result, there is no time to relax. Otherwise, you risk being beaten by your rivals and lose your customers and sales. 

We feel your pain and know for sure how tiresome it is to keep up with the latest innovations. That’s why to save your time, the Recom.ai team carefully tracks the most up-to-date trends and integrates them in our app to help you stay on a roll.

Without further ado, we want to introduce Scout, a brand new approach to online shopping! With this killer technology that millions of Amazon users have highly appreciated, you’ll enter a new era of personalized product recommendations.

Helpful info: The AI algorithm used by Recom.ai generates extremely accurate real-time recommendations that meet specific customers’ needs, thus changing their behavior, improving engagement, and boosting conversions. They are also designed to solve a more complex problem, such as creating recommendations for new visitors with no historical data. 

Why are personalized recommendations so great?

Customers have always welcomed the personal touch, whether it’s been expressed in using their name in an email or in providing personal discounts for their birthdays. All these small things make them feel unique and eventually build loyalty to your brand.

According to the latest stats, about 80% of online shoppers buy from brands that provide personalized experiences, while 71% of consumers express some level of disappointment facing impersonal offers. However, trying to provide a personalized experience to their audience, online merchants have to deal with many sticking points, such as applying data insights to decisions, using more artificial intelligence, understanding customers’ purchase intentions, and many others.

Infographic: Data use biggest hurdle for hyper-personalisation | Statista You will find more infographics at Statista

Real-time product recommendations by Recom.ai take hyper-personalization to a new level and solve all the problems mentioned above once and for all. Now, you can effortlessly offer products tailored to customers’ specific needs to improve their shopping experience and instantly notice a natural boost in conversions.

Keep on reading to find out how Scout changes the game of online shopping by providing new personalization opportunities and brings extra revenue to store owners.

Use Case #1 Improving the accuracy of personalized product offers for a large store

Problem

Linda is an online merchant who runs an apparel store with dozens of items in each product category. She was seeking alternative ways to optimize her conversion rate and sell more inventory from particular collections. She had already launched some cross-selling campaigns on her product and cart pages. But her stats showed that due to her store specifics, offering similar or complementary products based on vendor, category, type, or price was not enough. And unfortunately, her CTR numbers went below the desired result.

Challenges

On the one hand, a rich product selection is an obvious plus. The more various products you sell, the more chances to meet customers’ needs you have. But frequently, regular widgets with product recommendations and even catalog filters don’t display the items customers really need. Therefore, users spend tons of time trying to get what they want and leave your store without extra purchases or with no purchases at all.

Solution 

The AI-powered Scout algorithm helped Linda understand what her clients want and automatically suggest the items based on their preferences. No wonder that the perfect-match-recommendations had a positive impact on Linda’s CTR and even exceeded her expectations.

Helpful info: According to the Recom.ai statistics, the proper combination of the Scout widget with cross-selling and upselling offers ensures up to 45% revenue growth.

Magic? Well, let’s dig into the details.

How does it work?  

Step 1. To start a campaign with personalized recommendations, Linda doesn’t have to conduct any customer surveys or look for a pricey rocket science tool. Instead, she needs to activate the Scout option in the Recom.ai app, specify the pages where the widget should be placed, and that’s it!

Fine-tune Scout Settings

Step 2. Once the option is activated, the ML algorithm starts analyzing products visually similar to what a particular customer is currently investigating.

Step 3. It wraps the selected items in a handy widget and shows them to the customer. Along with the products, Scout displays “like” and “dislike” buttons to let the shopper vote for the products they are interested in and vote against the items that don’t hit the target.

Step 4. The smart algorithm automatically fine-tunes item selection depending on the customers’ “likes” and “dislikes.”

Step 5. Customers instantly get the products based on their specific preferences and happily adds them to the cart.

Recom Scout Widget

Results

  • Immediate revenue growth on day 1 after the personalized recommendations campaign is launched

Helpful info: On average, Recom.ai users earn over $200,000 of extra revenue every day.

  • Increased AOV (average order value)
  • The overall sales boost
  • Increased number of returned customers
  • Higher Google rankings because of improved user behavior factors
  • Boost of organic traffic

The user behavior data that Google relies on includes click-through rate, duration on the web page, conversion rate, bounce rate, frequency of visits, etc.

Now you can easily optimize all these metrics with just one tool for personalized recommendations!

Use Case #2 Improving customer satisfaction through real-time personalized suggestions

Problem 

Tom is a newbie merchant that has just started selling women’s accessories on his website. Unfortunately, his limited startup budget didn’t allow spending extra funds on numerous marketing activities. Therefore, he was looking for the “set it and forget it” solution to improve customer experience and increase the average order value at the same time.

Challenges

There are hundreds of marketing software solutions out there. But the overwhelming majority of them require time and specific knowledge to be fine-tuned and properly managed. Apart from that, some tools come up too expensive for a freshly started business. Thus, the choice of appropriate tools is significantly reduced.

Solution 

Here comes Scout with its real-time personalized recommendations! This is the perfect match for those who want to effortlessly run effective marketing campaigns and save time for other important tasks.

Tom simply activated the Scout option in the Recom app, and the ML algorithm immediately started analyzing the products in his catalog. Now, all his customers get real-time product suggestions accurately tailored to their needs.

Results  

  • The average order value boost
  • The growth of conversion rates
  • Increased average time on the page due to the gamification element
  • Increased user engagement
  • Decreased churn rates
  • Saved time for other business activities

Summing Up

Due to its innovative algorithm and complete automatization, the Scout feature opens new horizons for personalization marketing. It “reads” customers’ thoughts, predicts their desires, and timely delivers precisely tailored product recommendations.

Hence, with only one easy-to-use tool, you’ll increase your conversion rates and average order values, save time, and get helpful insights into what your clients like. Ready to get personal? Then you are on the right track!